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---------------------- ---------------------------------- | |Charlotte Bertrand/DC/USEPA/US@EPA |

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-------------------------------------------------------- | |Fw: Follow up From the June 21 Meeting |

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-------------------------------------------------------- |Keith W. Barnett

USEPA/OAQPS/SPPD/MMG Mail Code D243

- 02 Research Triangle Park, NC 27711
919

- 541

- 5605 barnett.keith@epa.gov

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-------------------------------------------------------- | |O’Hare, Andrew <AOhare@cement.org> |

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-------------------------------------------------------- | |Peter Tsirigotis/RTP/USEPA/US@EPA, Keith Barnett/RTP/USEPA/US@EPA |

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-------------------------------------------------------- | |Folow up From the June 21 Meeting |

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-------------------------------------------------------- |Peter and Keith,

Attached please find a letter summarizing PCA’s latest perspectives on the matters we discussed during the meeting on June 21 . There are three enclosures referenced in the cover letter. The first two are attached. I will forward the third, a large data file, to your attention separately.

· Enclosure A: Analysis of the THC Subcategories · Enclosur e B: MACT floor calculations for the proposed THC Subcategories · Enclosure C: A spreadsheet containing data used to support the floor calculations (addressing variability).

Please call with any questions.

Regards, Andy

Andrew T. O'Hare, CAE Vice President, Regulatory Affairs Portland Cement Association 500 New Jersey, Avenue, NW Washington, DC 20001 Phone: (202) 408

- 9494 Fax: (202) 408

- 0877 Cell: (202) 270

- 0094

e

- mail: aohare@ceme nt.org (See attached file: Peter Tsirigotis 6

- 29

- 10.pdf)(See attached file: THC Subcategroization Report 6

- 29

- 10.doc)(See attached file: THC MACT Floors Report 6

- 29

- 10.doc)500 New Jersey Avenue, NW

7 th Floor Washington, D.C. 20001 (202) 408

- 9494 June 2 9

, 2010

Peter Tsirigotis Director, Sector Policies and Programs Division Office of Air Quality and Planning and Standards U.S. Environmental Protection Agency Mail Code D205

- 01 Research Triangle Park, NC 27711

Mr. Keith Barnett Metals and Minerals Group (D243

- 02) Office of Air Quality Planning and Standards U.S. Environmental Protection Agency Research Triangle Park, NC 27711

RE: Follow

- up f

rom June 21 Meeting

Dear Mr. Tsirigotis and Mr. Barnett,

Thank you for meeting with the Portla nd Cement Association ( PCA ) on June 21, 2010, to discuss the results of PCA's and EPA's collabora tive efforts to collect and properly analyze data sufficient to support a n appropriate National Emissions Standard for Hazardous Air Pollutants (NESHAP) for th e portland cement sector. We welcomed the opportunity to present the data to you and discuss the outcomes the data presented. We address the following topic s herein:

Statistical methods for computing floors and accounting for variability;

Total hydrocar bon ( THC ) data analyses, subcategories, and associated MACT floors;

Mercury data analyses, subcategories, and associated floors; and

ISIS model improvements and summary of potential impacts on industry from a final NESHAP.

As we discussed, the data and appropriate analyses demonstrate that the proposed mercury and THC NESHAP standards should be revised. The table below summarizes PCA's recommendations for the emission limitations and associated subcategories, as appropriate, for the given pollutants.2

Parameter (Units) EPA Proposal PCA Recommendations

Existing Facilities New

Facilities Subcategory Existing Facilities New

Facilities

Mercury (lbs/million tons of feed) 26.2 8.4 99.9% 99.9%

Low limestone 76 30

High limestone (>250pp b ) 85%

Red. 85%

Red.

Total Hydrocarbons * (ppmv) 7 6 Major Non

Commingled (Low limestone) 36 12

Major Non

Commingled (high limestone) 204 68

Major Commingled 80 20

Area Work

Practice Work

Practice
Hydrochloric Acid (ppmv) 2.0 0.1 Site

- Specific Risk

- based Approach

Particulate Matter (lbs/ton of feed) 0.048 0.048 NA 0.092 0.062



### * Facilities would still have the alternative compliance option, where they would demonstrate compliance with a total organic HAP emission limit . The alternative HAP limits are presented in Enclosure B

.3

Statistical Methods

EPA should revise its statistical methods used in its proposed NESHAP to more properly calculate floors and account for variability. For THC, EPA has enough data to use the actual 99 th percen tile of 30

- day emissions because there are more than one hundred 30

- day averages reflected in the data set. In addition, EPA should use the same statistical equation used in the Boiler NESHAP, 75 Fed. Reg. 23020, with the variance weighted between source s (i.e., proportional variance). Variance for THCs should be adjusted for auto

- correlation and consideration of variance growth. Variance for mercury should consider intra

- quarry characteristics, fuel variability, and auto

- correlation. These methods wer e explained in the Boiler NESHAP rulemaking as the appropriate means to consider variability, but that rulemaking did not have sufficient data to perform these analyses. EPA should take advantage of the large data set presented now and perform the

correct analyses to set the MACT floors and account for variability. The PCA ’s recommendations, which are outlined above, were computed using the Boiler MACT equation, coupled with the above noted variability considerations.

THC Emission Limits

The table above shows the appropriate THC emission limits for new and existing sources applying the data set and appropriate statistical methods. While many possible subcategories were explored during the study, the data show a clear justification for subcategorizing po rtland cement facilities into commingled and non

- commingled kilns. In addition, PCA believes that a subcategory should be established to reflect the clear and undisputable impact of raw materials (limestone) organic content on raw materials. PCA also suggests that ar ea source kilns be subject to the existing work practice standards, as derived by EPA under the existing NESHAP (December 20, 2006, 71 Fed. Reg. 76518)

. Enclosure A describes the THC study database and explains how the subcategories were derived. Enclosu re B details how the THC MACT floors were calculated and how the "best performers" were identified. Enclosure C is a spreadsheet that was used in the development of the proposed floor limits.

The THC study revealed the importance and correctness of PCA 's contention that EPA should not simply make the new and existing source MACT standards for raw material dryers identical to the standards for the kilns . Instead, EPA should conduct a separate floor analyses for raw material dryers. See PCA Comments on the NESHAP from the Portland Cement Manufacturing Industry; Proposed Rule , pg. 83. In the proposed rulemaking, EPA treats the kiln and raw material dryers as two separate sources. However, EPA does not perform a separate floor analyses for the dyers and simply imposes the kiln standards on the dryers with no further analysis.

Th is approach is flawed because the two sources are not similar as recognized by
EPA in its proposal. First, t he oxygen levels in the dryers are well

- above 19% , where as the oxyg en content of the kiln exhaust gas is typically below 2% at the kiln exit. Second, the volume of gases drawn through kiln systems is 10 times greater than the volume passing through a raw material dryer . EPA should consider these two factors and the4

othe rs explained in PCA's comments and find that the dryers should have its own MACT floor analysis in order to establish an appropriate NESHAP. A potential way to remedy this would be to consider a work practice standard for these types of dryers, as suggest ed above for area sources.

This problem is highlighted in the use of the Lehigh Evansville facility in the THC database. The Evansville plant is somewhat unique in that a large amount of THC emissions are emitted from the dryers; therefore, the emission s from the kiln are extremely low. The emissions from the kiln at Evansville are not representative of the THC emissions from normal operating kilns . Considering this, using Evansville as a "best performing" source in a MACT floor analysis will cause EPA to set an unachievable THC standard for the sector ; or , a standard that would require the inst allation of regenerative thermal oxidizers ( RTO's ) at a large majority of kilns. As EPA has expressed on various occasions, RTOs are not a favored control devic e as the technology will impact demand for natural gas and significantly increase the carbon dioxide foot

- print of the industry. The THC CEMS used in the study did not calculate the THC emissions from the dryers, and thus the data collected from this plan t is incomplete. Based on these considerations, PCA has excluded the Evansville facility from the THC data, because the facility’s THC emissions are not representative of THC emissions from kilns.

HCl

As PCA has indicated on several occasions, the indus try continues to endorse the risk

- based exemption for this pollutant, adopted by EPA in the December 2006 changes to the portland cement NESHAP ( 71 Fed. Reg. 76518) . PCA has serious concerns about the efficacy of utilizing wet scrubbers for the purpose of controlling HCl emis sions, particularly for those plants located in arid areas of the U.S., where there is insufficient water resources to accommodate such devices.

Mercury Emissions Limits

The data suggests a clear subcategory to address high mercury content in limestone . PCA suggests that kilns using limestone with a mercury concentration greater than 250 ppb be subject to a beyond

- the

- floor standard of 85% reduction of mercury. All other kilns would have a MACT floor derived from a separate floor analysis. The table above shows the appropriate mercury standards applying the statistical methods discussed above.

