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 |Keith Barnett/RTP/USEPA/US 

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 |Cortney_Higgins@omb.eop.gov 

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 |Charlotte Bertrand/DC/USEPA/US@EPA 

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 |07/28/2010 03:46 PM 

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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

----- Forwarded by Keith Barnett/RTP/USEPA/US on 07/28/2010 03:45 PM

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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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 |06/30/2010 09:05 AM 

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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

 · Enclosure 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@cement.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 29, 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 from June 21 Meeting

Dear Mr. Tsirigotis and Mr. Barnett,

Thank you for meeting with the Portland Cement Association (PCA) on June 21, 

2010, to discuss the results of PCA's and EPA's collaborative efforts to collect and 

properly analyze data sufficient to support an appropriate National Emissions Standard 

for Hazardous Air Pollutants (NESHAP) for the portland cement sector. We welcomed 

the opportunity to present the data to you and discuss the outcomes the data presented. 

We address the following topics herein:

Statistical methods for computing floors and accounting for variability;

Total hydrocarbon (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

(>250ppb)

85%

Red.

85% 

Red.

Total 

Hydrocarbons*

(ppmv)

7 6 Major NonCommingled 

(Low 

limestone)

36 12

Major NonCommingled 

(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 99th percentile 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 sources (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 were 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 portland 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 area 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. Enclosure 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. 

This approach is flawed because the two sources are not similar as recognized by 

EPA in its proposal. First, the oxygen levels in the dryers are well-above 19%, where as 

the oxygen 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 the 
4

others 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 suggested 

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 emissions 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 

installation 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 device 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 plant 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 industry 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 emissions, 

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 predictions 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 loss 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 likely
5

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 nonexistent 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 any questions you may have regarding the 

perspectives of PCA. 

Sincerely, 

Andrew T. O’Hare

Vice President, Regulatory Affairs

Cc: Gina McCarthy

Steve Fruh

Steve Silverman
i

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 Consulting

2853 S. Quail Trail

Tucson, AZ 85730

June 29, 2010
i

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 .............................................................................................................................. 11
ii

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 Limestone Outgassing .......................... 11
iii

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: Kilns with Commingling ............ 8

Figure 5: THC Stack Emissions versus Limestone Outgassing: Kilns without Commingling .... 10

Figure 6: THC Stack Emissions versus Limestone Outgassing: Kilns with Commingling ......... 10
1

1. Introduction

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 emissions 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 were

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 

technology 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 what 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 unit in the 

project. In most 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 contractors. 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 expressed 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

 Conclusions
2

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 recruited. 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 omitted 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 

averaged 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 presented to EPA and approved in principle by EPA before the study 

started. The study design stratifies 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 mill, and 

commingling of the raw or coal mill exhaust and the main kiln exhaust in the same stack where 

the THC CEMS was located2. The a priori assessment of emission levels was used to achieve a 

sufficient representation of kiln types that may have high emissions. 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

 Cell 3 – Preheater and preheaters/precalciners (PH/PH-PC) kilns with in-line raw mills, 

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 preheaters/precalciners (PH/PH-PC) kilns with in-line raw mills, 

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 and preheaters/precalciners (PH/PH-PC) kilns without in-line raw 

mills, 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 exhaust passes through the mill as well.
3

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

CEMS Data Raw Materials

Cell No. Kiln Period THC record Sampling

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

Ash Grove Midlothian 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 58d 2 x 30d

Lafarge Seattle 2 x 30d 49d 1 x 30d

Buzzi Pryor

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

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

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

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

Cemex Fairborn 2 x 30d 38d 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 25d 1 x 30d

