Hello Cortney, 

I've attached the risk assessment and technical memos. There should be 8 attachments, let me know if they don't all come through. 

Let me know when you've had a chance to look over the package and want to set up a call to talk things over. 

Nathan Topham 

Environmental Engineer 

US EPA/OAQPS/SPPD/MIG 

Phone - (919)541-0483 

Hi Nate, 

We’ve received the final rule here for review. Can you send the risk assessment and supporting memos? 

 

Thanks, 

Cortney 

From: <Topham.Nathan@epamail.epa.gov>

To: "Higgins, Cortney" <Cortney_Higgins@omb.eop.gov>

Date: 11/28/2011 5:53 PM

Subject: Re: Secondary Lead RTR

CC:

 

<French.Chuck@epamail.epa.gov>, <Donna.Lazzari@erg.com>, <Michael.Burr@erg.com>, 

<Malave.Maria@epamail.epa.gov>, <silverman.steven@epamail.epa.gov>, 

<Talcott.Fred@epamail.epa.gov>, <Benner.Tim@epamail.epa.gov>, <Kirrane.Ellen@epamail.epa.gov>, 

<Moser.Ginger@epamail.epa.gov>, <Woodall.George@epamail.epa.gov>, 

<Chang.Andy@epamail.epa.gov>, <Doolan.Stephanie@epamail.epa.gov>, 

<Evans.Carlos@epamail.epa.gov>, <Davis.Matthew@epamail.epa.gov>, 

<Stewart.Michael@epamail.epa.gov>, <Guinnup.Dave@epamail.epa.gov>, 

<Secrest.Cary@epamail.epa.gov>, <Garlow.Charlie@epamail.epa.gov>, <South.Mia@epamail.epa.gov>

Attachments:

 

Draft Secondary Lead Promulgation Risk Assessment 11-28-2011.docx; Draft MACT Floor Analysis for 

the Secondary Lead Smelting Source Category 11-28-2011.docx; Draft Secondary Lead Cost Impacts of 

the Revised NESHAP 11-28-2011.docx; Draft Secondary Lead RTR Emissions Development 11-28-

2011.docx; Draft Secondary Lead Summary of Compliance Time for Revised NESHAP 11-28-2011.docx; 

Draft Small Business Analysis for the Secondary Lead Smelting Source Category 11-28-2011.docx; Draft 

Summary of Ambient Lead Monitoring Data Around Secondary Lead Smelting Facilities 11-28-

2011.docx; Draft Technology Review for the Secondary Lead Smelting Source Category 11-28-2011.docx

From: "Higgins, Cortney" <Cortney_Higgins@omb.eop.gov>

To: Nathan Topham/RTP/USEPA/US@EPA

Cc: Chuck French/RTP/USEPA/US@EPA

Date: 11/28/2011 02:29 PM

Subject: Secondary Lead RTR

Page 1 of 1
Residual Risk Assessment for the Secondary Lead Smelting 

Source Category

by

EPA’s Office of Air Quality Planning and Standards

Office of Air and Radiation

December 2011

1
Table of Contents

1 Introduction 4

2 Methods 5

2.1 Emissions and source data 5

2.2 Dispersion modeling for inhalation exposure assessment 5

2.3 Estimating chronic human inhalation exposure 8

2.4 Screening for potential acute impacts of concern 9

2.5 Multipathway human health and environmental risk screening 10

2.6 Dose-response assessment 13

2.6.1 Sources of chronic dose-response information 13

2.6.2 Sources of acute dose-response information 20

2.7 Risk characterization 24

2.7.1 General 24

2.7.2 Mixtures 26

2.7.3 Facility-wide risks 26

3 Risk results for the secondary lead source category 27

3.1 Source category description and results 27

3.2 Baseline risk characterization 30

3.3 Post-control risk characterization 34

4 General discussion of uncertainties and how they have been addressed 35

4.1 Exposure modeling uncertainties 35

4.2 Uncertainties in the dose-response relationships 37

5 References 47

Index of Tables

Table 2.2-1 AERMOD version 09292 model options for RTR modeling 6

Table 2.6-1 (a) Dose-Response Values for Chronic Inhalation Exposure to Carcinogens 17

Table 2.6-1 (b) Dose-Response Values for Chronic Oral Exposure to Carcinogens 18

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

19

Table 2.6-2 Dose-Response Values for Acute Exposure 23

Table 3.1-1 Summary of Emissions from the Secondary Lead Source Category and 

Availability of Dose-Response Values 28

Table 3.2-1 Summary of Source Category Level Inhalation Risks for Secondary Lead 

Smelting 31

Table 3.2-3 Secondary Lead Smelting Facility Modeled Maximum Ambient Lead 

Concentrations 34

(rolling three-month average values) 34

Appendices

Appendix 1 Technical Support Document for HEM-3 Modeling

2
Appendix 2 Meteorological Data for HEM-3 Modeling

Appendix 3 Analysis of data on short-term emission rates relative to long-term emission 

rates

Appendix 4 Technical Support Document for TRIM-Based Multipathway Screening 

Scenario for RTR: Summary of Approach and Evaluation

Appendix 5 Draft Detailed Risk Modeling Results

Appendix 6 Acute Impacts Refined Analysis Figures

Appendix 7 Dispersion Model Receptor Revisions and Additions

Index of Acronyms

AERMOD American Meteorological Society/EPA Regulatory Model

AEGL Acute exposure guideline level

ASTDR US Agency for Toxic Substances and Disease Registry

CalEPA California Environmental Agency

CTE Central Tendency Estimate

ERPG Emergency Response Planning Guideline

HAP Hazardous Air Pollutant

HEM Human Exposure Model

HI Hazard index

HQ Hazard quotient

IRIS Integrated Risk Information System

MACT Maximum Achievable Control Technology

MIR Maximum Individual Risk

MOA Mode of action

NAC National Advisory Committee

NAAQS National Ambient Air Quality Standards

NATA National Air Toxics Assessment

NEI National Emissions Inventory

NPRM Notice of Proposed Rulemaking

PB-HAP Persistent and Bioaccumulative - HAP

POM Polycyclic organic matter

REL Reference exposure level

RfC Reference concentration

RfD Reference dose

RME Reasonable Maximum Exposure

RTR Risk and Technology

TOSHI Target-organ-specific hazard index

URE Unit risk estimate

3
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 

Control Technology (MACT) standards as required under this provision. Under section 

112(d)(6), EPA must review each of these technology-based standards at least every eight 

years and revise a standard, as necessary, “taking into account developments in practices, 

processes and control technologies.” In the second stage, EPA is required under section 

112(f)(2) to assess the health and environmental risks that remain after implementation of the 

MACT standards. If additional risk reductions are necessary to protect public health with an 

ample margin of safety or to prevent an adverse environmental effect, EPA must develop 

standards to address these remaining risks. This second stage of the regulatory process is 

known as the residual risk stage. For each source category for which EPA issued MACT 

standards, the residual risk stage must be completed within eight years of promulgation of the 

initial technology-based standard.

In December of 2006 we consulted with a panel from the EPA's Science Advisory Board 

(SAB) on the “Risk and Technology Review (RTR) Assessment Plan,” and in June of 2007, 

we received a letter with the results of that consultation. Subsequent to the consultation, in 

June of 2009, a meeting was held with an SAB panel for a formal peer review of the “Risk 

and Technology Review (RTR) Assessment Methodologies” [2]. We received the final SAB 

report on this review in May of 2010 [3]. Where appropriate, we have responded to the key 

messages from this review in developing our current risk assessments and we will be 

continuing our efforts to improve our assessments by incorporating updates based on the SAB 

recommendations as they are developed and become available. Our responses to the key 

recommendations of the SAB are outlined in a memo entitled, “EPA’s Actions in Response to 

Key Recommendations from the SAB Review of RTR risk Assessment Methodologies” [4].

This document contains the methods and the results of baseline risk assessments performed 

for the Secondary Lead Smelting source category. The methods discussion includes 

descriptions of the methods used to screen for acute health risks, chronic non-inhalation 

health risks, and adverse environmental effects, as well as descriptions of the methods used to 

develop refined estimates of chronic inhalation exposures and human health risks for cancer 

and noncancer endpoints.

During the public comment period for the proposed rule, the some facilities in the source 

category submitted updated emissions, facility boundary, and other relevant information with 

respect to performing a risk assessment (see docket number: EPA-HQ-OAR-2011-0344 for 

public comments received). In addition, we also received emissions data for an additional 

facility that was not included in the modeling to support the proposed rulemaking. Thus, the 

methods and data used to generate the baseline and post-control risk results presented in this 

final risk assessment document consider the updated information received during the public 

4
1 The tagging of 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. MACT codes are assigned at the process level for the point source. 

comment period for the proposed rule.

2 Methods

2.1 Emissions and source data

Data from the 2005 National Emissions Inventory (NEI) which were used and published as 

part of the 2005 National Scale Air Toxics Assessment (NATA) served as the starting point 

for this assessment. The 2005 NEI contains information on actual emissions during the entire 

2005 base year. Using the process MACT code1, we developed a subset of this inventory that 

contains emissions and facility data for the Secondary Lead Smelting source category. Next, 

we performed an engineering review of the information using EPA engineers to identify 

readily apparent limitations and issues with the emissions data In 2010, following this initial 

engineering review, we sent an information collection request (ICR) survey to the six 

companies which own 14 of the 15 facilities in the U.S. The survey included many questions 

about emissions, stack parameters, locations, and other important inputs for the risk modeling. 

We also requested that facilities submit all existing test data. These data included stack test 

data for lead emissions for multiple years for most emissions points. In 2010, we also 

requested that most facilities conduct additional emissions testing of various furnaces and 

other emissions points. The facilities conducted emissions tests in 2010 for all HAP metals, 

dioxins, and various other HAPs. We received test data from most facilities in late 2010. We 

reviewed and analyzed all the ICR and stack test data and then incorporated these data into 

the model data set, as appropriate. However, with regard to the estimates of fugitive 

emissions, the data we received through the ICR were limited and uncertain. To estimate 

fugitive emissions we evaluated the ICR responses and other available information and did 

supplemental analyses to derive estimates of fugitive emissions for all facilities. In addition, 

as noted above during the public comment period for the proposed rule, EPA received some 

updated facility information, including updated emissions data from some facilities in the 

source category (see docket number: EPA-HQ-OAR-2011-0344). As a result, the emissions 

dataset used to generate the risk results presented in this final risk report consider the 

emissions data received during the public comment period for the proposed rule. In addition, 

EPA also received emissions information for an additional secondary lead smelting facility 

located in Puerto Rico. Thus, the total number of facilities in the source category, and the total 

number of facilities evaluated in this risk report, is 15.

Details on the development of the emissions and source data for this source category are 

discussed in: Summary of the RTR Emissions Dataset for the Secondary Lead Smelting 

Source Category, available in the docket for this rulemaking. Section 3 below provides a 

summary of the emissions. 

2.2 Dispersion modeling for inhalation exposure assessment

Both long- and short-term inhalation exposure concentrations and associated health risk from 

5
each facility in the source category of interest were estimated using the Human Exposure 

Model in combination with the American Meteorological Society/EPA Regulatory Model 

dispersion modeling system (HEM-3). The approach used in applying this modeling system 

is outlined below, and further details are provided in Appendix 1. HEM-3 performs three 

main operations: atmospheric dispersion modeling, estimation of individual human exposures 

and health risks, and estimation of population risks. This section focuses on the dispersion 

modeling component. The exposure and risk characterization components are discussed in 

other subsections of Sections 2 and 3.

The dispersion model in the HEM-3 system, AERMOD version 11103, is a state-of-thescience Gaussian plume dispersion 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 ambient concentrations through the simulation of hour-by-hour dispersion 

from the emission sources into the surrounding atmosphere. Hourly emission rates used for 

this simulation are generated by evenly dividing the total annual emission rate from the 

inventory into the 8,760 hours of the year.

The first step in the application of the HEM-3 modeling system is to predict ambient 

concentrations at locations of interest. The AERMOD model options employed are 

summarized in Table 2.2-1 and are discussed further below.

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

Modeling Option Selected Parameter for chronic exposure

Type of calculations Hourly Ambient Concentration

Source type Point, area 

Receptor orientation Polar (13 rings and 16 radials)

Discrete (census block centroids)

Terrain characterization Actual from USGS 1-degree DEM data

Building downwash Not Included

Plume deposition/depletion Not Included

Urban source option No

Meteorology 1 year representative NWS from nearest site (over 200 

stations)

In HEM-AERMOD, meteorological data are ordinarily selected from a list of over 200 

National Weather Service (NWS) surface observation stations across the continental United 

States, Alaska, Hawaii, and Puerto Rico. In most cases the nearest station is selected as 

representative of the conditions at the subject facility. Ideally, when considering off-site 

meteorological data most site specific dispersion modeling efforts will employ up to five 

years of data to capture variability in weather patterns from year to year. However, to 

6
minimize data processing time and resources for this assessment, we modeled only a single 

year, typically 1991. While the selection of a single year may result in under-prediction of 

long-term ambient levels at some locations, likewise it may result in over-prediction at others. 

For each facility identified by its characteristic latitude and longitude coordinates, the closest 

meteorological station was used in the dispersion modeling. The average distance between a 

modeled facility and the applicable meteorological station was 40 miles (72 km). Appendix 2 

(Meteorological Data Processing Using AERMET for HEM-AERMOD) provides a complete 

listing of stations and assumptions along with further details used in processing the data 

through AERMET. The sensitivity of model results to the selection of the nearest weather 

station and the use of one year of meteorological data is discussed in “Risk and Technology 

Review (RTR) Risk Assessment Methodologies” [2].

The HEM-AERMOD system estimates ambient concentrations at the geographic centroids of 

census blocks (using the 2000 Census) and at other receptor locations that can be specified by 

the user. The model accounts for the impacts of multiple facilities when estimating 

concentration impacts at each block centroid. Typically we combined only the impacts of 

facilities within the same source category, and assessed chronic exposure and risk only for 

census blocks with at least one resident (i.e., locations where people may reasonably be 

assumed to reside rather than receptor points at the fenceline of a facility). Chronic ambient 

concentrations were calculated as the annual average of all estimated short-term (one-hour) 

concentrations at each block centroid. Possible future residential use of currently uninhabited 

areas was not considered. Census blocks, the finest resolution available in the census data, 

are typically comprised of approximately 40 people or about ten households. 

In contrast to the development of ambient concentrations for evaluating long-term exposures, 

which was performed only for occupied census blocks, worst-case short-term (one-hour) 

concentrations were estimated both at the census block centroids and at points nearer the 

facility that represent locations where people may be present for short periods, but generally 

no nearer than 100 meters from the center of the facility (note that for large facilities, this 100-

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

rates were needed to screen for the potential for hazard via acute exposures, and since the NEI 

contains only annual emission totals, we typically apply the general assumption to all source 

categories that the maximum one-hour emission rate from any source other than those 

resulting in fugitive dust emissions was ten times the average annual hourly emission rate for 

that source. The factor of ten is not applied to fugitive dust sources because these emissions 

decrease during the meteorological conditions associated with the worst-case short-term 

impacts (i.e., during low-wind, stable atmospheric conditions).

The average hourly emissions rate is defined as the total emissions for a year divided by the 

total number of operating hours in the year. The choice of a factor of ten for acute screening 

was originally based on engineering judgment. To develop a more robust peak-to-mean 

emissions factor, and in response to one of the key messages from the SAB consultation on 

our RTR Assessment Plan, we performed an analysis using a short-term emissions dataset 

from a number of sources located in Texas (originally reported on by Allen et al. 2004)[7]. In 

that report, the Texas Environmental Research Consortium Project compared hourly and 

annual emissions data for volatile organic compounds for all facilities in a heavily7
industrialized 4-county area (Harris, Galveston, Chambers, and Brazoria Counties, TX) over 

an eleven-month time period in 2001. We obtained the dataset and performed our own 

analysis, focusing that analysis on sources which reported emitting high quantities of HAP 

over short periods of time (see Appendix 3, “Analysis of data on short-term emission rates 

relative to long-term emission rates”). Most peak emission events were less than twice the 

annual average, and the highest was a factor of 74 times the annual average and the 99th

percentile ratio of peak hourly emission rate to the annual hourly emission rate was 9. Based 

on these results, we chose the factor of ten for all initial screening; it is intended to cover 

routinely-variable emissions as well as startup, shutdown, and malfunction (SSM) emissions. 

While there have been some documented emission excursions above this level, our analysis of 

the data from the Texas Environmental Research Consortium suggests that this factor should 

cover more than 99% of the short-term peak gaseous or volatile HAP emissions from typical 

industrial sources (which were the biggest contributor to high short-term emission events) and 

more than account for peak HAP emission events associated with particulates.

 

Census block elevations for HEM-AERMOD 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 shortand long-term ambient concentrations were assumed to be equal to the highest elevation of 

any census block falling within the polar grid sector corresponding to the grid point. If a 

sector does not contain any blocks, the model defaults the elevation to that of the nearest 

block. If an elevation is not provided for the emission source, the model uses the average 

elevation of all sectors within the innermost model ring.

In addition to using receptor elevation to determine plume height, AERMOD adjusts the 

plume’s flow if nearby elevated hills are expected to influence the wind patterns. For details 

on how hill heights were estimated and used in the AERMOD modeling see Appendix 1. 

2.3 Estimating chronic human inhalation exposure

We used the annual average ambient air concentration of each HAP at each census block 

centroid as a surrogate for the lifetime inhalation exposure concentration of all the people 

who reside in the census block. That is, the risk analysis did not consider either the shortterm or long-term behavior (mobility) of the exposed populations and its potential influence 

on their exposure.

 

We did not address short-term human activity for two reasons. First, our experience with the 

NATA assessments (which modeled daily activity using EPA’s HAPEM model) suggests 

that, given our current understanding of microenvironment concentrations and daily activities, 

modeling short-term activity would, on average, reduce risk estimates about 25% for 

particulate HAPs; it will also reduce risk estimates for gaseous HAPs, but typically by much 

less. Second, basing exposure estimates on average ambient concentrations at census block 

centroids may underestimate or overestimate actual exposure concentrations at some 

residences. Further reducing exposure estimates for the most highly exposed residents by 

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

We did not address long-term migration nor population growth or decrease over 70 years, 

8
instead basing the assessment on the assumption that each person’s predicted exposure is 

constant over the course of their lifetime which is assumed to be 70 years. In assessing cancer 

risk, we generally estimated three metrics; the maximum individual risk (MIR), which is 

defined as the risk associated with a lifetime of exposure at the highest concentration; the 

population risk distribution; and the cancer incidence. The assumption of not considering 

short or long-term population mobility does not bias the estimate of the theoretical MIR nor 

does it affect the estimate of cancer incidence since the total population number remains the 

same. It does, however, affect the shape of the distribution of individual risks across the 

affected population, shifting it toward higher estimated individual risks at the upper end and 

reducing the number of people estimated to be at lower risks, thereby increasing the estimated 

number of people at specific risk levels. 

When screening for potentially significant acute exposures, we used an estimate of the highest 

hourly ambient concentration at any off-site location as the surrogate for the maximum 

potential acute exposure concentration for any individual.

2.4 Screening for potential acute impacts of concern

In establishing a scientifically defensible approach for the assessment of potential health risks 

due to acute exposures to HAP, we followed the same general approach that has been used for 

developing chronic health risk assessments for other rules under the residual risk program. 

That is, we developed a tiered, iterative approach. This approach to risk assessment was 

endorsed by the National Academy of Sciences in its 1993 publication “Science and 

Judgment in Risk Assessment” and subsequently was adopted in the EPA’s “Residual Risk 

Report to Congress” in 1999. 

With respect to screening for potential acute health risks, the assessment methodology is 

designed to eliminate from further consideration those facilities for which we have confidence 

that no acute adverse health effects of concern will occur. To do so, we use what is called a 

tiered, iterative approach to the assessment. This means that we began with a screening 

assessment, which relies on readily available data and uses conservative assumptions that in 

combination approximate a worst-case exposure. The result of this screening process is that 

either the facility being assessed poses no potential acute health risks (i.e., it “screens out”), or 

that it requires further, more refined assessment with respect to potential acute exposures from 

emitted HAP. A more refined acute assessment could use industry- or site-specific data on 

the temporal pattern of emissions, the layout of emission points at the facility, the boundaries 

of the facility, and/or the local meteorology. In some cases, all of these site-specific data are 

used to refine the assessment; in others, lesser amounts 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, meteorology, and exposure location. We used 

the following worst-case assumptions in our screening approach:

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

rates except in the case of fugitive dust (see section 2.2)

9
2 Although the two-letter chemical symbol for lead is Pb, in this assessment PB-HAP refers to the many air 

pollutants known to be persistent and bioaccumulative in the environment. In instances where the report is 

specifically referring to lead, it is spelled out (i.e., the two-letter chemical symbol for lead is not used in this 

document). 

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

• For facilities with multiple emission points, peak 1-hour emissions were assumed to 

occur at all emission points at the same time.

• For facilities with multiple emission points, 1-hour concentrations at each receptor 

were assumed to be the sum of the maximum concentrations due to each emission 

point, regardless of whether those maximum concentrations occurred during the same 

hour. 

• Worst-case meteorology (from one year at the nearest NWS site) was assumed to 

occur at the same time the peak emission rates occur. The recommended EPA localscale dispersion model, AERMOD, was used for simulating atmospheric dispersion 

during this worst-case hour.

• A person was assumed to be located downwind at the point of maximum modeled 

impact during this same worst-case 1-hour period, but no nearer to the source than 100 

meters. As a result, the maximum modeled 1-hour off-site concentration equals the 

worst-case acute exposure concentration.

• The maximum impact was compared to multiple short-term health benchmarks for the 

HAP being assessed to determine if a possible acute health risk might exist. These 

benchmarks are described in section 2.6 of this report.

As mentioned above, when we identify acute impacts which exceed their relevant 

benchmarks, we pursue refining our acute screening estimates to the extent possible. In some 

cases, this may include the use of a facility-specific emissions multiplier to estimate the peak 

hourly emission rates from the average rates (rather than the default factor of 10). In other 

cases, this may entail determining the actual physical layout and boundaries of a facility to 

more accurately gauge where people might reasonably be exposed for an hour.

2.5 Multipathway human health and environmental risk screening

The potential for significant human health risks and adverse environmental impacts due to 

exposures via routes other than inhalation (i.e., multipathway exposures) was screened by first 

determining whether any sources emitted any hazardous air pollutants known to be persistent 

and bioaccumulative in the environment (PB-HAP)2. The PB-HAP compounds or compound 

classes are identified for the screening from the EPA’s Air Toxics Risk Assessment Library 

[8], and they are cadmium compounds, chlordane, chlorinated dibenzodioxins and furans, 

DDE, heptachlor, hexachlorobenzene, hexachlorocyclohexane, lead compounds, mercury 

compounds, methoxychlor, polychlorinated biphenyls, polycyclic organic matter (POM), 

toxaphene, and trifluralin. Emissions of 5 different PB-HAP were identified in the emissions 

inventory for the Secondary Lead Smelting source category; they are POM, dioxins, 

cadmium, mercury, and lead. With respect to PB-HAP other than lead, emissions were 

evaluated for potential non-inhalation risks and adverse environmental impacts using our 

recently-developed screening scenario which was developed for use with the TRIM.FaTE3

model. This screening scenario uses environmental media outputs from the peer-reviewed 

10
4 EPA’s Human Health Risk Assessment Protocol (HHRAP) for Hazardous Waste Combustion Facilities;

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

5

In both scenarios, exposure via drinking water was not considered because it is unlikely that humans would use 

TRIM.FaTE to estimate the maximum potential ingestion risks for any specified emission 

scenario by using a generic farming/fishing exposure scenario that simulates a subsistence 

environment. The screening scenario retains many of the ingestion and scenario inputs 

developed for EPA’s Human Health Risk Assessment Protocols (HHRAP) for hazardous 

waste combustion facilities.4In the development of the screening scenario a sensitivity 

analysis was conducted to ensure that its key design parameters were established such that 

environmental media concentrations were not underestimated, and to also minimize the 

occurrence of false positives for human health endpoints. See Appendix 4 for a complete 

discussion of the development and testing of the screening scenario, as well as for the values 

of facility-level screening emission rates developed for screening potentially significant multipathway impacts. For the purpose of developing screening emission rates for our multipathway screening, we derived emission levels for each PB HAP at which the maximum 

human health risk would be 1 in a million for lifetime cancer risk or a hazard quotient of 1.0 

for noncancer impacts. 

For the secondary lead smelting source category, there were exceedences of screening

emissions rates at multiple facilities for multiple PB-HAP, and thus a multipathway analysis 

was performed. Two facilities were chosen as case study analyses to assess potential 

multipathway risks for mercury, cadmium, POM, and dioxins and furans. The selection 

criteria for modeling these two facilities included emissions rates of PB-HAPs, proximity to 

water bodies, proximity to farmland, average rainfall, average wind speed and direction, 

smelting furnace type, local change in elevation, and geographic representativeness of sites 

throughout the US. As a result of our selection process, we believe the multipathway risks 

associated with these two facilities are in the upper end of the potential for multipathway risks 

from the source category. Since the modeling used in these case study assessments utilize site 

specific parameters to describe naturally occurring physical, chemical and biological 

processes, we believe that the multimedia concentrations of PB-HAPs generated in this 

analysis are unbiased estimates of the true impacts. 

In general, results of this assessment were designed to characterize multipathway risks 

associated with high end consumption of PB-HAP predominantly from contaminated food 

sources. Thus, multipathway exposure and risk estimates were calculated for two basic 

scenarios, both of which are expected to give rise to high-end exposures and risks. The 

farmer scenario involves an individual living on a farm homestead in the vicinity of a PBHAP source who consumes contaminated produce grown on the farm, as well as 

contaminated meat and animal products raised on the farm. The farming scenario also 

accounts for incidental ingestion of contaminated surface soil at the location of the farm 

homestead. The recreational fisher scenario involves an individual who regularly consumes 

fish caught in freshwater lakes in the vicinity of a PB-HAP source. In the fishing scenario, in 

addition to the characterization of exposure and risks across the broad population of 

recreational anglers, exposures were also calculated for three subpopulations of recreational 

anglers (Hispanic, Laotian, and Vietnamese descent) who have higher rates of fish 

consumption5. Furthermore, in order to more fully characterize the modeled potential 

11
surface waters as a drinking water source. Groundwater, which is a likely source of drinking water, also was not 

included in the exposure scenarios because contamination of groundwater aquifers by air deposition sources was 

not expected to be significant. For dioxin, exposure via breast milk was considered in the farming scenario as 

well as the recreational fishing scenario, but not for the three recreational fishing subpopulations (Hispanic, 

Laotian, and Vietnamese descent) since subpopulation ingestion rates were only applicable to adult males. The 

breast milk pathway was not considered with respect to mercury exposure due to a current lack of data regarding 

this pathway.

multipathway risks that may be associated with high-end consumption of PB-HAP 

contaminated food, we present results based on two ingestion exposure scenarios: 1) a 

reasonable maximum exposure (RME) scenario that, for example, utilizes 90th percentile 

ingestion rates for farmers, recreational anglers, and the three subpopulations of recreational 

anglers (e.g., ingestion rates specific to Laotian recreational anglers); and 2) a central 

tendency exposure (CTE) scenario that for example, utilizes mean ingestion rates for the 

groups just described. We provide results from both scenarios to illustrate the range of 

potential modeled exposures and risks that may exist in the high-end of the complete 

distribution of potential multipathway risks for this source category.

In evaluating the potential multi-pathway risks from emissions of lead compounds, rather than 

developing a screening emission rate, we compared maximum estimated chronic (3-month 

average) atmospheric concentrations with the current primary National Ambient Air Quality 

Standard (NAAQS) for lead. The current primary National Ambient Air Quality Standard 

(NAAQS) for lead, which is set to a level of 0.15 μg/m3 based on a rolling 3-month averaging 

period with a not-to-be-exceeded form (see 73 FR 66964). Notably, in making these 

comparisons, we estimated maximum rolling 3-month ambient lead concentrations taking into 

account all of the elements of the NAAQS for lead. That is, our estimated 3-month lead 

concentrations are calculated in a manner that is consistent with the indicator, averaging time, 

and form of the NAAQS for lead, and those estimates are compared to the actual level of the 

lead NAAQS (0.15 μg/m3). Values below the NAAQS were considered to have a low 

potential for multi-pathway 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 quality 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 because 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 site-specific dispersion 

modeling used in this assessment to estimated ambient lead concentrations due to secondary 

lead smelting 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 health of children and other at-risk populations against an array 

12
of adverse health effects, most notably including neurological effects, particularly 

neurobehavioral and neurocognitive effects, in children (73 FR 67007). The Administrator, in 

setting the standard, also recognized that no evidence-or risk based bright line indicated a 

single appropriate level. Instead a 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 NAAQS, 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.

We also evaluated the potential for significant direct environmental exposures to HAP (other 

than lead) by evaluating the potential for exceedances of chronic human health inhalation 

thresholds in the ambient air near these facilities. Human health dose-response threshold 

values are generally derived from studies conducted on laboratory animals (such as rodents) 

and developed with the inclusions of uncertainty factors that could be as high as 3000. As a 

result, these human thresholds are often significantly lower than the level expected to cause 

an adverse effect in an exposed rodent. It should be noted that there is a scarcity of data on 

the direct atmospheric impact of these HAP on other receptors, such as plants, birds, and 

wildlife. Thus, if the maximum inhalation hazard in an ecosystem is below the level of 

concern for humans, we have generally concluded that mammalian receptors should be at no 

risk of adverse effects due to inhalation exposures from non PB-HAP, and have assurance that 

other ecological receptors are also not at any significant risk from direct atmospheric impact. 

In some isolated cases where we have data indicating potential adverse impacts on plants, 

birds, or other wildlife due to the direct atmospheric impacts of specific HAP, we note that as 

an uncertainty and, where possible, refine our analysis by comparing our modeled impacts to 

available threshold values from the scientific literature.

2.6 Dose-response assessment

2.6.1 Sources of chronic dose-response information 

Dose-response assessment (carcinogenic and non-carcinogenic) for chronic exposure (either 

by inhalation or ingestion) for the HAP reported in the emissions inventory for the Secondary 

Lead Smelting sources were based on the EPA Office of Air Quality Planning and Standards’ 

(OAQPS) existing recommendations for HAP [9], 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. The prioritization process was aimed at incorporating into our assessments the best 

available science with respect to dose-response information. The recommendations are based 

on the following sources, in order of priority: 

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

13
assessments for chronic exposure for many of the pollutants in this study. These 

assessments typically provide a qualitative statement regarding the strength of 

scientific data and specify a reference concentration (RfC, for inhalation) or reference 

dose (RfD, for ingestion) to protect against effects other than cancer and/or a unit risk 

estimate (URE, for inhalation) or slope factor (SF, for ingestion) to estimate the 

probability of developing cancer. The RfC is defined as an “estimate (with 

uncertainty spanning perhaps an order of magnitude) of a continuous inhalation 

exposure to the human population (including sensitive subgroups) that is likely to be 

without an appreciable risk of deleterious effects during a lifetime.” The RfD is “an 

estimate (with uncertainty spanning perhaps an order of magnitude) of a daily oral 

exposure to the human population (including sensitive subgroups) that is likely to be 

without an appreciable risk of deleterious effects during a lifetime.” The URE is 

defined as “the upper-bound excess cancer risk estimated to result from continuous 

lifetime exposure to an agent at a concentration of 1 μg/m3in air.” The SF is “an 

upper bound, approximating a 95% confidence limit, on the increased cancer risk from 

a lifetime exposure to an agent. This estimate, [is] usually expressed in units of 

proportion (of a population) affected per mg/kg-day...” EPA disseminates doseresponse 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 review. 

The current IRIS process includes review by EPA scientists, interagency reviewers 

from other federal agencies, and the public, and peer review by independent scientists 

external to EPA. New IRIS values are developed and old IRIS values are updated as 

new health effects data become available. Refer to the “IRIS Track” website for 

detailed information on status and scheduling of current individual IRIS assessments 

and updates (http://cfpub.epa.gov/ncea/iristrac/index.cfm). EPA’s science policy 

approach, under the current carcinogen guidelines, is to use linear low-dose 

extrapolation as a default option for carcinogens for which the mode of action (MOA) 

has not been identified. We expect future EPA dose-response assessments to identify 

nonlinear MOAs where appropriate, and we will use those analyses (once they are 

peer reviewed) in our risk assessments. At this time, however, there are no available 

carcinogen dose-response assessments for inhalation exposure that are based on a 

nonlinear MOA.

2) US Agency for Toxic Substances and Disease Registry (ATSDR). ATSDR, which is part 

of the US Department of Health and Human Services, develops and publishes Minimum 

Risk Levels (MRLs) [12] for inhalation and oral exposure to many toxic substances. As 

stated on the ATSDR web site: “Following discussions with scientists within the 

Department of Health and Human Services (HHS) and the EPA, ATSDR chose to adopt a 

practice similar to that of the EPA's Reference Dose (RfD) and Reference Concentration 

(RfC) for deriving substance specific health guidance levels for non neoplastic 

endpoints.” The MRL is defined as “an estimate of daily human exposure to a substance 

that is likely to be without an appreciable risk of adverse effects (other than cancer) over a 

specified duration of exposure.” ATSDR describes MRLs as substance-specific estimates 

to be used by health assessors to select environmental contaminants for further evaluation. 

14
6 Air Toxics Hot Spots Program, Risk Assessment Guidelines, Part III - Technical Support Document

for the Determination of Non-cancer Chronic Reference Exposure Levels. Air Toxicology and Epidemiology 

Section, Office of Environmental Health Hazard Assessment, California Environmental Protection Agency. 

February 2000 (http://www.oehha.ca.gov/air/chronic_rels/pdf/relsP32k.pdf)

Exposures above an MRL do not necessarily represent a threat, and MRLs are therefore 

not intended for use as predictors of adverse health effects or for setting cleanup levels.

3) California Environmental Protection Agency (CalEPA). The CalEPA Office of 

Environmental Health Hazard Assessment has developed dose-response assessments for 

many substances, based both on carcinogenicity and health effects other than cancer. The 

process for developing these assessments is similar to that used by EPA to develop IRIS 

values and incorporates significant external scientific peer review. As cited in the 

CalEPA Technical Support Document for developing their chronic assessments6: “The 

guidelines for developing chronic inhalation exposure levels incorporate many 

recommendations of the U.S. EPA [13] and NAS [14].” The non-cancer information 

includes available inhalation health risk guidance values expressed as 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 information 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 is used as a surrogate for other 

compounds in the group for which dose-response values are not available. This is done in 

order to examine, under conservative assumptions, whether these HAPs that lack doseresponse values may pose an unacceptable risk and require further examination, or screen 

out from further assessment. 

2) Where possible for emissions of unspecified mixtures of HAP categories such as metal 

compounds and POM (see Tables 2.6-1 (a) to 2.6-1 (c), 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/m3) was based on better 

science than the IRIS dose-response value (1.3 x 10-5 per μg/m3), and we switched from 

using the IRIS value to the CIIT value in risk assessments supporting regulatory actions. 

Based on subsequent published research, however, EPA changed its determination 

regarding the CIIT model and in 2010 the EPA returned to using 1991 IRIS value EPA 

has been working on revising the formaldehyde IRIS assessment and the National 

Academy of Sciences (NAS) completed its review of the EPA’s draft assessment in May 

of 2011 (http://www.nap.edu/catalog.php?record_id=13142). EPA is reviewing the public 

comments and the NAS independent scientific peer review. EPA will follow the NAS 

15
Report recommendations and will present results obtained by implementing the CIIT 

BBDR model for formaldehyde. EPA will compare these estimates with those currently 

presented in the External Review draft of the assessment and will discuss their strengths 

and weaknesses. As recommended by the NAS committee, appropriate sensitivity and 

uncertainty analyses will be an integral component of implementing the BBDR model. 

The draft IRIS assessment will be revised in response to the NAS peer review and public 

comments and the final assessment will be posted on the IRIS database. In the interim, 

we will present findings using the 1991 IRIS value as a primary estimate, and may also 

consider other information as the science evolves.

4) Emissions from secondary lead smelting facilities include POM. A substantial proportion 

of POM reported to EPA’s national emission inventory (NEI) are not speciated into 

individual compounds. As a result, it is necessary to apply the same simplifying 

assumptions to assessments that were used for the 1999 NATA study [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. 

The emissions inventory for the Secondary Lead Smelting source category includes emissions 

of HAP with available chronic quantitative inhalation dose-response values. These HAP, 

their dose-response values, and the source of the values are listed in Tables 2.6-1 (a) through 

(c).

16
7 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/m3in air. URE’s are considered upper bound estimates meaning they represent 

a plausible upper limit to the true value. 

8 Chemical Abstract Services identification number. For groups of compounds that lack a CAS number we have 

used a surrogate 3-digit identifier corresponding to the group’s position on the CAA list of HAPs.

9 Assigned the URE associated with a mixture of POM compounds having a similar potency. Details of this 

method, also used in the 1999 National Air Toxics Assessment, are available at 

http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf

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

Carcinogens

URE (unit risk estimate for cancer)7 = cancer risk per μg/m3 of average lifetime exposure. 

