Date: November 6, 2014

To: Jeff Telander, EPA/OAQPS/SPPD

From: Gabrielle Raymond and Kristin Sroka (RTI International)

Subject: Maximum Achievable Control Technology (MACT) Floor Analysis for Clay 

Ceramics

I. Introduction

In accordance with section 112 of the Clean Air Act (CAA), the U.S. Environmental 

Protection Agency (EPA) established national emission standards for hazardous air pollutants 

(NESHAP) on May 16, 2003, for the clay ceramics (CC) manufacturing industry, specifically the 

sanitaryware and ceramic tile industry sectors. The NESHAP regulated emissions of hydrogen 

fluoride (HF), hydrogen chloride (HCl), and particulate matter (PM)—a surrogate for hazardous 

air pollutant (HAP) metals—from kilns located at CC facilities. On March 13, 2007, the D.C. 

Circuit Court vacated the emission standards for CC manufacturing due to issues associated with 

the methodology used to determine the minimum regulatory “floors” for new and existing units.

1

 

Therefore, the EPA is proposing new standards for CC manufacturing, including standards for 

HF, HCl, mercury (Hg), non-Hg HAP metals (or PM surrogate), and dioxins/furans (D/F). The 

list of affected sources to be regulated has been expanded to include new and existing kilns, 

spray dryers (ceramic tile only), press dryers (ceramic tile only), and glaze spray booths.

Section 112 of the CAA requires that the EPA establish NESHAP for the control of the 

HAP emitted from both new and existing sources in a source category. These standards must 

reflect the maximum degree of reduction in the HAP emissions that is achievable. The minimum 

level of control is referred to as the “maximum achievable control technology (MACT) floor.” 

The method for determining the MACT floor is defined for both new and existing sources by 

CAA section 112(d)(3). For new sources, the MACT floor cannot be less stringent than the 

emission control that is achieved in practice by the best controlled similar source. For existing 

sources, the MACT floor cannot be less stringent than the average emission limitation achieved 

by the best performing 12 percent of existing sources for source categories with 30 or more 

sources, or the best performing 5 sources for source categories with fewer than 30 sources.

The purpose of this memorandum is to present the methodology and the results of the

MACT floor analysis for the CC source category. This MACT floor analysis uses data collected 

 1 Sierra Club v. EPA, 479 F.3d 875 (D.C. Cir. 2007).
2

in a survey of CC owners and operators conducted by the EPA in 2008 and 2010 under section 

114 of the CAA. The emissions data supplied by CC owners and operators in response to the 

survey were compiled into a Microsoft Excel® data base that serves as the dataset used for this 

MACT floor analysis (referred to in this memorandum as the “survey dataset”). For more details 

about the survey dataset, see Test Data Used in Clay Ceramics Proposed Rule (Raymond,

2014a).

II. Hazardous Air Pollutants

The specific chemicals, compounds, or groups of compounds designated to be HAP are 

listed in CAA section 112(b). Included on the list are metals, organic compounds, and inorganic 

chemicals. From this HAP list, the following HAP were identified to be emitted from CC

facilities: the acid gases HF, HCl, and Cl2; the metals antimony (Sb), arsenic (As), beryllium 

(Be), cadmium (Cd), chromium (Cr), cobalt (Co), lead (Pb), manganese (Mn), Hg, nickel (Ni), 

and selenium (Se); and dioxins and furans (D/F). MACT floor levels for HAP metals other than 

Hg were analyzed using filterable PM emissions as a surrogate for total non-Hg HAP metals 

from CC facilities (see the preamble to the CC proposed rule for more information about 

filterable PM as a surrogate for total non-Hg HAP metals).

MACT floors were not developed for acid gases. A health-based emission limit was 

developed for acid gases under CAA section 112(d)(4). The rationale behind these standards is 

discussed in the preamble to the CC proposed rule.

III. MACT Floor Analysis Subcategories

Under CAA section 112(d)(1), the EPA has the discretion to “...distinguish among 

classes, types, and sizes of sources within a category or subcategory in establishing...” standards. 

When separate subcategories are established, a MACT floor is determined separately for each 

subcategory. To determine whether the CC source category warrants subcategorization for the 

MACT floor analysis, the EPA reviewed CC kiln, dryer, and glazing operations design, 

operating information, and emissions data compiled in the survey dataset and other information 

collected by the Agency for development of the NESHAP for this source category (Raymond, 

2014b). Based on this review, the EPA concluded that there are significant design and 

operational differences in CC kilns, dryers, and glazing operations that affect the levels of 

emissions of certain HAP to justify subcategorizing CC kilns, dryers, and glazing operations for 

the purpose of establishing MACT floors. For the CC source category, the following 

subcategories were identified:

• Ceramic Floor tile roller kilns: New and existing CC roller kilns producing floor tile.

• Ceramic Floor tile press dryers: New and existing CC press dryers of floor tile.

• Ceramic Floor tile spray dryers: New and existing CC spray dryers of floor tile.

• Ceramic Wall tile roller kilns: New and existing CC roller kilns producing wall tile.

• Ceramic Wall tile press dryers: not subject to this rule
3

• Ceramic Wall tile spray dryers: New and existing CC spray dryers of wall tile.

• Ceramic Tile glaze lines: New and existing CC glazing operations for tile.

• Sanitaryware first-fire tunnel kilns: New and existing CC first-fire tunnel kilns 

producing sanitaryware.

• Sanitaryware ware dryers: not subject to this rule

• Sanitaryware first-fire manual glaze application: New and existing CC manual glazing 

operations for sanitaryware. 

• Sanitaryware first-fire spray machine glaze application: New and existing CC spray 

machine glazing operations for sanitaryware.

• Sanitaryware first-fire robot glaze application: New and existing CC robot glazing 

operations for sanitaryware.

IV. MACT Floor Analysis Concepts

A. Upper Prediction Limit

The MACT floor analysis for CC manufacturing uses an upper prediction limit (UPL)

approach to identify the average emission limitation achieved by those best performing sources. 

The EPA uses a UPL approach in its MACT floor analyses because it incorporates the average 

performance of the best performing sources and the variability of the performance during testing 

conditions. The UPL represents the value which one can expect the mean of a specified number 

of future observations (e.g., 3-run average) to fall below for the specified level of confidence, 

based upon the results of an independent sample from the same population. The level of 

confidence represents the level of protection afforded to facilities whose emissions are in line 

with the best performers. For example, a 99 percent level of confidence means that a facility 

whose emissions are in line with the best performers has one chance in 100 of exceeding the 

floor limit. A prediction interval for a single future observation (or an average of several test 

observations) is an interval that will, with a specified degree of confidence, contain the next (or 

the average of some other pre-specified number of) randomly selected observation(s) from a 

population. In other words, the UPL estimates what the upper bound of future values will be, 

based upon present or past background samples taken. The UPL approach encompasses all the 

data point-to-data point variability. The predictions derive from the dataset to which it is 

applied, and, thus, can be applied to any type of data.