Lehigh Mason City

TXI Midlothian K5

5 National Ragland 1 x 30d 20d 1 x 30d

Lafarge Sugar Creek 2 x 30d 55d 1 x 30d

Ash Grove Durkee 2 x 30d 55d 2 x 30d

Lehigh Union Bridge 2 x 30d 55d 2 x 30d

Titan Pennsuco 1 x 30d 27d 1 x 30d

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

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

Holcim Devil's Slide 2 x 30d 58d 2 x 30d

Giant Dragon Thomaston

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

1 x 15d 13d 1 x 30d

Lafarge Whitehall 2 x 30d 45d 2 x 30d

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

For purposes of this report, the term “commingled 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 participate 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 high 
4

in regard to THC emissions or to materials outgassing of THC, it refers to actual 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 feed 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 level 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 consecutive. THC CEMS emissions are expressed on a basis of ppm of propane, 

dry, at 7% O2 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 emissions 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 emissions 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 O2 monitors, a decision was made to classify any day having at least 18 reported 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 O2-adjusted THC emissions when the O2

level began to approach ambient levels (20.9 percent). There were a number of instances during 

the study in which O2 concentrations reached levels approaching ambient due to leaks in the O2

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 measured 
5

O2 concentration. The correction formula returns an infinite value when the measured O2 is 20.9 

percent, and it can yield very large correction factors whenever the O2 concentration is near the 

ambient value. In fact, the THC concentration on a dry basis at 7% O2 becomes increasingly 

hard to determine reliability as the O2 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 basis 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 content 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 29 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 R2(R2~0.35). 

THC stack emissions 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 and 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 both 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 limestone will vary over time as new portions of the quarry 

are mined.
6

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100

0 2 5 5 0 7 5 100 125 150

Stack Emissins (ppm THC, dry &% O2 )

Kiln Feed Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

Figure 1. THC Stack Emissions versus Kiln Feed Outgassing

0

2 0

4 0

6 0

8 0

100

120

140

0 2 5 5 0 7 5 100 125 150 175 200 225

Kiln Feed Outgassing (mg THC/kg)

Limestone Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

Figure 2. Relationship of Kiln Feed to Limestone Outgassing

4. Evidence Supporting 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 analysis 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 types, once the 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 dataset of 
7

a significant distinction in emission performance related to kiln type – i.e., long kilns versus

PH/PH-PC kilns. We see that stack emissions 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 varies by kiln and the characteristics of the 

material fed to the mill.

4.1 Subcategorization based on Technology: Commingling

A number of statistical analyses were 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 to kiln feed is somewhat lower. 

Figure 3 below shows the trend of stack emissions with kiln feed for non-commingled kilns3. 

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 

understood 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 mills to the main stack, while the lower slope is consistent 

with coal grinding 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 form 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 * Outgassingkiln feed + C * dCommingling (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 measured 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 only 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 commingled 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.

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100

0 2 5 5 0 7 5 100 125 150

Stack Emissins (ppm THC, dry &% O2 )

Kiln Feed Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

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

0

10

20

30

40

50

60

70

80

90

100

0 50 100 150

Stack Emissins (ppm THC, dry &% O2)

Kiln Feed Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

Figure 4. THC Stack Emissions versus Kiln Feed Outgassing: Commingled Kilns
9

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

R

2

= 0.43 F = 13.7

Parameter Coefficient

Value

Standard 

Error Prob>|t|

A Intercept 6.5 4.5 0.16

B Kiln Feed Outgassing 0.35 0.07 0.00

C Commingling 12.8 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 what 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 emissions 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 outgassing 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 emissions performance when viewed on this basis. The results of this 

analysis are summarized in Table 3 based on the following model:

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

Here, we find a statistically significant intercept and slope for the stack emissions effect of 

limestone outgassing. The term representing the effect of commingling is statistically significant 
10

at the p=0.05 level. That the intercept is larger and the slope smaller, compared to the kiln feed 

model presented above, 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 significant determinant 

of THC stack emissions.

0

1 0

2 0

3 0

4 0

5 0

6 0

7 0

8 0

9 0

100

0 2 5 5 0 7 5 100 125 150 175 200 225

Stack Emissins (ppm THC, dry &% O2 )

Limestone Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

Figure 5. THC Stack Emissions versus Limestone Outgassing: Kilns without Commingling

 

0

10

20

30

40

50

60

0 10 20 30 40 50 60 70

Stack Emissins (ppm THC, dry &% O2 )

Limestone Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

Figure 6. THC Stack Emissions versus Limestone Outgassing: Commingled Kilns
11

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 Commingling 11.8 5.8 0.05

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.