Sources: IRIS = EPA Integrated Risk Information System, CAL = California EPA Office of 

Environmental Health Hazard Assessment, EPA/OAQPS = interim value recommended by the 

EPA Office of Air Quality Planning and Standards. EPA ORD = EPA Office of Research and 

Development

Pollutant CAS Number8 URE5

(1/μg/m3)

Source

1,1,2,2-Tetrachloroethane 79345 0.000058 IRIS

1,3-Dichloropropene 542756 0.000004 IRIS

1,3-Butadiene 106990 0.00003 IRIS

2,3,7,8-TCDD TEQ 1746016 33 EPA ORD

Acetaldehyde 75070 2.2E-06 IRIS

Acrylonitrile 75058 0.000068 IRIS

Arsenic 7440382 4.3E-03 IRIS

Benzene 71432 7.8E-06 IRIS

Bis(2-Ethylhexyl)Phthalate 117817 2.4E-06 CAL

Beryllium 7440417 0.0024 IRIS

Cadmium 7440439 0.0018 IRIS

Chromium compounds

 

 Chromium (VI) 18540299 0.012 IRIS

Ethyl Benzene 100414 2.5E-06 CAL

Formaldehyde 50000 0.000013 IRIS

Methylene Chloride 75092 4.7E-07 IRIS

Polycyclic Organic Matter 246 9 EPA OAQPS

Chrysene 218019 1.1E-05 CAL

Benz[a]Anthracene 56553 1.1E-04 CAL

Benzo[b]Fluoranthene 205992 1.1E-04 CAL

Benzo[k]Fluoranthene 207089 0.00011 CAL

Indeno[1,2,3-c,d]Pyrene 193395 0.00011 CAL

Dibenzo[a,h]Anthracene 53703 0.0012 CAL

Naphthalene 91203 3.4E-05 CAL

Nickel 7440020 0.00009 ATSDR

Tetrachloroethylene 127184 5.9E-06 CAL

Trichloroethylene 79016 2.0E-06 CAL

17
10 The assessment report for dioxin is available in the docket for this Secondary Lead Smelting proposed 

rulemaking (see: Health Assessment Document for Polychlorinated Dibenzo-p-Dioxins; September, 1985)

Table 2.6-1 (b) Dose-Response Values for Chronic Oral Exposure to Carcinogens

SF (oral slope factor for cancer) = cancer risk per mg/kg/d of average lifetime exposure. Sources: IRIS 

= EPA Integrated Risk Information System, CAL = California EPA Office of Environmental Health 

Hazard Assessment, EPA/OAQPS = interim value recommended by the EPA Office of Air Quality 

Planning and Standards.

Pollutant CAS Number10 SF

(1/mg/kg/d)

Source

2,3,7,8-Tetrachlorodibenzo-p-dioxin 1746016 150000 EPA ORD10

Benzo(k)fluoranthene 207089 1.2 CAL

Polycyclic Organic Matter

 Dibenzo[a,h]Anthracene 53703 4.1 CAL

Indeno[1,2,3-c,d]Pyrene 193395 1.2 CAL

18
11 The descriptors L (low), M (medium), and H (high) have been added for IRIS RfC values to indicate the 

overall level of confidence in the RfC value, as reported in the IRIS file.

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

RfC (reference inhalation concentration) = an estimate (with uncertainty spanning perhaps an order of 

magnitude) of a continuous inhalation exposure to the human population (including sensitive subgroups) 

that is likely to be without an appreciable risk of deleterious effects during a lifetime. Sources: IRIS = EPA 

Integrated Risk Information System, CAL = California EPA Office of Environmental Human Health 

Assessment, ATSDR = US Agency for Toxic Substances Disease Registry. 

Pollutant CAS Number6 RfC 

(mg/m3)

Source11

1,3-Butadiene 106990 0.002 IRIS -- M

1,3-Dichloropropene 62737 0.0005 IRIS -- H

2,3,7,8-TCDD TEQ 1746016 4E-08 CAL

Acetaldehyde 75070 0.009 IRIS -- L

Acrylonitrile 107131 0.002 IRIS -- M

Acrolein 107028 0.00002 IRIS -- L/M

Antimony 1309644 (trioxide) 0.0002 IRIS -- L

Arsenic 174 0.000015 CAL

Benzene 71432 0.03 IRIS -- M

Beryllium 7440417 0.00002 IRIS -- M

Bis(2-Ethylhexyl)Phthalate 117817 0.01 P-CAL

Cadmium 176 0.00001 ATSDR

Carbon Disulfide 75150 0.7 IRIS -- M

Chlorine 7782505 0.00015 D-ATSDR

Chlorobenzene 108907 1 CAL

Chloroform 67663 0.098 ATSDR

Chromium compounds

Chromium (VI) 18540299 0.0001 IRIS -- M

Cumene 98828 0.4 IRIS -- M

Ethyl Benzene 100414 1 IRIS -- L

Ethyl Chloride 75003 10 IRIS -- M

Formaldehyde 50000 0.0098 ATSDR

Hexane 110543 0.7 IRIS -- M

Hydrochloric Acid 7647010 0.02 IRIS -- L

Lead 182 0.00015 EPA OAQPS

Manganese 183 0.00005 IRIS -- M

Methyl Bromide 74873 0.09 IRIS -- M/H

Methyl Chloride 74873 0.09 IRIS -- M/H

Methylene Chloride 75092 1 ATSDR

Methyl Isobutyl Ketone 108101 3 IRIS -- L/M

Mercury Compounds

19
12 See: U.S. EPA. Graphical Arrays of Chemical-Specific Health Effect Reference Values for Inhalation 

Exposures [Final Report]. (U.S. Environmental Protection Agency, Washington, D.C., EPA/600/R-09/061, 

2009. http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=211003.)

Elemental Gaseous Mercury 7439976 0.0003 IRIS -- M

Gaseous Divalent Mercury

Particulate Divalent Mercury

Naphthalene 91203 0.003 IRIS -- M

Nickel 186 0.00009 ATSDR

o-Cresol 95487 0.6 (mixed) CAL

Phenol 108952 0.2 CAL

Propionaldehyde 123386 0.008 IRIS -- L/M 

Selenium 7782492 0.02 CAL

Styrene 100425 1 IRIS -- M

Tetrachloroethylene 79016 0.6 CAL

Trichloroethylene 79016 0.6 CAL

Toluene 108883 5 IRIS -- H

Xylenes (Mixture of o, m, and p Isomers) 1330207 0.1 IRIS

 m-Xylene 108383 0.1 IRIS -- M

 o-Xylene 95476 0.1 IRIS -- M

p-Xylene 106423 0.1 IRIS -- M

2.6.2 Sources of acute dose-response information 

Hazard identification and dose-response assessment information for preliminary acute 

inhalation exposure assessments are based on the existing recommendations of OAQPS for 

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 Emergency Response Planning Guidelines 

(ERPGs), with the recognition that the ultimate interpretation of any potential risks associated 

with an estimated exceedance of a particular reference level depends on the definition of that 

level and any limitations expressed therein. Comparisons among different available 

inhalation health effect reference values (both acute and chronic) for selected HAPs can be 

found in an EPA document.12

California Acute Reference Exposure Levels (RELs). The California Environmental 

Protection Agency (CalEPA) has developed acute dose-response reference values for many 

substances, expressing the results as Acute inhalation Reference Exposure Levels (RELs). 

The acute REL (http://www.oehha.ca.gov/air/pdf/acuterel.pdf) is defined by CalEPA as 

“the concentration level at or below which no adverse health effects are anticipated for a 

specified exposure duration. [19]. 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 

20
uncertainties, exceeding the REL does not automatically indicate an adverse health 

impact.” Acute RELs are developed for 1-hour (and 8-hour) exposures. The values 

incorporate uncertainty factors similar to those used in deriving EPA’s Inhalation 

Reference Concentrations (RfCs) for chronic exposures (and, in fact, California also has 

developed chronic RELs).

Acute Exposure Guideline Levels (AEGLs). AEGLs are developed by the National Advisory 

Committee (NAC) on Acute Exposure Guideline Levels (NAC/AEGL) for Hazardous 

Substances, and then reviewed and published by the National Research Council. As 

described in the Committee’s “Standing Operating Procedures (SOP)” 

(http://www.epa.gov/opptintr/aegl/pubs/sop.pdf), AEGLs “represent threshold exposure limits 

for the general public and are applicable to emergency exposures ranging from 10 min to 8 

h.” Their intended application is “for conducting risk assessments to aid in the development 

of emergency preparedness and prevention plans, as well as real time emergency response 

actions, for accidental chemical releases at fixed facilities and from transport carriers.” The 

document states that “the primary purpose of the AEGL program and the NAC/AEGL 

Committee is to develop guideline levels for once-in-a-lifetime, short-term exposures to 

airborne concentrations of acutely toxic, high-priority chemicals.” In detailing the intended 

application of AEGL values, the document states that, “It is anticipated that the AEGL values 

will be used for regulatory and nonregulatory purposes by U.S. Federal and State agencies, 

and possibly the international community in conjunction with chemical emergency response, 

planning, and prevention programs. More specifically, the AEGL values will be used for 

conducting various risk assessments to aid in the development of emergency preparedness and 

prevention plans, as well as real-time emergency response actions, for accidental chemical 

releases at fixed facilities and from transport carriers.” The NAC/AEGL defines AEGL-1 and 

AEGL-2 as:

“AEGL-1 is the airborne concentration (expressed as ppm or mg/m3) of a substance above 

which it is predicted that the general population, including susceptible individuals, could 

experience notable discomfort, irritation, or certain asymptomatic nonsensory effects. 

However, the effects are not disabling and are transient and reversible upon cessation of 

exposure.”

“AEGL-2 is the airborne concentration (expressed as ppm or mg/m3) of a substance above 

which it is predicted that the general population, including susceptible individuals, could 

experience irreversible or other serious, long-lasting adverse health effects or an impaired 

ability to escape.”

“Airborne concentrations below AEGL-1 represent exposure levels that can produce mild 

and progressively increasing but transient and nondisabling odor, taste, and sensory 

irritation or certain asymptomatic, nonsensory effects. With increasing airborne 

concentrations above each AEGL, there is a progressive increase in the likelihood of 

occurrence and the severity of effects described for each corresponding AEGL. Although 

the AEGL values represent threshold levels for the general public, including susceptible 

subpopulations, such as infants, children, the elderly, persons with asthma, and those with 

other illnesses, it is recognized that individuals, subject to unique or idiosyncratic 

21
responses, could experience the effects described at concentrations below the 

corresponding AEGL.”

Emergency Response Planning Guidelines (ERPGs). The American Industrial Hygiene 

Association (AIHA) has developed Emergency Response Planning Guidelines (ERPGs) [20] 

for acute exposures at three different levels of severity. These guidelines represent 

concentrations for exposure of the general population (but not particularly sensitive persons) 

for up to 1 hour associated with effects expected to be mild or transient (ERPG-1), 

irreversible or serious (ERPG-2), and potentially life-threatening (ERPG-3). 

ERPG values (http://www.aiha.org/1documents/Committees/ERP-erpglevels.pdf) are 

described in their supporting documentation as follows: “Emergency Response Planning 

Guidelines (ERPGs) were developed for emergency planning and are intended as health based 

guideline concentrations for single exposures to chemicals. These guidelines (i.e., the ERPG 

Documents and ERPG values) are intended for use as planning tools for assessing the 

adequacy of accident prevention and emergency response plans, including transportation 

emergency planning and for developing community emergency response plans. The emphasis 

is on ERPGs as planning values: When an actual chemical emergency occurs there is seldom 

time to measure airborne concentrations and then to take action.” ERPG-1 and ERPG-2 

values are defined by AIHA as follows:

“ERPG-1 is the maximum airborne concentration below which it is believed that nearly 

all individuals could be exposed for up to 1 hour without experiencing other than mild 

transient adverse health effects or without perceiving a clearly defined, objectionable 

odor.” 

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

all individuals could be exposed for up to 1 hour without experiencing or developing 

irreversible or other serious health effects or symptoms which could impair an individual's 

ability to take protective action.”

The emissions inventory for the Secondary Lead Smelting source category includes emissions 

of numerous HAP with relevant and available quantitative acute dose-response threshold 

values. These HAPs, their acute threshold values, and the source of the value are listed below 

in Table 2.6-2.

Table 2.6-2 Dose-Response Values for Acute Exposure

Pollutant CAS Number AEGL-1

(1-hr)

(mg/m3

)

AEGL-2

(1-hr)

(mg/m3

)

ERPG-1

(mg/m3)

ERPG-2

(mg/m3)

REL 

1,3-Butadiene 106990 1500 12000 1500 12000

Acetaldehyde 75070 81 490 81 490 0.47

Acrolein 107028 0.069 0.23 0.069 0.23 0.0025

22
Acrylonitrile 107131 10 130 22 77

Antimony 1309644

Arsenic 7440382 0.0002

Benzene 71432 170 2600 170 2600 1.3

Beryllium 7440417 0.025

Biphenyl 92524 61

Carbon Disulfide 75150 40 500 40 500 6.2

Chlorine 7782505 1.5 5.8 1.5 5.8 0.21

Chlorobenzene 108907 46 690

Chloroform 67663 310 310 0.15

Cumene 98828 250 1500

Elemental Gaseous 

Mercury

7439976 1.7 2 .0006

Ethyl Benzene 100414 140 4800

Formaldehyde 50000 1.1 17 1.1 17 0.055

Hexane 110543 12000

Hydrochloric Acid 7647010 2.7 33 2.7 33 2.1

Methyl Bromide 74839 820 820 3.9

Methyl Chloride 74873

Methylene Chloride 75092 690 1900 690 1900 14

Methyl Iodide 74884 150 290

Nickel 7440020 0.006

Phenol 108952 58 89 58 89 5.8

Propionaldehyde 123386 110 620

Styrene 100425 85 550 85 550 21

Tetrachloroethylene 127184 240 1600 240 1600 20

Toluene 108883 750 4500 750 1900 37

Trichloroethylene 79016 700 2400 700 2400

Xylenes (Mixed) 1330207 560 4000 22

m-Xylene 108383 22

2.7 Risk characterization

2.7.1 General

The final product of the risk assessment is the risk characterization, in which the information 

from the previous steps is integrated and an overall conclusion about risk is synthesized that is 

complete, informative, and useful for decision makers. In general, the nature of this risk 

characterization depends on the information available, the application of the risk information 

and the resources available. In all cases, major issues associated with determining the nature 

and extent of the risk are identified and discussed. Further, the EPA Administrator’s March 

1995 Policy for Risk Characterization [21] specifies that a risk characterization “be prepared 

in a manner that is clear, transparent, reasonable, and consistent with other risk 

characterizations of similar scope prepared across programs in the Agency.” These principles 

of transparency and consistency have been reinforced by the Agency’s Risk Characterization 

23
13Memorandum for the Heads of Executive Departments and Agencies - Updated Principles for Risk Analysis 

(September 19, 2007), From Susan E. Dudley, Administrator, Office of Information and Regulatory Affairs, 

Office of Management and Budget; and Sharon L. Hays, Associate Director and Deputy Director for Science, 

Office of Science and Technology Policy (http://www.whitehouse.gov/omb/memoranda/fy2007/m07-24.pdf)

Handbook [22], in 2002 by the Agency’s information quality guidelines [23], and in the 

OMB/OSTP September 2007 Memorandum on Updated Principles for Risk Analysis13, and 

are incorporated in these assessments.

Estimates of health risk are presented in the context of uncertainties and limitations in the data 

and methodology. Through our tiered, iterative analytical approach, we have attempted to 

reduce both uncertainty and bias to the greatest degree possible in these assessments, within 

the limitations of available time and resources. We provide summaries of risk metrics 

(including maximum individual cancer risks and noncancer hazards, as well as cancer 

incidence estimates) along with a discussion of the major uncertainties associated with their 

derivation to provide decision makers with the fullest picture of the assessment and its 

limitations.

For each carcinogenic HAP included in an assessment that has a potency estimate available, 

individual and population cancer risks were calculated by multiplying the corresponding 

lifetime average exposure estimate by the appropriate URE. This calculated cancer risk is 

defined as the upper-bound probability of developing cancer over a 70-yr period (i.e., the 

assumed human lifespan) at that exposure. Because UREs for most HAPs are upper-bound 

estimates, actual risks at a given exposure level may be lower than predicted, and could be 

zero.

For EPA’s list of carcinogenic HAPs that act by a mutagenic mode-of-action [24], we applied 

EPA’s Supplemental Guidance for Assessing Susceptibility from Early-Life Exposure to 

Carcinogens [25]. This guidance has the effect of adjusting the URE by factors of 10 (for 

children aged 0-1), 3 (for children aged 2-15), or 1.6 (for 70 years of exposure beginning at 

birth), as needed in risk assessments. In this case, this has the effect of increasing the 

estimated life time risks for these pollutants by a factor of 1.6. In addition, although only a 

small fraction of the total POM emissions may be reported as individual compounds, EPA 

expresses carcinogenic potency for compounds in this group in terms of benzo[a]pyrene 

equivalence, based on evidence that carcinogenic POM have the same mutagenic mechanism 

of action as does benzo[a]pyrene. For this reason, EPA implementation policy [26] 

recommends applying the Supplemental Guidance to all carcinogenic PAHs for which risk 

estimates are based on relative potency. Accordingly, we applied the Supplemental Guidance 

to all unspeciated POM mixtures.

Increased cancer incidence for the entire receptor population within the area of analysis was 

estimated by multiplying the estimated lifetime cancer risk for each census block by the 

number of people residing in that block, then summing the results for the entire modeled 

domain. This lifetime population incidence estimate was divided by 70 years to obtain an 

estimate of the number of cancer cases per year.

In the case of benzene, the high end of the reported cancer URE range was used in our 

24
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 evaluated the impact of using the low end of the URE range on our risk 

results.

Unlike linear dose-response assessments for cancer, noncancer health hazards generally are 

not expressed as a probability of an adverse occurrence. Instead, “risk” for noncancer effects 

is expressed by comparing an exposure to a reference level as a ratio. The “hazard quotient” 

(HQ) is the estimated exposure divided by a reference level (e.g., the RfC). For a given HAP, 

exposures at or below the reference level (HQ≤1) are not likely to cause adverse health 

effects. As exposures increase above the reference level (HQs increasingly greater than 1), 

the potential for adverse effects increases. For exposures predicted to be above the RfC, the 

risk characterization includes the degree of confidence ascribed to the RfC values for the 

compound(s) of concern (i.e., high, medium, or low confidence) and discusses the impact of 

this on possible health interpretations. 

The risk characterization for chronic effects other than cancer is expressed in terms of the HQ 

for inhalation, calculated for each HAP at each census block centroid. As discussed above, 

RfCs incorporate generally conservative uncertainty factors in the face of uncertain 

extrapolations, such that an HQ greater than one does not necessarily suggest the onset of 

adverse effects. The HQ cannot be translated to a probability that adverse effects will occur, 

and is unlikely to be proportional to adverse health effect outcomes in a population.

Screening for potentially significant acute inhalation exposures also followed the HQ 

approach. We divided the maximum estimated acute exposure by each available short-term 

threshold value to develop an array of HQ values relative to the various acute endpoints and 

thresholds. In general, when none of these HQ values are greater than one, there is no 

potential for acute risk. In those cases where HQ values above one are seen, additional 

information is used to determine whether there is a potential for significant acute risks.

2.7.2 Mixtures

Since most or all receptors in these assessments receive exposures to multiple pollutants 

rather than a single pollutant, we estimated the aggregate health risks associated with all the 

exposures from a particular source category combined.

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

[27,28] default assumption of additivity of effects, and combine risks by summing them using 

the independence formula in the mixtures guidelines.

In assessing noncancer hazard from chronic exposures, in cases where different pollutants 

cause adverse health effects via completely different modes of action, it may be inappropriate 

to aggregate HQs. In consideration of these mode-of-action differences, the mixtures 

guidelines support aggregating effects of different substances in specific and limited ways. 

Consistent with these guidelines, we aggregated non-cancer HQs of HAPs that act by similar 

25
toxic modes of action, or (where this information is absent) that affect the same target organ. 

This process creates, for each target organ, a target-organ-specific hazard index (TOSHI), 

defined as the sum of hazard quotients for individual HAPs that affect the same organ or 

organ system. All TOSHI calculations presented here were based exclusively on effects 

occurring at the “critical dose” (i.e., the lowest dose that produces adverse health effects). 

Although HQs associated with some pollutants have been aggregated into more than one 

TOSHI, this has been done only in cases where the critical dose affects more than one target 

organ. Because impacts on organs or systems that occur above the critical dose have not been 

included in the TOSHI calculations, some TOSHIs may have been underestimated. As with 

the HQ, the TOSHI should not be interpreted as a probability of adverse effects, or as strict 

delineation of “safe” and “unsafe” levels. Rather, the TOSHI is another measure of the 

potential for adverse health outcomes associated with pollutant exposure, and needs to be 

interpreted carefully by health scientists and risk managers.

Because of the conservative nature of the acute inhalation screening and the variable nature of 

emissions and potential exposures, acute impacts were screened on an individual pollutant 

basis, not using the TOSHI approach.

2.7.3 Facility-wide risks

To help place the source category risks in context, we typically examine “facility-wide” risks 

using facility-wide and source category data files developed by EPA through emission data 

updates from industry and refined EPA profiles for the source category. In this instance, there 

are no other significant HAP emission sources present-- all significant HAP sources have 

been included in the source category risk analysis. Therefore, the facility-wide risk is 

essentially the same as the source category risk; no separate facility-wide analysis was 

necessary.

3 Risk results for the secondary lead source category

3.1 Source category description and results

26
The secondary lead smelting source category consists of facilities that use blast, rotary, 

reverberatory, and/or electric furnaces to recover lead metal from lead-bearing scrap 

materials, primarily lead-acid batteries. The secondary lead smelting process consists of: (1) 

breaking lead-acid batteries and separating the lead-bearing materials from the other materials 

(including the plastic case material and acid electrolyte); (2) melting lead metal and reducing 

lead compounds to lead metal in the smelting furnace; and (3) refining and alloying the lead 

to customer specifications. HAP are emitted from secondary lead smelters as: (1) process 

emissions contained in the primary exhaust of smelting furnaces; (2) process fugitive 

emissions associated with charging and tapping of smelting furnaces and lead refining kettles; 

and (3) fugitive dust emissions from wind or mechanically induced entrainment of dust from 

stockpiles, plant yards, and roadways. A complete description of the secondary lead smelting 

source category can be found in the text of the Notice of Proposed Rulemaking (NPRM): 

National Emissions Standards for Hazardous Air Pollutants: Secondary Lead Smelting. 

There are currently 15 secondary lead smelters operating in the U.S. and Puerto Rico. The 

NPRM data set for the secondary lead smelting category contains 14 facilities identified with 

a secondary lead smelting MACT code in the 2005 National-Scale Air Toxics Assessment 

(NATA) National Emissions Inventory (NEI), September 2010 version. All 14 of these 

facilities are identified as major sources in the NEI. 

The emissions in the secondary lead smelting source category NPRM data set (of 15 facilities) 

are summarized in Table 3.1-1. The total HAP emissions for the source category are 

approximately 670 tons per year. Based on these data, 22 HAP account for 99 percent of the 

mass of HAP emitted across the 15 facilities in the NPRM data set. Air emissions from 

secondary lead smelter facilities include a number of toxic air pollutants, including metals 

(e.g., lead, arsenic, chromium, cadmium) and organic and inorganic compounds. Organic 

toxic air pollutants emitted from secondary lead smelting include compounds such as 

polycyclic organic matter (POM), styrene, carbon disulfide, and dioxins/furans.

27
Table 3.1-1 Summary of Emissions from the Secondary Lead Source Category and Availability of 

Dose-Response Values

HAPa Emission 

Estimates 

(tpy)

Number of 

Facilities 

where HAP 

Reported or 

Estimated 

(15 facilities 

in NPRM 

data set)

Prioritized Inhalation Dose-Response Value 

Identified by OAQPSb

PBHAP?

Unit Risk 

Estimate for 

Cancer?

Reference 

Concentration 

for Noncancer?

Health 

Benchmark 

Values for Acute 

Noncancer?

Styrene 361 14 * *

Carbon Disulfide 96 14 * *

Methyl Isobutyl Ketone 50 14 *

p-Xylene 36 14 * *

Methyl Chloride 33 14 * *

Lead compounds 20 15 c *

Benzene 11 14 * * *

Toluene 11 14 * *

Bis(2-Ethylhexyl)Phthalate 8 14 * *

1,3-Butadiene 5 14 * * *

Acetaldehyde 4 14 * * *

Biphenyl 4 14 *

m-Xylene 3 14 * *

Arsenic compounds 3 15 * * *

n-Hexane 3 14 * *

Ethyl Benzene 2 14 * * *

Phenol 2 14 * *

Hydrochloric Acid 2 7 * *

Naphthalene 2 14 * *

Ethyl Chloride 2 14 *

Acrolein 2 14 * *

o-Xylene 1 14 * *

Methyl Bromide 0.9 14 * *

Antimony compounds 0.8 15 *

Acetophenone 0.8 14

Chlorobenzene 0.7 14 * *

Methylene Chloride 0.5 14 * * *

Selenium compounds 0.5 15 *

Polycyclic Organic Matter

POM 77002 0.5 14 * *

POM 76002 0.2 14 * *

POM 75002 0.0009 14 * *

POM 71002 0.0003 1 * *

POM 72002 0.000003 4 * *

28
POM 73002 0.0000007 3 * *

Methyl Iodide 0.4 14 *

Manganese compounds 0.4 15 *

Cadmium compounds 0.4 15 * * *

o-Cresol 0.3 14 *

1,3-Dichloropropene 0.3 14 * *

Formaldehyde 0.2 14 * * *

Nickel compounds 0.1 15 * * *

Mercury compounds

Mercury (elemental) 0.1 15 * * *

Mercuric Chloride 0.04 15 * *

Chloroform 0.1 14 * *

Cumene 0.1 14 * *

Acrylonitrile 0.08 14 * * *

Chromium compounds

Chromium (III) 0.08 15

Chromium (VI) 0.002 15 * *

Dibutylphthalate 0.04 14

Beryllium compounds 0.001 15 * * *

Xylenes (mixed) 0.0004 2 * *

p-Dichlorobenzene 0.00005 3 * *

2,3,7,8-TCDD TEQ 0.00004 14 * * *

Cobalt compounds 0.00001 5 *

a

 Notes for how HAP were speciated for risk assessment:

• For most metals, emissions reported as the elemental metal are combined with metal compound emissions (e.g., 

“cadmium” emissions modeled as “cadmium & compounds”). In the absence of speciation information, we assume the 

reported mass is 100 percent metal.

• For emissions reported generically as “chromium” or “chromium & compounds,” emissions are speciated for this 

category as about 99 percent “chromium (III) compounds” and about 1 percent “chromium (VI) compounds.” 

Chromium speciation profiles can be found on the EPA’s Technology Transfer Network website for emissions 

inventories at http://www.epa.gov/ttn/chief/net/2002inventory.htm;#inventorydata. 

• For emissions reported generically as “mercury” or “mercury & compounds,” emissions are speciated for this category 

as 80 percent “mercury (elemental)” 10 percent “mercuric chloride,” and 10 “percent particulate bound mercury” 

Mercury speciation profiles can be found on the EPA’s Technology Transfer Network website for emissions inventories 

at http://www.epa.gov/ttn/chief/net/2005inventory.html#inventorydata. 

• For emissions of any chemicals or chemical groups classified as polycyclic organic matter (POM), emissions were 

grouped into POM subgroups as found on EPA’s Technology Transfer Network website for the 2002 National-Scale Air 

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

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

toxics at http://www.epa.gov/ttn/atw/toxsource/summary.html.

c There is no reference concentration for lead. In considering noncancer hazards for lead in this assessment, we compared 

rolling three-month average exposure estimates to the National Ambient Air Quality Standards (NAAQS) for lead 

(0.15 μg/m3). These NAAQS for lead were recently reviewed with revisions adopted in October 2008 

(http://www.epa.gov/air/lead/actions.html). The primary (health-based) standard is a maximum or not-to-be-exceeded, 

rolling three-month average, measured as total suspended particles (TSP). The secondary (welfare-based) standard is 

identical to the primary standard. 

d Most of the test results for mercury emissions for this industry were below detection limit. The emissions estimates 

presented in this table are based on the assumption that all the non-detect test values were at the level of the detection limit. 

29
Therefore, these estimated emissions for mercury are clear overestimates. We conclude that the true amounts of emissions of 

mercury from this source category are much lower than shown here, but we are not able to quantify precisely how much 

lower. 

3.2 Baseline risk characterization

This section presents the results of the risk assessment for the secondary lead smelting source 

category based on the modeling methods described in the previous sections. All baseline risk 

results are developed using the best estimates of actual HAP emissions summarized in the 

previous section. The basic chronic inhalation risk estimates presented here are the maximum 

individual lifetime cancer risk, the maximum target organ specific chronic hazard index, and 

the cancer incidence. We also present results from our acute inhalation impact screening 

assessments in the form of maximum hazard quotients, as well as the results of our screen for 

potential non-inhalation risks from PB HAP. Also presented are the HAP “drivers,” which 

are the HAP that collectively contribute 90 percent of the maximum cancer risk or maximum 

hazard at the highest exposure location, A detailed summary of the facility-specific risk 

assessment results is available in Appendix 5.

Tables 3.2-1 and 3.2-2 summarize the preliminary chronic and acute inhalation risk results for 

this source category. The results of the chronic inhalation cancer risk assessment estimate the 

maximum lifetime individual cancer risk, considering both fugitive and stack emissions could 

be as high as 50 in a million. The maximum cancer risks for this source category exceeded a 

cancer risk of 1 in a million at all 15 facilities, with fugitive dust emissions of arsenic and 

cadmium dominating the risk. The total estimated cancer incidence from this source category 

based on actual emission levels is 0.02 excess cancer cases per year, or one excess case in 

every 50 years. Approximately 700 people were estimated to have cancer risks above 10 in a 

million and approximately 80,000 people were estimated to have cancer risks above 1 in a 

million considering all facilities in this source category. Considering MACT allowable 

emissions, the MIR could be as high as 200.

With respect to chronic inhalation noncancer risk, we estimate a maximum TOSHI value of 

0.6 for the secondary lead source category, with fugitive dust emissions of cadmium and 

arsenic dominating those impacts. In contrast, we note that considering MACT allowable 

emissions, we estimate a maximum TOSHI value of 3, driven primarily by emissions of 

arsenic from stacks.

30
Table 3.2-1 Summary of Source Category Level Inhalation Risks for Secondary Lead 

Smelting

Result HAP “Drivers”

Facilities in Source Category

Number of Facilities Estimated to be in Source 

Category

15 n/a

Number of Facilities Identified in NEI and 

Modeled in Risk Assessment

15 n/a

Cancer Risks

Maximum Individual Lifetime Cancer Risk (in 

1 million)

50 arsenic compounds, cadmium 

compounds

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

5 arsenic compounds, cadmium 

compounds, 2,3,7,8-

tetrachlorodibenzo-p-dioxin

Greater than or equal to 1 in 1 million 15 arsenic compounds, cadmium 

compounds, 2,3,7,8-

tetrachlorodibenzo-p-dioxin, 1,3-

butadiene

Chronic Noncancer Risks

Maximum Developmental Hazard Index 0.6 cadmium compounds

Number of Facilities with Maximum Developmental Hazard Index:

Greater than 1 0 n/a

Acute Noncancer Screening Results

Maximum Acute Hazard Quotient 20 arsenic compounds (REL)

Number of Facilities With Potential for Acute 

Effects

8 arsenic compounds

Population Exposure

Number of People Living Within 50 

Kilometers of Facilities Modeled

26,000,000 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

700 n/a

Greater than or equal to 1 in 1 million 80,000 n/a

Number of People Exposed to Noncancer Developmental Hazard Index:

Greater than 1 0 n/a

Estimated Cancer Incidence (excess cancer 

cases per year)

0.02 n/a

Contribution of HAP to Cancer Incidence

arsenic compounds 74% n/a

cadmium compounds 13% n/a

2,3,7,8-tetrachlorodibenzo-p-dioxin 7% n/a

31
14 Individual facility acute HQ values for all facilities can be found in Appendix 5, Table 3. Acute HQ values 

exceeding a value of 1 were as follows: 2, 2, 2, 3, 4, 5, 20, and .20

15 Site selection criteria is described in detail in section 2.5.1 of the document Human Health Multipathway 

Residual Risk Assessment for the Secondary Lead Smelting Source Category, which can be found in the docket 

for the proposed rule. In brief, the criteria for selecting these two facilities as case studies included emission 

rates of PB-HAPs, proximity to water bodies, proximity to farmland, average rainfall, average wind speed and 

direction, smelting furnace type, local change in elevation, and geographic representativeness of sites throughout 

the US.

Based upon the REL as the acute assessment value for emissions of arsenic, screening-level 

acute HQ values could exceed a value of 1 at 8 facilities. In addition, this worst-case 

screening analysis estimates that the maximum acute HQ value for a facility in this source 

category could be as high as 20, at two facilities in this source category largely due to stack 

emissions of arsenic at the Exide Baton Rouge facility and due to a combination of stack and 

fugitive dust emissions of arsenic at the Doe Run facility.14. These results indicate that there 

may be some potential for acute health effects from emissions of arsenic from facilities in this 

source category. 

 

In the risk assessment to support the proposed rule, to identify potential multipathway health 

risks from PB-HAP other than lead we first performed a screening analysis that compared 

emissions of PB-HAP emitted from the secondary lead source category to multipathway 

screening emission rates (see section 2.5). In doing so, we estimated that emissions of 

cadmium, POM, and dioxin were above their respective screening emission rates. In addition, 

based on using high-end, worst-case assumptions for mercury (e.g., assuming that all nondetect emissions test values are equal to the detection limit) we estimated that mercury 

emissions could theoretically be emitted over the screening level emissions rate. Therefore, 

to be all inclusive, we also included mercury along with POM, cadmium and dioxins for the 

detailed multipathway analyses to support the proposed rule. More specifically, in the 

multipathway analyses to support the proposed rule, we performed two detailed case study 

analyses for these 4 PB-HAP in areas near the Frisco Battery Recycling (Frisco, TX) and 

Revere Smelting & Refining (Middletown, NY) facilities15. In these case study analyses, in 

order to more fully characterize the potential multipathway risks associated with high end 

consumption of PB-HAP contaminated food, we presented results based on RME and CTE 

scenarios. The RME scenario utilized 90th percentile ingestion rates for farmers, recreational 

anglers, and for three subpopulations of recreational anglers) who have higher rates of fish 

consumption (Hispanic, Laotian, and Vietnamese descent), while the CTE scenario utilized 

mean ingestion rates for each of these groups. In the detailed multipathway analysis and risk 

assessment to support the proposed rule, we provided results from both scenarios to illustrate 

the range of potential modeled exposures and risks that may exist in the high-end of the 

complete distribution of potential multipathway risks for the secondary lead smelting source 

category.

During the public comment period for the proposed rule, the Exide Frisco facility (i.e., one of 

32
the two case study facilities included in the detailed multipathway analysis to support the 

proposed rule) submitted updated emissions information relevant to the multipathway 

analysis. To update the multipathway case study assessment for the Exide, Frisco facility we 

scaled the cancer and non-cancer multipathway risks from the initial assessment based on the 

updated facility emissions information. As a result, we now estimate for both the RME and 

CTE scenarios, that the MIR cancer risk from POM and dioxins is less than 1 in a million for 

both case study facilities (note: there is no cancer slope factor for mercury and cadmium and 

thus, no cancer MIR was calculated). With respect to chronic noncancer risk, in both case 

studies, using both exposure scenarios, we did not estimate chronic HQ values greater than 1 

for dioxin, mercury (even using the conservative emission assumptions just mentioned above) 

or cadmium (note: there is no chronic noncancer reference value for POM and thus, a chronic 

noncancer HQ value was not calculated). 

As noted above (see section 2.5), in evaluating the potential for multipathway effects from 

emissions of lead, modeled maximum 3-month rolling average lead concentrations were 

compared to the NAAQS for lead. Results of this analysis, presented in Table 3.2-3, estimate 

that the NAAQS for lead could be exceeded at about 9 of 15 facilities, largely due to fugitive 

dust emissions. Moreover, this analysis estimates that 3-month maximum lead concentrations 

could be as high as about 20 times the NAAQS for lead and that more than half these facilities 

have estimated 3-month maximum lead concentrations that are at least 2 times higher than the 

NAAQS lead (again, largely due to fugitive dust emissions). As mentioned above, to evaluate 

the potential for adverse environmental effects, we also compared maximum 3-month rolling 

average atmospheric concentrations with the current secondary NAAQS for lead (which is 

identical to the primary, health-based standard). Thus, the analyses presented in Table 3.2-3 

indicate the potential for both adverse human health impacts and adverse environmental 

effects from emissions of lead.

Finally, with respect to lead we note that modeled lead concentrations associated with MACT 

allowable stack emissions would be significantly higher than those just discussed. For 

example, we estimate that based on allowable emissions from stacks alone, estimated lead 

levels could be between 8 and 10 times above the NAAQS at a couple of facilities.

33
Table 3.2-3 Secondary Lead Smelting Facility Modeled Maximum Ambient Lead Concentrations

(rolling three-month average values)

Facility Name City State Highest Lead 

Concentration 

(μg/m3)

Concentration is 

X times higher 

than the NAAQS

DOE RUN COMPANY-BUICK MILL BOSS MO 2.36 20

SANDERS LEAD CO TROY AL 2.16 10

EXIDE CORPORATION VERNON CA 1.14 8

EXIDE TECHNOLOGIES/B R SMELTER BATON ROUGE LA 0.14 0.9

GULF COAST RECYCLING, INC. TAMPA FL 0.38 3

EXIDE TECHNOLOGIES-CANON HOLLOW PLANT FOREST CITY MO 0.47 3

EXIDE TECH/READING SMELTER READING PA 0.25 2

GOPHER RESOURCE CORP EAGAN MN 0.35 2

FRISCO BATTERY RECYCLING FRISCO TX 0.32 2

QUEMETCO INC INDUSTRY CA 0.17 1

REVERE SMELTING & REFINING CORP MIDDLETOWN NY 0.10 0.7

EXIDE TECHNOLOGIES MUNCIE IN 0.15 1

EAST PENN MFG CO INC/SMELTER PLT LYON STATION PA 0.02 0.1

QUEMETCO, INC. INDIANAPOLIS IN 0.07 0.5

BATTERY RECYCLING CO. ARECIBO PR 0.76 5

3.3 Post-control risk characterization

As noted above, modeled lead concentrations exceed the NAAQS for lead at almost all 

facilities in this source category. Fugitive dust emissions are primarily driving exceedences 

of the lead NAAQS, as well as substantially contributing to the cancer MIR value of 50, and 

to acute HQ values greater than 1 (both based primarily on emissions of arsenic). Given this, 

using the same methodology described above, we estimated what the risks would be if the 

facilities noted in Table 3.2-3 adopted control measures to limit fugitive dust emissions. 