ISIS Model Improvements

PCA and EPA contractors have been working together for some time to refine the ISIS analysis and models. PCA's revised ISIS predictio ns were presented to your staff at our meeting. Even under PCA's proposed THC and mercury emission limits, the ISIS model still predicts a substantial lo s s of U.S. production of cement. The loss would need to be replaced through imports to meet expected demand. As you are aware, it is likely5

that the countries that will provide the substitute supply of cement will not have the same environmental standards relating to hazardous air pollutants

, nor will they have greenhouse gases standards similar to those soon to be in place in the United States. Considering this, the reliance on imports from countries with less strict or even non

existent environmental regulations could result in an increase in global air pollution . We believe that a properly tailored rule can avoid the negative consequences.

Thank you again for your time on June 21 . We look forward to working with you

on these matters of great significance to the future of the U.S. cement industry. I may be reached at (202) 408

- 9494 to address a ny questions you may have regarding the perspectives of PCA.

Sincerely,

Andrew T. O’Hare Vice President

, Regulatory Affairs

Cc: Gina McCarthy Steve Fruh Steve Silvermani 

### Enclosure A

Portland Cement Kiln THC MACT Sub

- Categorization Analysis

Prepared for:

The Portland Cement Association 5420 Old Orchard Road Skokie, IL 60077

Prepared by:

AEMS, LLC 2443 North Quantico Street Arlington VA 22207

Rincon Ranch Co nsulting 2853 S. Quail Trail Tucson, AZ 85730

June 29 , 2010i Table of Contents

1. Introduction

................................ ................................ ................................ ................................ 1

2. Description of Study Database

................................ ................................ ................................ ... 2

3. Overview of the Analysis Methodology

................................ ................................ .................... 4

3

. 1 Data Preparation and Methodology

................................ ................................ ..................... 4
3

. 2 Relationship of Stack Emissions to Kiln Inputs

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

4. Evidence for Subcategorization

................................ ................................ ................................ . 6

4. 1 Subcategorization based on Technology: Commingling

................................ .................... 7
4. 2 Subcategorization based on Limestone Characteristics

................................ ...................... 9

5. Conclusions

................................ ................................ ................................ .............................. 11ii List of Tables

Table 1: Summary of CEMS and Raw Materials Data Used in Analysis

................................ ...... 3

Table 2: Statistical Test of Commingling Effect versus Kiln Feed Outgassing

............................ 9

Table 3: Statistical Test of Commingling Effect versus Lime stone Outgassing

.......................... 11iii List of Figures

Figure 1: THC Stack Emissions versus Kiln Feed Outgassing

................................ ...................... 6

Figure 2 : Relationship of Kiln Feed to Limestone Outgassing

................................ ...................... 6

Figure 3 : THC Stack Emissions versus Kiln Feed Outgassing: Kilns without Commingling

....... 8

Figure 4 : THC Stack Emissions versus Kiln Feed Outgassing: Kil n s with Commingling

............ 8

Figure 5 : THC Stack Emissions versus Limeston e Outgassing: Kilns without Commingling

.... 10

Figure 6 : THC Stack Emissions versus Limeston e Outgassing: Kilns with Commingling

......... 101

1. Intro duction

In comments to the EPA on the MACT standards applicable to Portland cement facilities

, the Portland Cement Association (PCA) noted that some cement kilns have inherently high THC emissions for reasons that were not fully understood. The high emiss ions could be related to the kiln type, the composition of the limestone and other raw materials , or the inclusion of raw mill
or coal mill exhaust in the main kiln exhaust

.
Because the then

- existing data on THC emissions and raw material organic content w ere insufficient to resolve these issues , PCA initiated an effort to collect additional data to better
understand these issues and to determine whether subcategories should be established for the
THC limit under MACT . The data gathering focused on process design distinctions and the potential for inherently high THC emissions due to raw material characteristics

. Thirty six kilns were asked to participate in a study in which THC CEMS were collected for a period of 90 days (3 successive 30

- day periods) and samples of raw materials were collected and analyzed for THC release upon heating, referred to here as outgassing, for each of the three months. The study design involved a stratified sample of the US kiln population divided among seven cells based on

tec hnology and anticipated THC emissions levels.

In the review of existing data, PCA noted that the true variability in THC emissions was not captured in short term data. That is, the variability in data collected for one year was consistently higher than wh at was found in a shapshot of 30 days of data. The original design called for data gathering for six months. After discussions with EPA and in recognition of their rulemaking schedule, the project design was to collect at least 90 days of data for each u nit in the project. In m ost instances, THC CEMS were not in place and they had to be leased or purchased
and installed and calibrated by the participating kiln staff or contractor s . Conduct of the study
has been adversely impacted by the adverse economic climate that has led to very low demand
for cement

, extended outages at a number of the kilns

, and shutdowns of some planned participants. These factors, plus the unavoidable difficulties of bringing newly installed equipment into routine operation, have precluded PCA from collecting the desired data ( for 90 days of operations) as quickly as originally planned.

This report has been prepared based on a substantial, but still interim, data set before the study could be completed because of the urgent need e xpressed by EPA to report both data and analysis results. This report is based on the THC CEMS and raw materials testing data that were completed and submitted by participants as of June 3, 2010. These data have been compiled into databases dated June 8, 2010 that will be submitted to EPA by PCA.

The report is divided into four sections that follow:

 Description of the study database

 Overview of the analysis methodology

 Evidence supporting Sub

- Categorization in the MACT standards

 Conclusions2

2. Description of the Study Database

As of the June 8, 2010 database, 26 of the kilns participating in the study have submitted CEMS emissions data covering periods ranging from 30 to 90 days of operation. These kilns comprise

72 percent of the kilns originally recruite d. In this analysis, we have excluded data from two reporting kilns (Lehigh Evansville and Lafarge Tulsa) because the THC CEMS did not measure
their full emissions. Specifically the emissions of THC from the grinding and drying of the kiln
feed were omitt ed due to the configuration of the vents from those operations. This action is
consistent with a recent discussion of the data with EPA where it was determined that the data are not representative of the kilns’ true emissions.

For 23 of the 26 kilns for which complete CEMS data are available , matching results on raw materials outgassing testing are available for at least one month. In total, the database used in this analysis contains 38 data points, each consisting of the THC CEMS stack emissions

avera ged for a 30

- day period matched to test results on THC outgassing for the same period.
Table 1 summarizes the data used in this analysis

. The study design was present ed to EPA and approved in principle by EPA before the study
started. The study design st ratifies kilns into seven cells based on process design and an a priori assessment of THC emission levels (Low and High) 1 . Process design was categorized according to kiln type (long kiln or preheater / preheater

- precalciner), presence of an inline raw mi ll, and commingling of the raw or coal mill exhaust and the main kiln exhaust in the same stack where
the THC CEMS was located 2 . The a priori assessment of emission levels was used to achieve a sufficient representation of kiln types that may have high em issions. The study cells found in the
table are defined as follows

 Cell 1

– Long wet or dry kilns (no in

- line raw mill and not commingled). Low THC emissions ( a priori )

 Cell 2

– Kilns as in Cell 1, but with an a priori assessment of High THC emissions

 Ce ll 3

– Preheater and preheaters/precalciners (PH/PH

- PC) kilns with in

- line raw mill s , kiln alone ( not commingled ) . Low THC emissions ( a priori )

 Cell 4

– Kilns as in Cell 3, but with an a priori assessment of High THC emissions

 Cell 5

– Preheater and prehe aters/precalciners (PH/PH

- PC) kilns with in

- line raw mill s , with commingling of raw/ coal mill and main kiln to same stack. Low THC emissions ( a priori )

 Cell 6

– Kilns as in Cell 5, but with an a priori assessment of High THC emissions

 Cell 7

– Preheater a nd preheaters/precalciners (PH/PH

- PC) kilns without in

- line raw mill s , kiln alone ( not commingled ) . Without respect to the a priori assessment of THC emissions.

1 The original study design had 12 cells but a number of the cells either had no identified units or very few identified units and they were either dropped or consolidated.

2 In such commingled units, it is not possible to monitor separately the kiln exhaust versus the mill exhaust and in
some instances kiln exhaus t passes through the mill as well.3 Table 1. Summary of CEMS and Raw Materials Data Used in Analysis

CEMS Data Raw Materials

Sampling Cell No. Kiln Period THC record

1 Holcim Trident 3 x 30d 82d 3 x 30d

Ash Grove Mid l othian 2 x 30d 58d n/a Cemex Wampaum Lafarge Joppa K2 3 x 30d 71d 2 x 30d Lafarge Revena 1 x 30d 30d 1 x 30d

2 Holcim Ada 2 x 30d 58 d 2 x 30d

Lafa rge Seattle 2 x 30d 49 d 1 x 30d Buzzi Pryor

3 Titan Roanoke 3 x 30d 88 d 3 x 30d

Suwannee Bradford 1 x 30d 31 d 1 x 30d

Cemex Miami 2 x 30d 55 d 2 x 30d

Alamo Cement 3 x 30d 81 d 2 x 30d

Cemex Fairborn 2 x 30d 38 d 2 x 30d Buzzi Chattanooga

CalPortland Mohave 1 x 30d 31d n/a

Cemex Clinchfield 1 x 30d 19d 1 x 30d Essroc Speed 2 x 30d 59d n/a GCC Rapid City Lehigh Redding