There is a clear and indisputable impact of limestone organic content on THC emissions, and a 

recognition 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 bases for developing subcategories. 

# # #
Enclosure B

ALTERNATIVE MACT FLOORS

FOR

PORTLAND CEMENT KILNS

Prepared by:

The Portland Cement Association 

5420 Old Orchard Road

Skokie, IL 60077

June 29, 2010
i

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 Determination.......................................................................... 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. Proposed MACT Floors for Sub-Categories ............................................................................ 10

 5.1 Determination of Best Performers..................................................................................... 11

 5.2 MACT Floors for Proposed Sub-Categories...................................................................... 12

 5.3 Equivalent Alternative Emission Limits for Organic HAP Species.................................. 14

Appendix A: Adjustments 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: Calculations Supporting Proposed MACT Floors ................................................ B-1
ii

List of Tables

Table 1: THC CEMS Data Used in Developing MACT Floors .................................................... 3

Table 2: Determination of Size of Best Performing Pool 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 Kilns: Organic HAP Limits .. 15

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 Limits .......... 15

Appendix A

Table A-1: First Order Serial Correlation r1 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-3
iii

List of 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-3
1

1. Introduction

Since EPA’s proposed MACT rule for cement kilns was published in 2009, the 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. This work has included 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 Subcategorization 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 

report

1

.

Relevant regulatory actions have taken place as well. EPA has recently published proposed rules 

regulating hazardous air pollutants from other sources – ones for industrial, commercial, and 

institutional boilers and process heaters and another for commercial and industrial solid waste 

incineration units. In these proposed rules, EPA proposes the use of alternative equations for 

calculating MACT floors. The equation proposed in the boiler MACT rule (termed here the 

Boiler MACT equation) takes a broader and more appropriate view of how variability should be 

accounted for in determining the emission limitations that the best performing units can meet,

than the statistical formula EPA has recently indicated will be used for cement kilns.

This report presents 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 database

 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 calculations 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 

2010.06.13.xls. 

Table 1 lists the 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 10 major kilns in the database compiled by EPA. PCA collected additional data on 

THC emissions for 9 of the 10 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. This exclusion 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.

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 units 

(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 formulas 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 collected 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 that 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 SubCategorization 

Study

Totals 24 10 9 20

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 Dundee 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 √ √

0

5

10

15

20

25

30

35

40

45

50

THC (ppm, 7% O2, dry)

Day in THC Record

Daily Average THC Emissions

Figure 1. Example of Short-term Data on THC Emissions
4

In analyzing the extended data series for 12 of the kilns, PCA noted that emissions variability 

increased as the length of the data record was extended. This finding is consistent with the 

realization that many sources of emissions 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 characteristics 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 the deficiencies of the available short-term data by analytical 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 

MACT 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 observed 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 data 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 performing 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 daily 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 MACT 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 formula and more recently has 

issued a document detailing the derivation of the currently proposed UPL formula for cement 

kilns3. Among the problems with the most recent cement kiln formula are that the computed 

UPL values fall far short of the 99th 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 representatives of all best 

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 different, 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 the 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 document4

describing the boiler MACT calculations in more detail states that “... the data used to calculate 

the MACT floor represents 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 

sample 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-day variability of 

emissions within units and the unit-to-unit variability of emissions across units in the pool. This 

is embodied in the following formula5, 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 Eddinger, 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 s2includes contributions from both unit-to-unit variability (between sources) and 

test-to-test variability (within source) in the available emissions data. The term s2is found inside 

the square root, but an equivalent formula can be written with the standard deviation s positioned 

outside the square root instead.

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 data 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 levels 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 variability is combined with the effect of having a finite number of tests 

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 s2is 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 s2/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 the time. The term t(0.99,n-1) 

is the Student’s t-statistic that translates the total variance s2into 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 arbitrarily excludes 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 performing 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 

for 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 99th percentile of 30-day emissions 

and the statistical characteristics of the distribution that are consistent with the actual 99th

percentile. Let:

E30 = average 30-day THC emissions as determined from the 30-day record

P99 = actual 99th percentile of emissions observed in the 30-day record

N30 = number of observations of 30-day average emissions in the 30-day record

Then, the effective standard deviation of 30-day average emissions is back-calculated as follows:

S30 = (P99 – E30) / t(0.99, N30-1) 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, any percentile of the 30-day emissions 

distribution can be calculated as follows:

P(p) = E30 + t(p, N30-1) * S30 Eq. 3

Kilns with Short-Term Record of Emissions

A different procedure is used for kilns in which fewer than 100 observations of 30-day average 

emissions are available. In this instance, we begin with a short-term estimate s30 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 corrected for the observed growth in variability that 

would be expected 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 series 

of 300 days or more were available. This analysis is documented in Appendix A.