More specifically, at each of these facilities, we estimated risks considering a decrease in 

fugitive dust emissions resulting primarily from the assumption that all facilities would be 

fully enclosed with negative pressure air inflow to a control device plus implementation of 

effective work practices. We also considered a reduction of the MACT limit that would result 

in reduced actual stack emissions for two of these facilities: Doe Run and Exide Technologies 

Baton Rouge Smelter. Based on this scenario, we estimated (based on use of the same 

modeling assumptions and methodologies used for the baseline risk assessment) that all but 2 

facilities would meet the NAAQS for lead. Of these 2 facilities, 1 is projected to be very 

close to the NAAQS for lead. The other facility (Exide, CA) is estimated to be about 3 times 

above the NAAQS for lead (primarily driven by fugitive emissions).

With respect to cancer risk, given the fugitive controls mentioned above, the cancer MIR 

would be reduced from 50 in a million (i.e., pre-controls) to approximately 7 in a million (i.e., 

post-controls), with an estimated reduction in cancer incidence to 0.01 excess cancer cases per 

34
year. 

We finally note that post-control, the maximum worst-case acute screening HQ value would 

be reduced from a potential high of 20 (i.e., pre-controls) to 5 (i.e., post-controls). Moreover, 

post-control there would only be 1 other facility in the source category with a maximum worstcase acute refined HQ value greater than 1 (i.e., Doe Run would have an estimated acute HQ 

value of approximately 2 based on the REL for arsenic).

4 General discussion of uncertainties and how they have been 

addressed

4.1 Exposure modeling uncertainties

Although every effort has been made to identify all the relevant facilities and emission points, 

as well as to develop accurate estimates of the annual emission rates for all relevant HAP, the 

uncertainties in our emission inventory likely dominate the uncertainties in our exposure 

modeling estimates. The chronic exposure modeling uncertainties are considered relatively 

small in comparison, since we are using EPA’s refined local dispersion model with sitespecific parameters and reasonably representative meteorology. If anything, the population 

exposure estimates are biased high by not accounting for short- or long-term population 

mobility, and by neglecting processes like deposition, plume depletion, and atmospheric 

degradation. Additionally, estimates of the maximum individual risk (MIR) contain 

uncertainty, because they are derived at census block centroid locations rather than actual 

residences. This uncertainty is known to create potential underestimates and overestimates of 

the actual MIR values for individual facilities, but, overall, it is not thought to have a 

significant impact on the estimated MIR for a source category. Finally, we did not factor in 

the possibility of a source closure occurring during the 70-year chronic exposure period, 

leading to a potential upward bias in both the MIR and population risk estimates; nor did we 

factor in the possibility of population growth during the 70-year chronic exposure period, 

leading to a potential downward bias in both the MIR and population risk estimates.

A sensitivity analysis performed for the 1999 NATA found that the selection of the 

meteorology dataset location could result in a range of chronic ambient concentrations which 

varied from as much as 17% below the predicted value to as much as 84% higher than the 

predicted value. This variability translates directly to the predicted exposures and risks in our 

assessment, indicating that the actual risks could vary from 17% lower to 84% higher than the 

predicted values.

We have purposely biased the acute screening results high, considering that they depend upon 

the joint occurrence of independent factors, such as hourly emissions rates, meteorology and 

human activity patterns. However, we note that there is an unquantified level of uncertainty 

regarding the emission estimates and the nature of the worst-case conditions for estimating 

the worst-case impacts of acute emissions of fugitive dusts. The current set of assumptions 

used in deriving the estimate assumes the average hourly emission level (annual emissions 

divided by 8760 hours per year) to occur at the default worst-case meteorological conditions 

(low winds with a stable atmosphere). It is acknowledged that the combination of average 

35
16 Data for the general U.S. population of recreational anglers was obtained from: EPA 2002, “Estimated Per 

Capita Fish Consumption in the United States, Office of Water, Office of Science and Technology, Washington, 

D.C., EPA-821-C-02-003. August 2002.

17 Shilling et., al. 2010 is available in the docket for this rulemaking

emissions during low winds would be an overestimate of the fugitive dust emission rate 

during those low wind periods. Therefore, for fugitive dusts the worst-case meteorology may 

not be the same as for other process emissions. Additionally, the level of hourly fugitive dusts 

emissions during this alternate worst-case condition compared to the average hourly 

emissions is unknown. The actual risks may be higher or lower than the estimates based upon 

the current set of assumptions. 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 postcontrols, we refined our assessment by developing a better understanding of the geography of 

the facility relative to potential exposure locations. In this case, refining the assessment for 

the two facilities that had HQ values greater than 1 post-controls resulted in lower acute risks. 

As noted in section 2.5, two facilities were chosen as case study analyses to assess potential 

multipathway risks for mercury, cadmium, POM, and dioxins and furans. The selection 

criteria for modeling these two facilities included emissions rates of PB-HAPs, proximity to 

water bodies, proximity to farmland, average rainfall, average wind speed and direction, 

smelting furnace type, local change in elevation, and geographic representativeness of sites 

throughout the US. However, there is uncertainty as to whether these two facilities represent 

the highest potential for multipathway human health risks from the source category. 

Since the modeling used in these case study assessments utilize site specific parameters to 

describe naturally occurring physical, chemical and biological processes, we believe that the 

multimedia concentrations of PB-HAPs generated in this analysis are unbiased estimates of 

the true impacts. 

With respect to the risk estimates generated from this analysis, we present results based on 

two ingestion exposure scenarios: the RME and CTE scenarios (see section 2.5). As noted 

above, we believe that these scenarios illustrate the range of potential modeled exposures and 

risks that may exist in the high-end of the complete distribution of potential multipathway 

risks for this source category.

To estimate potential high-end multipathway exposures and risks, in addition to utilizing fish 

consumption rate data for the general US population of recreational anglers16, we used fish 

consumption information for distinct fisher subpopulations that are known to have higher fish 

consumption rates. The data were obtained from Shilling, et al. (2010).17 In this publication, 

the authors provide fish consumption information for different ethnic groups including 

Hispanics, Laotians, and Vietnamese surveyed in California’s Central Valley Delta based on 

sample sizes of 45, 33, and 30, respectively. We note that there is uncertainty based on the 

limited sample sizes and in the extrapolation of these fish consumption rates to other parts of 

the United States. However, we note that for the highest fish-consuming subpopulation 

(Laotian), the mean local per capita fish ingestion rate (47.2 g/day) is somewhat less than the 

36
18 EPA’s 1997 Exposure Factors Handbook is available at 

http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=12464

mean fish ingestion rate (70 g/day) for native American subsistence populations 

recommended by the EPA’s 1997 Exposure Factors Handbook18 and the 90th percentile per 

capita fish ingestion rate calculated from the Shilling study and used in this RTR assessment 

(144.8 g/day) is somewhat less than the 95th percentile fish ingestion rate recommended by the 

EPA’s 1997 Exposure Factors Handbook for native American subsistence populations. While 

comparing local per capita fish ingestion to total ingestion is a somewhat imperfect 

comparison, it does help us gauge how the values in the Shilling study compare to other 

existing data. All of these fish ingestion rates are significantly greater than the 90th percentile 

fish ingestion rate across all recreational anglers.

We further note that high-end fisher populations could display considerable variability both in 

terms of the degree to which they frequent specific waterbodies or watersheds and the degree 

to which they target specific types of fish (or at least sizes of fish). Both of these factors can 

impact estimates of exposure. If a fisher population distributes their activity across a range of 

waterbodies and harvests a variety of fish species (and sizes) than the distribution of exposure 

and risk across that population will be smaller compared with a population that focuses 

activity at individual waterbodies and tends to focus on larger fish. 

A more detailed discussion of the multipathway analysis and its associated uncertainties is 

presented in section 5.3 of the document Human Health Multipathway Residual Risk 

Assessment for the Secondary Lead Smelting Source Category, which can be found in the 

docket for the proposed rule.

4.2 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), but may also be derived for acute (*<24 hours), shortterm (>24 hours up to 30 days), and subchronic (>30 days up to 10% of lifetime) exposure 

durations, all of which are derived based on an assumption of continuous exposure throughout 

the duration specified. For the purposes of assessing all potential health risks associated with 

the emissions included in an assessment, we rely on both chronic (cancer and noncancer) and 

acute (noncancer) benchmarks, which are described in more detail below.

Although every effort is made to identify peer-reviewed dose-response values for all HAPs 

emitted by the source category included in an assessment, some HAP have no peer-reviewed 

cancer potency values or reference values for chronic non-cancer or acute effects (inhalation 

or ingestion). Since exposures to these pollutants cannot be included in a quantitative risk 

estimate, an understatement of risk for these pollutants at environmental exposure levels is 

possible.

Additionally, chronic dose-response values for certain compounds included in the assessment 

may be under EPA IRIS review and revised assessments may determine that these pollutants 

37
19 IRIS glossary (www.epa.gov/NCEA/iris/help_gloss.htm).

20 The exception to this is the URE for benzene, which is considered to cover a range of values, each end of 

which is considered to be equally plausible, and which is based on maximum likelihood estimates.

21 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are 

generic approaches, based on general scientific knowledge and policy judgment, that are applied to various 

elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 

NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the 

option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to 

the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the 

agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be 

are more or less potent than currently thought. We will re-evaluate risks if, as a result of 

these reviews, a dose-response metric changes enough to indicate that the risk assessment 

may significantly mischaracterize human health risk

Cancer assessment

The discussion of dose-response uncertainties in the estimation of cancer risk below focuses 

on the uncertainties associated with the specific approach currently used by the EPA to 

develop cancer potency factors. In general, these same uncertainties attend the development 

of cancer potency factors by CalEPA, the source of peer-reviewed cancer potency factors 

used where EPA-developed values are not yet available. To place this discussion in context, 

we provide a quote from the EPA’s Guidelines for Carcinogen Risk Assessment [29] (herein 

referred to as Cancer Guidelines). “The primary goal of EPA actions is protection of human 

health; accordingly, as an Agency policy, risk assessment procedures, including default 

options that are used in the absence of scientific data to the contrary, should be health 

protective.” The approach adopted in this document is consistent with this approach as 

described in the Cancer Guidelines.

For cancer endpoints EPA usually derives an oral slope factor for ingestion and a unit risk 

value for inhalation exposures. These values allow estimation of a lifetime probability of 

developing cancer given long-term exposures to the pollutant. Depending on the pollutant 

being evaluated, EPA relies on both animal bioassay and epidemiological studies to 

characterize cancer risk. As a science policy approach, consistent with the Cancer 

Guidelines, EPA uses animal cancer bioassays as indicators of potential human health risk 

when other human cancer risk data are unavailable. 

Extrapolation of study data to estimate potential risks to human populations is based upon 

EPA’s assessment of the scientific database for a pollutant using EPA’s guidance documents 

and other peer-reviewed methodologies. The EPA Cancer Guidelines describes the Agency’s 

recommendations for methodologies for cancer risk assessment. EPA believes that cancer 

risk estimates developed following the procedures described in the Cancer Guidelines and 

outlined below generally provide an upper bound estimate of risk. That is, EPA’s upper 

bound estimates represent a “plausible upper limit to the true value of a quantity” (although 

this is usually not a true statistical confidence limit).19 In some circumstances, the true risk 

could be as low as zero; however, in other circumstances the risk could also be greater.20 

When developing an upper bound estimate of risk and to provide risk values that do not 

underestimate risk, EPA generally relies on conservative default approaches.21 EPA also 

38
appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions 

are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly 

overestimate risk). See EPA 2004 An Examination of EPA Risk Assessment Principles and Practices, 

EPA/100/B-04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf.

22 Per the EPA Cancer Guidelines: “The default option is that positive effects in animal cancer studies indicate 

that the agent under study can have carcinogenic potential in humans.” and “Target organ concordance is not a 

prerequisite for evaluating the implications of animal study results for humans.”

uses the upper bound (rather than lower bound or central) estimates in its assessments, 

although it is noted that this approach can have limitations for some uses (e.g. priority setting, 

expected benefits analysis).

Such health risk assessments have associated uncertainties, some which may be considered 

quantitatively, and others which generally are expressed qualitatively. Uncertainties may 

vary substantially among cancer risk assessments associated with exposures to different 

pollutants, since the assessments employ different databases with different strengths and 

limitations and the procedures employed may differ in how well they represent actual 

biological processes for the assessed substance. EPA’s Risk Characterization Handbook also 

recommends that risk characterizations present estimates demonstrating the impact on the 

assessment of alternative choices, data, models and assumptions [30]. Some of the major 

sources of uncertainty and variability in deriving cancer risk values are described more fully 

below. 

(1) The qualitative similarities or differences between tumor responses observed in 

experimental animal bioassays and those which would occur in humans is a source of 

uncertainty in cancer risk assessment. In general, EPA does not assume that tumor sites 

observed in an experimental animal bioassay are necessarily predictive of the sites at which 

tumors would occur in humans.22 However, unless scientific support is available to show 

otherwise, EPA assumes that tumors in animals are relevant in humans, regardless of target 

organ concordance. For a specific pollutant, qualitative differences in species responses can 

lead to either under-estimation or over-estimation of human cancer risks. 

(2) Uncertainties regarding the most appropriate dose metric for an assessment can also lead 

to differences in risk predictions. For example, the measure of dose is commonly expressed 

in units of mg/kg/d ingested or the inhaled concentration of the pollutant. However, data may 

support development of a pharmacokinetic model for the absorption, distribution, metabolism 

and excretion of an agent, which may result in improved dose metrics (e.g., average blood 

concentration of the pollutant or the quantity of agent metabolized in the body). Quantitative 

uncertainties result when the appropriate choice of a dose metric is uncertain or when dose 

metric estimates are themselves uncertain (e.g., as can occur when alternative 

pharmacokinetic models are available for a compound). Uncertainty in dose estimates may 

lead to either over or underestimation of risk.

(3) For the quantitative extrapolation of cancer risk estimates from experimental animals to 

humans, EPA uses scaling methodologies (relating expected response to differences in 

physical size of the species), which introduce another source of uncertainty. These 

methodologies are based on both biological data on differences in rates of process according 

to species size and empirical comparisons of toxicity between experimental animals and 

39
humans. For a particular pollutant, the quantitative difference in cancer potency between 

experimental animals and humans may be either greater than or less than that estimated by 

baseline scientific scaling predictions due to uncertainties associated with limitations in the 

test data and the correctness of scaled estimates. 

(4) EPA cancer risk estimates, whether based on epidemiological or experimental animal data, 

are generally developed using a benchmark dose (BMD) analysis to estimate a dose at which 

there is a specified excess risk of cancer, which is used as the point of departure (or POD) for 

the remainder of the calculation. Statistical uncertainty in developing a POD using a 

benchmark dose (BMD) approach is generally addressed though use of the 95% lower 

confidence limit on the dose at which the specified excess risk occurs (the BMDL), 

decreasing the likelihood of understating risk. EPA has generally utilized the multistage 

model for estimation of the BMDL using cancer bioassay data (see further discussion below).

(5) Extrapolation from high to low doses is an important, and potentially large, source of 

uncertainty in cancer risk assessment. EPA uses different approaches to low dose risk 

assessment (i.e., developing estimates of risk for exposures to environmental doses of an 

agent from observations in experimental or epidemiological studies at higher dose) depending 

on the available data and understanding of a pollutant’s mode of action (i.e., the manner in 

which a pollutant causes cancer). EPA’s Cancer Guidelines express a preference for the use 

of reliable, compound-specific, biologically-based risk models when feasible; however, such 

models are rarely available. The mode of action for a pollutant (i.e., the manner in which a 

pollutant causes cancer) is a key consideration in determining how risks should be estimated 

for low-dose exposure. A reference value is calculated when the available mode of action 

data show the response to be nonlinear (e.g., as in a threshold response). A linear low-dose 

(straight line from POD) approach is used when available mode of action data support a linear 

(e.g., nonthreshold response) or as the most common default approach when a compound’s 

mode of action is unknown. Linear extrapolation can be supported by both pollutant-specific 

data and broader scientific considerations. For example, EPA’s Cancer Guidelines generally 

consider a linear dose-response to be appropriate for pollutants that interact with DNA and 

induce mutations. Pollutants whose effects are additive to background biological processes in 

cancer development can also be predicted to have low-dose linear responses, although the 

slope of this relationship may not be the same as the slope estimated by the straight line 

approach. 

EPA most frequently utilizes a linear low-dose extrapolation approach as a baseline sciencepolicy choice (a “default”) when available data do not allow a compound-specific 

determination. This approach is designed to not underestimate risk in the face of uncertainty 

and variability. EPA believes that linear dose-response models, when appropriately applied 

as part of EPA’s cancer risk assessment process, provide an upper bound estimate of risk and 

generally provide a health protective approach. Note that another source of uncertainty is the 

characterization of low-dose nonlinear, non-threshold relationships. The National Academy 

of Sciences has encouraged the exploration of sigmoidal type functions (e.g., log-probit 

models) in representing dose response relationships due to the variability in response within 

human populations. Another National Research Council (NRC) report [31] suggests that 

models based on distributions of individual thresholds are likely to lead to sigmoidal-shaped 

40
dose-response functions for a population. This report notes sources of variability in the 

human population: “One might expect these individual tolerances to vary extensively in 

humans depending on genetics, coincident exposures, nutritional status, and various other 

susceptibility factors...” Thus, if a distribution of thresholds approach is considered for a 

carcinogen risk assessment, application would depend on ability of modeling to reflect the 

degree of variability in response in human populations (as opposed to responses in bioassays 

with genetically more uniform rodents). Note also that low dose linearity in risk can arise for 

reasons separate from population variability: due to the nature of a mode of action and 

additivity of a chemical’s effect on top of background chemical exposures and biological 

processes.

As noted above, EPA’s current approach to cancer risk assessment typically utilizes a straight 

line approach from the BMDL. This is equivalent to using an upper confidence limit on the 

slope of the straight line extrapolation. The impact of the choice of the BMDL on bottom line 

risk estimates can be quantified by comparing risk estimates using the BMDL value to central 

estimate BMD values, although these differences are generally not a large contributor to 

uncertainty in risk assessment (Subramaniam et. al., 2006) [32]. It is important to note that 

earlier EPA assessments, including the majority of those for which risk values exist today, 

were generally developed using the multistage model to extrapolate down to environmental 

dose levels and did not involve the use of a POD. Subramaniam et. al. (2006) also provide 

comparisons indicating that slopes based on straight line extrapolation from a POD do not 

show large differences from those based on the upper confidence limit of the multistage 

model.

(6) Cancer risk estimates do not generally make specific adjustments to reflect the variability 

in response within the human population — resulting in another source of uncertainty in 

assessments. In the diverse human population, some individuals are likely to be more 

sensitive to the action of a carcinogen than the typical individual, although compound-specific 

data to evaluate this variability are generally not available. There may also be important life 

stage differences in the quantitative potency of carcinogens and, with the exception of the 

recommendations in EPA’s Supplemental Cancer Guidance for carcinogens with a mutagenic 

mode of action, risk assessments do not generally quantitatively address life stage differences. 

However, one approach used commonly in EPA assessments that may help address variability 

in response is to extrapolate human response from results observed in the most sensitive 

species and sex tested, resulting typically in the highest URE which can be supported by 

reliable data, thus supporting estimates that are designed not to underestimate risk in the face 

of uncertainty and variability.

Chronic noncancer assessment

Chronic noncancer reference values represent chronic exposure levels that are intended to be 

health-protective. That is, EPA and other organizations which develop noncancer reference 

values (e.g., the Agency for Toxic Substances and Disease Registry – ATSDR) utilize an 

approach that is intended not to underestimate risk in the face of uncertainty and variability. 

When there are gaps in the available information, uncertainty factors (UFs) are applied to 

derive reference values that are intended to be protective against appreciable risk of 

41
23

 According to the NRC report Science and Judgment in Risk Assessment (NRC, 1994) “[Default] options are 

generic approaches, based on general scientific knowledge and policy judgment, that are applied to various 

elements of the risk-assessment process when the correct scientific model is unknown or uncertain.” The 1983 

NRC report Risk Assessment in the Federal Government: Managing the Process defined default option as “the 

option chosen on the basis of risk assessment policy that appears to be the best choice in the absence of data to 

the contrary” (NRC, 1983a, p. 63). Therefore, default options are not rules that bind the agency; rather, the 

agency may depart from them in evaluating the risks posed by a specific substance when it believes this to be 

appropriate. In keeping with EPA’s goal of protecting public health and the environment, default assumptions 

are used to ensure that risk to chemicals is not underestimated (although defaults are not intended to overtly 

overestimate risk). See EPA 2004 An examination of EPA Risk Assessment Principles and Practices, EPA/100/B04/001 available at: http://www.epa.gov/osa/pdfs/ratf-final.pdf. 

24 See IRIS glossary

deleterious effects. Uncertainty factors are commonly default values23 e.g., factors of 10 or 3, 

used in the absence of compound-specific data; where data are available, uncertainty factors 

may also be developed using compound-specific information. When data are limited, more 

assumptions are needed and more default factors are used. Thus there may be a greater 

tendency to overestimate risk—in the sense that further study might support development of 

reference values that are higher (i.e., less potent) because fewer default assumptions are 

needed. However, for some pollutants it is possible that risks may be underestimated.

For non-cancer endpoints related to chronic exposures, EPA derives a Reference Dose (RfD) 

for exposures via ingestion, and a Reference Concentration (RfC) for inhalation exposures. 

These values provide an estimate (with uncertainty spanning perhaps an order of magnitude) 

of daily oral exposure (RfD) or of a continuous inhalation exposure (RfC) to the human 

population (including sensitive subgroups) that is likely to be without an appreciable risk of 

deleterious effects during a lifetime.24 To derive values that are intended to be “without 

appreciable risk,” EPA’s methodology relies upon an uncertainty factor (UF) approach (U.S. 

EPA, 1993, 1994) which includes consideration of both uncertainty and variability.

 

EPA begins by evaluating all of the available peer-reviewed literature to determine noncancer endpoints of concern, evaluating the quality, strengths and limitations of the available 

studies. EPA typically chooses the relevant endpoint that occurs at the lowest dose, often 

using statistical modeling of the available data, and then determines the appropriate point of 

departure (POD) for derivation of the reference value. A POD is determined by (in order of 

preference): (1) a statistical estimation using the benchmark dose (BMD) approach; (2) use of 

the dose or concentration at which the toxic response was not significantly elevated (no 

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

level (LOAEL).

A series of downward adjustments using default UFs is then applied to the POD to estimate 

the reference value (U.S. EPA 1994, 2002). While collectively termed “UFs”, these factors 

account for a number of different quantitative considerations when utilizing observed animal 

(usually rodent) or human toxicity data in a risk assessment. The UFs are intended to account 

for: (1) variation in susceptibility among the members of the human population (i.e., interindividual variability); (2) uncertainty in extrapolating from experimental animal data to 

humans (i.e., interspecies differences); (3) uncertainty in extrapolating from data obtained in a 

42
study with less-than-lifetime exposure (i.e., extrapolating from subchronic to chronic 

exposure); (4) uncertainty in extrapolating from a LOAEL in the absence of a NOAEL; and 

(5) uncertainty when the database is incomplete or there are problems with applicability of 

available studies. When scientifically sound, peer-reviewed assessment-specific data are not 

available, default adjustment values are selected for the individual UFs. For each type of 

uncertainty (when relevant to the assessment), EPA typically applies an UF value of 10 or 3 

with the cumulative UF value leading to a downward adjustment of 10-3000 fold from the 

selected POD. An UF of 3 is used when the data do not support the use of a 10-fold factor. If 

an extrapolation step or adjustment is not relevant to an assessment (e.g., if applying human 

toxicity data and an interspecies extrapolation is not required) the associated UF is not used. 

The major adjustment steps are described more fully below.

1) Heterogeneity among humans is a key source of variability as well as uncertainty. 

Uncertainty related to human variation is considered in extrapolating doses from a subset or 

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

occupational epidemiologic studies), to a larger, more diverse population. In the absence of 

pollutant-specific data on human variation, a 10-fold UF is used to account for uncertainty 

associated with human variation. Human variation may be larger or smaller; however, data to 

examine the potential magnitude of human variability are often unavailable. In some 

situations, a smaller UF of 3 may be applied to reflect a known lack of significant variability 

among humans.

2) Extrapolation from results of studies in experimental animals to humans is a 

necessary step for the majority of chemical risk assessments. When interpreting animal data, 

the concentration at the POD (e.g. NOAEL, BMDL) in an animal model (e.g. rodents) is 

extrapolated to estimate the human response. While there is long-standing scientific support 

for the use of animal studies as indicators of potential toxicity to humans, there are 

uncertainties in such extrapolations. In the absence of data to the contrary, the typical 

approach is to use the most relevant endpoint from the most sensitive species and the most 

sensitive sex in assessing risks to the average human. Typically, compound specific data to 

evaluate relative sensitivity in humans versus rodents are lacking, thus leading to uncertainty 

in this extrapolation. Size-related differences (allometric relationships) indicate that typically 

humans are more sensitive than rodents when compared on a mg/kg/day basis. The default 

choice of 10 for the interspecies UF is consistent with these differences. For a specific 

chemical, differences in species responses may be greater or less than this value.

Pharmacokinetic models are useful to examine species differences in pharmacokinetic 

processing and associated uncertainties; however, such dosimetric adjustments are not always 

possible. Information may not be available to quantitatively assess toxicokinetic or 

toxicodynamic differences between animals and humans, and in many cases a 10-fold UF 

(with separate factors of 3 for toxicokinetic and toxicodynamic components) is used to 

account for expected species differences and associated uncertainty in extrapolating from 

laboratory animals to humans in the derivation of a reference value. If information on one or 

the other of these components is available and accounted for in the cross-species 

extrapolation, a UF of 3 may be used for the remaining component.

43
3) In the case of reference values for chronic exposures where only data from shorter 

durations are available (e.g., 90-day subchronic studies in rodents) or when such data are 

judged more appropriate for development of an RfC, an additional UF of 3 or 10-fold is 

typically applied unless the available scientific information supports use of a different value.

4) Toxicity data are typically limited as to the dose or exposure levels that have been 

tested in individual studies; in an animal study, for example, treatment groups may differ in 

exposure by up to an order of magnitude. The preferred approach to arrive at a POD is to use 

BMD analysis; however, this approach requires adequate quantitative results for a meaningful 

analysis, which is not always possible. Use of a NOAEL is the next preferred approach after 

BMD analysis in determining a POD for deriving a health effect reference value. However, 

many studies lack a dose or exposure level at which an adverse effect is not observed (i.e., a 

NOAEL is not identified). When using data limited to a LOAEL, a UF of 10 or 3-fold is 

often applied. 

5) The database UF is intended to account for the potential for deriving an 

underprotective RfD/RfC due to a data gap preventing complete characterization of the 

chemical’s toxicity. In the absence of studies for a known or suspected endpoint of concern, a 

UF of 10 or 3-fold is typically applied.

There is no RfD or other comparable chronic health benchmark value for lead compounds. 

Thus, to address multipathway human health and environmental risks associated with 

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 the 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. Instead, he noted, there is a collection of scientific evidence and 

judgments and other information, including information about the uncertainties inherent in 

many relevant factors, which needs to be considered together in making this public health 

policy judgment and in selecting a standard level from a range of reasonable values (73FR at 

66998). In so doing, the Administrator decided that, a level for the primary lead standard of 

0.15 μg/m3, in combination with the specified choice of indicator, averaging time, and form, 

is requisite to protect public health, including the health of sensitive groups, with an adequate 

margin of safety (73FR at 67006). A thorough discussion of the health evidence, risk and 

exposure analyses, and their associated uncertainties can be found in EPA’s final rule revising 

the lead NAAQS (73 FR 66970-66981, November 12, 2008). 

We also note the uncertainties associated with the health-based (i.e., primary) NAAQS are 

likely less than the uncertainties associated with dose-response values developed for many of 

44
the other HAP, particularly those HAP for which no human health data exist. In 1988, EPA’s 

IRIS program reviewed the health effects data regarding lead and its inorganic compounds 

and determined that it would be inappropriate to develop an RfD for these compounds, 

saying, “A great deal of information on the health effects of lead has been 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 most other environmental toxicants, the degree of uncertainty 

about the health effects of lead is quite low. It appears that some of these effects, particularly 

changes in the levels of certain blood enzymes and in aspects of children's neurobehavioral 

development, may occur at blood lead levels so low as to be essentially without a threshold. 

The Agency's RfD Work Group 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 airrelated multi-pathway exposures from industrial sources like primary and secondary lead 

smelting operations. It also considered background lead exposures from other sources (like 

contaminated drinking water and exposure to lead-based paints). In revising the NAAQS for 

lead, we note that the Administrator placed more weight on the evidence-based framework 

and less weight on the results from the risk assessment, although he did find the risk estimates 

to be roughly consistent with and generally supportive of the evidence-based framework 

applied in the NAAQS determination (73FR at 67004). Thus, when revising the NAAQS for 

lead to protect public health with an adequate margin of safety, EPA considered both the 

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

Acute noncancer assessment

Many of the UFs used to account for variability and uncertainty in the development of acute 

reference values are quite similar to those developed for chronic durations, but more often 

using individual UF values that may be less than 10. UFs are applied based on chemicalspecific or health effect-specific information (e.g., simple irritation effects do not vary 

appreciably between human individuals, hence a value of 3 is typically used), or based on the 

purpose for the reference value (see the following paragraph). The UFs applied in acute 

reference value derivation include: 1) heterogeneity among humans; 2) uncertainty in 

extrapolating from animals to humans; 3) uncertainty in LOAEL to NOAEL adjustments; and 

4) uncertainty in accounting for an incomplete database on toxic effects of potential concern. 

Additional adjustments are often applied to account for uncertainty in extrapolation from 

observations at one exposure duration (e.g., 4 hours) to arrive at a POD for derivation of an 

acute reference value at another exposure duration (e.g., 1 hour). 

Not all acute reference values are developed for the same purpose and care must be taken 

when interpreting the results of an acute assessment of human health effects relative to the 

45
reference value or values being exceeded. Where relevant to the estimated exposures, the 

lack of threshold values at different levels of severity should be factored into the risk 

characterization as potential uncertainties. 

46
5 References

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

2 US EPA, 2009. Risk and Technology Review (RTR) Risk Assessment Methodologies: For 

Review by the EPA’s Science Advisory Board with Case Studies – MACT I Petroleum Refining 

Sources and Portland Cement Manufacturing. EPA-452/R-09-006. 

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

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

http://yosemite.epa.gov/sab/sabproduct.nsf/4AB3966E263D943A8525771F00668381/$File/

EPA-SAB-10-007-unsigned.pdf

4. US EPA, 2010. Memorandum from Dave Guinnup to RTR Wood Furniture Docket, entitled, 

“EPA’s Actions in Response to Key Recommendations of the SAB Review of RTR Risk 

Assessment Methodologies.

5. US EPA, 2005. Revision to the Guideline on Air Quality Models: Adoption of a Preferred 

General Purpose (Flat and Complex Terrain) Dispersion Model and Other Revisions; Final Rule. 

40 CFR Part 51. http://www.epa.gov/EPA-AIR/2005/November/Day-09/a21627.htm

6. US EPA, 2004. Users’ guide for the AMS/EPA regulatory model – AERMOD. EPA-454/B-03-

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

7. Allen, D., C. Murphy, Y. Kimura, W. Vizuete, T. Edgar, H. Jeffries, B.-U. Kim, M. Webster, 

and M. Symons, 2004. Variable industrial VOC emissions and their impact on ozone formation 

in the Houston Galveston Area. Final Report: Texas Environmental Research Consortium 

Project H-13. 

http://files.harc.edu/Projects/AirQuality/Projects/H013.2003/H13FinalReport.pdf

8. US EPA, 2004. Air Toxics Risk Assessment Reference Library, Volume 1. EPA-453-K-04- 

001A. http://www.epa.gov/ttn/fera/risk_atra_vol1.html. 

9. US EPA, 2005. Table 1. Prioritized Chronic Dose-Response Values (2/28/05). Office of 

Air Quality Planning and Standards. http://www.epa.gov/ttn/atw/toxsource/table1.pdf

10. US EPA, 2005. 1999 National Air Toxics Risk Assessment. 

http://www.epa.gov/ttn/atw/nata1999

11. US EPA, 2006. Integrated Risk Information System. http://www.epa.gov/iris/index.html.

12. US Agency for Toxic Substances and Disease Registry. 2006. Minimum Risk Levels (MRLs) 

for Hazardous Substances. http://www.atsdr.cdc.gov/mrls/index.html.

13. US EPA, 1994. US Environmental Protection Agency. Methods for Derivation of 

Inhalation Reference Concentrations and Application of Inhalation Dosimetry. EPA/600/8-

90/066F. Office of Research and Development. Washington, DC: U.S.EPA.

47
14. NRC, 1994. National Research Council. Science and Judgment in Risk Assessment. 

Washington, DC: National Academy Press.

15. CA Office of Environmental Health Hazard Assessment, 2005. Chronic Reference 

Exposure Levels Adopted by OEHHA as of December 2008. 

http://www.oehha.ca.gov/air/chronic_rels/AllChrels.html. 

16. CA Office of Environmental Health Hazard Assessment, 2005. Technical Support Document 

for Describing Available Cancer Potency Factors, May 2005. 

http://www.oehha.ca.gov/air/hot_spots/may2005tsd.html.

17. US EPA, 2006. Approach for modeling POM. Technical support information for the 1999 

National Air Toxics Assessment. 

http://www.epa.gov/ttn/atw/nata1999/99pdfs/pomapproachjan.pdf.

18. US EPA, 2005. Table 2. Acute Dose-Response Values for Screening Risk Assessments 

(6/02/2005). Office of Air Quality Planning and Standards. 

http://www.epa.gov/ttn/atw/toxsource/table2.pdf

19. CA Office of Environmental Health Hazard Assessment, 2000. All Acute Reference 

Exposure Levels developed by OEHHA as of May 2000. 

http://www.oehha.ca.gov/air/acute_rels/allAcRELs.html

20. American Industrial Hygiene Association , 2009. Current AIHA ERPG Values. 

http://www.aiha.org/insideaiha/volunteergroups/Documents/ERP-erpglevels.pdf.

21. US EPA, 1995. Guidance for Risk Characterization. Science Policy Council. 

http://www.epa.gov/OSA/spc/pdfs/rcguide.pdf.

22. US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002.

23. US EPA, 2002. EPA’s Guidelines for Ensuring and Maximizing the Quality, Objectivity, 

Utility, and Integrity of Information Disseminated by the Environmental Protection Agency. 

EPA Office of Environmental Information. EPA/260R-02-008. 

http://www.epa.gov/quality/informationguidelines/documents/EPA_InfoQualityGuideline

s.pdf

24. US EPA, 2006. Performing risk assessments that include carcinogens described in the 

Supplemental Guidance as having a mutagenic mode of action. Science Policy Council 

Cancer Guidelines Implementation Workgroup Communication II: Memo from W.H. Farland 

dated 14 June 2006. http://www.epa.gov/osa/spc/pdfs/CGIWGCommunication_II.pdf

25. US EPA, 2005. Supplemental guidance for assessing early-life exposure to carcinogens. 

EPA/630/R-03003F. http://www.epa.gov/ttn/atw/childrens_supplement_final.pdf.

26. US EPA, 2005. Science Policy Council Cancer Guidelines Implementation Workgroup 

Communication I: Memo from W.H. Farland dated 4 October 2005 to Science Policy 

Council. http://www.epa.gov/osa/spc/pdfs/canguid1.pdf

48
27. US EPA, 1986. Guidelines for the Health Risk Assessment of Chemical Mixtures. EPA-630-R98-002. http://www.epa.gov/NCEA/raf/pdfs/chem_mix/chemmix_1986.pdf

28. US EPA, 2000. Supplementary Guidance for Conducting Health Risk Assessment of 

Chemical Mixtures. EPA-630/R-00-002. 

http://www.epa.gov/ncea/raf/pdfs/chem_mix/chem_mix_08_2001.pdf.

29. US EPA, 2005. Guidelines for Carcinogen Risk Assessment (2005). U.S. Environmental 

Protection Agency, Washington, DC, EPA/630/P-03/001F, 2005. 

http://cfpub.epa.gov/ncea/raf/recordisplay.cfm?deid=116283

30. US EPA, 2000. Risk Characterization Handbook. EPA 100-B-00-002.

31. NRC (National Research Council) 2006. Assessing the Human Health Risks of 

Trichloroethylene. National Academies Press, Washington DC.

32. R.P. Subramaniam, P. White and V.J. Cogliano. 2006. Comparison of cancer slope factors 

using different statistical approaches, Risk Anal. Vol 26, p. 825–830.

49
1

MEMORANDUM

To: Nathan Topham, U.S. Environmental Protection Agency, OAQPS

From: Mike Burr, Donna Lazzari, and Danny Greene, ERG 

Date: December 16, 2011

Subject: Summary of MACT Floor Analysis for the Secondary Lead Smelting Source 

Category

This memorandum presents the methodology and results of the maximum achievable 

control technology (MACT) floor determinations for dioxins and furans (D/F) and total 

hydrocarbons (THC) for the Secondary Lead Smelting source category.