4 Cemex Demopolos 1 x 30d 25 d 1 x 30d Lehigh Mason City

TXI Midlothian K5

5 National Ragland 1 x 30d 20 d 1 x 30d Lafarge Sugar Creek 2 x 30d 55 d 1 x 30d

Ash Grove Durkee 2 x 30d 55 d 2 x 30d Lehigh Union Bridge 2 x 30d 55d 2 x 30d

Titan Penns uc o 1 x 30d 27d 1 x 30d

6 Holcim Midlothian 3 x 30d 81 d 2 x 30d

Holcim Portland 1 x 30d 24 d 1 x 30d

Holcim Devil's Slide 2 x 30d 58 d 2 x 30d Giant Dragon Thomaston

7 Holcim Theodore 1 x 30d 30 d 1 x 30d

1 x 15d 1 3 d 1 x 30d Lafarge Whitehall 2 x 30d 45 d 2 x 30d

Cemex Knoxville 2 x 30d 25 d 1 x 30d

For purposes of this report, the term “commin gled kiln” refers to kilns in study cells 5 and 6 combined, while “non

- commingled kiln” refers to kilns in study cells 1

- 4 and cell 7 combined.
The a priori assessments of low versus high THC emissions were used only for purposes of recruiting kilns to pa rticipate in the study to improve the chances that the study would be able to adequately characterize the full range of emissions. Where this report uses the terms low or high4

in regard to THC emissions or to materials outgassing of THC, it refers to actu al measured THC emission or THC outgassing and not to the a priori assessment described above and indicated in
Table 1. Samples of kiln feed and limestone were obtained daily

. After thirty days of operation with the THC CEMS in service and samples being taken

, a 30 day composite sample was created
for both the kiln feed and the limestone. These samples were shipped to the FLSmidth laboratory for outgassing testing. The raw material testing results used are the measured THC outgassing values for kiln fee d and limestone individually. Testing results have been matched by time period to the average stack emission levels recorded by the THC CEMS.

3. Overview of the Analysis Methodology

3.1 Data Preparation and Methodology

The analysis was conducted at the l evel of monthly (30

- day) average THC CEMS emissions with matched outgassing measurements for the associated composite samples of kiln feed and
limestone. Each month consists of approximately a 30

- day period of operation, but the days are not necessarily c onsecutive. THC CEMS emissions are expressed on a basis of ppm of propane, dry, at 7% O 2 content , while raw materials outgassing is expressed in units of mg THC per kg
kiln feed or limestone

.
The THC CEMS emission data are based on reported hourly emissio ns that have been screened to eliminate hours with missing data, invalid data (as coded by the kiln operator) and hours when the kiln is not in operation. While PCA has taken the position that kiln startup, shutdown and
malfunctions should not be included in the period covered by any THC limit, the hours involving startup, shutdown, and malfunction have been retained in the record to be consistent with EPA’s proposal to include such hours when determining compliance with the standard.

Daily average THC emi ssions are based on the operating hours surviving these screens. Because not all hours are reported for all days, due to the kiln being down or because of failures in the

THC or O 2 monitors, a decision was made to classify any day having at least 18 repor ted hours as being “complete”. Average emissions for each 30

- day period are defined as the average of the emissions reported for complete calendar days within the period.

The THC CEMS data were subject to quality assurance / quality control review by the kiln operators, and questions regarding the data were referred to them. EPA should note that many kilns had problems in computing a valid measure of O 2 - adjusted THC emissions when the O 2 level began to approach ambient levels (20.9 percent). There were a number of instances during the study in which O 2 concentrations reached levels approaching ambient due to leaks in the O 2 sensor system, because the doors of the kiln were open, or for other reasons. Such instances can result in the computation of large correction factors using EPA’s approved formula, with correspondingly high THC emissions that are not representative of actual kiln performance. Every effort has been made in preparing the study data to identify such problems and to
eliminate hours where the corrected emission values are invalid or unrepresentative.

The correction formula adopted by EPA is based on the assumption that the measured THC concentration is a result of stack gas that has been diluted by ambient air to reach the measured5

O 2 conce ntration. The correction formula returns an infinite value when the measured O 2 is 20.9 percent, and it can yield very large correction factors whenever the O 2 concentration is near the ambient value. In fact, the THC concentration on a dry basis at 7% O 2 becomes increasingly hard to determine reliability as the O 2 concentration approaches ambient. This will be a continuing problem for kilns operating under the MACT standards if the use of THC CEMS is
retained in the final rule , and we strongly recommend that EPA address and remedy this measurement problem in its final rule.

The statistical analysis conducted for this report consists of both graphical presentation of the data to identify the major relationships between stack emissions and kiln type, kiln feed and limestone and the conduct of conventional regression analysis using Ordinary Least Squares (OLS). Regression analysis was used to test for the presence of technology or raw materials factors influencing THC stack emissions that are the logical ba sis for subcategorization of
cement kilns under MACT.

3.2 Relationship of Stack Emissions to Kiln Inputs

Figure 1 shows the overall relationship between THC stack emissions and kiln feed outgassing, distinguishing kilns with low and high limestone THC cont ent based on the outgassing test results. Kilns with kiln feed or limestone outgassing results less than the median of 29 mg/kg have been classified as low THC limestone, and kilns with kiln feed or limestone outgassing
results at or above the median of 2 9 mg/kg have been classified as high THC limestone.

There is a clear relationship between stack emissions and outgassing of kiln feed, but there is considerable scatter among the data points, leading to a relatively low overall R 2 (R 2 ~0.35).
THC stack emi ssions are seen to be approximately proportional to the THC outgassing of total kiln feed, and kilns with both low and high THC materials appear to follow a similar relationship overall. The scatter reflects a variety of kiln

- specific factors that lead to variations above and
below the trend line . From kilns with multiple months of data , there appear to be consistent differences among kilns in the ratio of stack emissions to kiln feed outgassing. Although the THC outgassing characteristics of kiln feed an d other raw materials are the primary determinants of THC stack emissions, there are other kiln

- specific differences present in the data.

Figure 2 shows that the outgassing of the limestone raw materials is a major determinant of kiln feed outgassing due b oth to the proportion of limestone in raw materials and the extent of its outgassing. The relationship is highly linear with little scatter except for two of the data points. Where we find that kiln feed is a determinant of stack emissions, we will also find that limestone is an important determinant. This is important, both because limestone characteristics are a factor beyond the control of the kiln operator due to location of kilns at or near their limestone
source and the characteristics of the limes tone will vary over time as new portions of the quarry
are mined.6 Figure 1 . THC Stack Emissions versus Kiln Feed Outgassing

Figure 2 . Relationship of Kiln Feed to Limestone Outgassing

4. Evidence Suppo rting Subcategorization

A formal statistical analysis was conducted to determine the relationship between kiln feed and stack THC emissions and the roles of kiln technology and outgassing characteristics of raw materials in that relationship. The analysi s establishes that both kiln feed and limestone outgassing are clear and statistically significant determinants of stack emissions. The analysis further establishes that the emissions performance of kilns differs for commingled kilns versus

all other typ es, once t he effects of outgassing by kiln feed are controlled for. In this context, “commingling” means that a raw mill or coal mill is vented to the same stack as the primary kiln.

Other tests were conducted during the formal statistical analysis. Once commingling and kiln
feed or limestone outgassing are accounted for, we do not find evidence in this limited data set of7

a significant distinction in emission performance related to kiln type

– i.e., long kilns versus PH/PH

- PC kilns. We see that stack emi ssions are slightly higher (~2 ppm) for kilns that are equipped with an inline raw mill, but the estimated effect is not statistically significant. How emissions are affected by in

- line raw mill operation var ies by kiln and the characteristics of the

ma terial fed to the mill

.
4.1 Subcategorization based on Technology: Commingling

A number of statistical analys e s w ere conducted to test for the presence of differences in emissions performance as a function of kiln technology. The clear, and statistically , significant difference among kiln types is related to commingling of the raw mill or coal mill and main kiln to the same stack. Commingled kilns have higher emissions at any given value for kiln feed outgassing, and the slope of emissions with respect t o kiln feed is somewhat lower.

Figure 3 below shows the trend of stack emissions with kiln feed for non

- commingled kilns 3

. Without commingling, the performance line passes through (or very close to) the origin

– as kiln feed outgassing approaches zero, measured stack emissions also approaches zero without clear
evidence of a non

- zero intercept. This is the result that would be expected for kilns that do not vent coal mill grinding gasses directly to the stack, because THC emissions generation is
unders tood to be primarily related to the outgassing of raw materials rather than emissions formed in the combustion process.

Figure 4 shows the relationship between stack emissions and total kiln feed outgassing for commingled kilns. The intercept is close to 20 ppm, while the emissions slope with respect to kiln feed appears to be somewhat lower than for non

- commingled kilns. The intercept represents the increased emissions from venting mill s to the main stack, while the lower slope is consistent with coal gr inding contributing to stack emissions in addition to contributions from kiln feed or limestone outgassing

. The formal test for the statistical significance of these results is given in Table 2 based on fitting a conventional regression model. The model f orm tests a dummy variable representing the presence of commingling (0=not commingled versus 1=commingled) against a base model consisting of an intercept and slope for emissions versus kiln feed outgassing:

E = A + B * Outgassing kiln feed + C * dC ommingling (Eq 1)

The results for the emissions slope B demonstrate that outgassing by kiln feed is a strong and statistically significant determinant of stack emissions. THC stack emissions increase by 0.35 ppm for every 1 mg/kg increase in the measu red outgassing of kiln feed.