The procedure described above is implemented as follows. Let:

n1 = number of observations of daily-average emissions in the short-term data record
8

e1 = average THC emissions as determined from the daily record

s1 = standard deviation of daily emissions as determined from the daily record

s30 = estimate of the short-term standard deviation of 30-day average emissions

Then,

s30 = s1 / 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 99th percentile of 30-day 

average emissions:

E30 = e1 Eq. 4

S30 = s30 * g(n1-29) * sqrt( 1 + r1 )

N30 = 336

P99 = E30 + t(0.99, N30-1) * S30

g(n) = ( 336 / n )0.370

r1 = 0.824

Here, the function 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 emissions record 

covering 365 days and 336 30-day periods. The term r1 is the estimated first-order serial 

correlation in 30-day average emissions data6. The empirical values for the exponent in g(n) and 

for r1 were developed using data for 4 best performing kilns, 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 used 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 computation 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 withinsource component of the long-term emissions variance S2

, we have partitioned it into its two 

components as follows:

Stotal

2

 = S2

units / U + S2within 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 characterizations of emissions for each of the best performing kilns 

are combined to estimate the mean emissions and the variance components pertaining to the 

average best performer:

 The mean emission level E30 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 S2

within is estimated by pooling the variances S230 for individual kilns, weighting 

each kiln in proportion to the number of 30-day averages used in the determination of S30. 

We denote the resulting pooled variance as S

2

30, pooled. Kilns where the S230 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 between-source variance S2

units has been approximated as being equal to the sample 

variance S2

units of the average emission values E30 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 s2/n anywhere in the 

variance calculations, to avoid double counting.

A better approach for determining S2

units would be to perform a components of variance analysis 

to estimate the variance components s2

units and s2within. 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 becomes:

UPL(p) = E30 + t(p, N30-1) * (S2

units / U + S230, pooled) Eq. 6
10

The analysis that follows has evaluated two probability levels for the floors. The first is the 99th

percentile level as proposed by EPA. Because compliance is to be demonstrated with THC 

CEMS data and 30 day averages computed daily, this percentile will cause the average best 

performer to experience 3 to 4 violations each year. A 99.9th 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 

significantly 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 statistical 

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 versus kilns that 

are not commingled. 

The subcategorization study also found that there 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 configurations 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 subcategory.

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 subcategory 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 

Holic 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 NonCommingled kilns to account for the difference in limestone organic content on average 
11

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.

0

10

20

30

40

50

60

70

80

90

100

0 2 5 50 75 100 125 150 175 200 225

Stack Emissins (ppm THC, dry &% O2 )

Limestone Outgassing (mg THC/kg)

Low THC Limestone High THC Limestone

High Limestone Subcategory

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 the 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 Determination 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 population is shrinking due to 
12

shutdowns of existing kilns in this 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 commingled 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. Determination 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-Commingled 

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 based 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 practices. 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 99th percentile of the distribution for 30-day average emissions. This 
13

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. The proposed 99th percentile fails to provide 

an adequate safety margin for best performers to allow for reasonably foreseeable adverse 

circumstances. Therefore, PCA recommends that EPA establish the MACT floors at the 

99.9th percentile of the emissions distribution. 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 supports 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

99th Percentile 30 ppm 11 ppm

99.9th Percentile 36 ppm 12 ppm

The detailed calculations 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 High Organics Limestone, 

defined as limestone THC out-gassing 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 Organics

Limestone (THC Outgassing ≥ 65 mg/kg)

Existing Units New Units

99th Percentile 170 ppm 62 ppm

99.9th Percentile 204 ppm 68 ppm
14

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. Alternative MACT Floors for THC

