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Date: June 28, 2010

Subject: Minutes of the June 17, 2010 Conference Call with Representatives from 

Environmental Groups

EPA Contract No. EP-D-06-118; EPA Work Assignment No. 4-06

RTI Project No. 0210426.004.006

From: Chuck French

OAQPS/SPPD/MMG (D243-02)

U.S. Environmental Protection Agency

Research Triangle Park, NC 27711

To: Docket ID No. EPA-HQ-OAR-2010-0239

I. Introduction

A conference call with representatives from several environmental groups was held on 

June 17, 2010. The purpose of the meeting was to discuss their potential comments to the 

National Emission Standards for Hazardous Air Pollutants: Gold Mine Ore Processing and 

Production Area Source Category and Addition to Source Category List for Standards; Proposed 

Rule. This memorandum summarizes the major topics discussed during the meeting.

II. Attendees

Kendra Zamzow, Center for Science in Public Participation

Brook Brisson, Clean Water and Mining Program, Northern Alaska Environmental Center

Bonnie Gestring, Earthworks

Dave Chambers, Center for Science in Public Participation

John Hadder, Great Basin Resource Watch

Joel Reynolds, Solutions Statistical Consulting

Glenn C. Miller, Department of Natural Resources and Environmental Science, University of 

Nevada, Reno

Chuck French, U.S. EPA, OAQPS

Jeremy Aldworth, RTI International

Marvin Branscome, RTI International

Gabrielle Raymond, RTI International

III. Discussion

The major topics discussed during the meeting included the methodology for calculating 

Maximum Achievable Control Technology (MACT) standards, the ore pretreatment affected 

source, and the carbon processes affected source. The EPA provided explanations and 
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clarifications on topics brought up by the teleconference participants. Several people wanted 

clarification on EPA’s basis for using the 99% Upper Prediction Limit calculation for the MACT 

standard and using data that had variations within the runs. The participants questioned why EPA 

grouped roasters and autoclaves together in the ore pretreatment group. They mentioned that a 

new proposed mine in Alaska, Donlin Creek, could emit 3,200 lbs of mercury under the proposed 

standard. For the alternative percent removal option for new sources in the carbon processes 

affected source, they want EPA to look at the Marigold Mine’s percent removal rather than 

Round Mountain’s.

Attachment 1 is a summary of the statistical review of the MACT floor analysis submitted 

by Mr. Reynolds prior to the conference call. Attachment 2 contains topics for discussion for the 

meeting submitted by Kendra Zamzow prior to the conference call.
Attachment 1 
Solutions Statistical Consulting 14 June 2010

SolutionsConsulting@ak.net 1

Statistical Review of: 

Development of the MACT floors and MACT for the proposed NESHAP for gold mine 

ore processing and production

 

Metals & Minerals Group

Sector Polices and Programs Division

Office of Air Quality Planning and Standards

U.S. EPA, RTP, NC.

April 14, 2010.

SUMMARY 

The formulas presented in the document improperly base the MACT floor on a 99% 

confidence interval for the population mean emission rate rather than a tolerance interval

for, say, the 99th percentile of the emission rate distribution. Further, unless the replicate 

observations (‘runs’) are based on the same amount of input (concentrate, ore) each time, 

the unit-specific and source-specific estimates of mean emissions rate and run-to-run 

variation (‘process variation’) in emissions rates should be based on ratio estimators. 

SUMMARY OF PROPOSED STANDARD 

According to the document under review:

• ‘... the maximum achievable control technology (MACT) standard for existing

affected sources must be at least as stringent as the average emissions limitation 

achieved by sources in the MACT pool

• For new sources, MACT standards must be at least as stringent as the control 

level achieved in practice by the best controlled similar [existing] affected 

source.’

,’ where the pool is (i) the best performing 

12 percent of existing affected sources for which the Administrator has data for 

categories with 30 or more sources, or (ii) the best performing 5 sources for 

source categories with fewer than 30 sources. 