There are different equations for calculating a UPL based on the distribution of the 

dataset. Data can be normally distributed, lognormally distributed, or neither and thus have a 

skewed/unknown distribution. The EPA implemented the statistical tests of skewness and 

kurtosis to determine the distribution of the best performing sources’ data.
4

The skewness statistic (S) characterizes the degree of asymmetry of a given data 

distribution. Normally distributed data have an S value of zero. An S value that is greater than 

zero indicates that the data are asymmetrically distributed with a right tail extending towards 

positive values; similarly, an S value that is less than zero indicates that the data are 

asymmetrically distributed with a left tail extending towards negative values. The value of S can 

be approximated using the following equation (which is implemented in Microsoft Excel® using 

the “SKEW” function):

( )( )

3

1 2 1

∑=





 



 −

− − =

n

i

i

stdev

x x

n n

n Skewness

where:

n = sample size

x = mean of MACT floor pool

xi = individual source mean

stdev = ( )

( ) ∑ −

−

1

2

n

x x i

As part of determining whether a data distribution can be considered normal, the S value 

must be compared to the standard error of the skewness statistic (SES). The SES value can be 

approximated using the following equation:

( )( )

( 2)( 1)( 3)

6 1

− + +

× − = n n n

n n SES

According to the skewness hypothesis test, if the absolute value of S is less than two times the 

absolute value of SES, the skewness of the data can be considered normal.

The kurtosis statistic (K) characterizes the degree of peakedness or flatness of a given 

data distribution in comparison to a normal distribution. Normally distributed data have a K 

value of zero. A K value that is greater than zero indicates a relatively peaked distribution. A K 

value that is less than zero indicates a relatively flat distribution. The estimate of K can be 

calculated one of two ways. For datasets with more than three run values, kurtosis can be 

estimated using the following equation (which is implemented in Microsoft Excel® using the 

“KURT” function):

( )

( )( )( )

( )

( 2)( 3)

3 1

1 2 3

1 4 2

− −

− −















 



 



 −

− − −

+ = ∑ n nn

stdev

x x

n n n

n n Kurtosis
5

This equation cannot be used for datasets with three run values (n=3) because there will 

be a zero in the denominator of the first and second term. Instead, for datasets with three run 

values, kurtosis is estimated using the following equation:

( )

( )( ) 3

1 4

1

4

− −

+

=

∑=

n stdev

x x

Kurtosis

n

i

i

As part of determining whether a data distribution can be considered normal, the K value 

must be compared to the standard error of the kurtosis statistic (SEK). The SEK value can be 

approximated using the following equation:

( ( ))

( 2)( 3)( 3)( 5)

24 1 2

− + − +

− = n n n nn n SEK

(for datasets with more than three runs (n>3))

n

SEK 24 =

(for datasets with three runs (n=3))

According to the kurtosis hypothesis test, if the absolute value of K is less than two times 

the absolute value of SEK, the kurtosis of the data can be considered normal.

For this MACT floor analysis, if the results from both the skewness and kurtosis 

hypothesis tests indicated the dataset was normally distributed, the dataset was treated as

normally distributed in subsequent UPL calculations. If either of these tests indicated the dataset 

was not normally distributed, the dataset was log-transformed, and the log-transformed dataset 

was evaluated for kurtosis and skewness. If both tests of the log-transformed data indicated the 

log-transformed dataset was normally distributed, the dataset was treated as lognormally 

distributed in subsequent UPL calculations. If either of these tests indicated the log-transformed 

dataset was not normally distributed, the dataset was treated as skewed/unknown distribution in 

subsequent UPL calculations.

For datasets with only three run values, the result of both the skewness and kurtosis 

hypothesis tests always indicate the dataset is normally distributed. Therefore, to determine the 

appropriate data distribution for those datasets, the skewness/SES values from raw data were 

compared to the skewness/SES values from log-transformed data. The smaller skewness/SES 

value was selected as an indication of a larger likelihood of the data to come from the 

corresponding distribution.

After completing the determination of the type of data distribution for each dataset, the 

UPL was calculated using the corresponding equation for the distribution for that dataset. The 

UPL equations for normal, lognormal, and skewed/unknown distribution datasets are provided 

below.
6

Normally Distributed Dataset





 



 = + +

n m

UPL x t s df

2 1 1 ,0.99

where:

UPL = upper prediction limit

x = mean of the data calculated as ∑= ∑ = = N

i

n

j ij

i

x

n

x

1 1

1

n = number of test runs = ∑=

N

i i n1

m = number of future test runs in the compliance average

N = number of sources

s

2 = pooled variance calculated as ∑ ( ) = = − n

i i x x

n

s

1

2 1 2

tdf,0.99 = quantile of t-distribution at the 99 percent level of confidence with degrees of 

freedom (df); this value can be calculated with the Student’s t-test statistical 

method, using the “TINV” function in Microsoft Excel® software

df = degrees of freedom calculated as ( ) 1

1 = ∑ − =

N

i i df n

Lognormally Distributed Dataset (Bhaumik and Gibbons, 2004)

( ) ( )















− = + − + + + + +

2 1

ˆ ˆ 1

2 4

99 2 ˆ ˆ ˆ 2 2 ˆ ˆ 2 0.

ˆ ˆ 2 2 2

2

n n

me e m e

m

z UPL e m σ σ m σ σ σ σ m

where:

μˆ = 

n

log y n

i ∑ i =1 ( )

= the average of the log transformed data from the data

2 σˆ = ( ( ) )

1

ˆ 1

2

−

∑ − =

n

log y n

i i μ

= variance estimate of the log transformed data

z0.99 = the 99th-percentile of the log-normal distribution estimated using the 

trapezoidal rule approach from the following equation:

( ) ( )( ) ( ) 0.99

24

3 3 6 3

6

1 0.99

0

2 4

1 3 2 = 













 − − + − − + ∫ z

z z

z z z z z φ β β
7

Skewed/Unknown Distribution (Non-Normal/Non-Lognormal) (Gayen, 1949)





 



 = + +

n m

UPL x t s df p

2 1 1 ,

where:

UPL = upper prediction limit

x = mean of the data calculated as ∑= ∑ = = N

i

n

j ij

i

x

n

x

1 1

1

n = number of test runs = ∑=

N

i i n1

m = number of future test runs in the compliance average

N = number of sources

s

2 = pooled variance calculated as ∑ ( ) = = − n

i i x x

n

s

1

2 1 2

tdf,p = recalculated quantile of t-distribution based on specified level of confidence 

(i.e., 99%)

df = degrees of freedom calculated as ( ) 1

1 = ∑ − =

N

i i df n

B. Representative Detection Limit

The imprecision of test method measurements is another component of data variability. 

At very low emissions levels, as encountered in some of the data in the CC dataset, the inherent 

imprecision in the pollutant measurement method has a large influence on the reliability of the 

data underlying a MACT floor emission limit. Of particular concern are those data that are 

reported near or below a test method’s pollutant detection capability. Because of matrix effects, 

laboratory techniques, sample volume, and other factors, method detection limits normally vary 

from test to test. The guidelines for the 2010 section 114 CC survey requested that sources 

identify (i.e., flag) data which were measured below the method detection limit and to report 

those values as equal to the test-specific method detection limit.

Variability of data due to measurement imprecision is inherently and reasonably 

addressed in calculating a MACT floor emission limit when most of the data are significantly 

above the method detection limit. For datasets with a large number of test results below the 

method detection limit (reported as method detection limit values), other techniques need to be 

used to account for data variability. Indeed, under such a shift, the data distribution becomes 

truncated on the lower end, leading to an artificial overabundance of values occurring at the 

method detection limit. There is a concern that a MACT floor emission limit based on a 

truncated data base (i.e., calculated using values at or near the method detection limit) may not 
8

account adequately for data measurement variability, because the measurement error associated 

with those values provides a large degree of uncertainty.