We determined the MACT floors using emissions data obtained from the recently 

implemented Information Collection Request (ICR). We ranked emissions test averages for each 

of the sources, calculated MACT floor averages, and conducted emissions test data variability 

analysis to estimate these best performing sources’ emissions performance over time. We 

determined the MACT floors based on the results of these analyses. We also conducted the 

beyond the floor analyses required by section 112 (d)(2), to evaluate possible standards that 

would be more stringent than the MACT floor. The organization of this memo is as follows:

1.0 Summary of Existing Limits

2.0 Background on MACT Floor Methodology

3.0 MACT Floor Determination Methodology

4.0 Beyond the Floor

5.0 Summary of MACT Floor Analysis

Appendix A: Total Hydrocarbons Emissions Data Used in the MACT Floor Calculation

Appendix B: Dioxin and Furan Emissions Data Used in the MACT Floor Calculation

Appendix C: Toxic Equivalency Factors used to Calculate Toxic Equivalency Quotient

1.0 SUMMARY OF EXISTING MACT LIMITS

The existing National Emissions Standard for Hazardous Air Pollutants (NESHAP) for 

the Secondary Lead Smelting source category (40 CFR part 63, subpart X) established emissions 

limits for lead (as a surrogate for metal hazardous air pollutants (HAP)) and THC (as a surrogate 

for organic HAP) based on furnace type. Table 1-1 summarizes the emissions limits in the 
2

1 ERG. Technology Review for the Secondary Lead Smelting Source Category. November 2011.

existing NESHAP.

Table 1-1. Emissions Limits in the 1997 Secondary Lead Smelting NESHAP.

Furnace Configuration Lead Compounds THC

Existing 

Sources

New 

Sources

Existing 

Sources

New 

Sources

Collocated Blast and 

Reverberatory furnace:

When both furnaces 

operating

2.0 mg/dscm 20 ppmv

When reverberatory 

furnace not operating

360 ppmv 70 ppmv

Blast 360 ppmv 70 ppmv

Reverberatory Not Applicable

Rotary

Electric

As shown in Table 1-1, the current NESHAP does not specify THC emissions limits for 

three furnace groups: (1) reverberatory furnaces not collocated with blast furnaces, (2) rotary 

furnaces, and (3) electric furnaces. Therefore, we have calculated THC MACT floors and 

conducted beyond the floor analyses for these three furnace types in this analysis. The existing 

NESHAP also does not set emissions limits for D/F. We therefore calculated MACT floors for 

D/F based on the same furnace types as THC. This is appropriate as the formation of D/F, like 

THC, is highly temperature dependent.1 We note that although the D/F and THC MACT floor 

calculations for rotary furnaces are presented in this document, the EPA is delaying 

promulgation of D/F and THC emissions limits for rotary furnaces due to insufficient and 

unrepresentative emissions test data. The information presented here for rotary furnaces is based 

on two test runs during one test period for one rotary furnace. This data was determined by the 

EPA to be insufficient to establish MACT floor limits. See the comment response document 

available in the docket for more information.

2.0 OVERVIEW OF MACT STANDARD DEVELOPMENT METHODOLOGY

2.1 MACT Determination

Section 112(d) of the CAA requires the EPA to set emissions standards for HAP emitted 

by major stationary sources. The MACT standards for existing sources must be at least as 

stringent as the average emissions limitation achieved by the best performing 12 percent of 

existing sources (for which the Administrator has emissions information) or the five bestperforming sources for source categories with less than 30 sources (CAA section 112(d)(3)(A) 

and (B)). This level of minimum stringency is called the MACT floor. For new sources, MACT 

standards must be at least as stringent as the control level achieved in practice by the best 

controlled similar source (CAA section 112(d)(3)). These requirements constitute the MACT 
3

floor for new and existing sources. The EPA may not consider costs or other impacts in 

determining the MACT floors. The EPA must consider cost, non-air quality health and 

environmental impacts, and energy requirements in connection with any standards that are more 

stringent than the MACT floor (beyond-the-floor controls).

MACT analyses involve an assessment of the emissions from the best-performing units in 

a source category. The assessment can be based on actual emissions data, on knowledge of the 

air pollution control in place in combination with actual emissions data, or on state regulatory 

requirements that may enable the EPA to estimate the actual performance of the regulated units 

and other relevant emissions information. For each source category, the assessment involves a 

review of actual emissions data with an appropriate accounting for emissions variability. Other 

methods of estimating emissions can be used provided that the methods can be shown to provide 

reasonable estimates of the actual emissions performance of a source or sources. 

In a March 2007 court decision (Sierra Club v. EPA, 479 F. 3d 875 [DC Cir. 2007]) 

(Brick MACT), the EPA was directed to set MACT floors conforming to the statute, with these 

specific directives:

• Floors for existing sources must reflect the average emissions limitation achieved 

by the best-performing 12 percent of existing sources, not levels the EPA 

considers to be achievable by all sources (479 F. 3d at 880–81).

• The EPA cannot set floors of “no control.” The court reiterated its prior holdings, 

confirming that the EPA must set floor standards for all HAP emitted by the 

major source, including those HAP that are not controlled by at-the-stack control 

devices (479 F. 3d at 883).

• The EPA cannot ignore non-technology factors that reduce HAP emissions. 

Specifically, the court held that “EPA’s decision to base floors exclusively on 

technology even though non-technology factors affect emissions violates the Act” 

(479 F. 3d at 883).

• The EPA may not use emissions levels of the worst performers to estimate 

variability of the best performers without a demonstrated relationship between the 

two (479 F. 3d at 882).

2.2 Considering Variability in Establishing Emissions Limits

Section 112(d)(3)(B) of the CAA requires that the EPA determine the emissions control 

that is achieved in practice by the average of the best-controlled top five sources when 

establishing the MACT floor for units in a source category with 30 or fewer units. The EPA must 

exercise its judgment, based on an evaluation of the relevant factors and available data, to 

determine the level of emissions control that has been achieved by the average of the bestperforming top five units under variable conditions. The Court has recognized that the EPA may 

consider variability in estimating the degree of emissions reduction achieved by best-performing 
4

sources and in setting MACT floors (see Mossville Envt’l Action Now v. EPA, 370 F.3d 1232, 

1241-42 D.C. Cir 2004), holding that the EPA may consider emissions variability in estimating 

performance achieved by best-performing sources and may set the floor at a level that bestperforming sources can expect to meet “every day and under all operating conditions.”

The MACT and other technology-based standards are necessarily derived from shortterm emissions test data, but such data are not representative of the range of operating conditions 

that the best-performing facilities face on a day-to-day basis. In statistical terms, each test 

produces a limited data sample, not a complete enumeration of the available data for 

performance of the unit over a long period of time. The EPA, therefore, often needs to adjust the 

short-term data to account for these varying conditions in order to properly estimate these 

sources’ performance over time. The types of variability that the EPA attempts to account for 

include operational distinctions between and within tests at the same unit.

“Between-test variability” can occur even where conditions appear to be the same when 

two or more tests are conducted. Variations in emissions may be caused by different settings for 

emissions testing equipment, different field teams conducting the testing, differences in sample 

handling or different laboratories analyzing the results. Identifying an achieved emissions level 

for best performing sources needs to account for these differences between tests for “a uniform 

standard [to] be capable of being met under most adverse conditions which can reasonably be 

expected to recur[.]” (See National lime Ass’n v. EPA, 627 F.2d at 431, n. 46.; see also v. 

Ruckelshaus, 486 F.2d at 396 noting industry point that “a single test offered a weak basis” for 

inferring that plants could meet the standards.)

The same types of differences leading to between-test variability also cause variations in 

results between various runs comprising a single test, or “within-test variability.” A single test at 

a unit usually includes at least three separate test runs. (See 40 CFR 63.7(e)(3) for MACT 

standards under CAA Section 112.) Each data point should be viewed as a snapshot of actual 

performance. Along with an understanding of the factors that may affect performance, each of 

these snapshots gives information about the normal, and unavoidable, variation in emissions that 

would be expected to recur over time. 

Variability can be accounted for using different statistical methods. For example, recent 

rules have used the upper limit (UL) or the upper prediction limit (UPL) to evaluate variability as 

part of the process for determining the MACT floor emissions limits. A UL is based on the 

distribution of the available emissions observations (e.g., test runs), and does not embody the 

predictive aspect that a UPL does. A prediction interval (e.g., a UPL) for a future observation is 

an interval that will, with a specified degree of confidence, contain the next (or some other prespecified) randomly selected observation from a population. In other words, the prediction 
5

2 Because a source must demonstrate compliance with the MACT floor using the average of a three-run test, the 

appropriate test condition to use to assess variability is three test runs. If a source had to demonstrate compliance by 

showing that each individual test run was below the MACT floor emissions limit, it would be appropriate to use a 

future test condition of one test run.

interval estimates what future values will be, based on present or past measurements. Given this 

definition, the UPL represents the value that the mean of three future test run observations (threerun average) can be expected to fall below, based on the results of the independent sample of 

size (n) from the same population. Therefore, should a future test condition be selected randomly 

from any of these sources (i.e., average of three runs), one can be 99 percent confident that the 

reported level will fall below a MACT floor emissions limit calculated using a UPL, assuming 

representativeness of the underlying data set. For these reasons, we used the UPL to account for 

variability in our MACT floor calculations.2 We did, however, examine alternative statistical 

methods to account for variability when calculating MACT floors for the rotary furnace group 

due to limited emissions data, as discussed further in section 3.2 of this memorandum.

3.0 MACT DETERMINATION FOR SECONDARY LEAD SMELTING SOURCE 

CATEGORY

The following sections outline the steps taken in determining the MACT floors for the 

Secondary Lead Smelting source category. We calculate emissions test averages and rank the top 

sources (section 3.1), perform statistical analyses to account for variability in emissions data 

(section 3.2), perform analyses to assess the impact of below detection level (BDL) emissions 

data (section 3.3), and calculate the 99% UPL for each furnace group (section 3.4).

3.1 Ranking the Best Performing Five Sources

The emissions data used to calculate the MACT floors for THC and D/F were obtained 

using an ICR survey sent to the six companies that own the existing secondary lead smelting 

facilities in June 2010. The emissions test data used in our MACT floor calculations for THC 

and D/F, including individual emissions test runs, is presented in Appendices A and B, 

respectively.

The MACT floor emissions limits for THC were calculated for the following furnace 

groups: (1) reverberatory furnaces not collocated with blast furnaces and reverberatory furnaces 

mixed with electric furnaces and (2) rotary furnaces. The MACT floor emissions limits for D/F 

were calculated for the following furnace groups: (1) reverberatory furnaces not collocated with 

blast furnaces and reverberatory furnaces mixed with electric furnaces, (2) blast furnaces, (3) 

collocated blast and reverberatory furnaces, and (4) rotary furnaces.

To determine the MACT floor emissions limits, the average pollutant concentration was 

calculated for each affected source within each furnace group. To maintain consistency with the 

current NESHAP, the MACT floors for THC were calculated in units of parts per million by 
6

3Van den Berg et al. “The 2005 World Health Organization reevaluation of human and mammalian toxic 

equivalency factors for dioxins and dioxin-like compounds.” Toxicol. Sci. 93 (2006): 223–241.

volume, expressed as propane and adjusted to 4% carbon dioxide (ppmv propane @ 4% CO2). 

The D/F MACT floors were calculated on a toxic equivalency (TEQ) basis in units of nanograms 

per dry standard cubic meter adjusted to 7 percent oxygen (ng/dscm @ 7% O2) to maintain 

consistency with previously-promulgated D/F standards. The TEQ was calculated using toxic 

equivalency factors (TEFs) recommended by the World Health Organization3(WHO) in 2005; 

these factors are presented in Appendix C. Because we had emissions test data for less than five 

sources for both pollutants for each furnace group, the average of the best-performing sources 

was determined as the average of all available emissions test data for each furnace group and 

pollutant. More specifically, each affected source for which emissions data were available fell 

within the top five (or fewer) performing sources of the respective furnace group. As described 

in the control technology review memo (Technology Review for the Secondary Lead Smelting 

Source Category), the control technologies applied at these facilities (for which we have 

emissions test data) are the same or better than the controls applied at similar affected sources in 

the industry. Therefore, we conclude that the facilities for which we have emissions data are 

among the top five (or fewer) performers for each furnace group. Tables 3-1 and 3-2 present the 

average concentration of THC and D/F, respectively, for each affected source (for which 

emissions data were available) within each furnace group considered in this analysis.

Table 3-1. Average Concentrations of THC

Furnace Group Company/Facility Average THC 

Concentration 

Rank

Reverberatory furnaces not 

collocated with blast furnaces and 

reverberatory furnaces mixed with 

electric furnaces

Revere Smelting and Refining – 

Middletown

3.30 1

Quemetco - Indianapolis 7.76 2

Rotary Furnaces Revere Smelting and Refining – 

Middletown

257 1

THC in parts per million by volume expressed as propane and adjusted to 4 percent CO2.

Table 3-2. Average Concentrations of TEQ

Furnace Group Company/Facility Average TEQ 

Concentration 

Rank

Reverberatory furnaces not collocated 

with blast furnaces and reverberatory 

furnaces mixed with electric furnaces

Quemetco – Industry 0.08 1

Revere Smelting and Refining – 

Middletown

0.09 2

Quemetco – Indiana 0.12 3

Blast Furnaces Exide Technologies – Forest City 1.3 1

Sanders Lead Company - Troy 76.4 2

Collocated Blast and Reverberatory 

Furnaces

East Penn Manufacturing – Lyons 0.19 1

Rotary Furnaces Revere Smelting and Refining – 

Middletown

0.14 1

TEQ in nanograms per dry standard cubic meter adjusted to 7 percent O2.
7

3.2 Incorporating Data Variability

Data variability was incorporated after ranking the emissions points and determining the 

top five (or fewer) best-performing sources. Each test run from the top sources was used in the 

variability analysis. By including multiple emissions tests from units with a test average from the 

top five facilities, the EPA can evaluate intra-unit variability of emissions tests over time, 

considering variability in control device performance and unit operations. As discussed 

previously, the UPL was used for the Secondary Lead Smelting MACT floor variability analysis.

The first step included a determination of whether the concentration data from the bestperforming sources were normally or log-normally distributed. If the data were normally 

distributed (e.g., similar to a typical bell curve), further variability analyses were conducted on 

the data set. If the data were not normally distributed (for example if the data were asymmetric 

or skewed to the right or left), the type of distribution (e.g., log-normal) was determined and a 

data transformation (e.g., taking the natural log of the data) was performed to normalize the data 

prior to conducting the variability analysis. Two statistical measures, skewness and kurtosis, 

were examined to determine if the data were normally or log-normally distributed. 

The skewness statistic (S) characterizes the degree of asymmetry of a given data 

distribution. Normally distributed data have a skewness of zero. A non-zero S value indicates 

that the data are asymmetrically distributed. A positive S value means that the data distribution 

has a right tail extending toward positive values. A negative S value means that the data 

distribution has a left tail extending toward negative values. Further assessment of data normality 

can be made using the standard error of the skewness statistic (SES) shown in Equation 1:

(Eq. 1)

Where: 

N = the sample size. 

According to the small sample skewness hypothesis test, if S is greater than two times the 

SES, the data distribution can be considered non-normal. 

The kurtosis statistic (K) characterizes the degree of peakedness or flatness of a given 

data distribution in comparison to a normal distribution. Normally distributed data have a 

kurtosis of zero. A K value that is greater than zero indicates a relatively peaked distribution 

while a K value less than zero indicates a relatively flat distribution. The normality of the data 

can be further evaluated using the standard error of the kurtosis statistic (SEK) shown in 

Equation 2:
8

(Eq. 2)

Where:

N = the sample size.

According to the small sample kurtosis hypothesis test, if K is greater than two times the 

SEK, the data distribution is typically considered to be non-normal.

The skewness and kurtosis hypothesis tests were applied to both the reported test values 

and the lognormal values of the reported test values. If the S and K statistics of the reported data 

set were both less than twice the SES and SEK, respectively, the data set was classified as 

normally distributed. If neither of the S and K statistics or only one of these statistics was less 

than twice the SES or SEK, respectively, skewness and kurtosis hypothesis tests were conducted 

for the natural log-transformed data. The distribution most similar to a normal distribution was 

selected as the basis for calculating the UPL. If both the reported values and the natural-log 

transformed reported values had S and K statistics that were greater than twice the SES or SEK, 

respectively, the normally distributed data set was selected as the basis of the floor to be 

protective of the environment. If the results of the skewness and kurtosis hypothesis tests were 

mixed for the reported values and the natural log-transformed reported values, the normal 

distribution was chosen to be protective of the environment. 

After determining the distribution of each dataset, a student’s t­test statistic was 

determined to calculate the UPL value. The t-statistic test, which can be found in standard 

statistical reference tables or by using the Excel function “TINV,” requires the degrees of 

freedom and the desired confidence interval. The degrees of freedom was calculated as one less 

than the number of test runs for the top five facilities and the confidence interval used was 99 

percent. 

Following the determination of the student’s t-test statistic, the 99 percent UPL values for 

each pollutant were calculated using the test run data for top five best-performing facilities. 

Because compliance with the MACT floor emissions limit is based on the average of a 3-run test, 

the UPL was calculated using the following equation:

(Eq. 3)

Where:

n = the number of test runs (i.e., sample size),

m = the number of test runs in the compliance average, 

s = standard deviation of the emissions test data, 
9

= mean, i.e., average of the emissions test data, and

t (0.99, n – 1) = t-statistic for 99% significance and a sample size of n.

Equation 3 was applied to the normally distributed data sets. However, for the 

transformed data, the average and the standard deviation of the test runs were replaced with the 

average and the standard deviation of the transformed data. The exponential function of Equation 

3 was calculated to obtain the 99 percent UPL value. 

The 99 percent UPL represents the value that one can expect the mean of future 3-run 

performance tests from the top five (or fewer) best-performing facilities to fall below with 99 

percent confidence, based upon the results of the independent sample of observations from the 

same best performing sources. Imprecision due to ND values was investigated after determining 

the 99 percent UPL values.

Because we received one emissions test with only two successful test runs for D/F and 

THC from rotary furnaces, the statistical analysis described in the above paragraphs provided 

inconclusive results. For this furnace type, we considered both the normally and log-normally 

distributed 99 percent UL in addition to the UPL; both values are presented for rotary furnaces in 

section 3.4. Because the limited data does not clearly indicate which statistical measure is a 

better measure of typical performance of the unit due to very limited emissions data, the limit 

that was the most protective of the environment and human health (i.e., the UL based limit) was 

chosen as the MACT floor. However, based on public comments, we are not promulgating a 

MACT standard for THC or D/F at this time. 

3.3 Use of Non-Detect Values

At very low emissions levels where emissions tests result in ND values, the inherent 

imprecision in the pollutant measurement method has a large influence on the reliability of the 

data underlying the regulatory floor emissions limit. Because of sample and emissions matrix 

effects, laboratory techniques, sample size and other factors, method detection levels normally 

vary from test to test for any specific test method and pollutant measurement. The confidence 

level that a value measured at the detection level is greater than zero is about 99 percent. The 

expected measurement imprecision for an emissions value occurring at or near the method 

detection level is about 40 to 50 percent. Pollutant measurement imprecision decreases to a 

consistent level of 10 to 15 percent for values measured at a level about 3 times the method 

detection level. 
10

One approach that can be applied to account for variations in concentration 

measurements in this situation starts with defining a method detection level that is representative 

of the data. The first step in this approach is to identify the highest test-specific method detection 

level reported in a data set that is also equal to or less than the average emissions calculated for 

the data set; this is termed the representative detection level (RDL). This approach has the 

advantage of relying on the data collected to develop the floor emissions limit, while to some 

degree, minimizing the effect of a test(s) with an inordinately high method detection level (e.g., 

the sample volume was too small, the laboratory technique was insufficiently sensitive or the 

procedure for determining the detection level was other than that specified). 

The second step is to determine the value equal to 3 times the RDL and compare it to the 

calculated 99 percent UPL value. If 3 times the RDL were less than the calculated UPL value, 

we would conclude that measurement variability is adequately addressed and we would not 

adjust the calculated UPL value. If, on the other hand, the value equal to 3 times the RDL was 

greater than the calculated UPL value, we would conclude that the calculated UPL value does 

not account entirely for measurement variability. Therefore, the use of the value equal to 3 times 

the method detection level in place of the UPL value ensures that the floor emissions limit 

accounts for measurement variability and imprecision. 

The following additional procedures were followed for calculating the D/F (TEQ) MACT 

floors. To calculate a limit on a TEQ basis for a test run with some, but not all values reported as 

ND, we first calculated the mean of the values that were flagged as ND for each test run. The 

toxic TEF for each congener was multiplied by the mean of the flagged values to produce a TEQ 

adjusted flagged value for each congener. A list of the TEF values used in the analysis is 

presented in Appendix C. The sum of the TEQ adjusted flagged values was used as detection 

level for each run. To calculate a detection limit for a run where all values were reported as ND, 

each ND value was multiplied by the TEF for the specific congener. The TEQ adjusted ND 

values were summed and used as the detection limit for the test run. We then continued with the 

second step discussed above to determine if measurement variability was adequately addressed 

in setting the limit.

With regards to the emissions data used in our MACT floor determinations, we did not 

receive any BDL emissions data for THC, and thus the above analyses were not necessary. For 

D/F, approximately 67 percent of the individual congener emissions data was above detection 

level (ADL). Additionally, the 99 percent UPL was in all cases greater than the 3 times the RDL.

3.4 MACT Floor and Variability Analysis Results

Tables 3-3 through 3-8 present the results of the existing source MACT floor and 

variability analysis for THC and D/F for each furnace group.
11

Table 3-3. Existing Source MACT Floor and Variability Analysis Results for THC – 

Reverberatory Furnaces Not Collocated with Blast Furnaces and Reverberatory 

Furnaces Mixed with Electric Furnaces

Parameter Normal Log-normal

Number of Test Runs 6 6

Average (ppmv) 5.53 2.04

Median (ppmv) 5.75 1.74

Standard Deviation (ppmv) 2.72 0.58

Minimum (ppmv) 2.12 0.75

Maximum (ppmv) 8.83 2.18

Skewness -0.14 -0.62

SE Skewness 1.00 1.00

Skewness Test normal normal

Kurtosis -1.86 -1.50

SE Kurtosis 2.00 2.00

Kurtosis Test normal normal

99.0% t-statistic for UPL 3.36 3.36

99.0% UPL (ppmv) 12.01 30.64

UPL Value Using Normally Distributed Data

99% UPL (ppmv) 12.01

UPL Value Using LN Transformed Data

99% UPL (ppmv) 30.64

ppmv – Parts per million volume expressed as propane, adjusted to 4 percent CO2

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN – Log-Normal

N/A – Not applicable

Table 3-4. Existing Source MACT Floor and Variability Analysis Results for THC – 

Rotary Furnaces*

Parameter Normal Lognormal

Sample Size 2 2

Average (ppmv) 256.73 5.54

Median (ppmv) 256.73 5.54

Standard Deviation (ppmv) 49.54 0.19

Minimum (ppmv) 221.70 5.40

Maximum (ppmv) 291.77 5.68

Skewness N/A N/A
12

SE Skewness 1.73 1.73

Skewness Test N/A N/A

Kurtosis N/A N/A

SE Kurtosis 3.46 3.46

Kurtosis Test N/A N/A

99.0% t-statistic for UL 2.62 2.62

99.0% UL (ppmv) 601.79 983.49

99.0% UPL (ppmv) 1695.91 71649.41

UL and UPL Values Using Normally Distributed Data

99% UL (ppmv) 601.79

99% UPL (ppmv) 1695.91

UL and UPL Values Using LN Transformed Data

99% UL (ppmv) 983.49

99% UPL (ppmv) 74649.41

ppmv – Parts per million volume expressed as propane, adjusted to 4 percent carbon dioxide

SE – Standard error (applied to skewness or kurtosis)

UL - Upper limit

UPL – Upper prediction limit

LN – Log-Normal

N/A – Not applicable

*Data is not sufficient to establish MACT floor limits as represented in this table

Table 3-5. Existing Source MACT Floor and Variability Analysis Results for D/F – 

Reverberatory Furnaces Not Collocated with Blast Furnaces and Reverberatory 

Furnaces Mixed with Electric Furnaces

Parameter Normal Lognormal

Sample Size 9 9

Average (ng/dscm) 0.10 -2.41

Median (ng/dscm) 0.08 -2.52

Standard Deviation (ng/dscm) 0.04 0.42

Maximum (ng/dscm) 0.17 -1.80

Minimum (ng/dscm) 0.04 -3.23

Skewness 0.60 -0.40

SE Skewness 0.82 0.82

Skewness Test normal normal

Kurtosis -0.21 0.72

SE Kurtosis 1.63 1.63

Kurtosis Test normal normal
13

99.0% t-statistic for UPL 2.82 2.82

99.0% UPL (ng/dscm) 0.17 0.20

UPL Value Using Normally Distributed Data

99% UPL (ng/dscm) 0.17

UPL Value Using LN Transformed Data

99% UPL (ng/dscm) 0.20

ng/dscm – Nanograms per dry standard cubic meter adjusted to 7 percent oxygen

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN – Log-Normal

N/A – Not applicable

Table 3-6. Existing Source MACT Floor and Variability Analysis Results for D/F – 

Blast Furnaces

Parameter Normal Lognormal

Sample Size 6 6

Average (ng/dscm) 38.83 2.23

Median (ng/dscm) 1.44 0.37

Standard Deviation (ng/dscm) 52.27 2.19

Minimum (ng/dscm) 1.20 0.18

Maximum (ng/dscm) 134.51 4.90

Skewness 1.52 0.14

SE Skewness 1.00 1.00

Skewness Test normal normal

Kurtosis 2.18 -2.89

SE Kurtosis 2.00 2.00

Kurtosis Test normal normal

99.0% t-statistic for UPL 3.36 3.36

99.0% UPL (ng/dscm) 163.20 1714.90

UPL Value Using Normally Distributed Data

99% UPL (ng/dscm) 163.20

UPL Value Using LN Transformed Data

99% UPL (ng/dscm) 1714.90

ng/dscm – Nanograms per dry standard cubic meter adjusted to 7 percent oxygen

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN – Log-Normal

N/A – Not applicable

Table 3-7. Existing Source MACT Floor and Variability Analysis Results for D/F – 
14

Parameter Normal Lognormal

Sample Size 3 3

Average (ng/dscm) 0.19 -1.68

Median (ng/dscm) 0.21 -1.55

Standard Deviation (ng/dscm) 0.04 0.23

Minimum (ng/dscm) 0.14 -1.95

Maximum (ng/dscm) 0.21 -1.54

Skewness -1.73 -1.73

SE Skewness 1.41 1.41

Skewness Test Normal normal

Kurtosis N/A N/A

SE Kurtosis 2.83 2.83

Kurtosis Test N/A N/A

99.0% t-statistic for UPL 6.96 6.96

99.0% UPL (ng/dscm) 0.42 0.70

UPL Value Using Normally Distributed Data

99% UPL (ng/dscm) 0.42

UPL Value Using LN Transformed Data

99% UPL (ng/dscm) 0.70

ng/dscm – Nanograms per dry standard cubic meter adjusted to 7 percent oxygen

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN – Log-Normal

N/A – Not applicable

Table 3-8. Existing Source MACT Floor and Variability Analysis Results for D/F – 

Rotary Furnaces*

Parameter Normal Lognormal

Sample Size 2 2

Average (ng/dscm) 0.14 0.04

Median (ng/dscm) 0.14 0.04

Standard Deviation (ng/dscm) 0.12 0.01

Minimum (ng/dscm) 0.06 0.03

Maximum (ng/dscm) 0.23 0.04

Skewness N/A N/A

SE Skewness 1.73 1.73

Skewness Test N/A N/A

Kurtosis N/A N/A
15

SE Kurtosis 3.46 3.46

Kurtosis Test N/A N/A

99.0% t-statistic for UL 6.96 6.96

99.0% UL (ng/dscm) 0.96 1.08

99.0% UPL (ng/dscm) 3.54 1.24

UL and UPL Values Using Normally Distributed Data

99% UL (ng/dscm) 0.96

99% UPL (ng/dscm) 3.54

UL and UPL Values Using LN Transformed Data

99% UL (ng/dscm) 1.08

99% UPL (ng/dscm) 1.24

ng/dscm – Nanograms per dry standard cubic meter adjusted to 7 percent oxygen

SE – Standard error (applied to skewness or kurtosis)

UL - Upper Limit

UPL – Upper prediction limit

LN – Log-Normal

N/A – Not applicable

*Data is not sufficient to establish MACT floor limits as represented in this table

New source limits for THC and D/F were determined by selecting the top performing 

source for each furnace group. A variability analysis similar to that used for existing sources was 

then performed using the 3 run test data from the top source. For THC and D/F from rotary 

furnaces and D/F from collocated blast and reverberatory furnaces, the MACT floor was 

calculated based on emissions data from one source; therefore, the new source MACT floor is 

the same as the existing source MACT floor. As noted above, emission limits for D/F and THC 

from rotary furnace are not being promulgated due to insufficient data. Results of the new source 

variability analyses for the other furnace groups for D/F and THC are presented in Tables 3-9 

through 3-11.

Table 3-9. New Source MACT Floor and Variability Analysis Results for THC – 

Reverberatory Furnaces Not Collocated with Blast Furnaces and Reverberatory 

Furnaces Mixed with Electric Furnaces

Parameter Normal Lognormal

Sample Size 3 3

Average (ppmv) 3.30 1.13

Median (ppmv) 2.78 1.02

Standard Deviation (ppmv) 1.51 0.44

Minimum (ppmv) 2.12 0.75

Maximum (ppmv) 5.00 1.61

Skewness 1.37 1.02
16

SE Skewness 1.41 1.41

Skewness Test Normal normal

Kurtosis N/A N/A

SE Kurtosis 2.83 2.83

Kurtosis Test N/A N/A

99.0% t-statistic for UPL 6.96 6.96

99.0% UPL (ppmv) 11.87 37.40

UPL Value Using Normally Distributed Data

99% UL (ppmv) 11.87

UPL Value Using LN Transformed Data

99% UL (ppmv) 37.40

ppmv – Parts per million volume expressed as propane, adjusted to 4 percent carbon dioxide

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN – Log-Normal

N/A – Not applicable

Table 3-10. New Source MACT Floor and Variability Analysis Results for D/F – 

Reverberatory Furnaces Not Collocated with Blast Furnaces and Reverberatory 

Furnaces Mixed with Electric Furnaces

Parameter Normal Lognormal

Sample Size 3 3

Average (ng/dscm) 0.08 -2.52

Median (ng/dscm) 0.08 -2.52

Standard Deviation (ng/dscm) 0.00 0.04

Minimum (ng/dscm) 0.08 -2.48

Maximum (ng/dscm) 0.08 -2.55

Skewness 0.33 0.28

SE Skewness 1.41 1.41

Skewness Test Normal normal

Kurtosis N/A N/A

SE Kurtosis 2.83 2.83

Kurtosis Test N/A N/A

99.0% t-statistic for UPL 6.96 6.96

99.0% UPL (ng/dscm) 0.10 0.10

UPL Value Using Normally Distributed Data

99% UPL (ng/dscm) 0.10

UPL Value Using LN Transformed Data
17

99% UPL (ng/dscm) 0.10

ng/dscm – Nanograms per dry standard cubic meter adjusted to 7 percent oxygen

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN-Log-Normal

N/A – Not applicable

Table 3-11. New Source MACT Floor and Variability Analysis Results for D/F – 

Blast Furnaces

Parameter Normal Lognormal

Sample Size 3 3

Average (ng/dscm) 1.30 0.26

Median (ng/dscm) 1.23 0.22

Standard Deviation (ng/dscm) 1.43 1.38

Minimum (ng/dscm) 1.20 0.18

Maximum (ng/dscm) 1.44 0.37

Skewness 1.43 1.38

SE Skewness 1.41 1.41

Skewness Test Normal normal

Kurtosis N/A N/A

SE Kurtosis 2.83 2.83

Kurtosis Test N/A N/A

99.0% t-statistic for UPL 6.96 6.96

99.0% UPL (ng/dscm) 9.45 3394.06

UPL Value Using Normally Distributed Data

99% UPL (ng/dscm) 9.45

UPL Value Using LN Transformed Data

99% UPL (ng/dscm) 3394.06

ng/dscm – Nanograms per dry standard cubic meter adjusted to 7 percent oxygen

SE – Standard error (applied to skewness or kurtosis)

UPL - Upper prediction limit

LN-Log-Normal

N/A – Not applicable

4.0 BEYOND THE FLOOR

To evaluate opportunities for emissions reductions beyond those that would result from 

requiring facilities to meet the MACT floor emissions limits, we typically identify control 

techniques that have the ability to achieve an emissions limit more stringent than the MACT 

floor and evaluate whether the standard should be more stringent based on consideration of the 

factors enumerated in section 112 (d)(2) of the Act. The following paragraphs summarize the 
18

results of this “beyond-the-floor” analysis for the affected sources in the Secondary Lead 

Smelting source category.

Through our technology review discussed in the Technology Review for the Secondary 

Lead Smelting Source Category document available in the docket, we identified one beyond-thefloor option to achieve further reduction in emissions of D/F and THC. This option is the 

installation of additional afterburner capacity at the facilities operating blast furnaces. This 

would include operating the currently installed afterburners at a temperature of 1600 degrees 

Fahrenheit (°F) with a residence time of 2.5 seconds, or installation of a new afterburner with 

these specifications at any facility currently operating a blast furnace without the use of an 

afterburner or with an afterburner that does not meet the mentioned specifications. Based on 

available information and our analysis described in the technology review, we estimate that these 

conditions would result in significant decreases in D/F and THC emissions.

Based on the current level of performance identified in the ICR surveys, we believe that 

this beyond-the-floor option would require four facilities to install additional capacity at their 

existing afterburners to operate the units at a temperature of 1600 °F with a residence time of 2.5 

seconds. The estimated total capital cost for the additional controls is $5.9 million, with a total 

annualized cost of $2.9 million. Based on an estimated control efficiency of 98 percent, TEQ 

emissions would be reduced by 31 grams per year and organic HAP emissions by 200 tons per 

year, resulting in a total estimated cost effectiveness of $93,500 per gram of TEQ and $14,500 

per ton of organic HAP. There would also be significant adverse energy implications to use of 

this technology. Non-air environmental impacts from use of this technology appear to be 

increased use of fuel. Another disadvantage of this beyond the floor option is that it would result 

in increased emissions of CO2 and NOx. 

5.0 SUMMARY OF MACT FLOOR ANALYSIS

We determined emissions limits for each MACT floor option and pollutant by rounding 

the UPL values less than 1 up to one significant figure and rounding the UPL values between 1 

and 10,000 up to two significant figures. This approach allows for an appropriate level of 

precision depending on the scale of the measured value. It should be noted that if the UPL values 

were rounded down, then the possibility exists that the best-performing units that comprise the 

MACT floor may not be able to achieve the emissions limit on an ongoing basis. In all cases, the 

significant figure approach and associated rounding does not meaningfully change the emissions 

limits. Tables 5-1 through 5-4 summarize the MACT floor limits calculated in document.

Table 5-1. Summary of Calculated THC Floor Limits for Existing Sources

Furnace Group Average of Top 5

Performers

99% UPL MACT Floor

Emissions Limit
19

Reverberatory furnaces not collocated with 

blast furnaces and reverberatory furnaces 

mixed with electric furnaces

5.53 12.01 13

Rotary Furnaces 256.73 601.79* 610**

*Calculated MACT floor emissions limit for rotary furnaces calculated based on the UL. 

**Data is insufficient to establish a MACT floor for this source.

Table 5-2. Summary of Calculated D/F Floor Limits for Existing Sources

Furnace Group Average of Top 5

Performers

99% UPL MACT Floor

Emissions Limit

Reverberatory furnaces not collocated with blast 

furnaces and reverberatory furnaces mixed with 

electric furnaces

0.10 0.17 0.2

Blast Furnaces 38.83 163.2 170

Collocated Blast and Reverberatory Furnaces 0.19 0.42 0.5

Rotary Furnaces 0.14 0.96* 1.0**

*Calculated MACT floor emissions limit for rotary furnaces is based on the Upper Limit (UL). 

**Data is insufficient to establish a MACT floor for this source.

Table 5-3. Summary of Calculated THC Floor Limits for New Sources

Furnace Group Average of Top

Performer

99% UPL MACT Floor

Emissions Limit

Reverberatory furnaces not collocated with blast 

furnaces and reverberatory furnaces mixed with 

electric furnaces

3.30 11.81 12

Rotary Furnaces 256.73 601.79* 610**

*Calculated MACT floor emissions limit for rotary furnaces is based on the Upper Limit (UL). 

**Data is insufficient to establish a MACT floor for this source.

Table 5-4. Summary of Calculated D/F Floor Limits for New Sources 

Furnace Group Average of Top

Performer

99% UPL MACT Floor

Emissions Limit

Reverberatory furnaces not collocated with blast 

furnaces and reverberatory furnaces mixed with 

electric furnaces

0.08 0.10 0.1

Blast Furnaces 1.30 9.45 10

Collocated Blast and Reverberatory Furnaces 0.19 0.42 0.5

Rotary Furnaces 0.14 0.96* 1.0**

*Calculated MACT floor emissions limit for rotary furnaces is based on the Upper Limit (UL). 

**Data is insufficient to establish a MACT floor for this source. 
20

Appendix A. Total Hydrocarbons Emissions Data

Facility ID Emissions Point Furnace Type Sample ID THC (ppmv @ 

4% CO2)

In top 5?

Quemetco IN EP1 Reverb/Electric Sample 1 7.94 Y

Quemetco IN EP1 Reverb/Electric Sample 2 6.51 Y

Quemetco IN EP1 Reverb/Electric Sample 3 8.83 Y

RSR EP17 Reverb Sample 1 2.12 Y

RSR EP17 Reverb Sample 2 2.78 Y

RSR EP17 Reverb Sample 3 5.00 Y

ND = Non-Detect
21

Appendix B. Dioxins and Furans (TEQ) Emissions Data

Facility ID Emissions Point Furnace Type Sample ID TEQ 

(ng/dscm @ 

7% O2)

In top 5?