The level of minimum stringency is called the MACT floor. 

• Due to variability in emissions resulting from variation in operating conditions, 

the floor should be set ‘...at a level that a best performing source can expect to 

meet “every day and under all operating conditions”’. 

• These objectives are interpreted as leading to the following formula for the 

achieved emission limit:

x + t df vT ,

where 

x is the average of the (average) total emission rates from each of the best 

performing sources in the MACT pool, 

tdf is the ‘99th percentile of the t distribution with df degrees of freedom, and vT is 

the total variance for the top performing affected sources.
Solutions Statistical Consulting 14 June 2010

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• Each of the terms is broken down into component formulas built up from unitspecific estimates of (i) mean emissions rates and (ii) variation in emissions rates, 

to source-specific estimates of (i) mean emissions rates and (ii) variation in 

emissions rates, to the top-level terms given above.

MAJOR CRITICISMS 

1. Consider the best performing source. Setting the floor ‘...at a level that the best 

performing source can expect to meet “every day and under all operating 

conditions”’ requires estimating the distribution of possible emissions rates from 

that source’s production process (say hourly emission rates, though this 

temporal scale choice is a decision that needs to be specified). This distribution 

reflects the process variation in emissions rates arising from variation in the 

production conditions. 

The floor is to be set at a threshold just exceeding the maximum possible 

emission rate. Unfortunately, this is an impossible standard to quantify. It 

requires assuming a specific mathematical distribution as an adequate 

description of the emissions rate distribution. Even then, most common feasible 

mathematical distributions have infinite upper thresholds, hence the floor 

would logically be set to ∞, an operationally useless threshold. 

2. A reasonable approach would be to interpret the language of the standard as 

requiring a threshold that is only exceeded in ‘standard operating conditions’ 1% 

or 5% or x% of the time. This requires a decision as to what percentile of the 

emissions rate distribution to use as the threshold (e.g., 99%? 95%? 90%?). Call 

the percentile p.

3. Then, for that source, the standard requires using the sample data to estimate 

the unknown value of the pth percentile of the emissions rate distribution. 

Further, you want to account for the uncertainty in this estimate by providing an 

interval estimate. Specifically, what you want is a tolerance interval (Vardeman 

1992). A tolerance interval ‘brackets a portion of the full population 

distribution, such as the smallest 99% of the population [of emissions rates from 

this source]. Thus a one-sided upper 99% tolerance interval with 95% 

confidence is a threshold expected [with 95% confidence] to exceeded by only 

1% (=100%-99%) of observations from the ...’ emissions rate process (Reynolds 

and Braman 2009).

4. Rather than the required tolerance interval, which estimates an upper limit on 

the feasible observation values, the proposal provides a form of 99% confidence 

interval on the mean source-specific emission rate (the first formula above). 

These are very distinct interval estimates estimating very different things.

5. For a new source, the MACT threshold would simply be the upper limit of the pth 

percentile tolerance interval from the best performing source. 
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6. Assuming one did employ an appropriate tolerance interval approach, the 

language of the written objectives is ambiguous as to how to accommodate both 

the source-specific tolerance interval component and the desire to average 

across the best performing sources.

Question 1: is ‘best performing’ defined with respect to the average emission 

rate from a source, or with respect to the tolerance interval on the emission 

rates of that source (which would account for differences in both mean 

emissions rate and process variation in the emissions rate at a source)?

Question 2: How should one ‘average’ the emission rates from the bestperforming sources?

Option 1: take the 5th best performing source and use its source-specific 

tolerance interval as the floor.

Option 2: calculate tolerance intervals for each source in the MACT pool, take 

the 5th smallest upper limit as the floor.

Option 3: calculate tolerance intervals for each source in the MACT pool, take 

the average of the upper limits.