The expected measurement imprecision for an emissions value occurring at or near the 

detection limit is about 40 to 50 percent. Relative pollutant measurement imprecision decreases 

to a consistent 10 to 15 percent for values measured at a level about three times the method 

detection limit (ASME, 2001).

The approach taken to account for measurement variability includes defining a detection 

limit that is representative of the data used in establishing a MACT floor emission limitation and 

also minimizes the influence of an outlier test-specific method detection limit value. The EPA 

has developed a list of representative detection levels (RDL) from available pollutant-specific 

method detection levels (Westlin and Merrill, 2011). These RDL values are then multiplied by 

three to decrease measurement imprecision to around 10 to 15 percent (as noted in the previous 

paragraph), resulting in values referred to as “3xRDL” values.

The appropriate 3xRDL value is compared to the calculated UPL value for each pollutant 

and subcategory. The larger of the 3xRDL value and the calculated UPL value is used for the 

MACT floor emission limit to ensure that measurement variability is adequately addressed. This 

check was part of the variability analysis for all existing MACT floors that had below detection 

level (BDL) or detection level limited (DLL) run data present in the best performing datasets.

For more information regarding the general use of the UPL and why it is appropriate for 

calculating MACT floors, see the memorandum Use of the Upper Prediction Limit for 

Calculating MACT Floors (Telander, 2014a).

V. MACT Floor Analysis Methodology

Step 1.

The first step in the MACT floor analysis was to calculate an average emission value for 

each source per pollutant based on the available test data.

For any run fractions per test run marked as “< method detection limit (or other reporting 

limit)” the fraction was considered BDL.

2 For this analysis, the method detection limit for that 

fraction was used as the mass to calculate a run value (e.g., lb/ton). For PM runs, if the mass was 

below the 1 milligram (mg) RDL value, 1 mg was used as the mass to calculate a run value

(Raymond, 2014a). Step 6 was added to the MACT Floor Calculation Steps to account for 

datasets with BDL values.

Step 2.

Once an average emission value was calculated for each source, in each subcategory and 

pollutant, all of the individual average emission values were ranked from lowest to highest value. 

See Appendix A for the rankings for each pollutant and subcategory.

 2 For the EPA Method 29 multi-metals test, each metal lab analysis typically has two separate fractions: front-half 

(filter) and back-half (impinger catch); mercury can have three additional back-half fractions.
9

Step 3.

From the rankings shown in Appendix A, the best performing sources were identified

consistent with the criteria in CAA section 112(d)(3) for determining MACT floors for new and 

existing sources. These sources are referred to as the “MACT floor pool.” For the new source 

MACT floors, the best controlled similar source was identified from the sources that had

individual source test run data in the survey dataset. For the existing source MACT floors, the 

number of sources in the MACT floor pool was determined on an individual subcategory basis,

as described in Table 1.
10

Table 1. Number of Sources in Existing Source MACT Floor Pool

Pollutant Subcategory

No. 

Sources 

Nationwide

No. 

Sources 

with Data

No. 

Sources in 

MACT Floor 

Pool Based on

Hg Floor tile roller kilns <30 7 5 best performing 5 

sources

PM <30 10 5 best performing 5 

sources

D/F (TEQ) <30 6 5 best performing 5 

sources

D/F (TEQ) Floor tile press dryers <30 4 4 best performing 5 

sources

D/F (TEQ) Floor tile spray dryers <30 5 5 best performing 5 

sources

Hg Wall tile roller kilns <30 1 1 best performing 5 

sources

PM <30 1 1 best performing 5 

sources

D/F (TEQ) <30 1 1 best performing 5 

sources

D/F (TEQ) Wall tile spray dryers <30 1 1 best performing 5 

sources

Hg Tile glaze lines <30 3 3 best performing 5 

sources

PM <30 3 3 best performing 5 

sources

Hg First-fire sanitaryware tunnel 

kilns <30 5 5 best performing 5 

sources

PM <30 6 5 best performing 5 

sources

D/F (TEQ) <30 5 5 best performing 5 

sources

PM First-fire sanitaryware manual 

glaze application <30 3 3 best performing 5 

sources

PM First-fire sanitaryware spray 

machine glaze application <30 3 3 best performing 5 sources

PM First-fire sanitaryware robot 

glaze application <30 4 4 best performing 5 sources

Step 4.

Each MACT floor dataset (for each subcategory and pollutant) was evaluated for kurtosis 

and skewness to determine the distribution, as described in Section IV.A of this memorandum.
11

Step 5.

After determining the type of data distribution for the dataset, the UPL was calculated 

using the corresponding equation for the distribution for that dataset, as described in 

Section IV.A of this memorandum. See Appendix B for UPL summary tables for new and 

existing sources.

Step 6.

For source datasets that contained BDL or DLL data, there was an additional step taken 

after the subcategory UPL was calculated. The results of the UPL calculation were compared to 

the 3xRDL value of the relevant performance test method(s) (Westlin and Merrill, 2011). As 

described in Section IV, this step ensures that data measurement variability is addressed.

The 3xRDL values in the guidance document (Westlin and Merrill, 2011) were given in 

units of concentration; specifically micrograms per dry standard cubic meter [μg/dscm] with no 

oxygen correction for metals and PM and nanograms per dry standard cubic meter (ng/dscm) 

with no oxygen correction for D/F TEQ. The PM emission limits for the proposed CC NESHAP

are in units of pound per ton (lb/ton) of ware produced or glaze sprayed. The proposed Hg 

emission limits are in units of lb/ton of ware produced or glaze sprayed. The proposed D/F TEQ 

emission limits are in units of nanograms per dry standard cubic meter at 7 percent oxygen 

(ng/dscm @7% O2). In order to compare the calculated UPL to the 3xRDL, the 3xRDL value 

was converted to the units of the emission limits using a ratio of the emission data in the units of 

interest (e.g., lb/ton ware) to the emission data in μg/dscm (uncorrected) for metals and PM or 

ng/dscm (uncorrected) for D/F TEQ. See Appendix C for more details about the conversion of 

the 3xRDL values to the units of measure used in UPL calculations.

The converted 3xRDL value was then compared to the calculated UPL in the same units 

of measure. If the calculated UPL value was less than the 3xRDL value, the 3xRDL value was 

used as the basis for the standard because the 3xRDL value provides the lowest emission rate 

that can be measured using the performance test method while maintaining a relative method 

precision on the order of 10 to 20 percent of the measured value. If the UPL value was equal to 

or greater than the 3xRDL value, then the UPL value was used as the basis for the standard.

Step 7.

For limited datasets with less than seven data points, the steps outlined in the 

memorandum Approach for Applying the Upper Prediction Limit to Limited Datasets (Telander, 

2014b) were followed. See Appendix D for more details about limited datasets.

