## 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 (C C ) 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 ass ociated 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 surroga te) , and dioxin s /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 tha t 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 r eferred 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
emi ssion 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 owner s and operators conducted by the EPA in 2008 and 2010 under s ection
114 of the C AA. 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

, 2014 a )

.

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 Cl 2 

## ; 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 d ioxin s and f urans (D/F)

. MACT floor levels for HAP metals other than Hg were analyzed us ing 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 aci d gases. A health

- based emission limit was developed for acid gases under CAA section 112(d)(4)

. The rationale behind these standards is
di scussed in the preamble to the C C 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 subcateg ory

. 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 inf ormation collected by the Agency for development of the NESHAP for this source category (R aymond,
2014b )

. Based on this review, the EPA concluded that there are significant de sign and operational differences in CC kiln s , 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 til e 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 ro ller 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 glazi ng 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 exi sting CC robot glazing operations for sanitaryware.

IV. MACT Floor Analysis Concepts

A. Upper Prediction Limit

T he MACT floor analysis for CC manufacturing uses an upper p rediction l imit (UPL) approach to identify the average emission limitation achieved by th os e best performing sources

. The EPA us es a UPL approach in its MACT floor analyses because it incorporates the average performance of the best performing source s 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
confiden ce 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 1 00 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

- specifi ed 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

- dat a point variability

. The predictions derive from the dataset to which it is applied, and, thus, can be applied to any type of data.

The re are different equations for calculating a UPL based on the distribution of the
data set . Data can be normally distrib uted, 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 source s ’ 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 positiv e 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 Micr osoft 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

x i 

## = individual source mean

stdev = 

# ( ) ( ) 

# ∑

− −
1 2



### n x x i



## As part of determin ing whether a data distribution can be considered normal, the S value must be compared to t he standard error of the skewness statistic (SES)

. The SES value can be approximated using the following equation :


# ( ) ( ) ( ) ( ) ( ) 3 1 2 1 6

+ +

− − ×

=
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 gi ven 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 ) :



# ( ) ( ) ( ) ( ) ( ) ( ) ( ) 3 2 1 3

3 2 1 1 2 4



## − − −

−     

          

−

− − − +

= 

# ∑

n n n
stdev x x

n n n n n Kurtosis

## 5 T his 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, f or datasets with three run values, kurtosis is estimated using the following equation:



# ( )

( ) ( ) 3 1 4 1 4



## −

− +

= 

# ∑

= 

## stdev n 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 t he standard error of the kurtosis statistic (SEK)

. The SEK value can be approximated using the following equation : 

# ( ) ( ) ( ) ( ) ( ) ( ) 5 3 3 2 1 24 2



## +

− +

− −

=
n n n n n 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, i f 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 U PL 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 k urtosis and skewness

. If both tests of the log

- transformed data indicated th e 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

approp riate data distribution for those datasets, the s kewness/SES values from raw data were compared to the skewness/SES values from log

- transformed data. T he smaller skewness/SES
value was selected as an indication of a larger likelihood of the data to come from t he corresponding distribut ion.

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, an d skewed/unknown distribution datasets are provided
below.

## 6 Normally Distributed Data s et



##      

+ + =
m n s t x UPL df 

## 1 1 2

99

. 0

,



## 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 = n umber of test runs = 

# ∑

= N

i i 

## n 1



## m = n umber of future test runs in the compliance average

N = n umber of sources

s 2



## = pooled variance calculated as 

# ( ) 

# ∑

= 

## − = n

i i 

## x x

n s 1 2

2 

## 1



## t df, 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” functi on in Microsoft Excel® software

df = degrees of freedom calculated as 

# ( ) 1

1 

## − = 

# ∑

= N

i i 

## n df

Lognormally Distributed Data s et (Bhaumik and Gibbons

, 2004) 

# ( ) ( )        

− + +

− + = + + +



## 1 2 ˆ ˆ 1 4 2

ˆ ˆ 2 2 ˆ ˆ ˆ 2 99

. 0 2 ˆ

ˆ 2 2 2 2



## n n e m e me

m z e UPL σ σ σ m σ σ m σ m



## where:

μ ˆ 

## =

n y log n

i i 

# ∑

= 1 

### ) (



## = the average of the log transformed data from the data

2 

### ˆ σ 

## = 

# ( ) ( )

1 ˆ

1 2



### − − 

# ∑

=



### n y log n

i i 

### μ



## = variance estimate of the log transformed data

z 0. 99 

## = the 99 th



## - percentile of the log

- normal distribution estimated using the trapezoidal rule approach from the following equation: 

# ( ) ( ) 

# ( ) ( ) 99

. 0 24 6 3 3 3 6 1 99

. 0

0 4 2

2 3 1



## =         +

− − +

− − 

# ∫ z z z z z z z z 

## φ β β

## 7 Skewed/ Unknown Distribution (Non

- Normal/Non

- Lognormal) (Gayen

, 1949)