3 The straight lines shown in this and subsequent figures are simple trendlines developed to display the major trends in the data. They do not reflect the results of a formal statistical analysis, which are reported onl y in table form.8

The commingling term C is statistically significant at the p=0.02 level, meaning that there is only one chance in 50 of obtaining an effect this large if commingling did not truly have an effect on stack emissions. For comming led units, stack emissions at zero kiln feed outgassing (the effective intercept) is estimated (by the sum of the A and C coefficients) to be 19 ppm and is statistically significant.

Figure 3 . THC Stack Emissions versus Kiln Fee d Outgassing: Kilns without Commingling

Figure 4 . THC Stack Emissions versus Kiln Feed Outgassing: Commingled Kilns9 Table 2. Statistical Test of Commingling Effect versus Kiln Feed Outgassing

R 2 = 0. 4 3 F = 13.7

Parameter C oefficient Value Standard

Error Prob>|t|

A Intercept 6.5 4. 5 0.1 6

B Kiln Feed Outgassing 0.35 0.07 0.00

C Commingling 1 2 .8 5. 2 0.02

The overall intercept term A in this model, which represents stack emissions of non

- commingled
units at zero kiln feed outgassing, is estimated to be 6.5 ppm but is not statistically significant. The data suggest that the non

- zero intercept results from the leverage of data points at high values for kiln feed outgassing on the linear model. A quadratic model in kiln feed reduces the estimated overall intercept, but it does not give a statistically significant quadratic term. The trends in the data at low outgassing values suggest that the overall intercept is small or zero for

non

- commingled kilns.

Other models were tested to determine whether there was a difference in emissions slope for commingled units. The results indicate that stack emissions from commingled units increase at a lower rate as kiln feed outgassing increases. The result is consistent with wh at is seen in the figures above, and with the fact that outgassing during coal grinding contributes to stack emissions, but the term did not prove to be statistically significant. The additional models tested do not add to the finding that commingling of the raw or coal mill and main kiln to the same
stack increases stack THC emissions compared to non

- commingled units.

4.2 Subcategorization based on Limestone Characteristics

A comparable analysis was conducted of the relationship between THC stack emissio ns and the outgassing of the limestone feed, which is shown in Figures 4 and 5 on the following page. Limestone outgassing is a major determinant of outgassing by total kiln feed, and there are clear relationships between stack emissions and limestone outg assing in both categories of kilns.

As for kiln feed, an analysis was conducted to demonstrate that outgassing of limestone feed is a statistically significant determinant of THC stack emissions and to confirm that commingled
kilns have distinctive emissio ns performance when viewed on this basis. The results of this analysis are summarized in Table 3 based on the following model:

E = A + B * Outgassing limestone + C * dCommingling (Eq 2)

Here, we find a statistically significant intercept and slop e for the stack emissions effect of limestone outgassing. The term representing the effect of commingl ing is statistically significant10

at the p=0. 05 level. That the intercept is larger and the slope smaller, compared to the kiln feed model presented abov e, is because this model does not directly represent the emissions effects of the other constituents of kiln feed. Its primary contribution to the analysis is to demonstrate that outgassing by the limestone raw material is an important and statistically s ignificant determinant
of THC stack emissions

.

Figure 5

. THC Stack Emissions versus Limestone Outgassing: Kilns without Commingling

Figure 6 . THC Stack Emissions versus Limestone Outgassing: Comming led Kilns11 Table 3. Statistical Test of Commingling Effect versus Limestone Outgassing
R 2 = 0.27 F = 6. 7

Parameter Coefficient Value Standard

Error Prob>|t|

A Intercept 13.9 4. 4 0.00

B Limestone Outgassing 0.23 0.07 0.00

C Comminglin g 11.8 5. 8 0.0 5

5. Conclusions

The statistical analysis demonstrates that the emissions performance of commingled kilns is distinctively different than the performance of non

- commingled kilns, after controlling for the effects of outgassing by kiln feed and /or limestone. This result is consistent with engineering expectations that kiln emissions are primarily related to THC outgassing from the materials fed
to the kiln and the direct venting of the raw mill or coal mill to the main stack in commingled
units changes the characteristics of the overall emissions

. Commingled kilns face distinctively different problems in controlling emissions compared to other kilns, and the THC statistical evidence is sufficiently strong to propose separate MACT subcategories for kilns without commingling versus kilns with commingling.

The statistical analysis also demonstrates the outgassing by the limestone raw material is the primary determinant of kiln feed outgassing and has a statistically significant effect on THC
stack emissions. The characteristics of the limestone material are a factor beyond the control of the kiln operator due to location and will vary over time as new portions of the quarry are mined. For this reason, kilns located at quarries where the limestone material outgases large amounts of THC are disadvantaged by their raw materials compared to kilns located at quarries with low amounts of THC outgassing.

T here is a clear and indisputable impact of limestone organic content on THC emissions, and a recogni tion of this in the floors will be required in order to create a valid standard. Such factors that are beyond the control of a unit are appropriate bas e s for developing subcategor ies

.

# # #E nclosure B

ALTERNATIVE MACT FLOORS

FOR

PORTLAND CEMENT KILNS

Prepared by :

The Portland Cement Association 5420 Old Orchard Road Skokie, IL 60077

June 2 9 , 2010i Table of Contents

1. Introduction

................................ ................................ ................................ ................................ 1

2. Summary of THC Emissions Database

................................ ................................ ...................... 2

3. Treatment of Variability in the MACT Floor

................................ ................................ ............ 2

4. Methodology for MACT Floor Determinat ion

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

4.1 EPA Boiler MACT Equation

................................ ................................ .............................. 5
4. 2 Estimation of Long

- term Variability in THC Emissions

................................ ................... 7
4. 3 Computation of MACT Floors

................................ ................................ .......................... 9

5. P roposed MACT Floors for Sub

- Categories

................................ ................................ ............ 10

5. 1 Det ermination of Best Performers

................................ ................................ ..................... 11
5. 2 MACT Floors for Proposed Sub

- Categories

................................ ................................ ...... 1 2

5.3 Equivalent Alternative Emission Limit s for Organic HAP Species

................................ .. 1 4

Appendix A : A djustments to Improve the Representation of Long

- term Emissions Variability

A.1 Growth Curve Analysis

................................ ................................ ................................ .. A

- 1

A .2 First

- Order Serial Correlation

................................ ................................ ........................ A

- 2

Appendix B : Calculati ons Supporting Proposed MACT Floors

................................ ................ B

- 1ii List of Tables

Table 1: THC CEMS Data Used in Developing MACT Floors

................................ .................... 3

Table 2: Determination of Size of Best Perform ing Poo l for Proposed Sub

- Categories

............. 12

Table 3: Alternative MACT Floors for THC: Major Non

- Commingled Kilns

........................... 13

Table 4 : Alternative MACT Floors for THC: Major Non

- Commingled Kilns with High Organics
Limestone

................................ ................................ ................................ ................................ ...... 13

Table 5 : Alternative MACT Floors for THC: Major Commingled Kilns

................................ ... 14

Table 6 : Alternative MACT Floors for Major Non

- Commingled Kil ns: Organic HAP Limit s

.. 1 5

Table 7 : Alternative MACT Floors for Major Non

- Commingled Kilns with High Organics Limestone: Organic HAP Limits

................................ ................................ ................................ . 15

Table 8 : Alternative MACT Floors for Major Commingled Kilns: Organic HAP Limit s

.......... 1 5

Appendix A

Table A

- 1 : Firs t Order Serial Correlation r 1 of 30

- day Average Emissions for Best Performing
Kilns

................................ ................................ ................................ ................................ ........... A

- 3

Appendix B

Table B

- 1 : Alternative MACT Floors for THC: Major Non

- Commingled Kilns

..................... B

- 2

Table B

- 2 : Alternative MACT Floors for THC: Major Commingled Kilns

............................. B

- 3iii List o f Figures

Figure 1: Example of Short

- term Data on THC Emissions

................................ ............................ 3

Figure 2 : Definition of High THC Limestone Subcategory for Major Non

- Commingled Kilns

. 11

Appendix A

Figure A

- 1 : Growth of 30

- day Average Emissions Variability for Best Performing Kilns

....... A

- 31

1. Introduction

Since EPA’s proposed MACT rule for cement kilns was published in 2009, t he Portland Cement Association (PCA) has conducted a series of studies and analyses to provide an improved basis for estimating long

- term emissions variability of cement kilns and the emissions limitations that should apply . Th is work has include d the compilation of data from industry sources to provide
extended data series of THC emissions on the kilns in EPA’s docket database. PCA has also

conducted a THC Subcategoriz ation Study

, in which THC CEMS emissions data were collected along with samples of raw materials used by participating kilns to better understand differences in emissions performance among kilns . The results of that study are documented in a related

repor t 1

.
R elevant r egulatory actions have taken place as well. EPA has recently published proposed rules regulating hazardous air pollutants from other sources

– one s for industrial, commercial, and institutional boilers and process heaters and another for c om mercial and i ndustrial s olid w aste
i ncineration u nits. In these proposed rules, EPA proposes the use of alternative equation s for calculating MACT floors. The equation proposed in the boiler MACT rule (termed here the Boiler MACT equation) takes a broade r and more appropriate view of how variability should be accounted for in determining the emission limitations that the best performing unit s can meet

, tha n the statistical formula EPA has recently indicated will be used for cement kilns.