VI. MACT Floor Analysis Results

Tables 2 and 3 present the existing source and new source MACT floor values 

determined for the CC source category. 
12

Table 2. Proposed Existing Source MACT Floors

Subcategory Pollutant Avg. 99% UPL 3xRDL

MACT 

Floor Unit of Measure

Floor tile roller 

kilns Hg 7.8E-05 1.3E-04 2.5E-06 1.3E-04 lb/ton

PM 0.054 0.18 NA 0.18 lb/ton

D/F TEQ 2.9 4.6 0.20 4.6 ng/dscm @ 7% O2

Floor tile press 

dryers DF/TEQ 0.078 0.17 0.19 0.19 ng/dscm @ 7% O2

Floor tile spray 

dryers DF/TEQ 0.96 44 0.17 44 ng/dscm @ 7% O2

Wall tile roller 

kilns Hg 5.0E-05 2.0E-04 3.1E-06 2.0E-04 lb/ton

PM 0.071 0.20 NA 0.20 lb/ton

D/F TEQ 0.065 0.17 0.17 0.17 ng/dscm @ 7% O2

Wall tile spray 

dryers D/F TEQ 0.053 0.12 0.12 0.12 ng/dscm @ 7% O2

Tile glaze lines Hg 2.0E-05 4.9E-05 1.6E-04 1.6E-04 lb/ton

PM 0.67 1.9 0.28 1.9 lb/ton

First-fire 

sanitaryware 

tunnel kilns

Hg 1.6E-04 2.6E-04 8.6E-06 2.6E-04 lb/ton

PM 0.12 0.33 NA 0.33 lb/ton

D/F TEQ 0.81 1.5 0.15 1.5 ng/dscm @ 7% O2

First-fire 

sanitaryware

manual glaze 

application

PM 14 33 NA 33 lb/ton

First-fire 

sanitaryware 

spray machine 

glaze 

application

PM 5.9 12 NA 12 lb/ton

First-fire 

sanitaryware 

robot glaze 

application

PM 4.4 8.8 NA 8.8 lb/ton

NA: Not Applicable
13

Table 3. Proposed New Source MACT Floors

Subcategory Pollutant Avg. 99% UPL 3xRDL

MACT 

Floor Unit of Measure

Floor tile roller 

kilns

Hg 3.5E-05 3.9E-05 NA 3.9E-05 lb/ton

PM 0.020 0.027 NA 0.027 lb/ton

D/F TEQ 1.1 1.5 0.20 1.5 ng/dscm @ 7% O2

Floor tile press 

dryers DF/TEQ 0.0070 0.012 0.19 0.19 ng/dscm @ 7% O2

Floor tile spray 

dryers DF/TEQ 0.010 0.015 0.17 0.17 ng/dscm @ 7% O2

Wall tile roller 

kilns

Hg 5.0E-05 2.0E-04 3.1E-06 2.0E-04 lb/ton

PM 0.071 0.20 NA 0.20 lb/ton

D/F TEQ 0.065 0.17 0.17 0.17 ng/dscm @ 7% O2

Wall tile spray 

dryers D/F TEQ 0.053 0.12 0.12 0.12 ng/dscm @ 7% O2

Tile glaze lines Hg 7.4E-06 3.4E-05 1.6E-04 1.6E-04 lb/ton

PM 0.15 0.61 0.28 0.61 lb/ton

First-fire 

sanitaryware 

tunnel kilns

Hg 6.4E-05 1.2E-04 8.6E-06 1.2E-04 lb/ton

PM 0.092 0.095 NA 0.095 lb/ton

D/F TEQ 0.23 0.37 0.15 0.37 ng/dscm @ 7% O2

First-fire 

sanitaryware

manual glaze 

application

PM 3.3 3.8 NA 3.8 lb/ton

First-fire 

sanitaryware 

spray machine 

glaze 

application

PM 2.0 3.2 NA 3.2 lb/ton

First-fire 

sanitaryware 

robot glaze

application

PM 1.3 2.2 NA 2.2 lb/ton

NA: Not Applicable

VIII. References

ASME (founded as the American Society of Mechanical Engineers). 2001. Reference Method 

Accuracy and Precision (ReMAP): Phase 1, Precision of Manual Stack Emission 

Measurements. CRTD Vol. 60, February 2001.

Bhaumik, D.K. and Gibbons, R.D. 2004. “An Upper Prediction Limit for the Arithmetic Mean 

of a Lognormal Random Variable.” Technometrics, 46(2):239-248.

Gayen, A. K. 1949. “The Distribution of Student’s t in Random Samples of any Size Drawn 

from Non-Normal Universes.” Biometrika, Vol. 36, No. 3/4 (Dec. 1949), pp. 353-369.
14

Raymond, G. 2014a. Test Data Used in Clay Ceramics Proposed Rule. Memorandum from 

Gabrielle Raymond, RTI International, to Jeff Telander, EPA/OAQPS/SPPD. November 6, 

2014.

Raymond, G. 2014b. Analysis of Potential Subcategories in the Clay Ceramics Source 

Category. Memorandum from RTI International, to Jeff Telander, EPA/OAQPS/SPPD. 

November 6, 2014.

Telander, J. 2014a. Use of the Upper Prediction Limit for Calculating MACT Floors. 

Memorandum from Jeff Telander, EPA/OAQPS/SPPD, to Docket ID No. EPA-HQ-OAR2013-0291. September 9, 2014. 

Telander, J. 2014b. Approach for Applying the Upper Prediction Limit to Limited Datasets. 

Memorandum from Jeff Telander, EPA/OAQPS/SPPD, to Docket ID No. EPA-HQ-OAR2013-0291. September 17, 2014.

Westlin, P. and Merrill, R. 2011. Data and procedure for handling below detection level data in 

analyzing various pollutant emissions databases for MACT and RTR emissions limits. 

Memorandum from Peter Westlin, SPPD/MPG and Raymond Merrill, AQAD/MTG, to 

SPPD management and MACT rule writers. December 13, 2011.
Appendix A

MACT Floor Ranking Tables
A-1

MACT Floor Ranking Tables

For each source per pollutant and subcategory, an average emission value was calculated. 

The average emission values for each source per pollutant and subcategory were than ranked by the 

average emission values to determine the best performing sources. The corresponding Appendix A 

Microsoft Excel® files provide the calculations for each source average emission value per 

pollutant and subcategory. They also provide the rankings of the average emission values per 

pollutant and subcategory. The following tables are summary excerpts of the rankings from those 

Microsoft Excel® files. The MACT floor pool in each table includes those kilns listed above the 

bolded line.
A-2

Table A-1. Proposed Standards for Floor Tile Roller Kilns – Hg lb/ton Ranking

Kiln No Class APCD Type Run Status Type of Tile Average (lb/ton) Variance n

Rank by 

Avg

36 Major None ADL Floor 3.45E-05 2.03E-12 3 1

60 Major Wet Scrubber ADL Floor 9.74E-05 8.12E-11 3 2

61 Major Wet Scrubber ADL Floor 9.74E-05 8.12E-11 3 3

62 Major Wet Scrubber ADL Floor 9.74E-05 8.12E-11 3 4

84 Major None DLL Floor 7.08E-05 3.86E-10 3 5

77 Major None DLL Floor 8.88E-05 1.00E-09 3 6

41 Major DIFF ADL Floor 2.98E-04 9.42E-10 3 7

Table A-2. Proposed Standards for Floor Tile Roller Kilns – PM lb/ton Ranking

Kiln No Class APCD Type

Below 1 mg RDL 

Value Type of Tile Average (lb/ton) Variance n

Rank by 

Avg

77 Major None Floor 0.0198 1.76E-06 3 1

84 Major None Floor 0.0314 4.93E-05 3 2

36 Major None Floor 0.0373 2.21E-05 3 3

76 Major None Floor 0.0383 9.50E-05 3 4

41 Major DIFF Floor 0.1429 2.86E-03 3 5

61 Major Wet Scrubber Floor 0.1808 2.35E-03 6 6

62 Major Wet Scrubber Floor 0.1808 2.35E-03 6 7

63 Major None Floor 0.2162 2.34E-03 6 8

60 Major Wet Scrubber Floor 0.3055 5.07E-02 12 9

59 Major Wet Scrubber Floor 0.3590 5.69E-02 9 10
A-3

Table A-3. Proposed Standards for Floor Tile Roller Kilns – D/F TEQ ng/dscm @ 7% O2 Ranking