Quemetco CA WESP Reverb Sample 1 0.08 Y

Quemetco CA WESP Reverb Sample 2 0.08 Y

Quemetco CA WESP Reverb Sample 3 0.08 Y

Quemetco IN EP1 Reverb/Electric Sample 1 0.08 Y

Quemetco IN EP1 Reverb/Electric Sample 2 0.14 Y

Quemetco IN EP1 Reverb/Electric Sample 3 0.13 Y

RSR EP17 Reverb/Electric Sample 1 0.04 Y

RSR EP17 Reverb Sample 2 0.17 Y

RSR EP17 Reverb Sample 3 0.07 Y

Sanders EP5 Blast Sample 1 39.00 Y

Sanders EP5 Blast Sample 2 55.56 Y

Sanders EP5 Blast Sample 3 134.51 Y

Exide Forest City EP01 Blast Sample 1 1.44 Y

Exide Forest City EP01 Blast Sample 2 1.20 Y

Exide Forest City EP01 Blast Sample 3 1.25 Y

East Penn C02 Collocated 

Blast/Reverb

Sample 1 0.21 Y

East Penn C02 Collocated 

Blast/Reverb

Sample 2 0.21 Y

East Penn C02 Collocated 

Blast/Reverb

Sample 3 0.14 Y

TEQ = toxic equivalency quotient
22

Appendix C. World Health Organization’s (WHO) Recommended Toxic 

Equivalency Factors (TEF)

Dioxin/Furan Congener Toxic Equivalency Factor

2,3,7,8-tetrachlorinated dibenzo-p-dioxin 1

1,2,3,7,8-pentachlorinated dibenzo-p-dioxin 0.5

1,2,3,4,7,8-hexachlorinated dibenzo-p-dioxin 0.1

1,2,3,7,8,9-hexachlorinated dibenzo-p-dioxin 0.1

1,2,3,6,7,8-hexachlorinated dibenzo-p-dioxin 0.1

1,2,3,4,6,7,8-heptachlorinated dibenzo-p-dioxin 0.01

octachlorinated dibenzo-p-dioxin 0.001

2,3,7,8-tetrachlorinated dibenzofuran 0.1

2,3,4,7,8-pentachlorinated dibenzofuran 0.05

1,2,3,7,8-pentachlorinated dibenzofuran 0.5

1,2,3,4,7,8-hexachlorinated dibenzofuran 0.1

1,2,3,6,7,8-hexachlorinated dibenzofuran 0.1

1,2,3,7,8,9-hexachlorinated dibenzofuran 0.1

2,3,4,6,7,8-hexachlorinated dibenzofuran 0.1

1,2,3,4,6,7,8-heptachlorinated dibenzofuran 0.01

1,2,3,4,7,8,9-heptachlorinated dibenzofuran 0.01

octachlorinated dibenzofuran 0.001
23

Appendix D. Secondary Lead Smelters Currently Operating in the U.S and 

Territories

Facility Parent Company City State Facility 

Abbreviation

East Penn 

Manufacturing

East Penn Manufacturing 

Co., Inc.

Lyon Station Pennsylvania East Penn

EnviroFocus 

Technologies, LLC

Gopher Resources, LLC Tampa Florida EnviroFocus

Gopher Resources, 

LLC

Gopher Resources, LLC Eagan Minnesota Gopher Eagan

Quemetco, Inc. Eco-Bat Technologies, 

LTD (Quemetco West, 

LLC)

Industry California Quemetco CA

Quemetco, Inc. Eco-Bat Technologies, 

LTD (Eco-Bat Indiana, 

LLC)

Indianapolis Indiana Quemetco IN

Revere Smelting and 

Refining Corporation 

(RSR)

Eco-Bat Technologies, 

LTD (Eco-Bat New York, 

LLC)

Middletown New York RSR

Sanders Lead 

Company

Sanders Lead Company Troy Alabama Sanders Lead

Baton Rouge 

Recycling Center

Exide Technologies, Inc. Baton Rouge Louisiana Exide Baton 

Rouge

Canon Hollow 

Recycling Facility

Exide Technologies, Inc. Forest City Missouri Exide Forest City

Frisco Battery 

Recycling

Exide Technologies, Inc. Frisco Texas Exide Frisco

Exide Technologies Exide Technologies, Inc. Muncie Indiana Exide Muncie

Exide Technologies – 

Reading Recycling

Exide Technologies, Inc. Reading Pennsylvania Exide Reading

Exide Technologies Exide Technologies, Inc. Vernon California Exide Vernon

Buick Resource 

Recycling Facility, 

LLC

The Doe Run Resources 

Corporation

Boss Missouri Buick RRF

The Battery Recycling 

Company

The Battery Recycling 

Company

Arecibo Puerto Rico TBR
1

1 ERG. Development of the RTR Emissions Dataset for the Secondary Lead Smelting Source Category, December 

16, 2011.

2 ERG. MACT Floor Analysis for the Secondary Lead Smelting Source Category, December 16, 2011.

MEMORANDUM

To: Nathan Topham, U.S. Environmental Protection Agency, OAQPS

From: Donna Lazzari and Mike Burr, ERG 

Date: December 16, 2011

Subject: Cost Impacts for the Secondary Lead Smelting Source Category 

The purpose of this memorandum is to describe the methodology used to estimate the 

costs, emissions reductions, and secondary impacts of the final revisions to the National 

Emissions Standards for Hazardous Air Pollutants (NESHAP) for the Secondary Lead Smelting 

source category. These impacts were calculated for existing units and new units projected to be 

operational by the year 2014, two years after the rule is expected to be promulgated and the 

anticipated year of implementation of the revised NESHAP. The results of the impacts analyses 

are presented for the most stringent regulatory options considered in addition to the regulatory 

options that were ultimately chosen for promulgation. The development of the baseline 

emissions estimates and the maximum achievable control technology (MACT) floors for this 

source category are discussed in other memoranda1,2.The organization of this document is as 

follows:

1.0 Summary of Cost Estimates and Emissions Reductions for the Regulatory Options 

Chosen for Proposal 

2.0 Regulatory Options Considered for Proposal

3.0 Methodology for Estimating Control Costs

4.0 Methodology for Estimating Emissions Reductions

5.0 Testing and Monitoring Cost Impacts

6.0 Summary of Cost by Facility

1.0 SUMMARY OF COST ESTIMATES AND EMISSIONS REDUCTIONS FOR THE 

REGULATORY OPTIONS CHOSEN FOR PROPOSAL

Regulatory options were considered for control of emissions of metal hazardous air 

pollutants (HAP), organic HAP, and dioxins and furans (D/F) from stacks and metal HAP from 
2

fugitive sources. For all options, total hydrocarbons (THC) are considered a surrogate for 

organic HAP (other than dioxins and furans) and lead a surrogate for metal HAP. A brief 

description of the options selected for the revisions to the NESHAP and the associated costs and 

emissions reductions are summarized in Table 1-1. The most stringent options considered in this 

analysis are summarized in Table 1-2. A more detailed description of all the regulatory options 

considered for proposal and their associated cost and emissions reductions estimates are 

presented in section 2.0 of this memorandum.

Table 1-1: Summary of the Estimated Costs and Emissions Reductions of 

Regulatory Options Selected for Final Rule

Option Description COST IN $ MILLIONS (2009 DOLLARS) Total HAP 

Emissions 

Reductions 

(tons per 

year)

Cost per 

ton HAP 

reduction 

($MM)

Capital 

Cost

Annualized 

Capital 

Cost

Annual 

Operation 

and 

Maintenanc

e Cost

Total 

Annualized 

Cost

3S Stack lead 

concentration 

limit of 1.0 

mg/dscm any 

stack, and 0.2 

mg/dscm 

facility 

average

$11.5 $1.1 $1.7 $2.7 8.2 $0.33 

1D D/F 

Concentratio

n based limit

$0 $0 $0.26 $0.26 30 $0.01

3F Fugitive 

enclosure + 

work practice

$38 $3.6 $5.8 $9.4 7.1 $1.3 

Test, 

Monitor, 

Report

Additional 

Testing, 

Monitoring

$0.10 $0.01 $0.79 $0.80 

Total $49.7 $4.7 $8.5 $13.2 45.0 $0.29

*Tons of total organic HAP (3 grams/yr D/F reduction)

Table 1-2: Summary of the Estimated Costs and Reductions for the Most 

Stringent Options Considered

Option Description COST IN $ MILLIONS (2009 DOLLARS) Total HAP 

Emissions 

Reductions 

(tons per 

year)

Cost per 

ton HAP 

reduction 

($MM)

Capital 

Cost

Annualized 

Capital 

Cost

Annual 

Operation 

and 

Maintenanc

e Cost

Total 

Annualized 

Cost

4S Stack lead 

concentratio

n <0.01 

mg/dscm 

$365 $34 $12 $46 19.5 $2.37
3

Stack lead 

concentratio

n <0.01 

mg/dscm 

(WESP)

$365 $34 $12 $46 19.5 $2.37

2D Beyond the 

floor D/F 

limits for 

blast 

furnaces

$5.9 $0.6 $2.4 $2.9 303 $0.01

1F and 2F Enclosures, 

work 

practices, 

monitoring

$38 $3.6 $6.2 $9.8 7.1 $1.37

Test, 

monitor, 

report

Additional 

testing and 

monitoring

$0.10 $0.0 $0.8 $0.8

Total $409 $38.6 $21.1 $18.8 330 $0.06

2.0 REGULATORY OPTIONS CONSIDERED FOR PROMULGATION

This section provides a detailed description of all regulatory options that were considered 

for the revisions to the Secondary Lead Smelting NESHAP and their associated costs and 

secondary impacts.

2.1 Stack Emissions – Metal HAP

The four regulatory options considered for control of metal HAP emissions from stacks 

are presented in the following sections.

a. Option 1S

Regulatory option 1S represents a scenario of reducing the existing lead emissions 

concentration limit from 2.0 milligrams per dry standard cubic meter (mg/dscm) to 0.5 mg/dscm. 

In order to estimate costs and emission reductions for this option, we assumed that individual 

stacks with concentrations more than half the standard of 0.5 mg/dscm would replace baghouses 

or improve the maintenance and change the filtration media. Based on emissions data received in 

an information collection request (ICR) sent to the industry, twenty emissions points at six 

facilities reported concentrations above 0.25 mg/dscm; estimates of cost and emissions 

reductions were made for 15 of these stacks. Three facilities are currently undergoing an upgrade 

to their emissions control equipment with plans to replace existing baghouses or add additional 

filtration capacity, and thus, we assumed this would reduce the lead concentration at these five 

stacks below 0.25 mg/dscm. For 12 of the stacks reporting concentrations above 0.25 mg/dscm, 

we assumed that a replacement baghouse would be installed. For three stacks that were near the 

evaluated limit of 0.25 mg/dscm we assumed that lead concentrations below 0.25 mg/dscm could 
4

be achieved through replacement bags and performance of additional maintenance on the unit. 

The total estimated capital cost for the 12 new baghouses that would likely be necessary to 

achieve concentrations below 0.25 mg/dscm is $14.8 million, resulting in an annualized capital 

cost of $1.4 million. Additional annual operational and maintenance costs, including more 

frequent bag changes for the 15 baghouses, are estimated at $2.0 million above the costs of 

operating the current air pollution control devices. The total estimated annualized cost above 

current cost for the 15 baghouses is $3.4 million (2009 dollars). The estimated emissions 

reductions of Option 1S are 7.1 tons per year of lead and 9.0 tons per year of total metal HAP. 

b. Option 2S

Option 2S considers a production-based lead emissions limit. A limit of 0.009 pounds of 

lead emissions per ton of lead production (lbs/ton Pb) was calculated as a facility-wide emissions 

limit using a methodology similar to a MACT floor analysis. We estimate that new or improved 

baghouses would likely be necessary at 18 emissions points at six facilities to meet the limit 

considered in this option. For facilities that were estimated to be above the limit considered in 

this option, we sequentially selected stacks for a baghouse replacement or upgrade (based on 

reported concentration) until the facility was estimated to have emissions below 0.009 lbs/ton Pb. 

Two of the stacks selected had relatively newer baghouses, and thus, we estimated the cost of 

changing all the existing bags to a new upgraded filter media and performing additional 

maintenance for these units. One selected stack had a baghouse that was less than 10 years old; 

we estimated 25 percent of the cost of a new unit to represent additional filtration media or 

substantial upgrade to this unit. For the remainder of the selected stacks, we assumed 

replacement baghouses would be needed. The total estimated capital cost for this regulatory 

option is $21.5 million, resulting in an annualized capital cost of $2.0 million. Additional annual 

operational and maintenance costs, including more frequent bag changes for the baghouses, are 

estimated at $2.5 million above current costs. The total annualized cost above current air 

pollution control device operating costs for the 18 baghouses is $4.5 million (2009 dollars). Total 

anticipated emissions reductions of lead and other metal HAP in this option are estimated at 9.6 

tons per year.

c. Option 3S

Option 3S is the regulatory option that was selected by the EPA for promulgation in the 

Secondary Lead Smelting NESHAP. This option represents an overall facility-wide flowweighted average lead concentration limit of 0.2 mg/dscm and a limit of 1.0 mg/dscm for any 

individual stack. In order to estimate costs and emission reductions for this option, we assumed 

that individual stacks with concentrations more than half the standard of 1.0 mg/dscm would 

replace baghouses or improve the maintenance and change the filtration media. We then 

reviewed the facility-wide flow-weighted average concentration from all the stacks after these 
5

improvements to determine if additional reductions were necessary. We determined that all the 

secondary lead facilities would be in compliance with the flow-weighted average after the 

upgrades described. In order to estimate costs and emission reductions for this option, we 

assumed that individual stacks with concentrations more than half the standard of 1.0 mg/dscm 

would replace baghouses or improve the maintenance and change the filtration media. Eleven 

emissions points at six facilities reported concentrations above 0.5 mg/dscm; estimates of cost 

and emissions reductions were made for ten of these stacks. A baghouse at one facility is 

currently undergoing an upgrade, and we assumed this would reduce the lead concentration 

below 0.5 mg/dscm. Three stacks had outlet concentrations near the evaluated limit, and we 

assumed an outlet concentration of less than 0.5 mg/dscm could be achieved through 

replacement bags and performance of additional maintenance on the unit. The total estimated 

capital cost for this regulatory option is $11.5 million, resulting in an annualized capital cost of 

$1.1 million. Additional annual operational and maintenance costs, including more frequent bag 

changes for the baghouses, are estimated at $1.7 million above current costs. The total 

annualized cost above current air pollution control device operating costs for the 11 baghouses is 

$2.7 million (2009 dollars). Total anticipated emissions reductions of lead and other metal HAP 

in this option are estimated at 8.2 tons per year.

d. Option 4S

Option 4S is a regulatory option that considers requiring installation of a wet electrostatic 

precipitator (WESP) or equivalent technology at each facility to control stack emissions of metal 

HAP. One facility in this source category currently utilizes a WESP to control metal HAP 

emissions from stacks (i.e., Quemetco, Inc. in City of Industry, CA). Based on emissions data 

received in the ICR, this facility is the lowest emitting facility in terms of stack emissions of 

metal HAP. In this option, the other 15 facilities in the source category would be required to 

install technology with equivalent performance to a WESP. Based on the configuration of the 

existing WESP reported in the ICR, we assumed that facilities that would need to install a WESP 

under this option would use the WESP to control metal HAP emissions from process and process 

fugitive emissions sources only. Additionally, we assumed that the process fugitive vents would 

be optimized to minimize the airflow from these sources. We also assumed that baghouses 

installed on building vents would not be routed to the WESP. The total estimated capital cost for 

installation of a WESP at 15 facilities is $365 million, resulting in an annualized capital cost of 

$34 million. Operating costs were estimated at $12 million. The total annualized cost above 

current cost is estimated at $46 million. Lead emissions reductions for this option are estimated 

at 15.4 tons per year with total estimated metal HAP emissions reductions of 19.5 tons per year. 

The cost of installation and projected emissions reductions from a facility currently under 

construction were included in this estimate. 
6

e. Option 5S

Option 5S is a regulatory option that was considered after proposal of the revised 

secondary lead NESHAP. This option was considered based on comments received that the 

emission controls proposed would not require a significant amount of emissions reduction, and 

the limits proposed did not represent advances in control technology. 

Regulatory option 5S represents a scenario of reducing the existing lead emissions 

concentration limit from 2.0 milligrams per dry standard cubic meter (mg/dscm) to 0.2 mg/dscm 

for all stacks. Based on emissions data received in an information collection request ( ICR) sent 

to the industry, 80 percent of the stacks in this source category reported concentrations below 0.2 

mg/dscm. In order to estimate costs and emission reductions for this option, we assumed that 

individual stacks with concentrations more than half the standard of 0.2 mg/dscm would replace 

baghouses or improve the maintenance and change the filtration media. There are 30 emissions 

points at six facilities that reported concentrations above 0.1 mg/dscm; estimates of cost and 

emissions reductions were made for 29 of these stacks. One facility is currently undergoing an 

upgrade with plans to replace an existing baghouse, and thus, we assumed this action would 

reduce the lead concentration in three stacks at this facility to below 0.1 mg/dscm. 

For 29 of the stacks reporting concentrations above 0.1 mg/dscm, we assumed that a 

replacement baghouse with an additional HEPA filter would be installed. The total estimated 

capital cost that would likely be necessary to achieve concentrations below 0.1 mg/dscm is $36 

million, resulting in an annualized capital cost of $3.1 million. Additional annual operational and 

maintenance costs, including more frequent bag changes for the baghouses, are estimated at $4.1 

million above the costs of operating the current air pollution control devices. The total estimated 

annualized cost above current cost for the 29 baghouses is $7.5 million (2009 dollars). The 

estimated emissions reductions of Option 5S are 9.8 tons per year of lead and 12.4 tons per year 

of total metal HAP. 

f. Summary

A summary of the costs and emissions reductions associated with the five regulatory 

options described above for stack emissions are summarized in Table 2-1.
7

Table 2-1: Estimated Costs and Emissions Reductions for the Regulatory Options 

Considered for Stack Emissions of Metal HAP.

Option Description COST IN $ MILLIONS (2009 DOLLARS) Total HAP 

Emissions 

Reductions 

(tons per 

year)

Cost per 

ton HAP 

reduction 

($MM)

Capital 

Cost

Annualized 

Capital 

Cost

Annual 

Operation 

and 

Maintenanc

e Cost

Total 

Annualized 

Cost

1S Concentratio

n limit of 0.5 

mg/dscm

$14.2 $1.3 $2.0 $3.4 9.0 $0..38 

2S 0.009 lb Pb / 

Ton Pb 

produced

$21.5 $2.0 $2.5 $4.5 9.6 $0.52

3S Concentratio

n limit of 1.0 

mg/dscm any 

stack, and 0.2 

mg/dscm 

facility 

average

$11.5 $1.1 $1.7 $2.70 8.2 $0.33 

4S Concentratio

n limit <0.01 

mg/dscm 

WESP

$365 $34 $12 $46 19.5 $2.37

5S Concentratio

n limit of 0.2 

mg/dscm

$36 $3.4 $4.1 $7.5 12.4

0.0.60

2.2 Stack Emissions – Organic HAP and D/F

The two regulatory options considered for control of stack emissions of organic HAP and 

D/F are presented in the following sections.

a. Option 1D

Option 1D is the regulatory option that EPA chose for the revised NESHAP for the 

Secondary Lead Smelting source category. This option represents calculating a MACT floor for 

D/F emissions from various furnace groupings that were formed based on similar operating 

characteristics. In addition to the D/F MACT floors, new MACT floors for THC were calculated 

for furnace types that are not regulated in the existing NESHAP. These include reverberatory 

furnaces not collocated with blast furnaces, and electric arc furnaces. Sufficient data was not 

available to calculate MACT floors for the rotary furnace category. The THC MACT limits for 

blast furnaces and collocated blast and reverberatory furnaces in the existing NESHAP would 

remain unchanged under the proposed revisions. We do not anticipate that this regulatory option 
8

will require installation of additional controls at any facilities. We do anticipate, however, that 

four facilities operating blast furnaces will likely increase the temperature of their afterburners to 

ensure continuous compliance with the new MACT floors for D/F. The cost of the natural gas 

required to raise the temperature 100 degrees Fahrenheit (°F) at afterburners was estimated at 

$260,000 per year (2009 dollars). Under this regulatory option, we estimate D/F emissions 

reductions of about 2.9 grams per year and organic HAP emissions reductions of about 30 tons 

per year.

b. Option 2D

Option 2D represents a beyond-the-floor option for D/F emissions from blast furnaces 

that are not collocated with reverberatory furnaces. This option was considered because based on 

emissions data submitted in the ICR, blast furnaces that are not collocated with reverberatory 

furnaces contribute approximately 78 percent of the total D/F emissions from the source 

category. In this option, a Toxic Equivalency Quotient (TEQ) based concentration limit of 17 

nanograms per dry standard cubic meter (ng/dscm) (corrected to 7 percent oxygen (O2)) was 

considered for blast furnaces. This concentration represents an approximate 90 percent reduction 

in total D/F emissions from blast furnaces in this source category. 

For this option, we assumed that additional afterburner capacity would be needed at five 

blast furnaces. Two of the blast furnaces have afterburners currently installed that meet the 

requirements of this considered regulatory option. The total estimated capital cost for installation 

of the additional afterburners is $5.9 million, which results in an estimated annualized capital 

cost of $0.56 million. Annual operational and maintenance costs increases, including additional 

natural gas fuel, are estimated at $2.4 million above current control device operating costs. The 

total annualized cost above current cost for the afterburners is estimated to be $2.9 million (2009 

dollars). Under this scenario, we anticipate D/F emissions reductions of 31 grams per year, with 

a co-reduction of 200 tons per year of all other organic HAP. We also estimate that this option 

would result in a significant increase in fuel use along with increased emissions of carbon 

dioxide (CO2) and oxides of nitrogen (NOx) associated with operation of the additional 

afterburners.

c. Summary

A summary of the costs and emissions reductions associated with the two regulatory 

described above for D/F and organic HAP emissions are summarized in Table 1-4.
9

Table 2-2: Cost Estimates and Emissions Reductions for Regulatory Options 

Considered for Stack Emissions of D/F and Organic HAP.

Option Description COST IN $ MILLIONS (2009 DOLLARS) Total HAP 

Emissions 

Reductions 

(tons per 

year)

Cost per 

ton HAP 

reduction 

($MM)

Capital 

Cost

Annualized 

Capital 

Cost

Annual 

Operation 

and 

Maintenanc

e Cost

Total 

Annualized 

Cost

1D Concentratio

n based 

MACT limit

$0 $0 $0.26 $0.26 30* $0.009

2D Beyond the 

floor for Blast 

furnaces

$5.9 $0.56 $2.4 $2.9 200* $0.01

* based on total organic HAP

2.3 Fugitive Emissions – Metal HAP

Three regulatory options were considered for control of fugitive metal HAP emissions. 

Because these emissions cannot be directly measured, a numerical emissions limit was not 

calculated. Instead, regulatory options were considered that prescribed specific controls or lead 

compliance monitoring at the property boundary as a means of demonstrating compliance. The 

three options considered are as follows:

1. Option 1F: This option requires facilities to conduct ambient lead monitoring at or near 

the property boundary to demonstrate compliance with the National Ambient Air Quality 

Standard (NAAQS) for lead. 

2. Option 2F: This option requires facilities to keep all lead-bearing materials and 

processes enclosed in permanent total enclosures that are vented to a control device. 

Additional fugitive control work practices would also be required. Compliance with this 

regulatory option would be demonstrated by ensuring full enclosure plus work practices 

and ambient lead monitoring at or near the property boundary. 

3. Option 3F: This is the regulatory option selected by EPA for the revised NESHAP for 

the Secondary Lead Smelting source category. This option is identical to option 2F with 

the exception that ambient lead monitoring at or near the boundaries of the facilities 

would not be required. Instead, compliance would be demonstrated through construction 

of total enclosures and operation according to a standard operating procedures (SOP) 

manual detailing how the required fugitive control work practices will be implemented. 

In options 2F and 3F, facilities would be required to have all lead manufacturing 

processes within total enclosures under negative pressure with conveyance to a control device. 

Although option 1F requires only monitoring at the property boundary, and does not explicitly 

require total enclosures, we assumed for cost purposes that facilities would need to operate all 
10

lead-bearing processes under negative pressure enclosures in order to comply with this option. 

Based on information submitted in the ICR, the facilities that are currently achieving ambient 

lead concentrations near the lead NAAQS at or near their property’s boundaries are facilities that 

already have their processes totally enclosed. Therefore, we assumed facilities that do not have 

all of their lead manufacturing processes in total enclosures will construct the appropriate 

enclosures and reconfigure their facilities to reduce their overall footprint as described in section 

3.3 of this memorandum. 

Costs were estimated for enclosures and associated control devices at 7 facilities. One of 

these facilities is currently under construction (Johnson Controls, Inc.), but an examination of the 

permit for the facility indicated that the battery breaking area enclosure was not vented to a 

control device; costs were estimated at the facility for this one process. One additional facility 

(Exide, Frisco TX) does not currently have enclosures for their secondary lead processes, but is 

under an agreed order with the state to install enclosures; this rule will not trigger additional 

costs. Another facility (Envirofocus) is in the process of enclosing all of their process areas as a 

permit requirement for expansion. No costs for additional enclosures were estimated for these 

two facilities. 

The total estimated capital cost for the total enclosures, ventilation systems, and 

associated control devices is $38 million, which results in an annualized capital cost of $3.6 

million. The total annual operation and maintenance cost, which includes building and baghouse 

maintenance, is estimated at $2.8 million above current cost. The total annualized cost of new 

enclosures and associated control devices for seven facilities is $6.4 million. Costs associated 

with the additional work practices are estimated at $250,000 per facility for 12 facilities at a total 

cost of $3 million. The total estimated annualized cost of reducing fugitive emissions for the 

primary regulatory option selected by the EPA (Option 3F) is $9.4 million (2009 dollars). For 

option 1F and 2F, the cost of operating two compliance monitors at or near the property 

boundary of each facility is estimated at $23,000 per facility for a total additional annualized cost 

of $347,000. We estimate reductions in fugitive emissions of 6.4 tons per year of lead and 7.2 

tons per year of metal HAP. 

The estimated costs and emissions reductions associated with the regulatory options 

considered for fugitive emissions of metal HAP are summarized in Table 1-5.
11

Table 2-3: The Estimated Costs and Metal HAP Reductions for Fugitive Sources

Option Descriptio

n

COST IN $ MILLIONS (2009 DOLLARS) Total HAP 

Emissions 

Reductions 

(tons per 

year)

Cost per 

ton HAP 

reduction 

($MM)

Capital 

Cost

Annualized 

Capital 

Cost

Annual 

Operation 

and 

Maintenanc

e Cost

Total 

Annualized 

Cost

1F and 2F Enclosure, 

work 

practice, 

monitoring

$38 $3.6 $6.2 $9.8 7.2 $1.37 

3 F Enclosure, 

work 

practice

$38 $3.6 $5.8 $9.4 7.2 $1.32 

3.0 METHODOLOGY FOR ESTIMATING CONTROL COSTS

The following sections present the methodologies used to estimate the costs associated 

with the regulatory options considered for the revised NESHAP for the Secondary Lead 

Smelting source category.

3.1 Stack Emissions – Metal HAP

The primary technologies used to control stack emissions of metal HAP in the Secondary 

Lead Smelting source category are filtration devices such as baghouses or cartridge collectors, 

some of which have high performance particulate air (HEPA) filters as a secondary filtration 

device. One facility uses a wet electrostatic precipitator (WESP) downstream of a baghouse as a 

polishing step to further reduce metal HAP emissions. Data collected in the ICR indicate that 

baghouses that are properly designed, installed, maintained and operated can meet all of the 

metal HAP stack emissions limits considered in this analysis except those under option 4S 

(which included a WESP).

In order to estimate the capital cost associated with a particular option, we first 

determined which stacks would be required to reduce emissions. For the concentration-based 

limits, we assumed that the baghouses at any stacks reporting concentrations in the ICR above 

the considered emissions limit would need to be repaired, improved, or replaced. If the reported 

concentration was more than 10 percent over the considered limit, we assumed the baghouse 

would need to be replaced. If the reported concentration was within 10 percent of the considered 

limit or the unit in question was relatively new (installed after the year 2000), we assumed that 

replacement bags or additional baghouse maintenance could sufficiently reduce the 

concentration. For options that included a flow-weighted average concentration limit or a 

production based emissions limit, control devices were chosen for replacement or upgrade one at 
12

a time, beginning with the highest reported lead concentration, until the facility’s emissions were 

below the considered limit.

In the ICR, the EPA requested information on costs of emissions control devices that 

have been installed in the last five years. Several facilities submitted cost information that was 

used as a basis for estimating the cost associated with installation of a new baghouse. We 

compared estimates submitted by all of the facilities and chose the highest of the estimates as the 

cost model for baghouse installations. We compared estimates using this methodology to 

estimates derived using techniques described in the sixth edition of the EPA Air Pollution 

Control Cost Manual 

(http://www.epa.gov/oaqps001/lead/pdfs/2002_01_cost_control_%20manual.pdf). While the 

estimates derived using the EPA’s manual were higher, we believe using data submitted directly 

by the industry is likely more representative of actual costs incurred by this source category.

Our cost model included installation of the baghouse and any necessary fans, ductwork, 

screw conveyors, and site work for each scenario, as appropriate. All costs are based on 2009 

dollars. We did not consider the associated downtime for the unit in our costs. We estimated 

capital costs on the basis of dollars per unit of air flow (i.e., cubic foot per minute) into the 

device and assumed linearity of cost within the range of air flows considered in our analysis. The 

total installed capital cost of a typical baghouse designed for a flow-rate of 80,000 actual cubic 

feet per minute (acfm) was estimated at $1.4 million. This cost assumes a 20 year life expectancy 

for the unit and, to be consistent with OMB Guidance in Circular A-4, a seven percent cost of 

capital as an estimate of the annualized capital cost. The design flow-rate for a baghouse was 

taken from information submitted in the survey, or the flow rate during a performance test if this 

flow was higher than design. If design information was not available, the flow was assumed to 

be 20 percent higher than the flow-rate measured during a compliance test. 

The major operating cost of a baghouse is associated with routine replacements of the 

filter media (bags). The number of compartments in the baghouse and the number of bags per 

compartment were estimated using either data submitted in the ICR for the particular unit or data 

submitted for a similar sized unit if the former data were not available. The estimated number of 

bags was used to calculate the ongoing maintenance cost of replacing bags. We assumed that 

facilities would be required to replace bags every two years for the devices that reported 

emissions above the considered limit. The cost of a replacement bag was estimated at $200 based 

on information submitted in the ICR. Other operating and maintenance costs were developed 

using information submitted in the ICR.

For the WESP option, we used information submitted by Quemetco, Inc. in the ICR as a 

basis for estimating cost. We assumed that the configuration of the new WESP installations 
13

3 Perry, Robert H & Green, Don W. (1984). Perry’s Chemical Engineers’ Handbook, (6th ed.). McGraw-Hill.

4

Ficarella, Antonio and Laforgia, Domenico. Numerical simulation of flow-field and dioxins chemistry for 

incineration plants and experimental investigation, Waste Management 20 (2000) 27-49.

would be similar to that of Quemetco. More specifically, we assumed that facilities would use 

the WESP to control process and process fugitive emissions sources, but not general building 

ventilation sources. Additionally, we assumed that facilities would optimize the flow from 

process fugitive ventilation devices in order to reduce the overall airflow to the WESP. We used 

the rapid estimation exponential method described in Perry’s Chemical Engineers’ Handbook3to 

derive an equation representing the expected flow-rate into the WESP at each facility. Our 

estimate of annualized costs primarily includes electricity to operate the WESP and capital 

recovery.

3.2 Stack Emissions – Organic HAP and D/F

The formation of D/F occurs in the smelting furnaces and is highly dependent on the 

operating temperature of the furnace. Very small amounts of D/F were detected in the emissions 

streams of reverberatory furnaces; higher amounts were detected in the emissions streams of 

blast furnaces that were not collocated with reverberatory furnaces. Emissions data submitted in 

the ICR indicate that D/F emissions from collocated blast and reverberatory furnaces are lower 

than those from blast furnaces not collocated with reverberatory furnaces, indicating that 

comingling the flue gas streams of a blast furnace with the hotter stream of the reverberatory 

furnace is an effective D/F control option. Based on information submitted in the ICR, 

temperatures of the reverberatory stream are typically around 2200°F, likely high enough to raise 

the overall temperature of the combined blast and reverberatory furnace stream to that typically 

achieved by an afterburner. Studies of D/F destruction indicate that properly designed and 

operated afterburners with a sufficient residence time can achieve high destruction efficiency4. 

The majority of the blast furnaces in this source category that are not collocated with 

reverberatory furnaces use afterburners as a means of controlling organic HAP emissions. 

However, based on information submitted in the ICR, the majority of these afterburners are not 

operated at temperatures necessary for efficient destruction of D/F. We estimated that an 

afterburner operating at 1600°F with a residence time of 2.5 seconds or longer would achieve a 

90 percent reduction in D/F emissions.

In order to estimate the capital cost of 90 percent control efficiency for D/F from blast 

furnaces, information contained in the ICR responses was used to determine the current furnace 

and afterburner temperature and residence time. We assumed that an existing afterburner would 

have the capability to increase the operating temperature 100°F without a major modification. 

Based on information submitted in the ICR, we determined that 5 of the 6 afterburners 

controlling blast furnaces (not collocated with reverberatory furnaces) in this source category 
14

were not capable of achieving a temperature of 1600°F. Therefore, we estimated the capital and 

operating costs associated with installation of a new afterburner for these sources. Three 

facilities submitted cost data in the ICR for afterburner installations; the highest of the three 

estimates was chosen as the basis for our cost estimate. For the capital cost estimate, we assumed 

that the existing afterburner would remain in place and a new afterburner capable of increasing 

the temperature of the stream leaving the existing afterburner to a temperature of 1600°F would 

be installed. We used an equation modeled after equation 2.32 in the EPA Air Pollution Control 

Cost Manual to scale the size and cost of a thermal incinerator based on the reported flow-rates 

for each of the blast furnaces. The typical cost for an installed afterburner with a design flow-rate 

of 17,000 acfm was estimated at $1.2 million. 

The annual cost of operating an afterburner was estimated using the approach described 

in the EPA Air Pollution Control Cost Manual. The cost of additional fuel required to increase 

the operating temperature of the afterburners was estimated based on the estimated amount of 

required natural gas. Other operating and maintenance costs were estimated using an approach 

described in the EPA Air Pollution Control Cost Manual. The annual capital cost was estimated 

using a 20 year equipment life and a 7 percent interest rate.

3.3 Fugitive Emissions – Metal HAP

There are two general categories of fugitive emissions of metal HAP at a secondary lead 

smelting facility: process fugitive emissions and fugitive dust emissions from material handling 

operations and re-entrainment of deposited dust. Process fugitive emissions result from furnace 

leaks and incomplete capture of emissions during tapping and charging of smelting furnaces. 

Charge materials contain fine lead-bearing particles that can be liberated during charging 

operations. Furnace upsets, particularly those caused by wet feed material, can result in 

overpressure of the smelting furnace. This may cause release of emissions that would normally 

be contained by negative pressure occurring inside the smelting furnaces. Process fugitive 

emissions can also result from incomplete capture of emissions at battery breakers, dryers, and 

refining and casting operations. Fugitive dust emissions can be generated during material 

handling operations. Lead bearing materials are transported throughout the plant in areas that 

may be open to the atmosphere. During transport, the material can spill or leak from the transport 

vehicles and settle on the floors and yards of the facilities. Wind, vehicle traffic, and other forces 

can then re-entrain the deposited dust as fine airborne particles. Stack emissions containing lead 

and other metal HAP can also settle onto surfaces near the facility and can be subsequently reentrained as fine airborne particles.

The current MACT standard for control of fugitive emissions of metal HAP from 

secondary lead smelters requires process fugitive emissions sources to be captured by negative 

pressure enclosure hoods and vented to a control device. There is a minimum face velocity 
15

requirement for the enclosure hoods that varies based on the emissions source. As an alternative 

to an enclosure hood requirement, the facility may operate the process fugitive emissions source 

in a building that is maintained at a lower than ambient pressure. The building ventilation air is 

required to be conveyed to a control device. Additional fugitive control work practice 

requirements in the current MACT standard include wetting of storage piles, cleaning of 

roadways, and washing of vehicles prior to leaving any areas where lead-bearing materials are 

handled. 

The EPA requested information in the ICR regarding the fugitive control techniques 

employed at each facility. Based on that information, we assessed the relative effectiveness of 

the controls implemented by each facility and estimated fugitive emissions at each facility based 

on that assessment (see Development of the RTR Emissions Dataset for the Secondary Lead 

Smelting Source Category for more details). The facilities achieving low ambient lead 

concentrations at nearby monitors were facilities that had total enclosures for their processes. 

Many implemented work practices that are more than that required by the 1997 NESHAP. We 

assumed that facilities that were not currently enclosed would install permanent total enclosures 

with ventilation to a control device and implement additional work practices to prevent the 

formation of fugitive dust in other areas of their facilities. For each facility, we estimated the 

area that is currently under a total enclosure ventilated to a control device. We then estimated the 

additional enclosure area necessary fully enclose the entire process. We assumed facilities that 

required a substantial area of new enclosures would re-configure their facility in a manner that 

reduces the overall footprint of the facility. 