This report prese nts the results of an analysis of alternative MACT floors for cement kilns that takes account of the newly acquired data on THC emissions and the changes in the statistical methodology for determining the MACT floors that EPA has introduced in the proposed boiler MACT rule. The report is divided into four sections:

 Summary of the THC emissions data base

 Treatment of Variability in the MACT Floor

 Methodology for MACT Floor Determination

 Proposed MACT Floors for Sub

- Categories

Appendices A and B are included to document the variability adjustments used in the analysis
and to summarize the calculation s supporting the alternative MACT floors.

1 Cement Kiln THC Sub

- Categorization Analysis , prepared by AEM, LLC and Rincon Ranch Consulting for the Portland Cement Association. June 22, 2010.2

2. Summary of THC Emissions Database

PCA has submitted its latest data base of THC emissions under separate cover to EPA. The database developed during the THC Subcategorization Study is contained in the Excel spreadsheet THC Study CEMS Database 2010.06.11.xls . A consolidation of all THC CEMS data compiled by PCA is contained in the Excel spreadsheet THC Combined Data

2010.0 6.1 3 .xls

.
Table 1 lists t he kilns for which THC CEMS emissions data are available and were used in the development of MACT floors

. The table excludes data on Area kilns, which were not used in developing MACT floors. EPA is not required to set a MACT floor for kilns associated with area sources, and PCA believes that EPA should establish an emissions limitation for them based on work practices. For major kilns, THC emissions data covering a nominal 30

- day period were
available for 1 0 major kilns in th e database compiled by EPA. PCA collected additional data on
THC emissions for 9 of the 1 0 major kilns, with the shortest of the data series exceeding 300 days when both EPA and PCA data are taken into account. The THC Sub

- Categorization Study
added data on 20 major kilns for periods ranging from 30 days up to 90 days

. In this, data from
the Lehigh Evansville and Mason City K2 and K3 kilns have been excluded because the THC
CEMS did not measure the full emissions. Specifically the emissions of THC from the grinding and drying of the kiln feed were omitted due to the configuration of the vents from those operations. Th is exclusion is consistent with a recent discussion of the data with EPA where it was determined that the data are not representative of t he kilns’ true emissions.

3. Treatment of Variability in the MACT Floor

A proper treatment of emissions variability is a critical component in developing the MACT floor, because the applicable statute refers to the emissions limitation that best performing un its (i.e., the ones used to set the floor) can meet in practice under the worst reasonably foreseeable operating conditions. Adequate data to characterize emissions variability over the long term and a proper treatment of variability in the statistical fo rmulas are required if the floors are to represent emissions limitations that the best performers can meet in actual operating practice. An example of the risk associated with relying on short term data is shown in Figure 1, which is
based on data collect ed in the THC study. If EPA had collected and used emissions data during the middle 30 days of the record, the kiln would likely be classified among the best performers. The classification would be proved wrong, however, by additional emissions data. If 30 days of emissions data can be insufficient for the purpose of identifying best performers, then 30 days of emissions data are clearly insufficient to characterize the variability in emissions that will occur in actual operations over the many years tha t the standard must be met.3 Table 1. THC CEMS Data Used in Developing MACT Floors

Kiln Name Area/Major Source Kilns

Represented EPA

Docket Database PCA Data

Compilation THC Sub

Categorization Study
Totals 24 1 0 9 2 0 CalPortland Mojave Major 1 √

Cemex Clinchfield Major 1 √
Cemex Demopolis Major 1 √

Cemex Fairborn Major 1 √

Cemex Knoxville Major 1 √

Cemex Miami Major 1 √
Essroc Speed Major 1 √

Holcim Ada Major 1 √

Holcim Devils Slide Major 1 √ √ √

Holcim Dun dee K1 K2 Major 1 √ √

Holcim Midlothian K1 Major 1 √ √

Holcim Midlothian K2 Major 1 √ √ √

Holcim Portland Major 1 √ √ √

Holcim Theodore Major 1 √ √ √
Lafarge Joppa K2 Major 1 √
Lafarge Ravena Major 2 √
Lafarge Sugar Creek Major 1 √
Lafarge Whitehall Major 1 √
Lehigh Union Bridge Major 1 √ √ √
National Ragland Major 1 √

Suwannee Branford Major 1 √ √ √

Titan Pennsuco Major 1 √ √

TXI Midlothian Major 1 √ √

Figure 1 . Example of Sh ort

- term Data on THC Emissions4

In analyzing the extended data series for 12 of the kilns, PCA noted that emissions variability
increase d as the length of the data record was extended. This finding is consistent with the
realization that many sources of em issions variability exist, but that not all sources may be in
effect at any given time. For example, the product mix may change seasonally, the characteristics of coal and other fuels will change from time to time as sources or suppliers change, and the c haracteristics of the limestone change on a long

- term basis as quarry mining progresses. One is unlikely to see the effects of most or all of the sources of variability unless the available record of THC emissions extends to one calendar year or more.

PCA compiled extended data series where they were available to enable an improved
characterization of their emissions variability . In the absence of extended data, it is still possible
to correct for t he deficiencies of the available short

- term data by analy tical means. In the proposed boiler MACT rule , EPA proposes to regulate CO emissions as a surrogate for hazardous air pollutants

, and EPA considered whether its available test data taken at near

- full load conditions adequately characterized CO emissions

, given that emissions can fluctuate with changes in the operating rate of a boiler. EPA collected additional information on hourly emissions and load data on six boilers that were among the best performers to address this

concern 2 . EPA concluded that :

“ CO (as a surrogate for non

- dioxin organic HAP) from best performing units did not vary much when such unit is operated at below design capacity. Therefore,

... we are proposing to add no additional variability factor to account for load variability to the
MA CT floor 99 percent UPL values determined from the stack test data for CO emissions. ” (p. 96)

Although EPA chose not to add variability in this case at the time of rule proposal , its consideration of this action clearly indicates that the variability obse rved in the data available on best performing units can be adjusted to better reflect the operating conditions under which compliance decisions will be made when the adjustment is needed to adequately characterize variability and can be developed using dat a from best performing
units

. As demonstrated here , an adjustment of this kind is necessary to adequately characterize the emissions variability of cement kilns under actual operating conditions.

Given this precedent, the extended data series for 4 best p erforming cement kilns has been analyzed to develop a “growth curve

. ” The growth curve is then used to adjust the observed variability in THC emissions in short

- term data series to the equivalent variability
that would be observed in a data series of dail y emissions covering one full calendar year. The development of the growth curve is documented in Appendix A and its application in the calculation of MACT floors is documented in the following discussion of the statistical methodology.

2 National Emission Standards for Hazardous Air Pollutants for Major Sources: Industrial, Commercial, and
Institutional Boilers and Process Heaters

. 40 CFR Part 63 . U.S. Environmental Protection Agency. pp 95

- 96.5

4. Methodology for MA CT Floor Determination

In its comments filed with EPA, PCA has noted problems with the statistical formula in the proposed MACT rule for cement kilns published in 2009 . In response to these and other comments, EPA has since indicated that it has modified its UPL f ormula and more recently has issued a document detailing the derivation of the currently proposed UPL formula for cement
kilns 3

. Among the problems with the most recent cement kiln formula are that the computed
UPL values fall far short of the 99 th percentile values actually observed in emissions data and that it excludes consideration of the variability of emission levels among best performing units. The data on the best performing units are used in setting the floor as representative s of all be st performing units in the US population. When the pool is small in size, its ability to accurately characterize the best performing US population is reduced, and at any given size its accuracy is
further reduced when the emission levels vary widely among the best performers. The UPL formula proposed by EPA for cement kilns excludes all consideration of such forms of uncertainty from the floor calculations.

4.1 EPA Boiler MACT Equation

In the proposed MACT rule for major boiler sources, EPA takes a differ ent, broader, and more appropriate view of variability than it has in the proposed cement kiln rule , and it proposes a
different UPL formula consistent with that view. In th e proposed boiler MACT rule, EPA recognizes that the data for units comprising the pool of best performers are actually a sample representing the population of best performers in the industry. The technical document 4
describing the boiler MACT calculations in more detail states that “... the data used to calculate the MACT floor represen ts a sample of the population of affected units ...” ; the discussion in the proposed rule is consistent with this view, if not explicitly stated. That the pool units are a sampl e can be seen clearly in the fact that the selection of units as best performers for the pool can, and does, change as additional emissions data become available.