Kiln No Class APCD Type Run Status Type of Tile

Average (ng/dscm 

@ 7% O2) Variance n

Rank by 

Avg

84 Major None DLL Floor 1.12 1.38E-02 3 1

60 Major Wet Scrubber DLL Floor 2.84 1.76E-01 3 2

61 Major Wet Scrubber DLL Floor 2.84 1.76E-01 3 3

62 Major Wet Scrubber DLL Floor 2.84 1.76E-01 3 4

41 Major DIFF DLL Floor 3.89 5.10E-01 6 5

77 Major None DLL Floor 5.94 1.02E+00 3 6

Table A-4. Proposed Standards for Floor Tile Press Dryers – D/F TEQ ng/dscm @ 7% O2 Ranking

Dryer No Class APCD Type Run Status Tile Type

Average (ng/dscm 

@ 7% O2) Variance n

Rank by 

Avg

PD-203 Major None DLL Floor 0.0070 9.33E-07 3 1

PD-201 Major None DLL Floor 0.0847 1.02E-03 3 2

PD-202 Major None DLL Floor 0.0885 1.22E-03 3 3

PD-200 Major None DLL Floor 0.1315 2.18E-04 3 4

Table A-5. Proposed Standards for Floor Tile Spray Dryers – D/F TEQ ng/dscm @ 7% O2 Ranking

Dryer No Class APCD Type Run Status Tile Type

Average (ng/dscm 

@ 7% O2) Variance n

Rank by 

Avg

SD-104 Major Fabric Filter DLL Floor 0.0101 8.06E-07 3 1

SD-101 Major Fabric Filter DLL Floor 0.0486 2.60E-04 3 2

SD-102 Major Fabric Filter DLL Floor 0.1511 1.83E-03 3 3

SD-100 Major Wet Scrubber DLL Floor 0.8806 9.74E-03 3 4

SD-103 Major Wet Scrubber DLL Floor 3.6945 7.38E-01 3 5
A-4

Table A-6. Proposed Standards for Wall Tile Roller Kilns – Hg lb/ton Ranking

Kiln No Class APCD Type

Run

Status Type of Tile Average (lb/ton) Variance n

Rank by 

Avg

64, 65, 66, 67, 68, 69, 

70, 71, 72, 73, 74, 75 Major None DLL Wall 5.05E-05 3.95E-09 6 1

Table A-7. Proposed Standards for Wall Tile Roller Kilns – PM lb/ton Ranking

Kiln No Class APCD Type

Below 1 

mg RDL 

Value Type of Tile Average (lb/ton) Variance n

Rank by 

Avg

64, 65, 66, 67, 68, 69, 

70, 71, 72, 73, 74, 75 Major None Wall 0.0710 4.65E-03 9 1

Table A-8. Proposed Standards for Wall Tile Roller Kilns – D/F TEQ ng/dscm @ 7% O2 Ranking

Kiln No Class APCD Type

Run 

Status Type of Tile

Average (ng/dscm 

@ 7% O2) Variance n

Rank by 

Avg

64, 65, 66, 67, 68, 69, 

70, 71, 72, 73, 74, 75 Major None DLL Wall 0.0647 2.13E-03 6 1

Table A-9. Proposed Standards for Wall Tile Spray Dryers – D/F TEQ ng/dscm @ 7% O2 Ranking

Dryer No Class APCD Type Run Status Tile Type

Average (ng/dscm 

@ 7% O2) Variance n

Rank by 

Avg

SD-105 Major Wet Scrubber DLL Wall 0.053 1.29E-04 3 1
A-5

Table A-10. Proposed Standards for Tile Glaze Lines – Hg lb/ton Ranking

Glaze_No Class APCD Type Run Status Average (lb/ton) Variance n

Rank by 

Avg

114; 116; 117; 119 Major Baghouse/Fabric Filter DLL 7.37E-06 4.60E-11 3 1

73, 74, 75 Major Wet Scrubber DLL 2.32E-05 3.49E-10 3 2

71 Major Baghouse/Fabric Filter DLL 2.89E-05 1.46E-10 3 3

Table A-11. Proposed Standards for Tile Glaze Lines – PM lb/ton Ranking

Glaze No. Class APCD Type

Below 1 mg 

RDL Value Average (lb/ton) Variance n

Rank by 

Avg

71 Major Baghouse/Fabric Filter Yes 0.15 6.46E-03 3 1

114; 116; 117; 119 Major Baghouse/Fabric Filter Yes 0.41 5.49E-02 3 2

73, 74, 75 Major Wet Scrubber 1.44 5.38E-02 3 3

Table A-12. Proposed Standards for First-fire Sanitaryware Tunnel Kilns – Hg lb/ton Ranking

Kiln No Class APCD Type Run Status Average (lb/ton) Variance n

Rank by 

Avg

2 Major None DLL 6.44E-05 9.84E-11 3 1

33 Major None ADL 1.43E-04 7.17E-11 3 2

19 Major None ADL 1.96E-04 1.23E-11 3 3

20 Major None ADL 1.96E-04 1.23E-11 3 4

7 Major None DLL 2.19E-04 1.76E-11 3 5
A-6

Table A-13. Proposed Standards for First-fire Sanitaryware Tunnel Kilns – PM lb/ton Ranking

Kiln No Class APCD Type

Below 1 mg RDL 

Value Average (lb/ton) Variance n

Rank by 

Avg

19 Major None 0.092279 8.03E-07 3 1

20 Major None 0.092279 8.03E-07 3 2

33 Major None 0.099641 9.44E-05 3 3

2 Major None 0.129963 7.86E-04 3 4

7 Major None 0.178809 3.60E-02 3 5

9 Major Wet Scrubber 0.213352 4.03E-03 6 6

Table A-14. Proposed Standards for First-fire Sanitaryware Tunnel Kilns – D/F TEQ ng/dscm @ 7% O2 Ranking

Kiln No Class APCD Type Run Flag

Average (ng/dscm 

@ 7% O2) Variance n

Rank by 

Avg

9 Major Wet Scrubber DLL 0.23 2.13E-03 3 1

33 Major None DLL 0.50 2.52E-03 3 2

7 Major None DLL 0.89 3.53E-03 3 3

19 Major None DLL 1.20 9.27E-03 3 4

20 Major None DLL 1.20 9.27E-03 3 5

Table A-15. Proposed Standards for First-fire Sanitarware Manual Glaze Application – PM lb/ton Ranking