Enclosure costs were estimated using the EPA Air Pollution Control Cost Manual. We 

used the 2008 version of the Air Compliance Advisor (ACA) program, a program developed by 

the EPA to facilitate the calculations required in the EPA Air Pollution Control Cost Manual, to 

estimate the cost of the building. The costs were then adjusted to 2009 dollars. The costs 

considered sheet metal walls, 30 feet high interior, automatic roll-up doors, louvers, make up air 

fans, ductwork, pressure monitors, and smoke detectors. We ran the ACA program for two 

model buildings. The average building capital cost based on these two runs was estimated at $40 

per square foot. This factor was used to the estimate the cost of the additional enclosure area 

required for all other facilities. 

The capital cost of the control devices required to control the enclosure ventilation air 

was estimated based on the flow-rate required to maintain the building under sufficient negative 

pressure. Based on information submitted in the ICR, we estimated a flow-rate that would result 

in an air turnover rate of five per hour in a building maintained under sufficient negative 

pressure. We estimated the cost of the baghouse using the methodology described in section 3.1 

of this memorandum.
16

Annualized costs for the enclosures and associated baghouses were based on a 20 year 

life expectancy and 7 percent cost of capital. Annual operating costs for the baghouse were 

estimated based on data obtained in the ICR. We chose this methodology because we believed it 

to be more representative of actual operation and maintenance costs for this situation. Additional 

operating and maintenance costs were estimated for the enclosures using guidelines supplied in 

the EPA Air Pollution Control Cost Manual. 

We calculated annual costs for required installation of two compliance monitors at the 

property boundary for each facility under regulatory options 1F and 2F. The monitoring costs 

were obtained from estimates made for similar monitors in the proposed revisions to the Primary 

Lead Smelting NESHAP, published February 17, 2011 (76 FR 94106). 

We anticipate that the work practices specified in the existing Secondary Lead Smelting 

NESHAP will not be adequate to maintain fugitive emissions from this source category at an 

acceptable level. We estimated that an additional three employees per facility at an annualized 

cost of $250,000 will be needed to implement the following additional fugitive control work 

practices: maintenance of negative pressure monitors in enclosures, weekly cleaning of all areas 

where waste generated by housekeeping activities are stored or disposed of, immediate cleaning 

after accidental releases, inspections of enclosures once per month, twice per week inspection of 

battery storage area and immediate processing of cracked batteries, and thorough cleaning and 

inspection of any vehicles leaving the process area.

4.0 METHODOLOGY FOR ESTIMATING EMISSIONS REDUCTIONS

This section discusses the methodology used to estimate emissions reductions associated 

with the control options presented in sections 1.0 and 2.0 of this memorandum.

4.1 Stack Emissions – Metal HAP

a. Option 1S

For Option 1S, the outlet lead concentration reported for each stack in the ICR was 

compared to the limit considered in this regulatory option (i.e., 0.5 mg/dscm ). If the reported 

concentration was significantly above one half the limit, we assumed that the facility would need 

to install a new baghouse at that emissions point. For stacks that were less than twenty percent 

above the limit, we assumed that additional maintenance and change out of filtration media 

would reduce the concentration to half the current concentration. We assumed that the outlet lead 

concentration from the newly installed baghouse would be equivalent to the average of all outlet 

lead concentrations reported in the ICR; we calculated this average to be 0.159 mg/dscm. We 

estimated the expected reduction in emissions as the difference between current stack emissions 

and the emissions that would occur after maintenance or replacement of the baghouse. Equation 
17

1 is an example calculation assuming an outlet lead concentration of 0.159 mg/dscm (see 

Equation 1).

(Eq. 1)

Where: 

Ci = outlet lead concentration reported in the ICR (mg/dscm),

F = flow rate (dscm/hr),

0.159 = expected outlet lead concentration of new baghouse (mg/dscm),

H = annual hours of operation, and

T = conversion factor for milligrams to tons (1.1 x 10-9).

b. Option 2S 

For option 2S, the stack lead emissions reported by each facility in the ICR were summed 

and divided by the annual lead production (average of 2008 and 2009) reported in the ICR. A 

statistical equation that considered variability in emissions was used to calculate a production 

based emissions limit of 0.009 lb/ton Pb. Based on emissions data received in the ICR, six 

facilities’ emissions were above 0.009 lb/ton Pb. We assumed that these six facilities would 

sequentially replace or improve their existing baghouses one-by-one, starting with the units 

reporting the highest lead concentrations, until the facility’s emissions were below 0.009 lb/ton 

Pb. Similar to option 1S, we assumed that a new baghouse could achieve an outlet lead 

concentration of 0.159 mg/dscm. We estimated that a total of 18 emissions points at six facilities 

would require reductions in lead emissions in this option. Total emissions reductions were 

calculated using Equation 1. We assumed emissions of other metal HAP would be reduced 

proportionally to lead emissions.

c. Option 3S

For Option 3S, we considered a facility-wide flow-weighted average lead concentration 

limit of 0.2 mg/dscm as well as a maximum lead concentration limit of 1.0 mg/dscm applicable 

to any individual stack. We calculated emissions reductions associated with the maximum 

concentration limit of 1.0 mg/dscm using a modified form of Equation 1. If the reported 

concentration was significantly above 0.5 mg/dscm, we assumed that the facility would need to 

install a new baghouse at that emissions point. For stacks that were less than twenty percent 

above 0.5 mg/dscm, we assumed that additional maintenance and change out of filtration media 
18

would reduce the concentration to half the current concentration. We assumed that the outlet lead 

concentration from the newly installed baghouse would be equivalent to the average of all outlet 

lead concentrations reported in the ICR; we calculated this to be 0.159 mg/dscm. We estimated 

the expected reduction in emissions as the difference between current stack emissions and the 

emissions that would occur after maintenance or replacement of the baghouse using Equation 1. 

Based on this analysis, we estimated that seven stacks would need replacement baghouses, and 

three baghouses needed additional maintenance. 

Additionally, each facility’s flow-weighted average lead concentration was calculated 

based on emissions data submitted in the ICR. We then compared that value to facility-wide flowweighted average limit of 0.2 mg/dscm considered in this option. We estimate that five facilities 

currently have a flow-weighted average lead concentration above the considered limit. We also 

considered the impacts of the proposed fugitive control standards presented in section 2.3 of this 

memorandum on the flow-weighted average concentration of each facility. Because we assumed 

that each facility will be required to have all processes under total enclosures with negative 

pressure and ventilation to a control device, we assumed that facilities needing additional 

enclosures would install one additional corresponding hygiene baghouse. Based on the average 

outlet lead concentration reported in the ICR for similar sources, we assumed that the outlet lead 

concentration from these hygiene baghouses would be 0.044 mg/dscm; the average of all 

building ventilation stacks. We estimated that three of the five facilities initially identified as 

having emissions above the limit considered in this option would meet the considered limit after 

installation of the additional enclosures required in the fugitive control options. Furthermore, we 

estimate that replacing or performing maintenance on all baghouses reporting concentrations 

above 0.5 mg/dscm in combination with the installation of additional enclosures will result in all 

facilities being in compliance with the limits considered in this option. The total emissions 

reductions for this option were calculated using Equation 1. 

d. Option 4S

For option 4S, we estimated emissions reductions of lead and other metal HAP using 

information submitted by Quemetco, Inc. regarding the efficiency of the WESP at their facility. 

Based on this information, we assumed that emissions of lead and other metal HAP from any 

source expected to be controlled by the WESP would be reduced by 99.98 percent.

e. Option 5S

For Option 5S, the outlet lead concentration reported for each stack in the ICR was 

compared to the limit considered in this regulatory option (i.e., 0.2 mg/dscm ). If the reported 

concentration was above one half the limit, we assumed that the facility would need to install a 

new baghouse at that emissions point. We assumed that a unit with a HEPA filter would be 
19

installed in order to reduce the concentration to below 0.1 mg/dscm. The emission reduction was 

estimated as the difference between current stack emissions and an outlet concentration of 0.1 

mg/dscm..

4.2 Stack Emissions – Organic HAP and D/F

a. Option 1D

Option 1D considers MACT floor emissions limits for D/F (TEQ) based on furnace type. 

This option also includes setting MACT floor emissions limits for THC for furnace types that are 

not regulated in the existing NESHAP (i.e., reverberatory furnaces not collocated with a blast 

furnace, rotary furnaces, and electric furnaces). Based on our MACT floor calculation (see 

MACT Floor Analysis for the Secondary Lead Smelting Source Category), we do not anticipate 

significant D/F or organic HAP emissions reductions associated with this option. However, we 

assume that facilities operating afterburners will likely increase the operating temperatures to 

ensure continuous compliance with the considered D/F limit. We believe reduction in D/F and 

other organic HAP on the order of 10 percent are possible using this assumption. 

b. Option 2D

Option 2D is a beyond-the-floor option for D/F that establishes a TEQ concentration limit 

of 17 ng/dscm for blast furnaces not collocated with a reverberatory furnace. Based on the study 

referenced in section 3.2 of this memorandum, the D/F destruction efficiency of an afterburner 

operating at 1600°F with a residence time of 2.0 – 2.5 seconds is between 90 and 94 percent. For 

the purposes of calculating emissions reductions associated with this option, we assumed a 90 

percent destruction efficiency of D/F and organic HAP for newly installed afterburners in this 

source category.

4.3 Fugitive Emissions – Metal HAP

For all the fugitive emissions control options considered, we assumed that all facilities 

would need to reduce their fugitive emissions to a level that would reduce ambient lead 

concentrations near their property boundary to levels below the lead NAAQS. 

We derived factors to estimate the reductions in fugitive emissions that are likely to occur 

as a result of enclosing all manufacturing processes material handling operations. Reductions in 

fugitive emissions of 77 percent from baseline levels were estimated if new total enclosures were 

installed at a facility where only partial enclosures currently exist. Additional reductions of 80 

percent (total reductions of 95 percent) were estimated as a result of implementation of the 

additional work practices described in section 3.3 of this memorandum. This methodology is 

described in detail in the Development of the RTR Emissions Dataset for the Secondary Lead 

Smelting Source Category.
20

5.0 TESTING AND MONITORING COST IMPACTS

The existing NESHAP requires annual stack testing for lead and allows for reducing 

stack testing to every two years if the measured lead concentrations are below 1.0 mg/dscm. The 

regulatory options chosen for the final rule in the revised NESHAP allows these same provisions 

for reduced testing if the emissions are half of the regulatory limit. The final rule also requires 

annual stack testing for THC, with a reduced testing frequency if emissions are half of the 

regulatory limit. Stack testing is required once every six years for D/F. The additional costs 

associated with the stack testing requirements above current costs are anticipated to be $383,000 

per year (an average of $24,000 per facility).

The capital cost associated with additional differential pressure monitors for total 

enclosures is $97,000. 

The total estimated annualized cost for additional testing, monitoring, recordkeeping, and 

reporting considering the first three years after the proposed revisions are implemented is 

$790,000. A detailed burden estimate is available in the docket for this rulemaking (Supporting 

Statement, National Emission Standards for Secondary Lead Smelting). 
21

6.0 SUMMARY OF COST BY FACILITY

Table 6-1 is a summary of estimated costs for each of the facilities in the secondary lead 

smelting source category. 

Table 6-1 Summary Cost Estimates by Facility

Facility Total Capital Cost Total Annual Cost

Doe Run 18,490,000 3,600,000

East Penn 0 300,000

EnviroFocus 0 300,000

Exide Baton Rouge 7,250,000 1,930,000

Exide Forest City 2,560,000 720,000

Exide Frisco 0 460,000

Exide Muncie 0 300,000

Exide Reading 7,020,000 1,460,000

Exide Vernon 0 50,000

Gopher Eagan 0 300,000

Quemetco (CA) 0 50,000

Quemetco (IN) 0 50,000

RSR 0 50,000

Sanders 11,690,000 2,490,000

Battery Recycling 1,990,000 700,000

Johnson Controls 610,000 420,000

Total 50,230,000 13,180,000
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MEMORANDUM

To: Nathan Topham, U.S. Environmental Protection Agency, OAQPS

From: Mike Burr, Donna Lazzari, and Danny Greene, ERG 

Date: December 16, 2011

Subject: Development of the RTR Emissions Dataset for the Secondary Lead Smelting 

Source Category

This memorandum summarizes the data and methodologies used to develop the sitespecific emissions and stack release characteristics that were used to conduct the risk assessment 

modeling for the Secondary Lead Smelting source category. This memorandum is organized as 

follows:

1.0 Background

2.0 Release Characteristics and Locations of Stack and Fugitive Emissions Sources

3.0 Metal HAP Emissions From Stacks 

4.0 Organic Compound Emissions from Stacks

5.0 Metal HAP Emissions From Fugitive Dust Sources

6.0 Estimating MACT-allowable emissions

7.0 Estimating Short-Term Acute Emissions

8.0 Estimating Emissions Reductions for Control Scenarios

1.0 BACKGROUND

Table 1-1 lists the secondary lead smelters currently in operation or under construction in 

the United States and Puerto Rico. In June of 2010, the EPA issued an information collection 

request (ICR) pursuant to section 114 of the Clean Air Act (CAA) to six companies who own 14 

secondary lead smelting facilities currently in operation in the United States. The six companies 

submitted responses for all 14 facilities. The ICR requested available information on process 

equipment, control devices, stack and fugitive emissions from their perspective facility, stack 

parameters, as well as other aspects of the facilities’ operations. The ICR also requested that 

each facility submit historical stack test data for any test conducted in 2003 or later. 

Additionally, 8 facilities were asked, as part of the ICR, to conduct stack tests for a variety of 

pollutants and processes that were considered representative of the industry. A limited request 

for information was sent to The Battery Recycling Company in Puerto Rico in August of 2011. 

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The Johnson Controls facility in Florence, South Carolina will not be operational until 2012 and 

was not surveyed. 

Table 1-1. Secondary Lead Smelters in the U.S. and Puerto Rico

FACILITY NAME PARENT COMPANY CITY STATE Facility 

Abbreviation

East Penn 

Manufacturing

East Penn Manufacturing 

Co., Inc.

Lyon Station Pennsylvania East Penn

EnviroFocus 

Technologies, LLC

Gopher Resources, LLC Tampa Florida EnviroFocus

Gopher Resources, LLC Gopher Resources, LLC Eagan Minnesota Gopher Eagan

Quemetco, Inc., 

California

Eco-Bat Technologies, LTD 

(Quemetco West, LLC)

City of 

Industry

California Quemetco CA

Quemetco, Inc., Indiana Eco-Bat Technologies, LTD 

(Eco-Bat Indiana, LLC)

Indianapolis Indiana Quemetco IN

Revere Smelting and 

Refining Corporation 

(RSR)

Eco-Bat Technologies, LTD 

(Eco-Bat New York, LLC)

Middletown New York RSR

Sanders Lead Company Sanders Lead Company Troy Alabama Sanders Lead

Baton Rouge Recycling 

Center

Exide Technologies, Inc. Baton Rouge Louisiana Exide Baton 

Rouge

Canon Hollow 

Recycling Facility

Exide Technologies, Inc. Forest City Missouri Exide Forest City

Frisco Battery Recycling Exide Technologies, Inc. Frisco Texas Exide Frisco

Exide Technologies, 

Indiana

Exide Technologies, Inc. Muncie Indiana Exide Muncie

Exide Technologies – 

Reading Recycling

Exide Technologies, Inc. Reading Pennsylvania Exide Reading

Exide Technologies, 

California

Exide Technologies, Inc. Vernon California Exide Vernon

Buick Resource 

Recycling Facility, LLC

The Doe Run Resources 

Corporation

Boss Missouri Buick RRF

The Battery Recycling 

Company

The Battery Recycling 

Company

Arecibo Puerto Rico TBR 

Johnson Controls 

Battery Group, Inc. 

Johnson Controls 

International

Florence South Carolina JCI

The emissions and process data collected under the ICR were used to develop sitespecific baseline emissions estimates and emissions source release characteristics (i.e., elevation, 

stack height, stack diameter, stack gas exit velocity, stack gas flow rate, stack gas exit 

temperature, and stack location (latitude and longitude)) for each of the facilities. The baseline 

emissions estimates include stack and fugitive dust emissions from secondary lead smelting 

processes. Table 1-2 summarizes the pollutants included in the baseline emissions estimates for 

both stack and fugitive emissions. We also evaluated a separate facility-wide dataset that 

included emissions from other process located on site in addition to those associated with the 

secondary lead smelting processes. Facility-wide emissions were essentially the same as those of 

the source category, so a separate facility-wide analysis was not performed. These baseline 

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emissions estimates and emissions source release characteristics were used as the data inputs for 

the EPA’s risk assessment modeling for this source category.

Table 1-2. Pollutants Included in the Secondary Lead Smelting Modeling File.

HAP STACK FUGITIVE

1,1,2,2-Tetrachloroethane ü

1,3-Butadiene ü

1,3-Dichloropropene ü

2,3,7,8-TCDD TEQ ü

Acetaldehyde ü

Acetophenone ü

Acrolein ü

Acrylonitrile ü

Antimony ü ü

Arsenic ü ü

Benz[a]Anthracene ü

Benzene ü

Benzo[a]Pyrene ü

Benzo[b]Fluoranthene ü

Benzo[k]Fluoranthene ü

Beryllium ü ü

Biphenyl ü

Bis(2-Ethylhexyl)Phthalate ü

Cadmium ü ü

Carbon Disulfide ü

Chlorine ü

Chlorobenzene ü

Chloroform ü

Chromium (VI) ü ü

Chromium III ü ü

Chrysene ü

Cumene ü

Dibenzo[a,h]Anthracene ü

Dibutyl Phthalate ü

Divalent Mercury ü ü

Elemental Gaseous Mercury ü

Ethyl Benzene ü

Ethyl Chloride ü

Formaldehyde ü

Hexane ü

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Hydrochloric Acid ü

Indeno[1,2,3-c,d]Pyrene ü

Lead ü ü

Manganese ü ü

Methyl Bromide ü

Methyl Chloride ü

Methyl Iodide ü

Methyl Isobutyl Ketone ü

Methylene Chloride ü

m-Xylene ü

Naphthalene ü

Nickel ü ü

o-Cresol ü

o-Xylene ü

Particulate Mercury ü ü

Phenol ü

Propionaldehyde ü

p-Xylene ü

Pyrene ü

Selenium ü ü

Styrene ü

Tetrachloroethylene ü

Toluene ü

Trichloroethylene ü

Xylenes (Mixture of o, m, and p)Isomers) ü

2.0 RELEASE CHARACTERISTICS AND LOCATIONS OF STACK AND FUGITIVE 

EMISSIONS SOURCES

Fixed parameters for stack release points, such as elevation, stack height, stack diameter, 

and stack location, were extracted from the surveys submitted by the facilities. The location 

coordinates for each emissions source submitted in the ICR surveys were checked using Google 

Earth©. For the Exide Frisco and the RSR NY facilities, the stack coordinates were found to be 

inaccurate. Therefore, the stack coordinates for Exide Frisco were extracted from a 2008 

modeling file provided by EPA contractor ICF International and the stack coordinates for RSR 

were estimated using Google Earth©. Google Earth© was also used to estimate the location and 

dimensions of the fugitive dust emissions sources at each facility. For risk assessment modeling 

purposes, the coordinates of the fugitive emissions sources were placed at the southwest corner 

of each facility and the dimensions were chosen such that the source spanned the entire facility.

Values for stack exit velocity, flow rate, and exit temperature were obtained from the 

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corresponding emissions test reports from which emissions data were extracted. In cases where 

emissions from multiple test reports were averaged, the stack parameters from those reports were 

averaged. In the event that any of the varying parameters were not available in the test report, 

estimates provided by the industry in their ICR surveys were used.

3.0 METAL HAP EMISSIONS FROM STACKS

Table 3-1 presents the metal hazardous pollutants (HAP) emissions estimates for stacks at 

each facility. The emissions estimates shown in Table 3-1 were developed using the site-specific 

emissions data collected by the ICR. In cases where stack test results included values reported as 

being below a test method detection limit (BDL), the detection limits specified in the test reports 

were used in the emissions estimates. For beryllium, none of the emissions test data were above 

the method detection limit. Consequently, stack emissions estimates for this metal were not 

developed. 

3.1 Lead

Because of the annual (or biannual) performance testing required by the current National 

Emissions Standards for Hazardous Air Pollutants (NESHAP) for the Secondary Lead Smelting 

source category (40 CFR part 63, subpart X), a large amount of data were available for lead 

emissions from stack (i.e., point) sources. Consequently, the site-specific lead emissions 

estimates were compiled using stack test data obtained for the years 2006 through 2010. In cases 

where multiple test reports in the 2006-2010 timeframe were available for a particular stack at a 

facility, the average of the emissions values from the test reports was used in the emissions 

estimate. If a facility had undergone recent modifications that affected stack emissions, only postmodification emissions were used in the emissions estimates (this holds true for all pollutants).

We obtained lead stack test data for 101 release points, which account for the vast 

majority of release points. However, site-specific lead emissions data were not available for two 

stack release points identified in the ICR surveys. For these emissions points, default emissions 

factors were developed using data from similar processes at other facilities.

3.2 Other Metals

Where available, site-specific data for non-lead metal HAP (i.e., arsenic (As), cadmium 

(Cd), trivalent chromium (Cr+3), hexavalent chromium (Cr+6), mercury (Hg), manganese (Mn), 

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Table 3-1. Point Source Metal HAP Emissions Estimates (lbs/yr) by Facility.

Name of Facility As Sb Cd Cr+6 Cr+3 Elemental 

Hg*

Divalent Hg* Particulate 

Hg*

Pb Mn Ni Se

Buick RRF 2,352.0 441.3 425.6 0.3 11.4 21.4 2.7 2.7 9,389.4 104.4 34.0 117.4

East Penn 3.8 14.1 0.9 0.1 3.2 7.4 0.9 0.9 299.5 15.0 6.0 3.7

Exide Vernon 12.0 23.5 0.4 0.1 9.7 13.9 1.7 1.7 499.6 45.6 16.0 6.2

Exide Reading 27.8 101.5 2.4 0.2 7.4 9.4 1.2 1.2 2,160.1 31.3 14.5 27.0

Exide Muncie 8.8 20.0 0.4 0.1 4.7 6.1 0.8 0.8 425.8 22.1 7.8 5.3

Exide Baton Rouge 42.8 203.9 7.2 0.2 5.6 7.2 0.9 0.9 4337.3 21.3 13.4 54.2

Exide Forest City 5.5 13.5 0.2 0.1 1.8 2.4 0.3 0.3 286.2 7.9 3.7 3.6

Exide Frisco 113.4 110.9 4.3 0.9 23.9 28.6 3.6 3.6 2595.871 87.5 26.5 32.4

Gopher Eagan 31.6 20.6 0.9 0.1 3.2 3.9 0.5 0.5 437.8 10.6 4.9 5.5

EnviroFocus 10.0 45.2 1.3 0.1 2.1 2.8 0.3 0.3 962.7 9.7 4.2 12.0

Quemetco (CA) 4.1 0.8 2.3 0.1 3.7 21.0 2.6 2.6 16.5 19.4 4.4 0.2

Quemetco (IN) 43.5 23.9 1.0 0.1 8.7 35.8 4.5 4.5 507.4 37.3 13.5 6.3

RSR 50.2 40.8 2.9 0.2 10.4 20.7 2.6 2.6 869.0 31.4 15.3 10.9

Sanders Lead 51.2 103.5 4.5 0.3 13.2 10.2 1.3 1.3 2,201.7 40.3 23.3 27.5

Battery Recycling 6.7 5.9 0.2 0.1 0.9 1.3 0.2 0.2 184.0 4.1 2.0 2.3

Total for the Source 

Category

2763 1169 455 3 110 192 24 24 25173 488 190 315

*Most stack test results for mercury were below the detection limit and the limit of detection was used as the concentration estimate; 

therefore, these mercury estimates are high-end conservative estimates of emissions. The true mercury emissions are probably much 

lower. 

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1 Memorandum from EC/R to EPA, “Updated Draft Population Inhalation Risk Estimates for the Secondary Lead 

Smelter Residual Risk Assessment,” November 26, 2002.

and nickel (Ni)) emissions from stacks were used for the emissions estimates. In cases where sitespecific data were not available, emissions estimates for non-lead metal HAP were developed 

using facility lead emissions and ratios of non-lead metal HAP to lead.

Analysis of the available emissions data collected by the ICR survey and test program 

revealed that a logarithmic relationship between the metal-to-lead ratios and the lead 

concentrations produced the best correlation. Least-squares regressions analyses were conducted 

on the logarithmic metal HAP/lead ratios and lead emissions to obtain trend line equations.

Figure 3-1 shows the scatter plots of the data and the corresponding regression equations. 

The regression line equations and site-specific lead emissions data were used as an empirical 

model to calculate non-lead metal HAP emissions for emissions points where other metal data 

were not available. 

Stack test data were not collected for selenium and antimony under the ICR test program. 

Therefore, site-specific estimates were made for these pollutants using the metal-to-lead ratios 

developed for the EPA’s 2002 Inhalation Risk Estimate report1. In this report, separate non-lead 

metal-to-lead ratios were developed from test data for process, process fugitive, and fugitive dust 

emissions sources. For this analysis, the selenium and antimony ratios for process fugitive 

emissions were selected because these ratios were most similar to the ratios developed from the 

ICR data for other metals.

The site-specific emissions estimates for total mercury and chromium were speciated to 

account for the different oxidation states of these metals. Total mercury emissions were 

speciated as follows based on the EPA’s default mercury speciation profile: 80 percent elemental 

mercury, 10 percent gaseous divalent mercury, and 10 percent particulate divalent mercury. 

These profiles are available on the EPA’s Technical Transfer Network (TTN) at: 

http://www.epa.gov/ttn/chief/net/2005inventory.html.

New stack test data for hexavalent chromium (Cr+6) were available for 7 of the emissions 

points included in the source category; all 7 of these emissions points were stacks containing 

furnace exhaust. A ratio of Cr+6 to total chromium was calculated based on the new stack test 

data and then used to estimate Cr+6 at the remaining furnace emissions points. The difference 

between total chromium and Cr+6 at these emissions points was designated as Cr+3. For nonfurnace emissions points, total chromium emissions, that were either extracted from test reports 

or estimated based on the logarithmic relationship previously outlined, were speciated to one 

percent Cr+6 and 99 percent Cr+3 based on speciation profiles provided by the EPA (available at: 

http://www.epa.gov/ttn/chief/net/2005inventory.html).

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Figure 3-1. Correlations Used to Estimate Stack Emissions of Non-Lead Metal HAP.

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9

4.0 ORGANIC COMPOUND EMISSIONS FROM STACKS

Table 4-1 presents the organic HAP, dioxin and furan (D/F), and total hydrocarbons 

(THC) emissions for stacks at each facility. The emissions estimates shown in Table 4-1 were 

developed using the site-specific emissions data collected by the ICR.

4.1 Organic HAP

Emissions of certain organic compounds were available only in the newest stack tests 

submitted under the ICR. The ICR test program collected emissions data for the following 

organic compounds: D/F, THC, 1,3-butadiene, naphthalene, and benzene. Note that while THC 

is not modeled, it is used to estimate emissions of other organic compounds by using ratios of 

these compounds to THC, as described later in this section. Because the smelting furnaces are 

the primary source of these pollutants, emissions estimates were made only for emissions points 

containing furnace exhaust. 

Of the 18 emissions points containing furnace exhaust, stack test data for D/F, THC, 1,3-

butadiene, naphthalene, and benzene were available for 9 points. Therefore, a methodology for 

developing emissions of these pollutants for the remaining 9 emissions points was developed. 

Note that for D/F, emissions are expressed in terms of the Toxic Equivalency Quotient (TEQ), 

rather than individual D/F congeners. The TEQ values were calculated using the speciated dioxin 

and furan congener data submitted in the ICR test reports and the Toxic Equivalency Factors 

(TEFs) recommended by the World Health Organization (WHO) in 2005 (see Table 4-2). 

Emissions factors for D/F TEQ, 1,3-butadiene, naphthalene and benzene were developed based 

on the 8 emissions points for which stack test data exists. Because emissions of organic 

compounds are highly dependent on furnace operating temperature, and thus also on furnace 

type, emissions factors were chosen for the missing emissions points based on the highest degree 

of commonality between furnace types. Due to lack of emissions data from rotary furnaces that 

process lead scrap, organic HAP emissions were not estimated for the rotary furnace emission 

point at The Battery Recycling Company’s Arecibo, Puerto Rico facility.

For other organic compounds not tested under the ICR program, ratios of these 

compounds to THC were developed based on prior testing data reported in the 2002 Inhalation 

Risk Estimates report. These ratios were then used to estimate emissions of these compounds at 

each of the furnace emissions points. These ratios are presented in Table 4-3.

Table 4-1. Organic HAP Emissions Estimates (lbs/yr) by Facility.

Facility Benzene 1,3-Butadiene Naphthalene D/F TEQ THC

Buick RRF 17320.73 695.15 1853.72 5.2E-03 3.3E+05

East Penn 7.33 7.02 2.72 4.6E-05 7.0E+02
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10

2 Organic HAP emissions for were not estimated for The Battery Recycling Company due to insufficient data.

Exide Vernon 1.37 2.89 44.12 3.9E-06 7.8E+02

Exide Reading 135.50 31.51 96.79 4.0E-05 6.1E+04

Exide Muncie 6.09 5.84 2.26 3.8E-05 6.0E+02

Exide Baton Rouge 592.29 1168.39 279.38 1.3E-02 4.0E+05

Exide Forest City 470.84 1035.84 207.17 1.1E-02 3.4E+05

Exide Frisco 12.00 2.40 3.20 1.3E-04 6.5E+03

Gopher Eagan 10.75 10.31 3.99 6.8E-05 1.0E+03

EnviroFocus 317.35 698.18 139.64 7.6E-03 2.3E+05

Quemetco (CA) 94.2 33.6 28.8 1.6E-05 4.9E+03

Quemetco (IN) 29.70 8.94 11.21 1.5E-05 1.8E+04

RSR 2126.49 3279.81 76.74 1.5E-05 9.9E+04

Sanders Lead 1752.00 3854.40 770.88 4.2E-02 1.2E+06

TBR2 Not Estimated Not Estimated Not Estimated Not Estimated Not 

Estimated

Table 4-2. Toxic Equivalency Factors (TEFs) used to Calculate the Toxic 

Equivalency Quotient (TEQ).

Dioxin/Furan Congener Toxic Equivalency Factor

2,3,7,8-tetrachlorinated dibenzo-p-dioxin 1.0

1,2,3,7,8-pentachlorinated dibenzo-p-dioxin 0.5

1,2,3,4,7,8-hexachlorinated dibenzo-p-dioxin 0.1

1,2,3,7,8,9-hexachlorinated dibenzo-p-dioxin 0.1

1,2,3,6,7,8-hexachlorinated dibenzo-p-dioxin 0.1

1,2,3,4,6,7,8-heptachlorinated dibenzo-p-dioxin 0.01

octachlorinated dibenzo-p-dioxin 0.001

2,3,7,8-tetrachlorinated dibenzofuran 0.1

2,3,4,7,8-pentachlorinated dibenzofuran 0.05

1,2,3,7,8-pentachlorinated dibenzofuran 0.5

1,2,3,4,7,8-hexachlorinated dibenzofuran 0.1

1,2,3,6,7,8-hexachlorinated dibenzofuran 0.1

1,2,3,7,8,9-hexachlorinated dibenzofuran 0.1

2,3,4,6,7,8-hexachlorinated dibenzofuran 0.1

1,2,3,4,6,7,8-heptachlorinated dibenzofuran 0.01

1,2,3,4,7,8,9-heptachlorinated dibenzofuran 0.01

octachlorinated dibenzofuran 0.001
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11

Table 4-3. Ratios of HAPs to THC Used for Emissions Estimates for the 

Secondary Lead Smelting Source Category.

HAP RATIO 

(HAP/THC)

HAP RATIO 

(HAP/THC)

1,1,2,2-Tetrachloroethane 0.00E+00 Ethyl Chloride 2.83E-02

1,3-Dichloropropene 4.26E-03 Formaldehyde 3.28E-03

Acetaldehyde 6.70E-02 Hexane 3.85E-02

Acetophenone 1.24E-02 Hydrochloric Acid 0.00E+00

Acrolein 2.64E-02 Indeno[1,2,3-c,d]Pyrene 2.59E-05

Acrylonitrile 1.35E-03 Methyl Bromide 1.45E-02

Benz[a]Anthracene 1.71E-03 Methyl Chloride 5.38E-01

Benzo[a]Pyrene 5.79E-06 Methyl Iodide 6.71E-03

Benzo[b]Fluoranthene 6.49E-04 Methyl Isobutyl Ketone 8.25E-01

Benzo[k]Fluoranthene 1.08E-04 Methylene Chloride 8.46E-03

Biphenyl 6.65E-02 m-Xylene 5.23E-02

Bis(2-Ethylhexyl)Phthalate 1.39E-01 o-Cresol 5.68E-03

Carbon Disulfide 1.57E+00 o-Xylene 1.61E-02

Chlorine 0.00E+00 Phenol 3.86E-02

Chlorobenzene 1.16E-02 Propionaldehyde 0.00E+00

Chloroform 1.61E-03 p-Xylene 5.82E-01

Chrysene 7.50E-03 Pyrene 0.00E+00

Cumene 1.83E-03 Styrene 2.40E-01

Dibenzo[a,h]Anthracene 8.45E-06 Tetrachloroethylene 0.00E+00

Dibutyl Phthalate 6.45E-04 Toluene 1.74E-01

Ethyl Benzene 3.90E-02 Trichloroethylene 0.00E+00

Xylenes (Mixture of o, m, and p 

Isomers)

0.00E+00

5.0 METAL HAP EMISSIONS FROM FUGITIVE DUST SOURCES

Because they cannot be readily captured or directly measured, fugitive emissions are 

challenging to estimate. For this analysis, we evaluated the estimates of fugitive lead emissions 

that were submitted by each of the facilities under the 2010 ICR program. The responses we 

received regarding fugitive emissions varied significantly. Of the 14 facilities surveyed, five 

facilities provided no estimate for fugitive emissions and five other facilities provided quite 

incomplete estimates. Additional information was later submitted by one of the facilities (East 

Penn). 

Based on our review, the estimates provided by five facilities (Exide Frisco, Exide 

Muncie, Exide Vernon, Gopher Eagan, and East Penn) seemed reasonable and relatively 

complete. Nevertheless, among those facilities, we concluded that Exide Frisco provided the best 

estimate. Therefore, due to the lack of reasonable estimates at nine facilities and the large 

amount of variability in emissions estimates and methodologies between the other facilities, the 

emissions provided by the Exide Frisco facility were selected as a basis for estimating fugitive 
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emissions at all other facilities. This facility was selected because of the estimating methodology 

(i.e., EPA AP-42 emissions factors and site-specific activity data) and the level of detail 

provided in the supporting documentation. Each facility was compared to the model facility and 

an estimate of total lead fugitives was calculated based on a number of factors, explained below, 

that described the activity level at the facility. 

Table 5-1 is a comparison of the estimates made by the facilities that submitted 

reasonable data and the estimates calculated using the methodology described. Based on this 

comparison, and the similarity of results between submitted and calculated using the derived 

method, we elected to use the identical estimation method for all facilities. 

 Table 5-1. Comparison of Estimated and Submitted Fugitive Lead Emissions 

Estimates for the Secondary Lead Smelting Source Category

Facility Fugitive Pb Emissions 

Estimated Based on Method 

Described in This Section

Fugitive Pb Emissions 

Estimates Submitted in ICR 

Exide Muncie 0.18 0.22

Exide Vernon 0.16 0.103

Gopher Eagan 0.28 0.35

East Penn 0.06 0.07

Information provided by each facility regarding the degree of containment of secondary 

lead smelting processes was used to categorize the facilities as having Level 1 enclosure, Level 2 

enclosure, or Level 3 enclosure. The facilities categorized as having Level 3 enclosure generally 

have complete enclosures with negative pressure for all their process activities. The facilities 

designated as having Level 2 enclosure have some, but not all parts of their process in negative 

pressure enclosures, while those facilities designated as having Level 1 enclosure generally did 

not have any of their major processes under a negative pressure enclosure. The Exide Frisco 

facility that was as used the model facility for the purpose of our estimates was classified as a 

level 2 facility. However, the only process at the facility that is currently fully enclosed and 

vented to a control device is the raw material storage area. Thus, we compared fugitive emissions 

estimates submitted by the Exide Frisco facility prior to enclosure of the raw materials storage 

area with the estimates submitted in the ICR. This comparison revealed that the fugitive 

emissions estimates submitted by Exide Frisco prior to enclosure of the raw materials storage 

area were 1.07 times higher than the estimates submitted in the ICR. We then analyzed each 

facility to determine their level of enclosure in comparison with the Exide Frisco facility. The 

facilities that were determined to have a lower level of enclosure than Exide Frisco were 

assigned a factor 1.07. The facilities that were determined to have a greater level of enclosure 

than the Exide Frisco facility, but did not have all processes enclosed (level 2), were assigned a 
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factor of 0.75. A factor of 0.25 was assigned to facilities with total enclosures for all processes 

(level 3). These factors were applied to the fugitive lead emission estimates at the facilities to 

reflect reductions that are likely to occur due to the level of enclosure at each facility. 

A housekeeping factor was also developed to characterize the level of work practices 

implemented by each facility to control fugitive emissions. Information reported by the industry 

in their surveys and during the comment period of the proposed rule was used to determine the 

extent to which they implemented work practices that go beyond the requirements of the current 

Secondary Lead Smelting NESHAP. Factors ranging from 1.0 (work practices consistent with 

the current NESHAP) to 0.2 (work practices far beyond the current NESHAP) were then also 

applied to the fugitive lead estimates at these facilities in order to reflect reductions that are 

likely to occur due to the work practices in place at each facility. Table 5-1 summarizes the 

enclosure and housekeeping factors used and lists the estimated fugitive lead emissions for each 

facility. The size factors were developed based on the activity level of each facility based on 

several factors supplied in the ICR.

