1 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 (N ESHAP) 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 a n analysis to identify developments in practices, processes, and control technologies for hazardous ai r 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, t h e 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 promulgati on 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, tha t 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 emis sions limit using the 2008 main stack emissions (which includes the sintering, blast furnace, and drossing operations) that the Doe Run facility reported in the ir annual state emission inventory submitted to the state of Missouri. This information was incl uded in Doe Run’s Section 114 ICR response

. V ariability 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 PROPOSA L

During the public comment period, we received comment s from the Doe Run facility that the proposed emission limit was not achievable and that the emission s information on which the limit was based were not representative of actual performance

. In their comment s , 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 that2 the compliance demonstration for the MACT standar d 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 STA CK EMISSION LIMIT FOR FINAL RULE

As a result of the emissions information received following proposal

, a revised emission limit for the main stack was calcu l ated 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 th e lead emission reduction observed is not the result of the MACT requirements, we believe that the current demonstrated emi ssion 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. Thes e 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.3 

## ATTACHMENT 14 

### Variabili ty 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 8 81

- 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 ac hieved by the best performing sources considering these sources’ operating variability).
Variability in lead producers’ performance has a numb er of causes. For emissions of lead compounds that are controlled by baghouses, the variability is chiefly due t o variations in performance of the control device for which both run

- to

- run and test

- to

- test variability must be accounted. 1

In determining a n emission limit for the main stack , we used annual production and emissions discharged from the air pollution co ntrol 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
equ ivalent to the source’s performance ba sed on future compliance tests. Specifically, the calculated limit is an upper prediction limit (UPL) calculated with the Student’s t

- test using the TIN V 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 pred iction 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 s ample 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 s 2 te rm) 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
p ollution 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 54878.5 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 equa tion 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  ̄ = 200 9 annual emissi ons 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 = 200 9 and 2008 stack t ests + [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

.6 Figure 1

- UPL Calculations for Main Stack Lead Emission