Glaze No Class APCD Type

Below 1 mg 

RDL Value Glaze Method

Average

(lb/ton) Variance n

Rank 

by 

Avg

57 Major Water Curtain Manual 3.33 3.06E-02 3 1

2 Major Water Curtain Manual 16.62 1.44E+00 3 2

14 Major Water Weir Manual 22.84 6.16E+01 3 3
A-7

Table A-16. Proposed Standards for First-fire Sanitarware Spray Machine Glaze Application – PM lb/ton Ranking

Glaze Line ID Class APCD Type

Below 1 mg 

RDL Value Glaze Method

Average

(lb/ton) Variance n

Rank 

by Avg

15 Major Water Weir Spray Machine 1.95 4.67E-02 3 1

3 Major Water Curtain Spray Machine 6.53 2.17E-01 3 2

8 Major Water Curtain Spray Machine 9.32 2.07E+00 3 3

Table A-17. Proposed Standards for First-fire Sanitarware Robot Glaze Application – PM lb/ton Ranking

Glaze Line ID Class APCD Type

Below 1 mg 

RDL Value Glaze Method

Average 

(lb/ton) Variance n

Rank 

by Avg

19 Major Water Curtain Robot 1.32 1.01E-01 3 1

39 Major Water Curtain Robot 3.26 1.14E+00 3 2

5 Major Water Curtain Robot 6.28 2.70E+00 3 3

48 Major Water Curtain Robot 6.84 4.01E-01 3 4
Appendix B

UPL Tables
B-1

UPL Tables

Once the best performing sources were identified per pollutant and subcategory, the 

existing and new source UPL values were calculated. The corresponding Appendix B Microsoft

Excel® files provide the calculations for each existing and new source UPL per pollutant and 

subcategory. They also provide a summary of the UPL values per pollutant and subcategory. 

The following tables are summary excerpts of the UPL values from those Microsoft Excel®

files.
B-2

Table B-1. Proposed Standards Existing Source UPL Summary

Subcategory Pollutant

No. of 

Sources 

Industrywide

No. of 

Sources 

with Data

Determination of 

No. of Sources 

in MACT Floor

No. of Sources 

in MACT Floor 

(N)

No. Data Points 

in MACT Floor 

(n)

Average 

of Top 

Sources UPL

Unit of 

Measure

Data 

Distribution

Floor tile roller kilns

Hg 27 7 best performing 5 

sources

5 15 7.8E-05 1.3E-04 lb/ton Normal

PM 27 10 best performing 5 

sources

5 15 0.054 0.18 lb/ton Skewed/ 

Unknown

D/F TEQ 27 6 best performing 5 

sources

5 18 2.9 4.6 ng/dscm 

@ 7% O2

Normal

Floor tile press dryers DF/TEQ 5 4 best performing 5 

sources

4 12 0.078 0.17 ng/dscm 

@ 7% O2

Normal

Floor tile spray dryers DF/TEQ 11 5 best performing 5 

sources

5 15 0.96 44 ng/dscm 

@ 7% O2

Lognormal

Wall tile roller kilns

Hg 14 1 best performing 5 

sources

1 6 5.0E-05 2.0E-04 lb/ton Normal

PM 14 1 best performing 5 

sources

1 9 0.071 0.20 lb/ton Normal

D/F TEQ 14 1 best performing 5 

sources

1 6 0.065 0.17 ng/dscm 

@ 7% O2

Normal

Wall tile spray dryers D/F TEQ 5 1 best performing 5 

sources

1 3 0.053 0.12 ng/dscm 

@ 7% O2

Normal

Tile glaze lines

Hg 24 3 best performing 5 

sources

3 9 2.0E-05 4.9E-05 lb/ton Lognormal

PM 24 3 best performing 5 

sources

3 9 0.67 1.9 lb/ton Normal

First-fire sanitaryware 

tunnel kilns

Hg 11 5 best performing 5 

sources

5 15 1.6E-04 2.6E-04 lb/ton Normal

PM 11 6 best performing 5 

sources

5 15 0.12 0.33 lb/ton Skewed/ 

Unknown

D/F TEQ 11 5 best performing 5 

sources

5 15 0.81 1.5 ng/dscm 

@ 7% O2

Normal

First-fire sanitaryware 

manual glaze 

application

PM 14 3 best performing 5 

sources

3 9 14 33 lb/ton Normal

First-fire sanitaryware 

spray machine glaze 

application

PM 4 3 best performing 5 

sources

3 9 5.9 12 lb/ton Normal
B-3

Subcategory Pollutant

No. of 

Sources 

Industrywide

No. of 

Sources 

with Data

Determination of 

No. of Sources 

in MACT Floor

No. of Sources 

in MACT Floor 

(N)

No. Data Points 

in MACT Floor 

(n)

Average 

of Top 

Sources UPL

Unit of 

Measure

Data 

Distribution

First-fire sanitaryware 

robot glaze 

application

PM 10 4 best performing 5 

sources

4 12 4.4 8.8 lb/ton Normal
B-4

Table B-2. Proposed Standards New Source UPL Summary

Subcategory Pollutant

No. of 

Sources 

Industrywide

No. of 

Sources 

with Data

Determination of 

No. of Sources 

in MACT Floor

No. of Sources 

in MACT Floor 

(N)

No. Data Points 

in MACT Floor 

(n)

Average 

of Top 

Sources UPL

Unit of 

Measure

Data 

Distribution

Floor tile roller kilns

Hg 27 7 best performing 5 

sources

1 3 3.5E-05 3.9E-05 lb/ton Lognormal

PM 27 10 best performing 5 

sources

1 3 0.020 0.03 lb/ton Normal

D/F TEQ 27 6 best performing 5 

sources

1 3 1.1 1.5 ng/dscm 

@ 7% O2

Lognormal

Floor tile press dryers DF/TEQ 5 4 best performing 5 

sources

1 3 0.0070 0.012 ng/dscm 

@ 7% O2

Normal

Floor tile spray dryers DF/TEQ 11 5 best performing 5 

sources

1 3 0.010 0.015 ng/dscm 

@ 7% O2

Normal

Wall tile roller kilns

Hg 14 1 best performing 5 

sources

1 6 5.0E-05 2.0E-04 lb/ton Normal

PM 14 1 best performing 5 

sources

1 9 0.071 0.20 lb/ton Normal

D/F TEQ 14 1 best performing 5 

sources

1 6 0.065 0.17 ng/dscm 

@ 7% O2

Normal

Wall tile spray dryers D/F TEQ 5 1 best performing 5 

sources

1 3 0.053 0.12 ng/dscm 

@ 7% O2

Normal

Tile glaze lines

Hg 24 3 best performing 5 

sources

1 3 7.4E-06 3.4E-05 lb/ton Lognormal

PM 24 3 best performing 5 

sources

1 3 0.15 0.61 lb/ton Normal

First-fire sanitaryware 

tunnel kilns

Hg 11 5 best performing 5 

sources

1 3 6.4E-05 1.2E-04 lb/ton Normal

PM 11 6 best performing 5 

sources

1 3 0.092 0.095 lb/ton Lognormal

D/F TEQ 11 5 best performing 5 

sources

1 3 0.23 0.37 ng/dscm 

@ 7% O2

Lognormal

First-fire sanitaryware 

manual glaze 

application

PM 14 3 best performing 5 

sources

1 3 3.3 3.8 lb/ton Lognormal

First-fire sanitaryware 

spray machine glaze 

application

PM 4 3 best performing 5 

sources

1 3 2.0 3.2 lb/ton Normal
B-5

Subcategory Pollutant

No. of 

Sources 

Industrywide

No. of 

Sources 

with Data

Determination of 

No. of Sources 

in MACT Floor

No. of Sources 

in MACT Floor 

(N)

No. Data Points 

in MACT Floor 

(n)

Average 

of Top 

Sources UPL

Unit of 

Measure

Data 

Distribution

First-fire sanitaryware 

robot glaze 

application

PM 10 4 best performing 5 

sources

1 3 1.3 2.2 lb/ton Lognormal
Appendix C

Conversion of 3xRDL Values to Units Other Than Concentration to Facilitate Comparison 

with UPL Values
C-1

Conversion of 3xRDL Values to Units Other Than Concentration to Facilitate Comparison 

with UPL Values

The standard 3xRDL values developed for specific pollutants at certain sample volumes 

are presented in a guidance document developed by the EPA (Westlin and Merrill, 2011).