The importance of this newly

- articulated view is that all sources of variability present in the emissions data are accounted for in setting the floor, including the day

- to

- d ay variability of
emissions within units and the unit

- to

- unit variability of emissions across units in the pool. This is embodied in the following formula 5 , which is a text book application of computing prediction limits for a population based on a sample

.

3 Constructing the UPL for the average of “m” new test runs

. Document UPLequation_May10_2010Breda.doc provided by EPA to PCA.

4 MACT Floor Analysis (2010) for the Industrial, Commercial, and Institutional Boilers and Process Heaters, National Emission Standards for Hazardous Air Pollutants

– Major Sources. Prepared by Amanda Singleton, ERG for Jim Eddin ger, USA EPA. April 2010.

5 National Emission Standards for Hazardous Air Pollutants for Major Sources: Industrial, Commercial, and
Institutional Boilers and Process Heaters

. 40 CFR Part 63 . U.S. Environmental Protection Agency. pp 76

- 80.6 Eq. 1

Where:

s = the sample standard deviation n = the number of test runs (meaning total emissions tests in the pool ) m = the number of test runs in the compliance averages

The variance s 2 includes contributions from both unit

- to

- unit variab ility (between sources) and

test

- to

- test variability (within source) in the available emissions data. The term s 2 is found inside the square root, but an equivalent formula can be written with the standard deviation s positioned outside the square root in stead.

Treating the pool as a sample of the population of best

- performers in the industry is both a sensible interpretation of the statutory language and a correct assessment of what the emissions data on best performers actually are. If EPA could draw da ta on another sample of units from the industry, the pool of best performers would consist of different units than we have now, and we would obtain a different estimate of the mean emission level for the best performers. The wider the range in emission le vels among the best performers, the greater is our uncertainty in estimating the mean emission of the population of best

- performers in the industry using any one sample. This sampling varia bility is combined with the effect of having a finite number of te sts in the pool, resulting in a measure of the uncertainty variance of the computed mean emissions
level equal to s 2 /n (the first term inside the square root).

The same variance s 2 is assumed to apply to the average best performer when it is later subject to m test runs to determine its compliance with the floor. The average of those tests will have a
variance of s 2 /m, which must be added to the uncertainty variance in the mean to define the emissions limit that the average best performer can meet 99% of t he time. The term t(0.99,n

- 1)
is the Student’s t

- statistic that translates the total variance s 2 into a specific position on the
distribution of the mean

, depending on the desired percentile (0.99) and sample size (n

- 1).

EPA’s boiler MACT formula captures the full range of variation that is present in the pool data

– including differences in the design of the units, differences in the raw materials and fuels used by the units, and differences in operational circumstances at the time the data were collected

– and it does so without regard to whether the variability is realized within sources or between sources. This form of the MACT formula will yield a more correct and appropriate floor value than the formula proposed for the cement kiln rule, which arbitr arily exclud es an important source of variability between units. The proposed MACT rule for major boilers also allows for the incorporation of additional data to estimate the long

- term variation of emissions when that can be done using data for best perfo rming units in the pool. This precedent supports the position that the cement industry has taken on the need to incorporate better estimates of the long

- term variation in emissions, and it has been used in the development of the alternative MACT floors
fo r THC presented in this document.7

The following sections describe the methodology for applying the boiler MACT formula to cement kilns. The first section deals with development of improved estimates of the long

- term
variation in THC emissions from cement kilns. The second section shows how these estimates are used in the computation of MACT floors.

4

. 2 Estimation of Long

- term Variability in THC Emissions

Kilns with Long

- Term Record of Emissions

For a kiln for which the emissions data provide at least 100 observations of 30

- day average emissions, we use the available data to determine the actual 99 th percentile of 30

- day emissions
and the statistical characteristics of the distribution that are consistent with the actual 99 th
percentile. Let:

E 30 = a verage 30

- day THC emissions as determined from the 30

- day record

P 99 = actual 99 th percentile of emissions observed in the 30

- day record

N 30 = number of observations of 30

- day average emissions in the 30

- day record

Then, the effective standard devi ation of 30

- day average emissions is back

- calculated as follows:

S 30 = (P 99 – E 30 ) / t(0.99, N 30 - 1) Eq. 2

where t(p,df) is the Student’s t distribution for a one

- sided probability p

. Using this empirically

- defined distribution for such a kiln, a ny percentile of the 30

- day emissions
distribution can be calculated as follows:

P(p) = E 30 + t( p, N 30 - 1) * S 30 Eq. 3

Kilns with Short

- Term Record of Emissions

A different procedure is used for kiln s in which fewer than 100 observations of 30

- day average emissions are available. In this instance, we begin with a short

- term estimate s 30 for the standard
deviation of 30

- day average emissions as developed from the available data on daily

- average emissions. The short

- term estimate is then correct ed for the observed growth in variability that
would be expect ed based on continuing data collection to complete a one year daily

- average emissions record. Such a data record would produce 336 observations of 30

- day average
emissions. Because successive 30

- day averages are highly correlated, a correction for first

- order serial correlation is then applied. The variability growth curve and the correction for serial correlation were developed from an analysis of four best performing kilns for which data ser ies of 300 days or more were available. This analysis is documented in Appendix A.

The procedure described above is implemented as follows. Let:

n 1 = number of observations of daily

- average emissions in the short

- term data record8

e 1 = average THC emissions as determined from the daily record

s 1 = standard deviation of daily emissions as determined from the daily record

s 30 = estimate of the short

- term standard deviation of 30

- day average emissions

Then,

s 30 = s 1 / sqrt( 30 )

where 30 is the value of the parameter m representing the number of daily values used to compute the compliance average.

Using the notation established above, we have the following relationships for kilns where the
emissions record is too short to permit direct determination of the 99 th percentile of 30

- day average emissions:

E 30 = e 1 Eq. 4

S 30 = s 30 * g(n 1 - 29) * sqrt( 1 + r 1 )

N 30 = 336

P 99 = E 30 + t( 0. 99, N 30 - 1) * S 30 g(n) = ( 336 / n ) 0.37 0

r 1 = 0.824

Here, the functio n g is the growth curve function that adjusts the standard deviation of 30

- day
emissions that is estimated from a short

- term emissions record of length n days into an estimate
of the long

- term standard deviation that would be estimated from a daily emissio ns record covering 365 days and 336 30

- day periods. The term r 1 is the estimated first

- order serial
correlation in 30

- day average emissions data 6 . The empirical values for the exponent in g(n) and
for r 1 were developed using data for 4 best performing ki lns, as described in Appendix A.

The long

- term standard deviation values developed by the procedures given above are estimates
of the within

- source variability of emissions, which is one of two sources of variability considered in the MACT floor equation u sed in the major boiler MACT rule. The other source is the variability of mean emissions across the units in the pool.

4

. 3 Computation of MACT Floors

In Eq.1 above, EPA applies the sample standard deviation of emissions s calculated in the usual way from the data in the pool. The standard deviation includes contributions from both unit

- to

-

6 The comp utation is carried out using the formulation given in Section 8 of the document UPLequation_May10_2010Breda.doc provided by EPA to PCA.9

unit variability (between sources) and test

- to

- test variability (within source) in the emissions data. Because the corrections for the growth in variability over time apply only to the within

source component of the long

- term emissions variance S 2 , we have partitioned it into its two components as follows:

S total 2 = S 2 units / U + S 2 within Eq. 5

where:

U = the number of units in the pool

S 2 units = the unit

- to

- unit variability of mean emission levels across pool units

S 2 within = the long

- term variability of 30

- day average emissions, corrected for first

- order
serial correlation.

In the floor calculations, the characterization s of emissions for each of the b est performing kilns

are combined to estimate the mean emissions and the variance components pertaining to the average best performer:

 The mean emission level E 30 for the pool is estimated as the sample average of the 30

- day average emission levels of the individual kilns in the pool.

 The term S 2 within is estimated by pooling the variances S 2 30 for individual kilns, weighting each kiln in proportion to the number of 30

- day averages used in the determination of S 30

. We denote the resulting pooled variance a s S 2 30 , pooled

. Kilns where t he S 2 30 values were estimated using the growth curve and serial correlation corrections are treated as having
336 30

- day averages in the weighting

, irrespective of the actual number of 30

- day averages in the record

.

 The betwee n

- source variance S 2 units has been approximated as being equal to the sample
variance S 2 units of the average emission values E 30 for the units in the pool. Because this
variance includes the contribution related to uncertainty in estimating the means (due to having a finite number of tests), we have not included the term s 2 /n anywhere in the variance calculations, to avoid double counting.

A better approach for determining S 2 units would be to perform a components of variance analysis
to estimate the varian ce components s 2 units and s 2 within . However, the simpler method can be used here (and is necessary because of the urgent deadline for this rulemaking ), because almost all of the best performing units are now represented by data series containing at least 30 days of data. As a result, the estimated mean emission levels are in most cases affected only modestly by the uncertainty resulting from the within

- source variability present in the data for each unit.