The lead emissions estimates for each facility were calculated by multiplying the fugitive 

lead emissions rate for the Exide Frisco facility (0.71 tons/yr) by the site-specific size factor, 

enclosure factor, and housekeeping factor. For example, we estimated a size factor of 0.76 for 

Exide Forest City. Additionally, Exide Forest City is a level 2 enclosure (0.75) and does work 

practices consistent with the requirements of the current NESHAP (i.e., housekeeping factor = 

1). Therefore, the estimated fugitive lead emissions for Exide Forest City, MO are calculated as 

follows:

0.71 tons/yr x 0.76 x 0.75 x 1.0 = 0.41 tons per year.

In this analysis, we did not take into consideration the legacy sources of fugitive lead 

emissions at the facilities. These sources of lead on or near the facility grounds could contribute 

to higher levels of airborne lead emissions from roadways or other wind-blown dust. We expect 

there to be differences in the amount of lead from legacy sources at these facilities, but were not 

able to quantify them for this assessment. 

The estimates of fugitive lead emissions that are shown in table 5-2 were used as input to 

the risk assessment modeling. To estimate fugitive emissions for metals other than lead (i.e., 

arsenic, cadmium, chromium, manganese, mercury, and nickel), a ratio of these other metals to 

lead was developed based on total stack emissions of these pollutants from all the facilities (see 

Table 5-3). This industry-wide ratio for each metal was multiplied by the individual facility lead 

fugitive emissions estimate to produce estimates of fugitive emissions of non-lead metal HAP.

Stack test data for selenium and antimony were not available, and therefore, the process 
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fugitive ratios included in the 2002 Inhalation Risk Estimates report were used. These ratios 

were then applied to the fugitive lead emissions at each facility. Note that one facility’s arsenic 

emissions were identified as an outlier and were not considered when developing the arsenic to 

lead ratio.

Table 5-2. Summary of Fugitive Lead Emissions Estimates for the Secondary 

Lead Smelting Source Category.

Facility Size Factor Enclosure Factor Housekeeping 

Factor

Fugitive Pb Emissions 

(lbs/yr)

Exide Baton Rouge 0.84 1.07 1.0 1277

Exide Forest City 0.76 0.75 1.0 807

Exide Frisco 1.03 1.00 1.0 1463

Exide Muncie 1.04 0.25 1.0 370

Exide Reading 1.00 0.75 1.0 1070

Exide Vernon 1.84 0.25 0.5 327

RSR 1.36 0.25 0.25 121

Quemetco (CA) 1.19 0.25 0.2 85

Quemetco (IN) 1.27 0.25 0.25 113

Sanders Lead 1.40 1.07 1.0 2133

EnviroFocus 0.44 0.75 1.0 472

Gopher Eagan 1.55 0.25 1.0 553

Buick RRF 3.13 1.07 1.0 4773

East Penn 1.34 0.25 0.25 119

TBR 0.32 1.07 1.0 488

Table 5-3. Ratios Used to Estimate Fugitive Emissions of Metals Other than Lead.

HAP HAP/Pb Ratio

Arsenic 2.54E-02

Beryllium 1.73E-04

Cadmium 1.86E-02

Chromium 3.76E-03

Chromium+6 3.76E-05

Chromium+3 3.72E-03

Manganese 1.71E-02

Mercury 8.37E-03

Elemental Hg 6.70E-03

Divalent Hg 8.37E-04

Particulate Hg 8.37E-04

Nickel 7.07E-03

Selenium 1.25E-02

Antimony 3.20E-02

6.0 ESTIMATING SHORT-TERM ACUTE EMISSIONS

As part of the risk assessment conducted for the Secondary Lead Smelting source 
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category, the potential for hazard via acute short term exposures is analyzed. Because the dataset 

described in this document is based on the development of estimates of annual emissions for 

each facility, a means of estimating maximum one-hour emissions rates associated with each 

emissions point was needed. For this analysis, it was assumed that the maximum one-hour 

emissions rate from any source other than those resulting in fugitive dust emissions were 10 

times the average annual hourly emissions rate for that source. The factor of 10 is not applied to 

fugitive dust sources because these emissions decrease during the meteorological conditions 

associated with the worst-case short-term impacts (i.e., during low-wind, stable atmospheric 

conditions). Information regarding the development of this factor and other details regarding the 

emissions data used for the acute exposure assessment can be found in the Residual Risk 

Assessment for the Secondary Lead Smelting Source Category document available in the docket.

7.0 ESTIMATING MACT-ALLOWABLE EMISSIONS

The emissions data in our data set represent the estimates of mass of emissions actually 

emitted on an annual basis for stacks and fugitives for the 2008-2010 timeframe. With most 

source categories, we generally find that “actual” emissions levels are lower than the emissions 

levels that a facility is allowed to emit and still comply with the MACT standards. The emissions 

levels allowed to be emitted by the MACT standards are referred to as the “MACT-allowable” 

emissions levels. This represents the highest emissions level that could be emitted by facilities 

without violating the MACT standards. 

For the Secondary Lead Smelting source category, we evaluated actual emissions versus 

allowable emissions for both stack emissions and fugitive dusts emissions. As described above, 

the actual emissions data for this source category were compiled based on the ICR responses, 

available test data, various calculations, and the NEI. Most of this analysis (on actual versus 

allowable emissions) was focused on lead compound emissions, which we considered the most 

important HAP emitted from this source category based our preliminary risk assessments.

With regard to fugitive dust emissions, based on available information, we believe that 

the higher emitting facilities (and higher risk facilities) are implementing the basic work practice 

standards pursuant to the requirements described in the MACT standards and not doing extra 

work practices (no practices beyond those required by the MACT standard). Therefore, we 

assume that “actual” fugitive dust emissions are equal to “allowable” fugitive dust emissions for 

these facilities. Based on available information (such as ICR responses and other information 

gathered and analyzed about this industry), we do believe that some facilities are implementing 

work practices beyond those required by the MACT standard, and therefore their actual fugitive 

dust emissions are probably lower than allowable. However, we cannot quantify how much 

lower the actual emissions are compared to allowable. Moreover, even if we did have estimates 

of allowable emissions of fugitive dusts from these sources, this information would not affect the 
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conclusions about the risks due to fugitive dust emissions (described in the Risk Assessment 

Report) and would not affect the EPA’s requirements to address fugitive emissions from this 

source category (described in the preamble). Therefore, we have not calculated “allowable” 

fugitive dust emissions for these sources. Therefore, for our analyses, we assume that “actual” 

fugitive dust emissions are equal to “allowable” fugitive dust emissions for all facilities. 

In contrast, we did calculate allowable emissions for the stacks. To estimate emissions at 

the MACT-allowable level from the stacks (e.g., process vents and building vents), we 

developed a ratio of MACT-allowable to actual emissions for each facility in the source 

category. We calculated these ratios by first estimating the emissions from stacks that would 

occur if facilities were emitting lead exactly at the maximum allowed by the standard (i.e., 2.0 

mg/m3) from all vents. Then we compared these estimated “allowable emissions” to the 

estimated emissions using the actual stack test data for lead for each facility. Estimates of actual 

and allowable lead emissions from this source category are shown in table 8-1. Based on this 

analysis, we conclude that all facilities are emitting lead at levels lower than allowable; however, 

the range is significant. For 2 facilities, the estimated actual emissions were only moderately 

lower than allowable (about 2-3 times lower). The vast majority of facilities have estimated 

actual emissions in the range of about 10 to 100 times lower than allowable. Finally, one facility, 

which has highly advanced controls, has estimated actual emissions of about 1500 times below 

the MACT allowable emissions level. 

Table 8-1. Estimated Ratios of Actual Emissions to MACT-Allowable Emissions 

For Secondary Lead Smelting Facilities.

Facility Actual Lead Emissions 

Rate (lb/hr)

MACT Allowable 

Emissions (lb/hr)

Ratio of MACTAllowable to Actual

Quemetco (CA) 0.00 2.84 1513.5

Exide Muncie 0.05 4.92 95.3

Exide Vernon 0.06 4.92 77.7

Gopher Eagan 0.05 3.06 59.4

Quemetco (IN) 0.06 3.27 56.5

East Penn 0.04 1.45 34.8

RSR 0.10 3.19 32.2

Exide Forest City 0.04 0.64 17.9

TBR 0.021 0.29 13.6

Exide Reading 0.26 2.73 10.6

EnviroFocus 0.12 1.16 9.9

Exide Frisco 0.31 2.63 8.6

Sanders 0.25 1.66 6.6

Exide Baton Rouge 0.53 1.43 2.7

Doe Run 1.21 2.97 2.5

After developing these ratios, we applied these ratios on a facility-by-facility basis to the 
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maximum modeled ambient lead concentrations (i.e., ratios were applied to stack emissions 

while leaving fugitive dust emissions at actual levels since, as described above, actual fugitive 

dust emissions were considered equal to allowable fugitive dust emissions) to estimate the 

maximum ambient concentrations that would occur if all stacks were emitting at maximum 

allowable levels. This analysis and the results are described in the Risk Assessment Report. 

8.0 ESTIMATING EMISSIONS REDUCTIONS FOR CONTROL SCENARIOS

To assess the reduction in risk associated with implementation of the control options 

presented in the final rulemaking for the Secondary Lead Smelting Source category, we 

estimated reductions in baseline emissions that will occur after the controls are installed. The 

development of the post-control emissions estimates are described in the following sections. The 

resulting risk analysis based on these emissions can be found in the Residual Risk Assessment 

for the Secondary Lead Smelting Source Category.

8.1 Post-Control Stack Emissions of Metal HAP

In order to assess the reductions in stack emissions of metal HAP that will occur as a 

result of the revised lead emissions limit, we performed an analysis for each emissions point at 

each facility to determine whether added control would be needed in order to meet the limit.

We identified seven baghouses that by our estimation will need to be replaced. These 

include three baghouses at Doe Run, two baghouses at Sanders, one baghouse at Exide Baton 

Rouge, and one baghouse at Exide Reading. We also identified three additional baghouses that 

will need maintenance in order for the facilities to comply with the revised lead emissions limit. 

These include one baghouse at Doe Run, one baghouse at Exide Frisco, and one baghouse at 

Exide Baton Rouge. In order to estimate emissions from an upgraded/replaced baghouse, we 

assumed that the emissions would be reduced to a level consistent with the average lead 

emissions calculated from all emissions points in the source category. We assumed that the 

reductions in emissions of other metal HAP from these emissions points would be reduced 

proportionally to lead.

8.2 Post-Control Fugitive Dust Emissions of Metal HAP

As described in the Residual Risk Assessment for the Secondary Lead Smelting Source 

Category, fugitive dust emissions are the primary driver in exceedances of the lead NAAQS as 

well as a substantial contributor to the chronic cancer risks and potential acute non-cancer risks. 

We estimated the reduction in fugitive emissions of metal HAP that would occur as a result of 

the implementation of the fugitive dust controls outlined in the final rulemaking for this source 

category. These emissions estimates were used to estimate the post-control risks described in the 

risk assessment document.
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Section 5.0 describes how we estimated the baseline fugitive metal HAP emissions for 

each facility. These baseline fugitive lead emissions estimates were used as the starting point for 

the development of post-control fugitive emissions estimates. We adjusted the baseline 

housekeeping and enclosure factors for each facility to reflect the level of fugitive dust control 

required in the final rule. This included level 3 enclosure (enclosure factor of 0.25) and 

implementation of work practices beyond the current NESHAP which are described in the final 

rule (housekeeping factor of 0.2) for each facility. The resulting post-control fugitive lead 

emissions estimates are shown in Table 9-1.

After we determined the post-control fugitive lead emissions for each facility, we used 

the ratios (shown in table 5-2 above) to estimate post-control emissions of all other metal HAP 

by applying the ratios to the estimates shown for lead in table 9-1.

Table 9-1. Estimated Post-Control Fugitive Lead Emissions.

Facility Post-Control Fugitive Pb Emissions (TPY)

Exide Baton Rouge 0.03

Exide Forest City 0.03

Exide Frisco 0.04

Exide Muncie 0.04

Exide Reading 0.04

Exide Vernon 0.07

RSR 0.05

Quemetco (CA) 0.04

Quemetco (IN) 0.05

Sanders Lead 0.05

EnviroFocus 0.02

Gopher Eagan 0.06

Buick RRF 0.11

East Penn 0.05

TBR 0.01

8.3 Post-Control Stack and Fugitive Emissions of PM

In order to assess the co-reductions in emissions of PM resulting from the revisions to the 

Secondary Lead Smelting NESHAP, we developed a ratio of lead to PM based on emissions data 

submitted in the ICR. Based on that data, we calculated a lead to PM ratio of 1 to 10.1 and 

applied it to the lead emissions reductions from stack and fugitive sources. In order to estimate 

the fraction of the PM emissions reductions that are PM2.5, we developed a range of particle size 

distributions for secondary lead smelters based on AP-42 emissions data and a 2009 emissions 
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inventory for the Exide Frisco facility. Based on this information, we estimated that between 30 

and 48 percent of the PM emissions from secondary lead smelters is PM2.5.
1

MEMORANDUM

To: Docket No.: EPA-HQ-OAR-2011-0344

From: Nathan Topham, Project Lead

Risk and Technology Review – National Emissions Standards for Hazardous Air 

Pollutants (NESHAP) for Secondary Lead Smelting

Date: December 16, 2011

Subject: Estimated Time Needed to Comply with the Final Revisions to the Secondary 

Lead Smelting NESHAP

The purpose of this memorandum is to present the results of an analysis to estimate the 

time required for the 16 secondary lead smelting facilities operating or under construction in the 

U.S. and Puerto Rico to comply with the final revisions to the Secondary Lead Smelting 

NESHAP.

1.0 SUMMARY OF FINAL REVISIONS

As part of the Risk and Technology Review (RTR) for the Secondary Lead Smelting 

source category, the EPA is finalizing revisions to the stack and fugitive emissions standards in 

the NESHAP. 

For stack emissions, the EPA is lowering the current lead-based concentration limit of 2.0 

milligrams per dry standard cubic meter (mg/dscm) applicable to all stacks in the source category 

to 1.0 mg/dscm. Additionally, the EPA is adding a facility-wide flow-weighted average lead 

concentration limit of 0.2 mg/dscm.

For fugitive emissions, the EPA is requiring that facilities operate all lead-bearing 

processes within total enclosures that are maintained at negative pressure and are vented to a 

control device. The EPA is also requiring additional work practices beyond those required in the 

existing NESHAP.

The EPA is finalizing these revisions under Sections 112(d)(6) and 112(f)(2) of the Clean 

Air Act (CAA). As outlined in the Act, sources must comply with any standards promulgated 

under 112(f)(2) within 90 days of promulgation. However, the Administrator may grant a waiver 

allowing up to a two year compliance period if the Administrator finds that “such period is 

necessary for the installation of controls and that steps will be taken during the period of the 

waiver to assure that the health of persons will be protected from imminent endangerment” 

(CAA Section 112(f)(4)(A)-(B)). In this memorandum, we estimate the time that will be 
2

required for facilities in this source category to comply with the final revisions to the Secondary 

Lead Smelting NESHAP. The results of our analyses are presented in the following sections.

2.0 STACK EMISSION STANDARDS

Based on the final revisions to the stack emissions limits described in section 1.0 of this 

memorandum, we estimate that five facilities will not be in initial compliance with the flow 

weighted average stack emissions limit of 0.2 mg/dscm. However, we expect that three of these 

facilities will come into compliance with the flow weighted average limit after installation of the 

total enclosures and associated control devices that are required under the revisions to the 

fugitive emissions standards described in section 1.0. We further estimate that 6 facilities will 

need to reduce their stack emissions in order to ensure compliance with the concentration limit of 

1.0 mg/dscm applicable to all stacks. 

Based on the analyses described above, we estimate that 4 facilities will need to replace 

existing baghouses at 7 stacks (see Cost Impacts of the Revised NESHAP for the Secondary 

Lead Smelting Source Category for more details). An additional 3 control devices will require 

additional maintenance or replacement of bags in baghouses. We estimate that a replacement 

control device will require 21 to 24 months to be fully operational. This includes 2-4 months for 

evaluation of existing control devices and development of an engineering plan to meet the 

revised emissions limits, 2-4 months for engineering of replacement control device(s), 2-3 

months for capital approval, 5-7 months for delivery of the control device, 2-4 months for 

construction and installation, and 2-3 months of operation until stack testing is conducted. These 

facilities will also likely have several other ongoing projects to comply with the revisions to the 

fugitive emissions standards.

3.0 FUGITIVE EMISSION STANDARDS

Based on the revisions to the fugitive emissions standards described in section 1.0, we 

estimate that 11 of the 15 operating secondary lead smelting facilities will be required to 

implement additional fugitive emissions control work-practices. We also estimate that 8 facilities 

will need to construct total enclosures for their lead-bearing processes if they do not currently 

exist. Table 3-1 presents a summary of the actions that we expect will be taken by the facilities to 

comply with the revised fugitive emissions standards.

We estimate that construction of new enclosures for one or more of the specified fugitive 

emissions sources will require 21 to 24 months. This includes an estimated 5-7 months for 

engineering analysis and design, 2-3 months for capital approval, and 12-16 months for 

construction of the enclosure, installing additional ventilation systems and duct work, and 

ensuring appropriate venting of gases to the control devices.
3

Table 3-1. Summary of Required Actions for Compliance with the Revisions to the Fugitive 

Emissions Standards in the Secondary Lead Smelting NESHAP.

Number of 

Facilities that 

would need to do 

action

Construct Total Enclosures Implement 

Additional 

Work 

Practices

Develop an SOP, 

and submit the 

SOP for review 

and approval by 

the Administrator

Furnace 

Area

Raw 

Materials 

Storage 

Area

Refining 

and 

Casting 

Area

Battery 

Breaker 

Area

 1 ü ü ü

 1 ü ü ü ü

 4 ü

 3 ü ü ü ü ü

 3 ü ü

 4 ü ü ü ü ü ü

Some facilities already have all of the specified fugitive emissions sources in total 

enclosures and will only need to develop and implement additional fugitive work practices. We 

estimate that development and implementation of the additional work practices will require a 

minimum of 6 months. We believe that some facilities may need to hire additional employees to 

dedicate to the new work-practices. Thus, an estimated 2-4 months may be required to hire and 

train new employees. Additionally, all facilities will need to develop standard operating 

procedures (SOPs) and submit those draft SOPs to the Administrator for review and approval. 

They may potentially then need to revise those plans based on comments by the Administrator 

and resubmit the revised SOPs for further review and approval. Finally, the facilities will need to 

implement those work practices pursuant to the approved SOP. We estimate that this overall 

process could take 6-9 months.

4.0 CONCLUSIONS

Based on our analysis, at least half of the secondary lead smelting facilities affected by 

the revisions to the existing NESHAP will need 21 to 24 months to complete the projects 

necessary for compliance. With regard to the steps that will be taken during the period to assure 

that the health of persons will be protected from imminent endangerment, we conclude that the 

public will be protected from imminent endangerment during these extra months because 

facilities will continue to comply with the existing 1997 NESHAP and various State programs 

which ensure emissions are limited. Therefore, we believe that a two year compliance period is 

appropriate for all secondary lead smelting facilities.
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1 Final Guidance for EPA Rulewriters: Regulatory Flexibility Act as amended by the Small Business Regulatory 

Enforcement Fairness Act, November 2006. http://www.epa.gov/sbrefa/documents/rfaguidance11-00-06.pdf 

MEMORANDUM

To: Nathan Topham, U.S. Environmental Protection Agency, OAQPS

From: Donna Lazzari and Mike Burr ERG 

Date: December 16, 2011

Subject: Small Business Evaluation for the Secondary Lead Smelting Source Category

This memorandum describes the expected economic impact of the revisions to the 

National Emissions Standards for Hazardous Air Pollutants (NESHAP) for the Secondary Lead 

Smelting source category (40 CFR 63, Subpart X) on the small entities in the source category 

that were identified based on a screening level analysis as recommended in the Regulatory 

Flexibility Act, as amended by the Small Business Regulatory Enforcement Fairness Act 

(RFA/SBREFA).1 The organization of this memo is as follows:

1.0 Background on the Source Category

2.0 Identification of Small Entities

3.0 Estimated Cost Impact of Proposed Revisions

4.0 Conclusion and Decisions

1.0 BACKGROUND ON THE SOURCE CATEGORY

The Secondary Lead Smelting source category consists of 16 facilities (15 already 

existing and one under construction) owned by eight legal entities. These legal entities include: 

Exide Technologies Corporation (six facilities), Revere Smelting and Refining Corporation 

(three facilities), Doe Run Resources Corporation (one facility), East Penn Manufacturing 

Company, Inc. (one facility), Sanders Lead Company (one facility), Gopher Resources, LLC 

(two facilities), The Battery Recycling Company (one facility), and Johnson Controls, Inc. (one 

facility under construction). A section 114 information collection request (ICR) was sent to the 

industry in June of 2010 requesting available information on process equipment, control devices, 

stack and fugitive emissions, and other aspects of the operations. Information obtained in the 

surveys was used to perform a risk and technology review (RTR) for the source category. 

2.0 IDENTIFICATION OF SMALL ENTITIES

The EPA is required by RFA/SBREFA to determine whether a rule will have a 

significant economic impact on a substantial number of small entities (SISNOSE) within the 
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2

 http://www.sba.gov/content/table-small-business-size-standards

corresponding source category. The Small Business Administration’s (SBA) threshold for 

qualification as a small entity for North American Industry Classification System (NAICS) code 

331419, which applies to the Secondary Smelting and Refining of Nonferrous Metal (except 

copper and aluminum) source category, is a maximum of 750 employees.2 Using this threshold, 

we examined information submitted by the industry in the ICR to determine whether any small 

parent entities exist in this source category. Based on survey responses regarding the number of 

employees at each facility, we identified two companies in the Secondary Lead Smelting source 

category as small entities.

Gopher Resource, LLC, which owns the Gopher Resource facility in Eagan, MN (hereby 

referred to as Gopher Eagan) and the EnviroFocus Technologies facility in Tampa, FL (hereby 

referred to as EnviroFocus), claimed a combined total of 315 employees for all of their 

operations, potentially qualifying them as a small entity. We contacted Gopher Resources and 

confirmed that they employ a total of 359 employees across their entire operation and are 

therefore considered a small entity according to the SBA guidelines. The Battery Recycling 

Company in Arecibo, Puerto Rico was also identified as a small business that employs 140 

people. 

Because there are only eight legal parent entities in this source category, we determined 

that two small entities constitutes a substantial number of small entities. Therefore, as required 

by RFA/SBREFA, we analyzed whether the revisions under consideration for proposal in the 

Secondary Lead Smelting NESHAP will significantly impact Gopher Resources and The Battery 

Recycling Company.

3.0 ESTIMATED COST IMPACT OF PROPOSED REVISIONS

According to SBREFA guidance, we used one to three percent of annualized the cost to 

revenue ratio as a threshold for what constitutes a significant economic impact. Our estimated 

costs and revenue information are both for 2009. Based on revisions to the NESHAP under 

consideration for this source category, we believe that certain facilities will need to make 

improvements in controls of two major sources: stack and fugitive emissions. We analyzed 

potential improvements in control of both stack and fugitive emissions sources that the Gopher 

Resources and The Battery Recycling facilities may be required to implement and the potential 

economic impact of those improvements on the companies. The results of this analysis are 

presented in the following sections.

3.1 Stack Emissions

Based on the information obtained on the source category in the ICR and a risk analysis, 

the EPA evaluated a number of control scenarios to reduce the health risks associated with stack 
DRAFT

3

emissions from the Secondary Lead Smelting source category. These control scenarios 

potentially reduce stack emissions of the following pollutants: metal hazardous air pollutants 

(HAP), organic HAP, and dioxins and furans (D/F). The control option selected for stack 

emissions of metal HAP is typically achieved using efficient particulate collection devices. 

Measures to achieve the emissions limit may include upgrading existing control devices (e.g., 

fabric filters) or installing newer, more efficient control devices. Additional controls that could 

be used to achieve compliance with the emissions limits for D/F and organic HAP include 

increasing the temperature at which afterburners are operated and for facilities that operate blast 

and reverberatory furnaces to combine the hotter reverberatory furnace stream with the cooler 

blast furnace stream prior to entry into a control device.

Based on the information submitted in the ICR, the Gopher Eagan, MN facility is among 

the best five facilities in terms of stack emissions of metal HAP. Therefore, we do not anticipate 

that this facility will be required to further control stack emissions of metal HAP. While the stack 

emissions at Gopher Eagan were not tested for organic HAP and D/F, an analysis of ICR 

emissions data for similar furnace and afterburner configurations at other facilities indicates that 

Gopher Eagan will likely not be required to implement additional controls for stack emissions of 

organic HAP and D/F. Based on emissions data received in the ICR, we believe that the 

EnviroFocus Technologies facility in Tampa may be required to implement additional controls 

for stack emissions of metal HAP, organic HAP, and D/F. Such controls may include upgrading 

their existing fabric filters and/or installing new fabric filters for control of metal HAP emissions 

and increasing the capacity of their afterburner to achieve higher destruction efficiency of 

organic HAP and D/F.

After further investigation, we discovered that Gopher Resources had submitted a facility 

upgrade and production increase permit for the EnviroFocus Technologies facility that had 

recently been approved by the Florida Department of Environmental Protection. Several large 

projects were authorized in this permit, including: installation of a new reverberatory furnace; 

installation of new baghouses with additional airflow capacity to control particulate matter (PM) 

and metal HAP from the dryer, furnaces, and refining kettles; complete enclosure of all 

processes under negative pressure; and a capacity increase to the particulate collection device for 

the existing enclosures to accommodate the new expected enclosure ventilation. These projects 

are expected to be completed within the next two years.

We believe that the new control devices and enclosures being installed by Gopher 

Resources at the EnviroFocus Technologies facility will ensure that they are within compliance 

with the revisions to the stack emissions limits for metal HAP, organic HAP, and D/F that are 

required for the revised NESHAP for this source category. Therefore, further controls for stack 

emissions beyond what is included in the aforementioned permit for the EnviroFocus 
DRAFT

4

Technologies facility are not expected to be required at either of the facilities owned by Gopher 

Resources, LLC.

The Battery Recycling Company’s facility in Arecibo, Puerto Rico currently has one 

stack through which all emissions are directed. Stack test data submitted by the facility indicates 

that the facility’s lead emissions are below the newly promulgated lead emission standard, and 

thus no additional control will be required. The facility operates rotary furnaces that process lead 

scrap materials. The revised NESHAP does not include a limit for D/F and THC for rotary 

furnaces. No cost impact to the facility is anticipated as a result of these organic emissions. 

3.2 Fugitive Emissions

Similar to stack emissions, EPA considered a number of control scenarios to reduce the 

emissions associated with fugitive sources in this source category. These control scenarios 

focused on reducing fugitive emissions of metal HAP which are of significant concern for this 

industry. Specific fugitive controls required by the final rule include complete enclosure of all 

lead-bearing processes and operating the enclosure under negative pressure with ventilation to a 

control device, and requiring additional work practices designed to limit the formation of 

fugitive dust. 

Based on fugitive control information submitted by the Gopher Eagan facility in the ICR, 

this facility currently contains all lead-bearing processes in total enclosures under negative 

pressure that are vented to a control device. Therefore, additional capital costs associated with 

construction of enclosures for their processes are not expected. This facility may be required to 

implement additional fugitive control work practices beyond what was described in their ICR 

response. We do not anticipate that the facility will incur capital costs associated with the 

implementation of these additional work practices. However, we estimated an annualized cost of 

$250,000 for performance of the additional work practices. We estimate the annualized cost for 

additional testing, monitoring, recordkeeping, and reporting considering the first three years after 

the proposed revisions are implemented is $52,000. Based on the projects listed in the previously 

discussed permit for the EnviroFocus facility, we do not anticipate requiring construction of 

additional enclosures for fugitive dust control. We believe that completion of the projects 

mentioned in their permit application will result in the EnviroFocus facility having their entire 

process under a total enclosure with negative pressure that is vented to a control device. 

However, the EnviroFocus facility may be required to implement additional fugitive control 

work practices beyond what was described in their ICR response. We do not anticipate that the 

facility will incur significant capital costs associated with these additional work practice 

practices. We do, however, estimate an annualized cost of $250,000 associated with the 

performance of these additional work practices. We estimate the annualized cost for additional 

testing, monitoring, recordkeeping, and reporting considering the first three years after the 
DRAFT

5

3 ERG. Cost Impacts of the Revised NESHAP for the Secondary Lead Smelting Source Category, December 16, 

2011.

proposed revisions are implemented is $52,000. 

We do anticipate that The Battery Recycling Company will incur an estimated annualized 

cost of $412,000 for construction and operation of enclosures and the associated control device. 

The facility may also be required to implement additional fugitive control work practices beyond 

what was described in their limited ICR response. We do not anticipate that the facility will incur 

significant capital costs associated with these additional work practice practices. We do, 

however, estimate an annualized cost of $250,000 associated with the performance of these 

additional work practices. We estimate the annualized cost for additional testing, monitoring, 

recordkeeping, and reporting considering the first three years after the proposed revisions are 

implemented is $38,000. 

A description of the methodology used to derive these estimates is included in the cost 

impacts memorandum for this source category.3

4.0 CONCLUSION AND DECISIONS

Based on the analyses presented in this memorandum, we estimate the total maximum 

annualized cost to Gopher Resources, LLC, resulting from additional requirements associated 

with proposed revisions under consideration for the Secondary Lead Smelting NESHAP, will be 

no more than $604,000. We compared this amount with the annual revenue for Gopher 

Resources (obtained through discussion with the company) and concluded that it represents less 

than one percent of their annual revenue. The total cost impact for The Battery Recycling 

Company is anticipated to be $690,000. Based on information received from the company on the 

annual revenue, this cost impact is between one and three percent of the company’s annual 

revenue. 

A matrix was developed for this analysis of the secondary lead smelting source category 

based on guidelines in the Final Guidance for EPA Rulewriters noted above to determine if 

changes to the NESHAP will result in a significant economic impact on small businesses. 

Because the number of entities in the source category is small, a matrix was developed that 

considered an impact to a significant number of small entities based on a discrete number of 

facilities and the production capacity of the small businesses rather than a percentage of small 

entities. The matrix is included as Table 1 below.

Table 1: Secondary Lead Smelting Source Category SISNOSE Certification Decision Process

Economic Impact Number of Small Percent of Small Certification Category
DRAFT

6

Entities Subject to the 

Rule and 

Experiencing Given 

Economic Impact

Business Capacity 

of Entities Subject 

to the Rule That 

are Experiencing 

Given Economic 

Impact

Less than 1% of 

Total Revenue

Any Number Any Percent Presumed No SISNOSE

Between 1% and 

3% of Total 

Revenue

One or Less Impacted facilities 

have less than 20% 

of the capacity of all 

small businesses

Presumed No SISNOSE

2 or More Impacted facilities 

have more than 20% 

of the capacity of all 

small businesses

Uncertain – No 

Presumption, Proceed 

with Regulatory 

Flexibility Analysis

3% or Greater of 

Total Revenue

One or more Any Capacity Uncertain – No 

Presumption, Proceed 

with Regulatory 

Flexibility Analysis

An evaluation of the two small entities (three facilities) as compared to the matrix in 

Table 1 is presented in Table 2 below. 
DRAFT

7

Table 2: Small Entity Impact Summary

Facility Total Annual 

Economic 

Impact

Impact Range

<1%, 1-3%, 

>3% of Annual 

Revenue

Percent of Total 

Small Business 

Capacity

SISNOSE 

Determinatio

n

Gopher Resources $317,000

<1%

>20% Presumed no 

impact

Envirofocus 

(owned by Gopher 

Resources)

$317,000

The Battery 

Recycling 

Company

$716,000 1-3% <20% Presumed no 

impact

Based upon the SISNOSE decision matrix established for this industry and the impacts 

presented in Table 2 above, we conclude that the revisions to the Secondary Lead NESHAP are 

not anticipated to have a significant impact on a substantial number of small entities. 
1

MEMORANDUM

To: Nathan Topham, U.S. Environmental Protection Agency, OAQPS

From: Mike Burr and Donna Lazzari, ERG 

Date: December 16, 2011

Subject: Summary of the Ambient Lead Monitoring Data near Secondary Lead Smelting 

Facilities

The EPA has recently conducted a Risk and Technology Review (RTR) for the 

Secondary Lead Smelting source category. As part of this process, ambient lead monitoring data 

was used as one of the indicators of the effectiveness of fugitive emissions controls at these 

facilities. This memorandum summarizes the available ambient lead monitoring data near 

secondary lead smelting facilities in the U.S. that was utilized as part of the EPA’s RTR process 

for the Secondary Lead Smelting source category. This memorandum is organized as follows:

1.0 Data Extraction

2.0 Summary of Monitoring Stations

3.0 Summary of Ambient Lead Data

4.0 Ambient Lead Concentrations Based on Enclosure Category

1.0 DATA EXTRACTION

The EPA’s repository of ambient air quality data, the Air Quality System (AQS), was 

utilized to search for available ambient lead monitoring data around secondary lead smelting 

facilities. Where available, the 3-month rolling average lead concentrations were extracted for 

the period of 2008-2010 at any available monitoring stations within three miles of each of the 

facilities. The 2008-2010 time frame was chosen to be consistent with modeling conducted as 

part of the EPA’s risk and technology review (RTR) for the Secondary Lead Smelting source 

category. Three-month rolling average concentrations were extracted to be consistent with the 

averaging time for the National Ambient Air Quality Standards (NAAQS) for lead.

2.0 SUMMARY OF MONITORING STATIONS

Ambient lead monitoring stations are located near 13 of the 15 operational secondary 

lead smelting facilities; data near the Exide Technologies facilities in Baton Rouge, LA, and 

Forest City, MO, were not available. Table 1 presents a summary of the available data from 
2

monitoring stations near each of the secondary lead smelting facilities.

Table 1. Summary of Available Ambient Lead Monitoring Data near Secondary Lead Smelting 

Facilities.

Facility Number of 

Monitors

AQS Site ID’s Monitor Distance from 

Facility Center(miles)**

Buick Resources Recycling 

Facility (Boss, MO)

3 290930016*

290930021*

290930032

0.6

1.5

1.5

East Penn Manufacturing 

(Lyons, PA)

4

420110005

420110717

420110021

420110022

0.5

0.6

0.7

0.9

Exide Technologies 

(Vernon, CA)

2

060371405

060371406 0.1

0.3

Exide Technologies 

(Reading, PA)

2

420111717

420110020 0.1

0.5

Exide Technologies 

(Muncie, IN)

2

180350008

180350009 0.1

0.3

Exide Technologies

(Frisco, TX)

3

480850003

480850009

480850007

0.3

0.3

0.6

Gopher Resources

(Eagan, MN)

1

270370465

0.2
3

EnviroFocus Technologies

(Tampa, FL)

2

120571066

120571073 0.1

0.4

Quemetco, Inc. 

(Industry, CA)

1

060371404

0.2

Quemetco, 

Inc.(Indianapolis, IN)

2

180970063

180970076 0.5

0.7

Revere Smelting and 

Refining 

(Middletown, NY)

3

360713001

360713002

360713004

0.2

0.3

0.9

Sanders Lead Company 

(Troy, AL)

1

011090003

0.2

The Battery Recycling Co.

(Arecibo, PR)

1

720130001

0.3

*Information received from Buick Resources indicated these sites are located within the facility 

fenceline

**Estimated using Google Earth

3.0 Summary of Ambient Lead Data

Table 2 presents a summary of all the ambient lead concentration data at each monitor 

near the secondary lead smelting facilities. Note that “N/A” indicates that data for the specific 

monitor is not available for the specified time period. Figure 1 displays the mean of all 3-month 

rolling averages across all monitors for each facility and Figure 2 displays the maximum 3-

month rolling average across all monitors for each facility. As shown in Table 2, at least one 

maximum 3-month rolling average lead concentration from 2008-2010 exceeds the NAAQS for 

lead of 0.15 μg/m3 near 10 of the 13 facilities for which ambient monitoring data was available. 

All raw ambient data used in this summary is available in the docket for the proposed Secondary 
4

Lead Smelting NESHAP.
5

Table 2. Summary of Ambient Lead Concentrations near Secondary Lead Smelting Facilities

Facility AQS ID Maximum 3-Month Rolling 

Average Lead Concentration 

(μg/m3)

Mean 3-Month Rolling Average 

Lead Concentration 

(μg/m3)

2008 2009 2010 2008 2009 2010

Buick Resources Recycling Facility 

(Boss, MO)

290930016

*

2.46 2.07 0.64 0.90 0.62 0.49

290930021

*

1.12 1.94 0.72 0.81 0.86 0.42

290930032 N/A N/A 0.56 N/A N/A 0.31

East Penn Manufacturing

(Lyons, PA)

420110005 0.07 0.05 0.04 0.06 0.04 0.04

420110717 0.21 0.12 0.06 0.12 0.07 0.06

420110021 N/A N/A 0.32 N/A N/A 0.09

420110022 N/A N/A 0.26 N/A N/A 0.08

Exide Technologies (Vernon, CA)

060371405 2.49 0.66 0.25 1.42 0.44 0.24

060371406 0.22 0.08 0.05 0.17 0.07 0.04

Exide Technologies (Reading, PA)

060371405 0.24 0.25 0.20 0.17 0.14 0.12

060371406 N/A N/A 0.19 N/A N/A 0.13

Exide Technologies (Muncie, IN)

420111717 0.34 0.11 0.07 0.16 0.08 0.07

420110020 2.14 0.26 0.26 0.79 0.20 0.18

Exide Technologies (Frisco, TX)

480850003 0.26 0.32 0.37 0.21 0.22 0.22

480850009 1.26 0.65 0.77 0.75 0.46 0.61

480850007 0.17 0.15 0.20 0.12 0.10 0.11

Gopher Resources (Eagan, MN)

270370465 0.40 0.25 0.27 0.30 0.18 0.13

EnviroFocus Technologies 

(Tampa, FL)

120571066 1.77 0.25 0.73 0.47 0.16 0.29

120571073 0.40 0.11 0.13 0.18 0.08 0.08

Quemetco, Inc. (Industry, CA)

060371404 0.06 0.10 0.05 0.06 0.08 0.05

Quemetco, Inc.(Indianapolis, IN)

180970063 0.05 0.03 0.08 0.03 0.02 0.03

180970076 0.03 0.01 0.01 0.01 0.01 0.01

Revere Smelting and Refining 

360713001 0.04 0.04 0.04 0.03 0.03 0.02
6

360713002 0.09 0.08 0.08 0.06 0.04 0.05

360713004 0.01 0.01 0.01 0.01 0.01 0.00

Sanders Lead Company (Troy, AL)

011090003 1.18 0.91 1.00 0.60 0.43 0.66

The Battery Recycling Co. 