##      

+ + =
m n s t x UPL

p df 

## 1 1 2

,



## 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 

## n 1



## 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

2 

## 1



## t df,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 

## n df

B. Representative Detection Limit

The imprecision of t est method measurement s 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 dete ction capability. Because of matrix effects,
la boratory 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 ac count 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 limi t 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 p ollutant measurement imprecision decreases

to a consistent 10 to 15 percent for values measured at a lev el 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 mi nimizes 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 eac h 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 exis ting 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 M ACT floors, see th e 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 a s “< 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, 2014 a )

. Step 6 was added to the MACT Floor Calculation Steps to account for
datasets wit h 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 

### Fo r 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 th e ranking s 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 referre d 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 i n 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 s anitaryware manual glaze application <30 3 3 best performing 5

sources

PM First

- fire s anitaryware spray machine glaze application <30 3 3 best performing 5

sources

PM First

- fire s anitaryware 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 determinin g 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 sour ces

.

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) (W estlin 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 th e 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% O 2 

## )

. 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 A ppendix C for more details about the conversion of
the 3xRDL values to the units of measure used in UPL calculations

.

T he converted 3xRDL value was then compared to the calculated UPL in the sa me 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 m aintaining 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.

V I

. M ACT Floor Analysis Results

Table s 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

Subc ategory Pollutant Avg. 99% UPL 3xRDL MACT
Floor Unit of Measure

Floor tile roller
kilns Hg 7.8 E

- 05 1. 3 E

- 04 2.5 E

- 06 1.3E

- 04 lb/ton

PM 0.0 54 0. 1 8 NA 0. 1 8 lb/ton

D/F TEQ 2.9 4.6 0.20 4.6 n g/dscm @ 7% O 2 Floor tile press dryers DF/TEQ 0.078 0.17 0.19 0.19 n g/dscm @ 7% O 2

Floor tile spray dryers DF/TEQ 0.96 44 0.17 44 n g/dscm @ 7% O 2

Wall tile roller
kilns Hg 5.0 E

- 05 2.0 E

- 04 3.1E

- 06 2.0 E

- 04 lb/ton

PM 0.071 0.20 NA 0.20 lb/ton

D/F TEQ 0.065 0.17 0.17 0.17 n g/dscm @ 7% O 2 Wall tile spray dryers D/F TEQ 0.053 0.12 0.12 0.12 n g/dscm @ 7% O 2

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 0.1 2 0. 33 NA 0. 33 lb/ton

D/F TEQ 0.81 1.5 0.15 1.5 n g/dscm @ 7% O 2 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

Subc ategory 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 n g/dscm @ 7% O 2 Floor tile press dryers DF/TEQ 0.0070 0.012 0.19 0.19 n g/dscm @ 7% O 2

Floor tile spray dryers DF/TEQ 0.010 0.015 0.17 0.17 n g/dscm @ 7% O 2

Wall tile roller
kilns Hg 5.0 E

- 05 2.0 E

- 04 3.1E

- 06 2.0 E

- 04 lb/ton

PM 0.071 0.20 NA 0.20 lb/ton

D/F TEQ 0.065 0.17 0.17 0.17 n g/dscm @ 7% O 2 Wall tile spray dryers D/F TEQ 0.053 0.12 0.12 0.12 n g/dscm @ 7% O 2

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 n g/dscm @ 7% O 2 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



## V II I

. 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. 2014 a

. Test Data Used in C lay Ceramics Proposed Rule . Memorandum from Gabrielle Raymond, RTI International, to J eff Telander, EPA/OAQPS/SPP D

. November 6,

2014.

Raymond, G. 2014 b

. 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. 2014 a

. Use of the Upper Prediction Limit for Calculating MACT Floors

. Memorandum from Jeff Telander, EPA/OAQPS/SPPD, to Docket ID No. EPA

- HQ

- OAR

2013

- 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

- OAR

2013

- 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 sub category. They also provide the rankings of the average emission values per pollutant and subcat egory. 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 R anking

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% O 2 

### Ranking

Kiln No Class APCD Type Run Status Type of Tile Average (ng/dscm @ 7% O 2 

### ) 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% O 2 

### Ranking

Dryer No Class APCD Type Run Status Tile Type Average (ng/dscm @ 7% O 2 

### ) 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% O 2 

### Ranking

Dryer No Class APCD Type Run Status Tile Type Average (ng/dscm @ 7% O 2 

### ) 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% O 2 

### Ranking

Kiln No Class APCD Type Run Status Type of Tile Average (ng/dscm @ 7% O 2 

### ) 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% O 2 

### Ranking

Dryer No Class APCD Type Run Status Tile Type Average (ng/dscm @ 7% O 2 

### ) 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% O 2 

### Ranking

Kiln No Class APCD Type Run Flag Average (ng/dscm @ 7% O 2 

### ) 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 sub category, the existing and new source UPL values were calculated. The corresponding Appendix B M icrosoft
Excel ® file s provide the calculations for each existing and new source UPL per pollutant and
sub category. They also provide a summary of the UPL valu es 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% O 2 Normal