Option 4: pool the process variation information from across sources (equivalent 

to assuming that all sources share the same shaped distribution of emission 

rates but that is simply centered at different mean rates), use as the basis for a 

tolerance interval centered on the 5th smallest mean emission rate.

Option 2 seems closest to the intention of the description. Option 4, if the 

assumption is tenable, would provide the most precise estimate of the desired 

threshold.

7. The observations are rates constructed by dividing two measurements (lbs 

mercury emitted, tons ore or concentrate processed). Such data structures are 

most appropriately summarized using ratio estimators (Cochran 1977). The 

current unit-specific and source-specific estimation formulas for the emission 

rate mean and variance are not correct unless the input quantity (ore or 

concentrate) is held constant as part of the observation process. 

8. It is unclear why the higher level averages are in all cases taken to be equally 

weighted averages of the lower level estimates: unit-type means from unitspecific means, source means from unit-specific means, mean total emission rate 

from source-specific emissions rates. It seems reasonable that some of these 

should be weighted means: e.g., weighting the unit-specific mean emission rates 

by each unit’s total input processed (divided by the sum of input processed 

across units) to properly account for variation among units in the tons of 

material processed (and hence variation in the total emissions from each 
Solutions Statistical Consulting 14 June 2010

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source). I.e., treat the estimation as a form of stratified sample, with each unit 

(or unit type or source) as a strata.

9. This would require different variance estimators as well.

10. In effect, it seems like the proper approach would be to use a stratified ratio 

estimator.

OTHER COMMENTS 

1. The second term in the formula for vT is unclear and appears erroneous (the first 

term gives the pooled variance for the average total emissions across sources, 

assuming all units within a sources and all sources vary independently). I’ve not 

pursued it, however, as the whole interval is in error as shown by my comments 

above.

2. The formula assumes normality of emission rates. I’ve not checked the data to 

see if this is a tenable assumption.

Cochran, W.G. 1977. Sampling Techniques (3rd ed). Wiley, New York.

Reynolds, J.H. and N. Braman. 2009. Using tolerance intervals to assess recovery of 

mussel beds impacted by the Exxon Valdez oil spill. Marine Pollution 

Bulletin 58, 1496-1504.

Vardeman, S.B. 1992. What about the other intervals? The American Statistician 46, 

193-197l
Attachment 2
From: Kendra Zamzow <kzamzow@csp2.org>

 

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

 

 Cc: Brook Brisson <Brook@northern.org>, Bonnie Gestring 

<bgestring@earthworksaction.org>, Dave Chambers 

 <dchambers@csp2.org>, John Hadder <john@gbrw.org>, Joel 

Reynolds dba SOLutions Consulting 

 <solutionsconsulting@ak.net>, Glenn C Miller 

<glennm@unr.edu> 

 

 Date: 06/16/2010 01:16 PM 

 

 Subject: Topics for discussion at tomorrow's teleconference, proposed 

Hg rulemaking 

 

Dear Mr. French:

Here are some topics I believe would benefit from some discussion

tomorrow:

1. Separation of roasters and autoclaves in the "pretreatment" category 

(create 2 different categories) 2. Definition and treatment of "outliers" 

in runs used to develop MACT floor and also in future runs used in 

monitoring 3. Removal of Twin Creeks in the development of MACT floor for 

ore pretreatment We ranked all of the sources for which we had valid data 

representing current performance based on their emissions and identified 

the lowest emitting of the existing affected sources, which included four 

facilities with ore pretreatment processes, 11 facilities for those with 

carbon processes, and two facilities with the non-carbon concentrate 

processes. (page 3 "Development of MACT floors, technical memo) 4.

Disposal issues (location/cost/ETA for repositories, disposal of carbon 

filters, keeping material out of tailings ponds) 5. Donlin

Thank you for your time and consideration,

--

Kendra Zamzow, PhD

Center for Science in Public Participation PO Box 54 Sutton, Alaska 99674

907.745.3882 office

907.354.3886 cell