For the CC MACT floors, the units of measure used to develop the UPL values were 

lb/ton ware, lb/ton glaze sprayed, and ng/dscm @ 7% O2. However, the 3xRDL values from the 

guidance document are given in units of concentration, specifically μg/dscm for metals and PM

and ng/dscm for D/F TEQ. In order to compare the calculated UPL with the 3xRDL for a 

particular pollutant, we needed to convert the 3xRDL value to the units of measure used in the 

UPL calculation. This appendix describes the procedure used for that conversion.

The Appendix C Microsoft Excel® file provides the run-by-run test data and the 

calculations used to convert the 3xRDL values for each pollutant and subcategory. The tables in 

this appendix are summary excerpts of the information from that Microsoft Excel® file.

1. For all of the sources in the MACT floor pool, we looked at each test run that was 

flagged by respondents to the CC survey as below detection level (BDL) or detection 

level limited (DLL). If any test runs were BDL or DLL, we proceeded with the following 

steps to convert the 3xRDL value to the units of measure used in UPL. For PM, if any 

run was below the 1 mg RDL value, we also proceeded with the following steps. If all 

runs were above detection level (ADL) and all PM runs were above 1 mg, it was not 

necessary to compare a 3xRDL value to the UPL; instead, we used the UPL value for 

MACT floor. For the CC source category, there were values below the 1 mg RDL for 

PM, and values BDL/DLL for Hg and D/F TEQ.

2. For all of the sources in the PM, Hg, and D/F TEQ MACT existing source floor pools, we 

compiled the available concentration, oxygen-corrected concentration, and lb/ton values 

for those sources and noted the sample volume (dscm) for all runs used in the dataset.

3. We calculated the ratio of the run-by-run data for PM lb/ton / μg/dscm; Hg lb/ton / 

μg/dscm; and D/F TEQ ng/dscm @ 7% O2 / ng/dscm.

4. We calculated the average of all the ratio values. Table C-1 provides the calculated 

average of all of the ratio values for each pollutant and subcategory.
C-2

Table C-1. Average of All the Run-by-Run Ratios

Subcategory Pollutant Average Ratio Unit of Measure

Floor tile roller kilns Hg 5.94E-06 lb/ton / μg/dscm

PM NA lb/ton / μg/dscm

D/F TEQ 7.14E+00 ng/dscm @ 7% O2 / ng/dscm

Floor tile press dryers DF/TEQ 6.70E+00 ng/dscm @ 7% O2 / ng/dscm

Floor tile spray dryers DF/TEQ 6.00E+00 ng/dscm @ 7% O2 / ng/dscm

Wall tile roller kilns Hg 7.30E-06 lb/ton / μg/dscm

PM NA lb/ton / μg/dscm

D/F TEQ 5.80E+00 ng/dscm @ 7% O2 / ng/dscm

Wall tile spray dryers D/F TEQ 4.32E+00 ng/dscm @ 7% O2 / ng/dscm

Tile glaze lines Hg 3.77E-04 lb/ton / μg/dscm

PM 3.77E-04 lb/ton / μg/dscm

First-fire sanitaryware tunnel kilns Hg 2.04E-05 lb/ton / μg/dscm

PM NA lb/ton / μg/dscm

D/F TEQ 5.24E+00 ng/dscm @ 7% O2 / ng/dscm

First-fire sanitaryware manual glaze application PM NA lb/ton / μg/dscm

First-fire sanitaryware spray machine glaze 

application PM NA lb/ton / μg/dscm

First-fire sanitaryware robot glaze application PM NA lb/ton / μg/dscm

NA: Not Applicable 

5. We identified the typical sample volume (in units of dscm) for each dataset. For Hg, PM, 

and D/F TEQ, the typical sample volume was equal to 4 dscm for most CC tests. For PM 

from sanitaryware glazing tests, the typical sample volume was equal to 1 dscm.

6. We identified the appropriate 3xRDL concentration values for the typical sample volume 

of the test runs in this dataset (4 dscm) to use from the memorandum Data and procedure 

for handling below detection level data in analyzing various pollutant emissions 

databases for MACT and RTR emissions limits (Westlin and Merrill, 2011). Table C-2 

displays the appropriate 3xRDL concentration values for Hg, PM, and D/F TEQ at the 

typical sample volume of 4 dscm and other various dscm tests.
C-3

Table C-2. 3xRDL Values from Guidance Document (Westlin and Merrill, 2011)

Pollutant RDL (μg)

3xRDL 

(μg)

3xRDL Concentrations (μg/dscm)

1 dscm test 2 dscm test 3 dscm test 4 dscm test

PM filterable 

(Method 5) 1.0E+03 3.0E+03 3.0E+03 1.5E+03 1.0E+03 7.5E+02

Mercury (Method 29) 

analyzed by Cold 

Vapor AA

5.6E-01 1.7E+00 1.7E+00 8.4E-01 5.6E-01 4.2E-01

Pollutant RDL (ng)

3xRDL 

(ng)

3xRDL Concentrations (ng/dscm)

1 dscm test 2 dscm test 3 dscm test 4 dscm test

Utilities TEQ 

(Method 23) 3.6E-02 1.1E-01 1.1E-01 5.5E-02 3.7E-02 3.7E-02

7. We multiplied the appropriate 3xRDL concentration value for the typical sample volume 

by the average ratio in Table C-1 to convert the 3xRDL value into the units of measure 

used in the UPL calculation (e.g., lb/ton or ng/dscm @7% O2). Table C-3 displays a

summary of the converted 3xRDL values.
C-4

Table C-3. Converted 3xRDL Values

Subcategory Pollutant

Average 

Ratio

Average Ratio 

Units Of 

Measure

3xRDL at 

Typical Sample 

Volume 

(μg/dscm for 

Hg; ng/dscm 

for D/F TEQ)