Given the above, the formula for the MACT floor b ecomes:
UPL(p) = E 30 + t(p, N 30 - 1) * (S 2 units / U + S 2 30 , pooled ) Eq. 610

The analysis that follows has evaluated two probability levels for the floors. The first is the 99 th
percentile level as proposed by EPA . Because compliance is to be demons trated with THC CEMS data and 30 day aver a ges computed daily, this percentile will cause the average best performer to experience 3 to 4 violations each year. A 99.9 th percentile level is also proposed,
which is necessary to reduce the expected frequency of violations to less that 1 per year.

5. Proposed MACT Floors for Sub

- Categories

The THC Sub

- Categorization Study demonstrated that kilns that vent the exhaust from a
stabnd alone raw mill, coal mill or other device to the same stack as the main kiln have
si gnificantly higher THC stack emissions than other kilns , even after controlling for the composition of kiln feed and raw materials. Such “commingled kilns” face distinctively different problems in controlling emissions compared to other kilns, and the sta tistical
evidence is sufficiently strong to justify separate MACT subcategories for kilns without commingling versus kilns with commingling. Based on these findings, PCA recommends
that EPA establish separate subcategories for kilns that are commingled v ersus kilns that are not commingled.

The subcategorization study also found that t here is a clear and indisputable impact of raw material (limestone) organic content on THC emissions

. Kilns using limestone that outgas large amounts of THC, and with conf igurations that make their stack emissions more sensitive to material outgassing, face a very difficult problem in complying with emission
limitations. The study demonstrated that kilns with an inline raw mill had THC emissions that were 2 ppm higher on average than kilns without, as a result of material off

- gassing. The result was not statistically significant, however, and could not be used as the basis for a technology s ubcategory.

A factor such as limestone organic content that is beyond the control of the unit operator is a suitable basis for establishing a sub

- category. PCA believes that a recognition of this in the floors is required in order to create a valid standard and believes that it can be done with existing data by establishing a subcatego ry within Major Non

- Commingled kilns for units with the highest THC limestone.

Figure 2 shows how a subcategory can be defined for Major Non

- Commingled kilns with high THC content in their limestone. Kilns with THC out

- gassing of 65 mg/kg or higher

are a distinctive population among major non

- commingled kilns in terms of both limestone
THC content and THC stack emissions. Such kilns would be classified as having high organics limestone . The two kilns in the subcategorization study (Cemex Demopolis and

Ho lic Ada, with two data points) represent additional kilns in the US population with similarly high organic content in their limestone. PCA recommends that EPA establish standards for such kilns by adjusting the MACT floor calculated for all Major Non

Comm ingled kilns to account for the difference in limestone organic content on average11

between kilns with low and high THC limestone in the figure. This will remove the significant disadvantage faced by kilns with high THC limestone compared to other kilns.

Figure 2 . Definition of High THC Limestone Subcategory for Major Non

- Commingled Kilns

Lastly, PCA recommends that EPA establish a separate subcategory for Area Source kilns

. While EPA is required to set a floor for Major Source kilns based on the best 12% or best five units, EPA has no such obligation for kilns associated with Area Sources. Because a tight THC limit will cause kilns to install RTOs

, which are expensive and generate GHGs, EPA should avoid their application on these smaller HAP sources. One way to avoid the application of RTO technology on Area Source kilns is to set separate standards that are not as restrictive. PCA recommends that work practices apply to THCs from Area Source kilns. The requirement for good combustion practice in th e current cement MACT rule
should be retained for Area Source kilns.

In summary, PCA proposes that EPA adopt separate MACT THC standards for the following three sub

- categories:

 Major Non

- commingled Kilns

 Major Commingled Kilns

 All Area Kilns

5.1 Determina tion of Best Performers

The procedures used to select the pool of best performers are summarized in Table 2 below. The US population was estimated to be 167 kilns during the design work for the
THC sub

- categorization study last year , and the total populat ion is shrinking due to12

shutdowns of existing kilns in th is adverse economic climate. A total of 16 area kilns have been identified based on an inventory of kilns, leaving approximately 151 major kilns.

The design work for the THC study identified 13 comm ingled kilns among a dataset covering 87 kilns (more than one

- half of the US population). By extrapolation, this indicates that there are fewer than 26 commingled kilns in the US population, one of which
is known to be an area kiln.

Table 2. Determinati on of Size of Best Performing Pool for Proposed Sub

- Categories

Sub Category Estimated US Population Kilns for Which

Data Are Available Procedure for Selecting Pool of

Best Performing Kilns Existing Units New Units Rule Pool Size
Major Non

- Commin gled Kilns > 30 17 Best 12% 3 Best 1

Major Commingled Kilns < 30 7 Best 5 5 Best 1

Area Kilns < 30 6 Work Practices Standard

As a result of these population estimates, the US population of major non

- commingled kilns is in excess of 30 units, so that the pool of best performers was determined based on the best 12 percent of the units for which data are available. The population of major commingled kilns is less than 30 units, so that the pool of best performers was determined by the best 5 units for which data are available.

EPA is not required to set standards for Area Source kilns based on the MACT floor
calculations. Because of the high cost and adverse secondary environmental effects of
RTOs to control THC , PCA recommends that the standard be bas ed on work practices.

In all cases but Area Source kilns , the proposed MACT floor for new units has been determined by the one best existing unit. For Areas Source kilns, PCA again recommends that the standard be based on work practices

.
5.2 Alternative MACT Floors For Proposed Sub

- Categories

The alternative MACT floors determined for the proposed sub

- categories are summarized in table form in the following sections. The floor values shown have been rounded up to the nearest 1 ppm in accordance with EPA pr actices . In each case, a reference is given to a table presenting the detailed calculations in Appendix B.

Two different percentile levels have been evaluated. EPA has proposed establishing the
MACT floor at the 99 th percentile of the distribution for 30

- day average emissions. This13

floor level is at the upper end of the emissions distribution , but , due to the use of THC CEMS to demonstrate compliance, it implies that the best performing units will still experience 3 or 4 violates per calendar year. T he proposed 99 th percentile fails to provide

a n adequate safety margin for best performers to allow for reasonably foreseeable adverse circumstances. Therefore, PCA recommends that EPA establish the MACT floors at the

99.9 th percentile of the emissions di stribution. This floor level will reduce violations experienced by best performers to less than 1 per year.

Major Non

- Commingled Kilns

The population of major non

- commingled kilns is greater than 30. Data are available for a
total of 17 kilns, which supp orts a pool of 3 best performers (using the 12% rule, rounded up).

Table 3. Alternative MACT Floors for THC Major Non

- Commingled Kilns

Existing Units New Units

99 th Percentile 30 ppm 11 ppm

99.9 th Percentile 36 ppm 1 2 ppm

The detailed calculatio ns may be found in Table B

- 1 in Appendix B to this report.

Within the group of Major Non

- Commingled Kilns, PCA recommends that EPA establish a separate subcategory for Major Non

- Commingled Kilns with H igh O rganics Limestone

, defined as limestone THC out

- ga ssing greater than or equal to 65 mg/kg. The floors would be established by adjusting the Table 3 floors by the ratio of the average limestone THC outgassing for kilns with high organic limestone (150 mg/kg) versus the average limestone THC outgassing for all other major non

- commingled kilns (26 mg/kg). The proposed limits for this additional subcategory are shown in Table 4.

Table 4

. Alternative MACT Floors for THC Major Non

- Commingled Kilns with High Organic s Limestone (THC Outgassing ≥ 65 mg/kg)

Exi sting Units New Units

99 th Percentile 170 ppm 62 ppm

99.9 th Percentile 204 ppm 68 ppm14

Major Commingled Kilns

The population of major commingled kilns is estimated to be less than 30. Data are
available for a total of 7 kilns, and a pool consisting of the 5 best units has been used, consistent with EPA procedures.

Table 5 . Alter native MACT Floors for THC Major Commingled Kilns

Existing Units New Units

99 th Percentile 70 ppm 17 ppm

99.9 th Percentile 80 ppm 20 ppm

The detailed calculations may be found in Table B

- 2 in Appendix B to this report.

Area Kilns

The population of A rea Source kilns is estimated to be 16, and data are available for a total
of 6 kilns. A floor analysis is not required for area sources and a numerical limit could
result in the installation of RTOs on Area Sources. PCA recommends setting the standard applicable to Area Source kilns based on work practices.

5. 3 Equivalent Alternative Emission Limits for Organic HAP Species

In the proposed rule, EPA has proposed an equiv alent alternative emissions limit for organic HAP species based on data showing that 24 percent of the measured THC
emissions consisted of non

- dioxin organic HAP 7 . Cement kilns could chose to measure organic HAP directly and comply with the alternate limi t. PCA recommends th at EPA establish the following alternative limits for non

- organic HAP, which are equivalent emissions limitations to those for total THC proposed in Tables 3 and 4 above. The values shown have been calculated as 24 percent of the corr esponding values in Tables 3 and 4 above. No such limitation would be established for Area Kilns, for which PCA recommends setting the standard based on work practices.