(Arecibo, PR)

720130001 N/A N/A 0.25 N/A N/A 0.16

Figure 1. Mean of 3-Month Rolling Average Lead Concentrations near Secondary Lead Smelting Facilities from 2008-2010
7

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

Mean 3-monthPrriomllianryg Laevaed raNgeAAQS

Concentration (μg/m3

Mean 3-Month Rolling Average Lead Concentration

Buick ResourcEeassRt ePceynnclinMgEaFxnuaidcfeiliaTctytuec(riBEhnxoigss, od leo(MLgTyieeO) ocsnhnE(sV,xoiePdlrA) oengoTienes,chn(RCA) EexoiadlodeginiTeges,cP(GhnMA)oouphlnocegEireienvR,sIeirN) (sFooriFusorccoeu,sT(TX)EeQacughneamno,leMotgcQN) ioeuR,seeInm(vTceae.rmt(ecInopSdu,amI,neFsctlL)t.ri(ynI,ndgCA) SaiandnadRpeeorsflins,LeinIaBN) gda(ttCMeoirmddypRlaeenytcoywnc(Tlirn,ogNy(Y) ,AArL)ecibo, PR)

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

Figure 2. Maximum 3-Month Rolling Average Lead Concentrations near Secondary Lead Smelting Facilities from 2008-2010
8

0.00

0.50

1.00

1.50

2.00

2.50

3.00

Max 3-monthPrroimllianryg aLveeard ageNAAQS

Concentration (μg/m3

Maximum 3-Month Rolling Average Lead Concentration

Buick ResourcEeas sRt ePceynnclinMgEaFxnuaidcfeiliaTtyctuec(riBEhnxoiss, god leo(MLgTyieeO) ocsnhE(s,nVxoiePdlrA) oengoTienes,chnCA) (REexoiadlodeginiTeges,cP(GhnMA)oounphlocegEirieenvR,sIeN) ir(sFooriFusorccoeu,sT(TX)EeQacughneamno,leMotgcQN) ioeuR,seeInm(vTceae.rmt(ecInopSd,amuI,neFsctlL)t.ri(ynI,ndgCA) SaiandndaRpeeorsflins,LeinIaBN) gda(ttCMeoirmddypRlaeenytcoywnc(Tlirn,ogNy(Y) ,AArL)ecibo, PR)

0.00

0.50

1.00

1.50

2.00

2.50

3.00
DRAFT

MEMORANDUM

To: Nathan Topham, U.S. Environmental Protection Agency, OAQPS

From: Mike Burr, Donna Lazzari, and Danny Greene, ERG 

Date: December 16, 2011

Subject: Summary of the Technology Review for the Secondary Lead Smelting Source 

Category

This memorandum summarizes the results of an analysis to identify developments in 

practices, processes, and control technologies for emissions sources of hazardous air pollutants 

(HAP) from the Secondary Lead Smelting source category. This analysis is part of the EPA’s 

review efforts in accordance with section 112(d)(6) of the Clean Air Act (CAA). This 

memorandum is organized as follows:

1.0 Background

1.1 Requirements of Section 112(d)(6) of the CAA

1.2 Description of the Secondary Lead Smelting Source Category and 

Requirements of the 1997 NESHAP

2.0 Developments in Practices, Processes and Control Technologies

2.1 Stack Emissions

2.2 Fugitive Emissions

3.0 Recommended Revisions Based on Developments in Practices, Processes and 

Control Technologies

3.1 Stack Emissions

3.2 Fugitive Emissions

4.0 Conclusions

1.0 BACKGROUND

1.1 Requirements of Section 112(d)(6) of the CAA

Section 112 of the CAA requires the EPA to establish technology-based standards for 

sources of HAP. These technology-based standards are often referred to as maximum achievable 

control technology, or MACT, standards. Section 112 also contains provisions requiring the EPA 

to periodically revisit these standards. Specifically, paragraph 112(d)(6) states:
DRAFT

(6) REVIEW AND REVISION. – The Administrator shall review, and revise as 

necessary (taking into account developments in practices, processes, and control 

technologies), emissions standards promulgated under this section no less often 

than every 8 years.

1.2 Description of the Secondary Lead Smelting Source Category and Requirements of 

the 1997 NESHAP

The current National Emissions Standards for Hazardous Air Pollutants (NESHAP) for 

the Secondary Lead Smelting source category was promulgated on June 13, 1997 (62 FR 32216) 

and codified at 40 CFR part 63, subpart X. As promulgated in 1997, the NESHAP applies to 

affected sources of HAP emissions at secondary lead smelters. The 1997 NESHAP (40 CFR 

63.542) defines “secondary lead smelters” as “any facility at which lead-bearing scrap material, 

primarily, but not limited to, lead-acid batteries, is recycled into elemental lead or lead alloys by 

smelting.” The secondary lead smelting process consists of: (1) pre-processing of lead bearing 

materials, (2) melting lead metal and reducing lead compounds to lead metal in the smelting 

furnace, and (3) refining and alloying the lead to customer specifications. The NESHAP for the 

Secondary Lead Smelting source category does not apply to primary lead smelters, lead 

remelters, or lead refiners. 

Today, there are 15 secondary lead smelting facilities that are subject to the NESHAP 

and one facility currently under construction. One existing facility is currently in the process of 

expanding their operations. 

HAP are emitted from secondary lead smelting as stack releases (i.e., process emissions, 

and process fugitive emissions) and fugitive dust emissions. Process emissions include exhaust 

gases from feed dryers and from blast, reverberatory, rotary, and electric furnaces. The HAP in 

process emissions are comprised primarily of metals (mostly lead compounds, but also some 

arsenic, cadmium, and other metals) and also may include organic compounds that result from 

incomplete combustion of coke that is charged to the smelting furnaces as a fuel or fluxing agent, 

combustion of natural gas or other fuels, or combustion of small amounts of plastics or other 

materials that get fed into the furnaces along with the lead-bearing materials. Process fugitive 

emissions are released from various sources throughout the smelting process, including smelting 

furnace charging and tapping points, refining kettles, agglomerating furnace product taps, and 

drying kiln transition equipment. Process fugitive emissions are comprised primarily of metal 

HAP. Fugitive dust emissions are emissions that are not associated with a specific process or 

process fugitive vent or stack. Fugitive emissions are comprised of metal HAP and result from 

the entrainment of HAP in ambient air due to material handling activities, vehicle traffic, wind, 

and other activities.
DRAFT

The 1997 NESHAP applies to process emissions from blast, reverberatory, rotary, and 

electric smelting furnaces, agglomerating furnaces, and dryers; process fugitive emissions from 

smelting furnace charging points, smelting furnace lead and slag taps, refining kettles, 

agglomerating furnace product taps, and dryer transition equipment; and fugitive dust emissions 

from roadways, battery breaking areas, furnace charging and tapping areas, refining and casting 

areas, and material storage areas. For process sources, the 1997 NESHAP specifies numerical 

emissions limits for total hydrocarbons (THC) and lead compounds for blast furnaces and 

collocated blast and reverberatory furnaces. Additionally, emissions limits for lead are specified 

for reverberatory, electric, and rotary furnaces. Lead compound emissions from all smelting 

furnace configurations are limited to an outlet concentration of 2.0 milligrams per dry standard 

cubic meter (mg/dscm) (0.00087 grains per dry standard cubic foot (gr/dscf)) (40 CFR 

63.543(a)). THC emissions from collocated blast and reverberatory furnaces are limited to an 

outlet concentration of 20 parts per million volume (ppmv) (expressed as propane) corrected to 4 

percent carbon dioxide (CO2). THC emissions are limited to 360 ppmv (as propane) at 4 percent 

CO2 from existing blast furnaces and 70 ppmv (as propane) at 4 percent CO2 from new blast 

furnaces (40 CFR 63.543(c)). The 1997 NESHAP does not specify limits for THC emissions 

from reverberatory furnaces not collocated with blast furnaces, rotary furnaces, or electric 

furnaces.

The 1997 NESHAP requires that process fugitive emissions sources be equipped with an 

enclosure hood meeting minimum face velocity requirements or be located in a total enclosure 

subject to general ventilation that maintains the building at negative pressure (40 CFR 

63.543(b)). Ventilation air from the enclosure hoods and total enclosures are required to be 

conveyed to a control device. Lead emissions from these control devices are limited to 2.0 

mg/dscm (0.00087 gr/dscf) (40 CFR 63.544(c)). Lead emissions from all dryer emissions vents 

and agglomerating furnace vents are limited to 2.0 mg/dscm (0.00087 gr/dscf) (40 CFR 

63.544(d)). The 1997 NESHAP also requires the use of bag leak detection systems for 

continuous monitoring of baghouses in cases where a high efficiency particulate air (HEPA) 

filters are not used in series with a baghouse (40 CFR 63.548(c)(9)).

For fugitive dust sources, the 1997 NESHAP requires that facilities develop and operate 

according to a standard operating procedures (SOP) manual that describes, in detail, the 

measures used to control fugitive dust emissions from plant roadways, battery breaking areas, 

furnace areas, refining and casting areas, and material storage and handling areas.
DRAFT

2.0 DEVELOPMENTS IN PRACTICES, PROCESSES, AND CONTROL 

TECHNOLOGIES

For the purposes of this technology review, a “development” was considered to be a(n): 

• add-on control technology or other equipment that was not identified during the 

development of the 1997 NESHAP for the source category; 

• improvement in add-on control technology or other equipment that was identified 

and considered during development of the 1997 NESHAP for the source category 

that could result in significant additional HAP emissions reductions; 

• work practice or operational procedure that was not identified during 

development of the 1997 NESHAP for the source category; or 

• applicable process change or pollution prevention alternative that was not 

identified and considered during the development of the 1997 NESHAP for the 

source category. 

We investigated developments in practices, processes, and control technologies for three 

categories of HAP emissions sources from secondary lead smelters: (1) stack emissions of lead 

and other metal HAP, (2) stack emissions of organic HAP, and (3) fugitive emissions of lead and 

other metal HAP. To identify developments, we conducted searches of the EPA’s 

RACT/BACT/LAER (Reasonably Achievable Control Technology/Best Available Control 

Technology/Lowest Achievable Emissions Rate) clearinghouse and the Internet for information 

on secondary lead smelting and similar processes, examined the Section 114 information 

collection request (ICR) responses from 15 secondary lead smelting facilities, reviewed 

technologies employed by similar industries, and reviewed new or updated NESHAPs for other 

source categories. The results of these analyses are presented in the following sections.

2.1 Stack Emissions

The 1997 NESHAP specifies emissions limits for metal HAP (using lead as a surrogate) 

and organic compounds (using THC as a surrogate) from stacks. This section of the technology 

review will focus on developments in practices, processes, and control technologies applicable to 

emissions of metal HAP and organic compounds from stacks.

a. Metal HAP Emissions from Stacks

Based on a review of the ICR responses, the most common control technology employed 

by the industry to control emissions of metal HAP from stacks is fabric filtration (or baghouses). 

Several types of baghouses are currently used by the industry, including shaker, pulse jet, and 

reverse pulse jet bag filters. One facility uses a wet electrostatic precipitator (WESP) 

downstream of a baghouse to further reduce emissions of metal HAP from stacks. Two other 

facilities have plans to install similar WESP units. Several facilities also reported using HEPA 

filters as an add-on control downstream of their baghouses. Additionally, some facilities reported 
DRAFT

using cartridge collectors; however these types of controls are generally suited to reduce metal 

HAP emissions from sources that have lower inlet concentrations and are typically not used to 

control metal HAP in smelting furnace exhaust.

The first part of our analysis included attempting to determine which control technology 

(e.g., fabric filter, WESP, HEPA filter, cartridge collectors) achieves the greatest control 

efficiency for metal HAP. We could not directly calculate control efficiencies due to lack of inlet 

concentration data; however, we compared the outlet lead concentrations from the different 

control technologies based on emissions data that we received in the ICR. 

As displayed in Figure 2-1, the average stack outlet lead concentration from the baghouse 

and WESP combination was almost 50 times lower than the outlet concentration achieved by 

using baghouses alone. HEPA filters used downstream of a baghouse achieved approximately 20 

percent lower outlet lead concentrations than baghouses alone. Cartridge collectors appear to 

achieve outlet lead concentrations approximately three times lower than baghouses; however, as 

mentioned, cartridge collectors are generally limited to emissions points with lower flow rates 

and inlet loading concentrations.

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Pb Concentration (mg/dscm)

Average Outlet Lead Concentration by Control Technology

Fabric Filter HEPA FilterCartrige collectors WESP 0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

Figure 2-1. Comparison of Control Device Outlet Lead Concentrations from Different 

Technologies.

Based on emissions data received in the ICR, we also compared the relative performance 

of each baghouse across facilities and attempted to determine the factors that correlate best with 

low outlet lead concentrations. The factors that we considered include baghouse type (e.g., 

shaker, pulse jet, reverse bag pulse), filter material, and age of the unit. Figure 2-2 shows the 

results of these analyses. Based on our analysis, the most significant factor affecting baghouse 

performance is the age of the unit. We found that units installed prior to 1989 generally had 

significantly higher outlet lead concentrations than the newer units. Shaker baghouses appear to 

have higher outlet lead concentrations than those of the pulse jet or reverse bag pulse type. 
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0.00

0.05

0.10

0.15

0.20

0.25

Pb Co0nc.30entration (mg/dscm) Average Outlet Lead Concentration from Baghouses by Type

Shaker Reverse Air Pulse

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

Pb Concentration (mg/dscm)

Average Outlet Lead Concentration from Baghouses by Filter Material

Teflon Other Polyester

0.00

0.02

0.04

0.06

0.08

0.10

0.12

0.14

0.16

0.18

0.20

1960 1970 1980 1990 2000 2010 0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40 Pb Concentration (mg/dscm)

Average Outlet Lead Concentrations from Baghouses by Installation Year

1960 1970 1980 1990 2000 2010 0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

Figure 2-2. Comparison of Baghouse Outlet Lead Concentrations Based on Type (Upper Left), Filter Media (Upper Right), and 

Installation Year (Bottom).
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7

However, the majority of the older units appear to be shaker types, and thus the age of the 

baghouse may be the controlling factor. We did not find a significant correlation between the 

outlet lead concentration and the filtration media used in the baghouses, although one company 

in the industry suggested, based on its experience, that Teflon (polytetrafluoroethylene) bags 

specifically supplied by Gore-Tex© performed better than other bag types. The company also 

suggested that the most critical factors influencing baghouse performance are proper installation 

and maintenance practices. They mentioned specific practices such as ensuring proper 

installation of the bags and properly sealing all ducts and dust conveyance devices. Additionally, 

they claim that replacing torn bags, rather than repairing them, can significantly improve 

baghouse performance.

Based on our analyses, we believe that the most important development in the control of 

stack emissions of metal HAP from this source category has been improvement in the 

performance of baghouses throughout the industry. The biggest indicator of such improvements 

is the level of metal HAP emissions currently being achieved in the industry in relation to the 

allowable level in the 1997 NESHAP (referred to as “MACT-allowable”), which is a lead based 

concentration standard of 2.0 mg/dscm for all stacks. Figure 2-3 shows the lead concentrations 

reported by the industry in the ICR compared to the lead concentration limit in the 1997 

NESHAP. As illustrated by Figure 2-3, the outlet lead concentrations currently being achieved 

by the industry are far below, and in most cases orders of magnitude below, the concentration 

limit specified in the 1997 NESHAP. The average reported stack lead concentration was 0.16 

mg/dscm with a median of 0.04 mg/dscm. This large discrepancy between actual and MACTallowable stack lead concentrations is likely a result of improvements in practices, processes, and 

control technologies that have significantly improved the performance of baghouses employed 

by this industry since the promulgation of the 1997 NESHAP. We also believe that the 

concentration data presented in Figure 2-3 clearly show that improvements in baghouse 

technology and operation have occurred that resulted in the capability of achieving significantly 

lower stack lead emissions than what is required by the 1997 NESHAP. 
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0

0.5

1

1.5

2

2.5

Reported Lead Concentrations Current MACT

Individual Stack Test Results

ntration (mg/dscm)

Reported Stack Lead Concentrations

0

0.5

1

1.5

2

2.5

Figure 2-3. Comparison of Stack Lead Concentrations Reported by the Industry with the 1997 

MACT Standard.

b. Organic HAP and Dioxin and Furan Emissions

Based on our review of the ICR responses, we found that emissions of organic HAP from 

smelting furnaces vary substantially among the different furnace types. In general, emissions of 

organic HAP from blast furnaces are much higher than those from other furnace types. 

Information collected in the ICR indicates that this is likely due to the much lower exit 

temperature of the blast furnace exhaust relative to the other furnace types. The majority of 

facilities that operate blast furnaces use afterburners to control emissions of organic HAP. The 

exhaust of reverberatory furnaces is sufficiently hot that the use of an afterburner is generally not 

required to meet the 1997 NESHAP limit for THC. Some facilities that operate both blast and 

reverberatory furnaces comingle the hotter reverberatory furnace stream with the cooler blast 

furnace stream to control organics in the blast furnace stream. We did not identify new control 

technologies that would achieve reductions in organic HAP emissions beyond the limits 

established in the 1997 NESHAP. 

However, we do believe it is possible to further reduce organic HAP emissions from blast 

furnaces by designing and operating an afterburner with a higher temperature and residence time. 

A blast furnace afterburner temperature as high as 2100 degrees Fahrenheit was reported in the 

ICR. This blast furnace exhaust gas was cooled and then mixed with reverberatory furnace 

exhaust, and therefore it was not possible to determine the exact concentration of THC resulting 

from the blast furnace alone. However, the THC concentration in the mixed exhaust was low; 

therefore we estimated that the THC concentration in the blast furnace exhaust must have been 
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1 Gullett, Brian (EPA) and Seeker, Randy (EER Corporation), Chlorinated Dioxin and Furan Formation 

Control and Monitoring. Presentation at the Industrial Combustion Coordinated Rulemaking Meeting.

September 17, 1997.

below approximately 5 ppmv @ 4% O2. This is a considerably lower THC concentration than 

reported for other blast furnace exhausts and other mixed blast and reverberatory furnaces 

exhausts. Because of the many different furnace configurations, it was not possible to establish a 

significant correlation between temperature of the exhaust gas and THC concentration. Average 

exhaust THC concentrations for the various furnace types are summarized in Table 2-1. 

Table 2-1. Summary of Exhaust THC Concentrations by Furnace Type.

Furnace Type Average THC (ppmv@4% O2)

Reverberatory furnaces not collocated with blast furnaces, and reverberatory 

furnaces mixed with electric furnaces

5.8

Blast Furnaces 372

Collocated Blast and Reverberatory Furnaces 3.7

Rotary Furnaces* 257

Blast and Reverberatory Furnace Mixed, not collocated 45

*Based on one test with only two runs.

Although dioxin and furan (D/F) emissions limits are not specified in the 1997 NESHAP, 

we investigated technologies available for prevention and/or control of D/F emissions from the 

smelting furnaces. Based on data submitted by the industry in the ICR, D/F emissions from blast 

furnaces are one to three orders of magnitude higher than emissions from reverberatory and 

electric furnaces. The key conditions typically associated with higher D/F emissions, listed in 

order of relative importance1, are:

• Poor combustion conditions,

• High particulate concentration in the flue gases of a combustion process,

• Increased residence time for particulate in critical temperature window (150 - 450 

degrees Celsius), 

• Particulate matter containing metals that can catalyze formation to dioxin,

• Waste or fuel that is comprised of complex organic or lignin-like structure, and

• Sufficient chlorine.

We believe the controlling factor for D/F formation in blast furnaces is the relatively low 

exit temperature of the exhaust stream in comparison to other furnace types. 

We identified two technologies employed by this source category that have demonstrated 

effective control of D/F emissions from blast furnaces: (1) incineration of the furnace exhaust, 

and (2) comingling of the blast furnace exhaust with the hotter reverberatory furnace exhaust. 
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2 Ficarella, Antonio and Laforgia, Domenico, Numerical Simulation of Flow-Field and Dioxins 

Chemistry for Incineration Plants and Experimental Investigation, Waste Management, 20 

(2000) 27-49. http://www.bvsde.paho.org/bvsacd/cd43/antonio.pdf

Based on information submitted in the ICR and information in the literature on dioxin 

destruction efficiency, operating an afterburner at sufficient temperature (approximately 1,600 

degrees Fahrenheit) with adequate residence time (approximately 2.0-2.5 seconds) can achieve 

significant reductions in D/F emissions from blast furnaces2. Additionally, emissions data 

submitted in the ICR indicate that D/F emissions from collocated blast and reverberatory 

furnaces are generally lower than emissions from a blast furnace alone. Average exhaust D/F 

concentrations of the various furnace types are summarized in Table 2-2. 

Table 2-2. Summary of Exhaust D/F Concentrations by Furnace Type.

Furnace Type Average D/F 

(nanograms/dscm)

Reverberatory furnaces not collocated with blast furnaces, and reverberatory 

furnaces mixed with electric furnaces

0.10

Blast Furnaces 38.83

Collocated Blast and Reverberatory Furnaces 0.19

Rotary Furnaces* 0.14

*Based on one test with only two runs.

Because the presence of chlorine is necessary for D/F formation, we also examined the 

potential sources of chlorine in the feed materials charged to the smelting furnaces. Historically, 

the plastic battery casings used in the construction of automotive batteries contained polyvinyl 

chloride (PVC). Although battery casings are no longer made of PVC, the battery casings can 

sometimes contain small amounts of chlorinated flame retardants. This material may be 

introduced into the furnace through incomplete separation of the battery casing material from the 

lead-bearing material in the feed preparation process. Moreover, we believe that occasionally 

some older batteries that still contain PVC casings could be processed.

Based on our review, control of D/F emissions occurs due to measures initially 

implemented to control organic HAP emissions (i.e., incineration and co-mingling of furnace 

exhaust streams). 

2.2 Fugitive Emissions

As outlined in section 1.2 of this memorandum, the pollutants emitted from fugitive 

emissions sources in this source category are metal HAP. Therefore, we focused on identifying 

advancements in practices, processes, and control technologies related to fugitive emissions of 

metal HAP. Sources of fugitive emissions at secondary lead smelters include dust from plant 

roadways, battery breaking operations, material storage areas, and process fugitives that are not 

captured by a control device.
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11

3 Exide Technologies at Frisco, TX operates a total enclosure for only the raw material storage area. Fugitive 

emissions from this facility therefore may be more typical of a level 1 enclosure facility.

The minimum requirements for control of fugitive emissions in the 1997 NESHAP for 

the following specified fugitive sources are:

• Plant roadways – must be cleaned twice per day;

• Battery breaking area – partial enclosure of storage piles and wet suppression 

with twice daily pavement cleaning;

• Furnace and refining and casting areas – partial enclosure and pavement cleaning; 

and

• Material Storage and Handling Areas – partial enclosure, wet suppression, and 

vehicle wash at exits.

Based on our analysis of information received in the ICR, we grouped the facilities into 

three categories that describe the level of fugitive emissions control implemented. Table 2-2 

defines these categories and Table 2-2 summarizes our categorization for each facility.

Table 2-3. Enclosure Category Definitions.

Enclosure Category Description

Level 1 Enclosure Facilities described as having Level 1 enclosure meet the enclosure 

requirements in the 1997 NESHAP. The facilities rely primarily on 

enclosure hoods to capture process fugitive emissions and partial 

enclosures with wet suppression for process units and storage areas.

Level 2 Enclosure Facilities described as having Level 2 enclosure generally employ, in 

addition to enclosure hoods for process fugitive sources, a 

combination of negative pressure total enclosures and partial 

enclosures with wet suppression for process units and storage areas.

Level 3 Enclosure Facilities described as having Level 3 enclosure generally employ, in 

addition to enclosure hoods for process fugitive sources, negative 

pressure total enclosures for all process units and storage areas.

Table 2-4. Enclosure Category Assigned to the 15 Secondary Lead Smelting 

Facilities.

Facility Enclosure Category

Exide Technologies – Baton Rouge, LA Level 1

Exide Technologies – Forest City, MO Level 2

Exide Technologies – Frisco, TX Level 23

Exide Technologies – Muncie, IN Level 3

Exide Technologies – Reading, PA Level 2

Exide Technologies – Vernon, CA Level 3

Revere Smelting And Refining – Middletown, NY Level 3

Quemetco Inc. – Industry, CA
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Level 3

Quemetco Inc. – Indianapolis, IN Level 3

Sanders Lead Co. – Troy, AL Level 1

EnviroFocus Technologies – Tampa, FL Level 2

Gopher Resources – Eagan, MN Level 3

Buick Resource Recycling Facility – Boss, MO Level 1

East Penn Manufacturing – Lyons, PA Level 3

The Battery Recycling Company – Arecibo, PR Level 1

As displayed in Table 2-3, our analysis concludes that 11 of the 15 facilities are 

controlling fugitive emissions beyond the levels required by the 1997 NESHAP. Additionally, 

seven of the 15 facilities have placed all of their process areas in total enclosures under negative 

pressure with ventilation to a control device. EnviroFocus Technologies has a current project to 

implement level 3 enclosures due to a permit requirement for a facility expansion. Exide in 

Frisco, TX is in the process of implementing level 3 enclosures due to a consent order with the 

state of Texas and the state’s lead NAAQS SIP implementation. After completing these projects, 

nine of the 15 secondary lead smelters will be classified as level 3 enclosure facilities. 

Of the seven facilities that are currently level 3 enclosures, several facilities claimed 

performing additional work practices (beyond the enclosures) that exceed the requirements of the 

1997 NESHAP to further limit the formation of fugitive dust in other areas of their facilities. 

Examples of these work practices include:

• more complete vehicle washing inside buildings;

• improved roadway cleaning techniques and frequency;

• pavement of entire facility grounds;

• cleaning of building roofs and exteriors;

• use of daily ambient monitoring to diagnose plant activities that lead to 

exceedances of the National Ambient Air Quality Standards (NAAQS) for lead;

• timely cleaning of accidental releases;

• inspection of outside battery storage areas for broken batteries; and

• performance of all maintenance activities inside total enclosures operated under 

negative pressure.

Our analysis of ambient lead concentration data measured near the facilities indicates that 

facilities with level 3 enclosure that implement the work practices described above are generally 

achieving much lower lead concentrations near their property boundaries (see Figure 3-2). For 

this reason, we believe that developments in practices, processes, and control technologies with 
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13

regard to fugitive emissions of metal HAP have occurred that can result in reduced metal HAP 

emissions from fugitive sources beyond the standards contained in the 1997 NESHAP.

3.0 RECOMMENDED REVISIONS BASED ON DEVELOPMENTS IN PRACTICES, 

PROCESSES, AND CONTROL TECHNOLOGIES

Based on the analyses presented above, we are recommending the following revisions to 

the 1997 NESHAP with regards to stack and fugitive emissions from the Secondary Lead 

Smelting source category.

3.1 Stack Emissions

As described in section 2.1 of this memorandum, the concentrations of lead in stacks 

reported by this industry in the ICR are far below the level specified in the 1997 NESHAP, 

indicating improvements in the control of metal HAP emissions since promulgation of the 1997 

NESHAP. Our analysis indicates that this is primarily a result of improved performance of 

baghouses. Therefore, we recommend revising the 1997 NESHAP to reflect the level of 

performance currently being achieved by facilities that implement well-performing baghouses to 

control emissions of metal HAP from stacks.

When considering the most appropriate form of a revised lead standard for this source 

category, the EPA considered alternatives to the current form (i.e., outlet lead concentration). 

However, the EPA analysis indicates that a concentration-based lead standard continues to be the 

most appropriate form for this industry. The EPA then determined the appropriate reduction to 

the lead concentration limit of 2.0 mg/dscm. As outlined in section 2.1, the average stack 

concentration of lead reported by the industry in the ICR was 0.16 mg/dscm with a median 

concentration was 0.04 mg/dscm. Over 96 percent of the reported concentrations were less than 

half the 1997 NESHAP limit of 2.0 mg/dscm and over 80 percent of the reported concentrations 

were at least an order of magnitude less than the 1997 NESHAP limit. Our analyses conclude 

that advancements in the performance of baghouses appear to be the controlling factors for these 

lower concentrations and that reducing the lead concentration limit from 2.0 to 0.2 mg/dscm 

would reflect the level of control achieved in practice by facilities that implement wellperforming baghouses.

Figure 3-1 compares the lead concentrations reported by the industry in the ICR with a 

potential revised lead concentration limit of 0.2 mg/dscm. Although the majority of stacks 

reported concentrations well below 0.2 mg/dscm, a limited number of stacks would need 

improvements, possibly in the form of improved maintenance practices on their existing 

baghouses or installation of newer, more efficient units. To provide the facilities flexibility in 

determining the best approach to meeting a revised concentration limit, the EPA proposed and is 

finalizing a facility-wide flow-weighted average lead concentration limit of 0.2 mg/dscm. For 
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14

this limit, facilities would assign a weighting factor to each stack lead concentration based on the 

flow rate of the stack. They would then sum the flow-weighted concentration of all the stacks at 

their facility to get a facility-wide flow-weighted concentration. An additional limit on any one 

emission point of 1.0 mg/dscm was established as an upper concentration limit. A limit in this 

form would reflect the level of metal HAP emissions control being achieved in practice by well 

performing baghouses while providing flexibility to the facilities in determining the most costeffective approach to achieving the necessary reductions. 

As required under section 112(d)(6), we considered the costs and other impacts associated with 

revising the lead concentration limit in the manner described above. As described in the Cost 

Impacts of the Revised NESHAP for the Secondary Lead Smelting Source Category, we estimate 

that ten baghouses at five facilities would need either to be replaced, or undergo a significant 

maintenance upgrade as a result of the revised limit. Emission points were selected for 

improvement that had a lead concentration above 0.5 mg/dscm (one half the standard for any one 

emission point). After emissions reductions at these stacks, all the facilities would be in 

compliance with the 0.2 mg/dscm flow weighted average limit. The estimated total capital cost is 

$11.5 million with a total annualized cost of $2.7 million. We estimate that the revised limit 

would result in annual reductions of metal HAP of approximately 8.2 tons with co-reductions in 

emissions of particulate matter (PM) of approximately 82 tons. We do not anticipate additional 

energy use associated with this revised limit, as only replacement baghouses, as opposed to new 

additional units, are expected. Furthermore, we do not anticipate any adverse non-air 

environmental impacts associated with the implementation of this revised limit.

For these reasons, we are recommending that a flow-weighted average lead concentration 

limit of 0.2 mg/dscm be applied to the sum of all stacks at each facility in this source category. 

To limit the potential impacts of any individual stack, we are also recommending that a 

maximum lead concentration limit of 1.0 mg/dscm be applied to individual stacks in this source 

category. This is warranted given the fact that, as described above, over 96 percent of stack lead 

concentrations reported in the ICR were less than 1.0 mg/dscm.
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Figure 3-1. Comparison of Stack Lead Concentrations Reported by the Industry with a Potential 

Revised Lead Concentration Limit.

3.2 Fugitive Emissions

As outlined in section 2.2 of this memorandum, several facilities in this source category 

are currently implementing controls for fugitive emissions of metal HAP that exceed what is 

required in the 1997 NESHAP. Based on our analyses, we are recommending revising the 1997 

NESHAP to reflect the level of control currently being achieved by the better performing 

facilities in this source category with regards to fugitive emissions of metal HAP.

Because fugitive emissions cannot be directly captured or measured, the most feasible 

limit is a work practice standard. Although lack of direct measurement makes comparisons of the 

efficiency of different control technologies challenging, analysis of ambient lead monitoring data 

near the facilities has generally been considered an accurate indicator of the level of fugitive 

emissions of metal HAP. The Residual Risk Assessment for the Secondary Lead Smelting 

Source Category presents dispersion modeling results for this source category indicating that 

fugitive emissions are overwhelmingly the most significant source contributing to ambient lead 

concentrations near the property boundaries of secondary lead smelting facilities. The same 

modeling results indicate that lead emissions from this source category could result in 

exceedances of the lead NAAQS at 9 of the 15 facilities.

We analyzed available ambient monitoring data to determine which facilities were 

implementing the most effective controls for fugitive emissions of metal HAP. Figure 3-2 

0

0.5

1

1.5

2

2.5

Reported Lead Concentrations Potential Revised MACT

Individual Stack Test Results

ncentration (mg/dscm)

Reported Stack Lead Concentrations

0

0.5

1

1.5

2

2.5
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16

displays the annual average lead concentrations at ambient monitoring locations around facilities 

based on the enclosure category assigned to the facility in section 2.2 of this memorandum. The 

figure includes concentration data for 13 of the 15 facilities (monitoring data near Exide Baton 

Rouge and Exide Forest City were not available). All data in this figure were taken from 

http://www.epa.gov/airexplorer/monitor_kml.htm. The most recent year’s monitoring data 

available was selected for each facility. In cases where data were available at multiple 

monitoring locations around a facility, we chose the monitor with the highest annual lead 

concentration.

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

tration (mg/dscm)

Annual Ambient Lead Concentrations by Enclosure Category

Level 1 Level 2 Level 3

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

Figure 3-2. Comparison of Annual Ambient Lead Concentrations for Each Enclosure Category.

As the figure shows, facilities categorized as level 3 enclosures achieved significantly 

lower ambient lead concentrations than those classified as level 1 or 2 enclosures. As previously 

mentioned, seven of the 15 facilities are currently classified as level 3 enclosures, two other 

facilities planning to implement level 3 enclosures in the near future. Of the facilities classified 

as having level 3 enclosures, four facilities also implement some or all of the additional work 

practices mentioned in section 2.2 to further prevent the formation of fugitive dust in other areas 

of their facilities. Based on this analysis, we concluded that level 3 enclosure plus the 

implementation of additional fugitive control work practices is necessary to achieve ambient lead 

concentrations below the NAAQS near the fence line of a facility. Because several facilities are 

already implementing these controls and because we estimate that these controls are necessary to 

ensure to ensure ambient lead concentrations below the NAAQS, we recommend revising the 

1997 NESHAP to require these controls.

As with the revised stack lead concentration limit discussed in section 3.1 of this 
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17

memorandum, we considered the potential cost impacts of revising the fugitive emissions 

standard in the 1997 NESHAP to include the controls mentioned above. As described in the Cost 

Impacts of the Revised NESHAP for the Secondary Lead Smelting Source Category, we estimate 

that the total capital cost to implement level 3 enclosure and additional fugitive control work 

practices throughout the industry is approximately $38 million with a total annualized cost of 

approximately $9.4 million. We estimate reductions in metal HAP emissions of 7.2 tons per year 

resulting from this revised standard with co-reductions of PM of approximately 72 tons. We do 

not anticipate any adverse non-air environmental impacts associated with this recommended 

standard. However, we do anticipate some additional energy use associated with the operation of 

the new total enclosure. After consideration of the costs, emissions reductions, and other 

potential impacts, we believe the revision of the fugitive emissions standard for this source 

category to include the control measures described in this memorandum is warranted and 

necessary.

As an alternative to requiring level 3 enclosure and the implementation of an extensive 

list of fugitive control work practices, EPA considered an option that would allow facilities to 

demonstrate compliance through ambient lead monitoring, and included this option in the 2011 

NESHAP proposal. However, during the comment period, several comments from were received 

that objected to this alternative. Based on the public comments and because the EPA ultimately 

concluded that the controls comprising level three enclosure would be necessary to achieve 

compliance with a lead concentration in air standard even if that alternative were included, this 

option was not included in the final 2011 NESHAP. 

4.0 CONCLUSIONS

This review identified several developments in practices, processes, or control 

technologies that have been implemented in this source category since promulgation of the 1997 

NESHAP. Our analysis indicates that several facilities have significantly reduced stack 

emissions of metal HAP, primarily though improved performance of baghouses. Additionally, 

several facilities have implemented fugitive emissions control practices that exceed the 

requirements of the 1997 NESHAP. Based on our review, we conclude that it is feasible and costeffective for facilities to achieve a facility-wide, flow-weighted average lead concentration of 0.2 

mg/dscm with a limit of 1.0 mg/dscm for any individual stack. We conclude that it is feasible for 

all facilities to fully enclose all process areas under negative pressure of and implement a 

prescribed list of work practices to limit fugitive emissions. Implementing these controls would 

achieve reductions in lead emissions of approximately 12.9 tons with total metal HAP reductions 

of approximately 15.4 tons. Additionally, we expect total co-reductions of PM emissions of 

approximately 130 tons. We estimate that between 39 and 63 tons of the total PM reductions will 

be reductions in particles with diameters less than 2.5 microns (PM2.5), depending on the nature 
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18

of the particle size distribution of emissions from this source category. Since the controls being 

required are already employed by a significant portion of the industry, we believe that these 

controls and measures are cost-effective measures that reflect achievable performance for this 

industry.