Converted 

3xRDL 

Value

Converted 

3xRDL Value 

Units Of 

Measure

Floor tile roller kilns

Hg 5.94E-06 lb/ton / μg/dscm 4.20E-01 2.50E-06 lb/ton

PM NA lb/ton / μg/dscm NA NA lb/ton

D/F TEQ 7.14E+00 ng/dscm @ 7% O2

/ ng/dscm 2.80E-02 2.00E-01 ng/dscm @ 7% O2

Floor tile press dryers DF/TEQ 6.70E+00 ng/dscm @ 7% O2

/ ng/dscm 2.80E-02 1.88E-01 ng/dscm @ 7% O2

Floor tile spray dryers DF/TEQ 6.00E+00 ng/dscm @ 7% O2

/ ng/dscm 2.80E-02 1.68E-01 ng/dscm @ 7% O2

Wall tile roller kilns

Hg 7.30E-06 lb/ton / μg/dscm 4.20E-01 3.07E-06 lb/ton

PM NA lb/ton / μg/dscm NA NA lb/ton

D/F TEQ 5.80E+00 ng/dscm @ 7% O2

/ ng/dscm 2.80E-02 1.62E-01 ng/dscm @ 7% O2

Wall tile spray dryers D/F TEQ 4.32E+00 ng/dscm @ 7% O2

/ ng/dscm 2.80E-02 1.21E-01 ng/dscm @ 7% O2

Tile glaze lines Hg 3.77E-04 lb/ton / μg/dscm 4.20E-01 1.58E-04 lb/ton

PM 3.77E-04 lb/ton / μg/dscm 7.50E+02 2.83E-01 lb/ton

First-fire sanitaryware tunnel kilns

Hg 2.04E-05 lb/ton / μg/dscm 4.20E-01 8.57E-06 lb/ton

PM NA lb/ton / μg/dscm NA NA lb/ton

D/F TEQ 5.24E+00 ng/dscm @ 7% O2

/ ng/dscm 2.80E-02 1.47E-01 ng/dscm @ 7% O2

First-fire sanitaryware manual glaze 

application PM NA lb/ton / μg/dscm NA NA lb/ton

First-fire sanitaryware spray machine glaze 

application PM NA lb/ton / μg/dscm NA NA lb/ton

First-fire sanitaryware robot glaze application PM NA lb/ton / μg/dscm NA NA lb/ton
C-5

8. We compared the 3xRDL value to the calculated UPL.

a. If the 3xRDL value was less than or equal to the calculated UPL value, we used the UPL value as the MACT floor 

emission limit.

b. If the 3xRDL value was greater than the calculated UPL value, we used the 3xRDL value as the MACT floor emission 

limit.

c. Table C-4 and C-5 summarize the results of the calculated UPL and 3xRDL comparison for existing and new source 

floors.
C-6

Table C-4. Existing Source Floors

Subcategory Pollutant

Converted 

3xRDL Valuea UPL Floor

Floor Based 

On Units Of Measure

Floor tile roller kilns Hg 2.50E-06 1.3E-04 1.3E-04 UPL lb/ton

PM NA 0.18 0.18 UPL lb/ton

D/F TEQ 2.00E-01 4.6 4.6 UPL ng/dscm @ 7% O2

Floor tile press dryers DF/TEQ 1.88E-01 0.17 0.19 3xRDL ng/dscm @ 7% O2

Floor tile spray dryers DF/TEQ 1.68E-01 44 44 UPL ng/dscm @ 7% O2

Wall tile roller kilns Hg 3.07E-06 2.0E-04 2.0E-04 UPL lb/ton

PM NA 0.20 0.20 UPL lb/ton

D/F TEQ 1.62E-01 0.17 0.17 UPL ng/dscm @ 7% O2

Wall tile spray dryers D/F TEQ 1.21E-01 0.14 0.14 UPL ng/dscm @ 7% O2

Tile glaze lines Hg 1.58E-04 4.9E-05 1.6E-04 3xRDL lb/ton

PM 2.83E-01 1.9 1.9 UPL lb/ton

First-fire sanitaryware tunnel kilns Hg 8.57E-06 2.6E-04 2.6E-04 UPL lb/ton

PM NA 0.33 0.33 UPL lb/ton

D/F TEQ 1.47E-01 1.5 1.5 UPL ng/dscm @ 7% O2

First-fire sanitaryware manual 

glaze application PM NA 33 33 UPL lb/ton

First-fire sanitaryware spray 

machine glaze application PM NA 12 12 UPL lb/ton

First-fire sanitaryware robot glaze 

application PM NA 8.8 8.8 UPL lb/ton

a NA: Not Applicable if all runs in the MACT floor pool were ADL for Hg and D/F TEQ; and above the 1 mg RDL value for PM.
C-7

Table C-5. New Source Floors

Subcategory Pollutant

Converted 

3xRDL Valuea UPL Floor

Floor Based 

On Units Of Measure

Floor tile roller kilns Hg NA 3.9E-05 3.9E-05 UPL lb/ton

PM NA 0.027 0.027 UPL lb/ton

D/F TEQ 2.00E-01 1.5 1.5 UPL ng/dscm @ 7% O2

Floor tile press dryers DF/TEQ 1.88E-01 0.012 0.19 3xRDL ng/dscm @ 7% O2

Floor tile spray dryers DF/TEQ 1.68E-01 0.015 0.17 3xRDL ng/dscm @ 7% O2

Wall tile roller kilns Hg 3.07E-06 2.0E-04 2.0E-04 UPL lb/ton

PM NA 0.20 0.20 UPL lb/ton

D/F TEQ 1.62E-01 0.17 0.17 UPL ng/dscm @ 7% O2

Wall tile spray dryers D/F TEQ 1.21E-01 0.12 0.12 3xRDL ng/dscm @ 7% O2

Tile glaze lines Hg 1.58E-04 3.4E-05 1.6E-04 3xRDL lb/ton

PM 2.83E-01 0.61 0.61 UPL lb/ton

First-fire sanitaryware tunnel kilns Hg 8.57E-06 1.2E-04 1.2E-04 UPL lb/ton

PM NA 0.095 0.095 UPL lb/ton

D/F TEQ 1.47E-01 0.37 0.37 UPL ng/dscm @ 7% O2

First-fire sanitaryware manual 

glaze application PM NA 3.8 3.8 UPL lb/ton

First-fire sanitaryware spray 

machine glaze application PM NA 3.2 3.2 UPL lb/ton

First-fire sanitaryware robot glaze 

application PM NA 2.2 2.2 UPL lb/ton

a NA: Not Applicable if all runs in the MACT floor pool were ADL for Hg and D/F TEQ; and above the 1 mg RDL value for PM.
Appendix D

Limited Datasets
D-1

Limited Datasets

For the clay ceramics source category, we have limited datasets for the following 

pollutants and subcategories: Hg, PM, and TEQ for new floor tile roller kilns; TEQ for new floor 

tile press dryers and spray dryers; Hg and TEQ for existing and new wall tile roller kilns; TEQ 

for existing and new wall tile spray dryers; Hg and PM for new tile glaze lines; Hg, PM, and 

TEQ for new sanitaryware tunnel kilns; PM for new sanitaryware manual, spray machine, and 

robot glaze spray booths. Therefore, we evaluated these specific datasets to determine whether it 

is appropriate to make any modifications to the approach used to calculate MACT floors for each 

of these datasets.

For each dataset, we performed the following steps: ensuring that we selected the data 

distribution that best represents each dataset; ensuring that the correct equation for the 

distribution was then applied to the data; and comparing individual components of each limited 

dataset to determine if the standards based on limited datasets reasonably represent the 

performance of the units included in the dataset (Telander, 2014b). We determined that no 

changes to our standard floor calculation procedure were warranted and are proposing the 

MACT floor limits as calculated (Telander, 2014b).