7 National Emission Standards for Hazardous Air Pollutants From the Portland Cement Manufacturing Industry.
Federal R egister, Vol 74, No. 86, May 6, 2009, pp 21151

- 21152.15

Major Non

- Commingled Kilns

Table 6

. Alternative MACT Floors for Major Non

Commingle d Kilns : Organic HAP Limit s
Existing Units New Units

99 th Percentile 8 ppm 3 ppm

99.9 th Percentile 9 ppm 3 ppm

Table 7

. Alternative MACT Floors for Major Non

Commingled Kilns with High Organic s Limestone:

Organic HAP Limits

Existing Units New U nits

99 th Percentile 41 ppm 15 ppm

99.9 th Percentile 49 ppm 17 ppm

Major Commingled Kilns

Table 8 . Alter native MACT Floors for Major Commingled Kilns : Organic HAP Limit s

Existing Units New Units

99 th Percentile 17 ppm 5 ppm

99.9 th Percentile 20 ppm 5 ppm

# # #A

- 1 APPENDIX A

ADJUSTMENTS TO IMPROVE THE REPRESENTATION OF LONG

- TERM EMISSONS VARIABILITY

In the course of this rulemaking, PCA concluded that developing an improved representation of long

- term emissions variability was essential to de termining emissions limitations that can actually be met over time by the best performing kilns that set the standard. To this end, PCA compiled additional THC emissions data to extend the data record for kilns in the EPA database,
and was successful in o btaining additional data for 12 of the 14 kilns. These extended data series are used in the development of alternative MACT floors in this report.

A.1 Growth Curve Analysis

In the process of compiling the data, PCA saw that emissions variability increase d as the emissions data record was extended. The phenomenon is discussed in Section 3 of this report and is at odds with EPA’s assumption that the variance of test runs is stationary over time and

that the variance of the mean necessarily decreases when th e length of data series increases. These assumptions are at the center of EPA’s derivation of the UPL from first principles. However, these assumptions are contradicted by the increasing variance observed in the
extended time series . Therefore , short

- ter m variances need to be corrected to represent long

term values. Variance adjustments have been discussed with EPA and are essential to computation of realistic MACT floors because, contrary to EPA’s assumption, the variance

increases with the length of th e data series.

To characterize this phenomenon, PCA used data for 4 best performing kilns (Holcim Trident, Lehigh Union Bridge, Suwannee Branford, and TXI Midlothian) and developed a “growth curve” model for emissions variability as a function of emissio ns record length. The data used in this analysis are compiled in the Excel spreadsheet ShortLongTermVariabilityModel 20100622 .xls

.

Data series ranging in length from one 30

- day emissions average up to 270 30

- day emissions averages were formed from the avai lable data for each of the 4 best performing kiln s , and the
observed standard deviation of 30

- day average emissions was determined for each series. For the initial data series giving a single 30

- day average, the standard deviation of 30

- day average
emissi ons was estimated from the standard deviation of the daily data using the usual statistical
formula for the standard deviation of a mean.

The extended data series described above are plotted in Figure A

- 1 below. The horizontal axis is
the number of 30

- day averages that are observed and the vertical axis is the estimated standard
deviation of 30

- day average emissions developed from that record. What we see is that the
standard deviation of 30

- day emissions consistently grow s as the length of the data se ries is extended. Some kilns (e.g, Trident) show consistent variability before abruptly changing to aA

- 2

different level. Other kilns (e.g., Branford) show a more consistent upward trend in variability. Averaged across the 4 best performing kilns, the over all curve shows a consistent upward trend.

The overall trends shown in the figure were represented in the form of a power function for the average of the 4 kilns : s = 0.242 N 0.370 , where N is the number of 30

- day average values that
are observed and s is the estimated standard deviation for the average best performing kiln

. This function is turned into a growth curve that can be applied to any unit by selecting a standard length of time at which one judges the variance to have reached a long

- term value. Because seasonal variations occur in a number of factors influencing the operational patterns and conditions of cement kilns, we believe that a full calendar year (365 days ) is the shortest interval
over which one can observe emissions to obtain a reliab le estimate of long

- term variability. A 365 day period will yield 336 values for the rolling 30

- day average. Therefore, the growth curve
used in MACT floor calculations is defined to be:

g(n) = ( 336 / n ) 0.37 0

where n = number of 30

- day averages avail able for a kiln. For example, if 15 values are
available for 30

- day average emissions for a best performing kiln, then the standard deviation observed (or estimated) for 30

- day average emissions would be expected to grow on average by a factor of g(n) = ( 336/15) 0.37 0 = 3.16 if data collection were to continue to complete a 365 day record of daily emissions

.

A.2 First

- Order Serial Correlation

The complete data series for the 4 best performing kilns were also used to estimate the first

- order
serial corre lation coefficient (r 1 ) for 30

- day averages. The serial correlation coefficient is expected to be large because two successive 30

- day averages have 29 data values in common. The following table shows the computation 8 of r 1 for the 4 best performing kilns . The calculated long

- term 30

- day standard deviation is adjusted by sqrt(1+r 1 ) when computing UPL limits in the MACT floor analysis in order to remove the bias in estimating percentiles of the emissions
distribution that serial correlation would otherwise cause.

8 The computation is carried out using the formulation given in Section 8 of the document UPLequation_May10_2010Breda.doc provided by EPA to PCA.A

- 3

Figure A

- 1 . Growth of 30

- day Average Emissions Variability for Best Performing Kilns

Table A

- 1. First Order Serial Correlation r 1 of 30

- day Average Emissions for Best Performing Kilns

r 1 (i) (1+r 1 )

Holcim Trident 0.982 1.982 Lehigh Unio n Bridge 0.995 1.995

Suwannee Branford 0.336 1.336

TXI Midlothian 0.983 1.983 Average 0.824 1.824B

- 1 APPENDIX B

CALCULATIONs SUPPORTING PROPOSED MACT FLOOR SB

- 2 Subc ategorization. MACT Floor for Major Source Non

- Commingled Kilns

The population is great er than 30. D ata exist on 17 such kilns, which supports a pool of 3 units (12% rule, rounding up).

Table B

- 1 . MACT Floor Analysis Using Current PCA Database : Major Non

- Commingled Kilns

Short Term (Daily Avgs) Long Term (30d Averages) MACT F loor 30d Average

Days Average Std Dev Rolling 30d Averages Mean

Emissions (30d) Serial

Corr (r 1 ) Growth
Factor Standard Deviation
99%

- tile 99.9%

- tile Between Source Within

Source Combined

Std Dev

Rank Total Pool 1,085 6.8 1.4 8.1 8.1 29.6 35.1

1 TXI Midlothian 444 5.8 1.5 10.2 11.2

2 Suwannee Branford 305 6.1 1.7 10.9 12.1

3 Cal Portland Mojave 31 8.4 8.7 336 8.4 0.824 6.66 14.3 48.9 58.8
a/ Uses Bo iler MACT UPL equation in which within

- source and between

- source variances have been partitioned. The within

- source variance has been adjusted for short/long

- term growth in variability and corrected for serial correlation. The between

- source variance inc ludes contributions from the uncertainties in average emission levels and from differences in the average emission levels among units.

Note 1: In the table, the columns labeled Short Term (Daily Avgs) are statistics for daily

- average emissions. The col umns labeled Long Term (30d Averages) are
statistics for the data series of 30d rolling averages.

Note 2: Kilns highlighted have sufficiently long time series for 30d average emissions to be fully characterized by the data. The observed mean and 99 th

perc entiles have been cast into the form of a UPL calculation to fit within the EPA UPL framework. Kilns without highlight are t reated by means of UPL calculations using long

- term variances that have been estimated from the observed short

- term variances with the aid of the growth curves and the adjustment for
first

- order se rial autocorrelation

.B

- 3 Subc ategorization. MACT Floor for Major Source Commingled Kiln s
The US population is estimated to be less than 30. Based on this, the pool consists of 5 best perform ers. The current database has data on 7 such
kilns.

Table B

- 2 . MACT Floor Analysis Using Current PCA Database : Major Commingled Kiln s

Short Term (Daily Avgs) Long Term (30d Averages) MACT Floor 30d Average

Days Average Std Dev Rolling 30d Av erages Mean

Emissions (30d) Serial

Corr (r 1 ) Growth

Factor Standard Deviation

99%

- tile 99.9%

- tile

Between Source Within

Source Combined

Std Dev

Rank Total Pool 2,592 30.5 18.7 11.2 14.0 69.7 79.1

1 Lehigh Union Bridge 730 4.6 4.3 16.7 19.6

2 Titan Pennsuco 54 18.0 7.7 336 18.0 0.824 2.62 5.0 32.0 35.5

3 Lafarge Sugar Creek 55 35.5 15.7 336 35.5 0.824 2.58 10.0 63.8 70.7

4 Holcim Portland 854 45. 6 11.2 77.1 84.7

5 National Ragland 20 48.5 10.3 336 48.5 0.824 8.60 21.9 110.4 125.4
a/ Uses Boiler MACT UPL equation in which within

- source and between

- source variances have been partitioned. The within

- source variance has been adjusted fo r short/long

- term growth in variabili ty and corrected for serial correlation. The between

- source variance includes contributions from the uncertainties in average emission levels and from differences in the average emission levels among units.

Notes 1

- 2 apply as stated on the prior table.