Major Commingled Kilns

Existing Units New Units

99th Percentile 70 ppm 17 ppm

99.9th 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 Area 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 equivalent alternative emissions limit for 

organic HAP species based on data showing that 24 percent of the measured THC 

emissions consisted of non-dioxin organic HAP7. Cement kilns could chose to measure 

organic HAP directly and comply with the alternate limit. PCA recommends that 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 corresponding 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 Register, Vol 74, No. 86, May 6, 2009, pp 21151-21152.
15

Major Non-Commingled Kilns

Table 6. Alternative MACT Floors for Major NonCommingled Kilns:

Organic HAP Limits

Existing Units New Units

99th Percentile 8 ppm 3 ppm

99.9th Percentile 9 ppm 3 ppm

Table 7. Alternative MACT Floors for Major NonCommingled Kilns with High Organics Limestone:

Organic HAP Limits

Existing Units New Units

99th Percentile 41 ppm 15 ppm

99.9th Percentile 49 ppm 17 ppm

Major Commingled Kilns

Table 8. Alternative MACT Floors for 

Major Commingled Kilns: Organic HAP Limits

Existing Units New Units

99th Percentile 17 ppm 5 ppm

99.9th 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 determining 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 obtaining 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 increased 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 the 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-term variances need to be corrected to represent longterm 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 the 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 emissions record length. The data used in 

this analysis are compiled in the Excel spreadsheet ShortLongTermVariabilityModel20100622.xls.

Data series ranging in length from one 30-day emissions average up to 270 30-day emissions 

averages were formed from the available data for each of the 4 best performing kilns, 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 

emissions 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 grows as the length of the data series is 

extended. Some kilns (e.g, Trident) show consistent variability before abruptly changing to a 
A-2

different level. Other kilns (e.g., Branford) show a more consistent upward trend in variability. 

Averaged across the 4 best performing kilns, the overall 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 N0.370, 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 reliable 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 )0.370

where n = number of 30-day averages available 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) 0.370 = 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 correlation coefficient (r1) 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 computation8of r1 for the 4 best performing kilns. The calculated 

long-term 30-day standard deviation is adjusted by sqrt(1+r1) 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

y = 0.242x0.370

R2 = 0.757

0.0

1.0

2.0

3.0

4.0

5.0

6.0

7.0

0 3 0 6 0 9 0 120 150 180 210 240 270 300 Srandard Deviation

Number of 30-Day Rolling Averages

Trident

Union Bridge

Branford

TXI

Average

Figure A-1. Growth of 30-day Average Emissions Variability for Best Performing Kilns

Table A-1. First Order Serial Correlation r1 of

30-day Average Emissions for Best Performing Kilns

r1(i) (1+r1)

Holcim Trident 0.982 1.982

Lehigh Union Bridge 0.995 1.995

Suwannee Branford 0.336 1.336

TXI Midlothian 0.983 1.983

Average 0.824 1.824
B-1

APPENDIX B

CALCULATIONs SUPPORTING PROPOSED MACT FLOORS
B-2

Subcategorization. MACT Floor for Major Source Non-Commingled Kilns

The population is greater than 30. Data 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 Floor 30d 

Average

Days Average Std Dev

Rolling 

30d 

Averages

Mean 

Emissions 

(30d)

Serial 

Corr 

(r1)

Growth 

Factor

Standard Deviation

99%-tile 99.9%-

Between tile

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 Boiler 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 includes 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 columns 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 99th

percentiles have been cast into the form of a UPL calculation to fit within the EPA UPL framework. Kilns without highlight are treated 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 serial autocorrelation.
B-3

Subcategorization. MACT Floor for Major Source Commingled Kilns

The US population is estimated to be less than 30. Based on this, the pool consists of 5 best performers. The current database has data on 7 such 

kilns.

Table B-2. MACT Floor Analysis Using Current PCA Database: Major Commingled Kilns

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

Average

Days Average Std Dev

Rolling 

30d 

Averages

Mean 

Emissions 

(30d)

Serial 

Corr (r1)

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 for short/long-term 

growth in variability 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.