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MEMORANDUM 

Date: October 31, 2011

Subject: Section 112(d)(6) Technology Review for Primary Lead Processors: Final Rule

From: Nathan Topham, Project Lead

Risk and Technology Review - National Emission Standards for Hazardous Air 

Pollutants (NESHAP) for Primary Lead Processing

To: Docket No.: EPA-HQ-OAR-2004-0305

The purpose of this memorandum is to present the background and results of an analysis to identify 

developments in practices, processes, and control technologies for hazardous air pollutants (HAP) 

emission sources for the final rule for the Primary Lead Processing 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).

1.0 BACKGROUND

On February 17, 2011, the EPA proposed changes to the plant-wide emission limit for the Primary Lead 

Smelting source category based on several developments in practices, controls or processes that have 

been implemented in the primary lead smelting source category since promulgation of the 1999 MACT

rule. At the time of promulgation of the Primary Lead Smelting MACT rule, there were three operating 

primary lead smelters. Today there is one operating facility, The Doe Run Resources Corporation (Doe 

Run) in Herculaneum, Missouri, that is subject to the MACT standard. The improvements identified 

were requirements imposed on the Doe Run facility through the Missouri Lead state implementation 

plan (SIP) in order to comply with the lead NAAQS. 

At proposal, the EPA calculated a lead emissions limit using the 2008 main stack emissions (which 

includes the sintering, blast furnace, and drossing operations) that the Doe Run facility reported in their

annual state emission inventory submitted to the state of Missouri. This information was included in Doe 

Run’s Section 114 ICR response. Variability was calculated based on recent stack tests at the Doe Run 

facility. Using this approach, we calculated annual emissions of 14.8 tons per year from the sintering, 

blast furnace, and drossing operations (i.e. the main stack), combined it with the risk-based emission 

levels, and normalized using 2008 annual lead production to arrive at a facility-wide lead emission limit 

of 0.22 pound of lead per ton of lead produced. 

2.0 CHANGES INCORPORATED SINCE PROPOSAL

During the public comment period, we received comments from the Doe Run facility that the 

proposed emission limit was not achievable and that the emissions information on which the 

limit was based were not representative of actual performance. In their comments, the Doe Run 

facility provided 2009 stack test results, which they indicated were representative of the 

performance of the operations discharging to the main stack. Doe Run also commented that that
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the compliance demonstration for the MACT standard did not include emissions from the 

furnace area and refining operations stacks because they were not controlled at the time that the 

original MACT was promulgated and were therefore not subject to the original MACT emission 

limit. 

3.0 REVISED MAIN STACK EMISSION LIMIT FOR FINAL RULE

As a result of the emissions information received following proposal, a revised emission limit for the 

main stack was calculated based on 2008 and 2009 stack tests (including variability). (See Attachment

1). Using the new test data, lead emissions were calculated to be 0.97 tons of lead per ton of lead 

produced when variability was applied. Although the lead emission reduction observed is not the result 

of the MACT requirements, we believe that the current demonstrated emission level represents an 

achievable performance and that a reduction in the standard is warranted to bring the standard in line 

with actual performance. Further reductions were contemplated for the main stack, refining stacks, and 

furnace area stack. These reductions were rejected based on economic infeasibility. See the technical 

support document for this final rule (available in Docket ID EPA-HQ-OAR-2004-0305) for a more 

detailed discussion of the costs of further reductions.
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ATTACHMENT 1
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Variability and Upper Predictive Limit Calculation

Main Stack Lead Emissions

In assessing sources’ performance, the EPA may consider variability both in identifying which 

performers are “best” and in assessing their level of performance. Brick MACT, 479 F. 3d at 881-82; 

see also Mossville Envt’l Action Now v. EPA, 370 F.3d 1232, 1241–42 (D.C. Cir 2004) (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 best performing sources considering these 

sources’ operating variability). 

Variability in lead producers’ performance has a number of causes. For emissions of lead compounds 

that are controlled by baghouses, the variability is chiefly due to variations in performance of the control 

device for which both run-to-run and test-to-test variability must be accounted.1

 

In determining an emission limit for the main stack, we used annual production and emissions 

discharged from the air pollution control devices used to control lead emissions from the Doe Run 

primary lead smelter based on the 2008 and 2009 stack tests provided by Doe Run Company. 

We assessed variability using a statistical formula designed to estimate an emissions level that is 

equivalent to the source’s performance based on future compliance tests. Specifically, the calculated 

limit is an upper prediction limit (UPL) calculated with the Student’s t-test using the TINV function in 

Microsoft Excel®. The Student’s t-test has also been used in other EPA rulemakings (e.g., NESHAP for 

Portland Cement Manufacturing; NSPS for Hospital/Medical/Infectious Waste Incinerators; NESHAP 

for Industrial, Commercial, and Institutional Boilers and Process Heaters) in accounting for variability.

A prediction interval for a future observation is an interval that will, with a specified degree of 

confidence, contain the next (or some other pre-specified) randomly selected observation from a 

population. In other words, the prediction interval estimates what the upper bound of future values will 

be, based upon present or past samples taken. The UPL consequently represents the value which we can 

expect the mean of future observations (3-run average for lead) to fall below within a specified level of 

confidence, based upon the results of an independent sample from the same population. In other words, 

if we were to randomly select a future test condition from any of these sources (i.e., average of 3 runs or 

30-day average) we can be 95 percent confident that the reported level will fall at or below the UPL 

value. Use of the UPL is appropriate in this rulemaking because it sets a limit any single or future 

source can meet based on the source’s past performance. 

This formula uses a pooled variance (in the s2 term) that encompasses all the data-point to data-point 

variability. Where variability was calculated using the UPL statistical approach, we used the sample 

standard deviation calculated from the emissions data distributions for lead. The standard deviation is 

 1 Run-to-run variability is essentially within-test variability, and encompasses variability in individual runs comprising the 

compliance test, and includes uncertainties in correlation of monitoring parameters and emissions, and imprecision of stack 

test methods and laboratory analysis. 72 FR at 54877 (Sept. 27, 2007). Test-to-test variability results from variability in 

pollution device control efficiencies over time (depending on many factors, including for fabric filters the point in the 

maintenance cycle in which a fabric filter is tested). Test-to-test variability can be termed long-term variability. 72 FR at 

54878.
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the common measure of the dispersion of the data set around an average. We note here that the 

methodology accounts for both short-term and long-term variability and encompasses run-to-run and 

test-to-test variability. 

We adopted a form of the UPL equation that has been used in more recent rulemakings. See 75 FR 

54970 (September 9, 2010), 75 FR 32020 (June 4, 2010) and 75 FR 31905 (June 4, 2010). The UPL 

used in this proposed rule is calculated by:

Where:

x ̄ = 2009 annual emissions

n = the number of test runs

m = the number of test runs in the compliance average

s

2 = observed variance 

t = student t distribution statistic

This calculation was performed using the following Excel functions:

95 percent UPL = 2009 and 2008 stack tests + [STDEV(Test Runs) x TINV(2 x probability, n-1 degrees 

of freedom)*SQRT((1/n)+(1/m))], for a one-tailed t-value, probability of 0.05, and 

sample size of n

Figure 1 presents a listing of stack test results used in the calculation of the UPL and the UPL 

calculation for the main stack at the Doe Run Herculaneum facility.
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Figure 1 - UPL Calculations for Main Stack Lead Emission