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

sources 4 12 0.078 0.17 ng/dscm @ 7% O 2 Normal

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

sources 5 15 0.96 44 ng/dscm @ 7% O 2 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% O 2 Normal

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

sources 1 3 0.053 0.12 ng/dscm @ 7% O 2 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% O 2 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% O 2 Lognormal

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

sources 1 3 0.0070 0.012 ng/dscm @ 7% O 2 Normal

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

sources 1 3 0.010 0.015 ng/dscm @ 7% O 2 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% O 2 Normal

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

sources 1 3 0.053 0.12 ng/dscm @ 7% O 2 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% O 2 Lognormal

First

- fire s anitaryware manual glaze application PM 14 3 best performing 5

sources 1 3 3.3 3.8 lb/ton Lognormal

First

- fire s anitaryware 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 s anitaryware 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 s tandard 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 U PL value s were lb /ton ware, lb/ton glaze sprayed, and n g/ dscm @ 7% O 2



## . However, t he 3xRDL value s 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 Micr osoft Excel ® file provide s the run

- by

- run test data and the
calculations used to convert the 3xRDL values for each pollutant and sub category. The tables in this appendix are summary excerpts of the information from th at Microsoft Excel ® file

.

1. For all of t he sources in the MACT floor pool , we look ed at each test run that was flag ged by respondents to the CC survey as below detection level (BDL) or detection level limited (DLL) . If any test runs we re BDL or DLL, we proceed ed with the following
steps to conv ert 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 we re 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 use d 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 pool s , we compile d the available concentration

, oxygen

- corrected concentration

, and lb/ton values
for those sources and note d the sample volume (dscm) for all runs used in the dataset.

3. We c alculate d the ratio of the run

- by

- run data for PM lb/ton / μg/dscm; Hg lb/ton / μg/dscm; and D/F TEQ n g/dscm @ 7% O 2 

## / n g /dscm

.

4. We c alculate d the average of all the ratio values. Table C

- 1 provides the calculated average of all of the ratio values for each pollutant and sub category.

## C

- 2 Table C

- 1. Average of All the Run

- by

- Run Ratios

Subc ategory Pollutant A verage 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 n g/dscm @ 7% O 2 / n g/dscm
Floor tile press dryers DF/TEQ 6.70E+00 n g/dscm @ 7% O 2 / n g /dscm
Floor tile spray dryers DF/TEQ 6.00E+00 n g/dscm @ 7% O 2 / n g /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 n g/dscm @ 7% O 2 / n g /dscm
Wall tile spray dryers D/F TEQ 4.32E+00 n g/dscm @ 7% O 2 / n g /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 n g/dscm @ 7% O 2 / n g /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 id entif ied the typica l sample volume (in units of dscm) for each dataset

. F or Hg, PM

, and D/F TEQ

, the typical sample volume was equal to 4 dscm for most CC tests. For PM
from s anitaryware g lazing tests, the typical sample volume was equal to 1 dscm.

6. We i de ntif ied the appropriate 3xRDL concentration value s 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
databa ses for MACT and RTR emissions limits ( Westlin and Merrill, 2011 ). Table C

- 2 displays the appropriate 3xRDL concentration v alues 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) 1.0 E +03 3.0 E +03 3.0 E +03 1.5 E +03 1.0 E +03 7.5 E +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 ( n g) 3xRDL ( n g) 3xRDL Concentrations ( n g/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 n g/dscm @7% O 2 

## ). 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% O 2 / ng /dscm 2.80E

- 02 2.00E

- 01 ng/dscm @ 7% O 2

Floor tile press dryers DF/TEQ 6.70E+00 ng/dscm @ 7% O 2 / ng /dscm 2.80E

- 02 1.88E

- 01 ng/dscm @ 7% O 2

Floor tile spray dryers DF/TEQ 6.00E+00 ng/dscm @ 7% O 2 / ng /dscm 2.80E

- 02 1.68E

- 01 ng/dscm @ 7% O 2

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% O 2 / ng /dscm 2.80E

- 02 1.62E

- 01 ng/dscm @ 7% O 2

Wall tile spray dryers D/F TEQ 4.32E+00 ng/dscm @ 7% O 2 / ng /dscm 2.80E

- 02 1.21E

- 01 ng/dscm @ 7% O 2

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% O 2 / ng /dscm 2.80E

- 02 1.47E

- 01 ng/dscm @ 7% O 2

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 Value a 

### 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% O 2 Floor tile press dryers DF/TEQ 1.88E

- 01 0.17 0.19 3xRDL ng/dscm @ 7% O 2 Floor tile spray dryers DF/TEQ 1.68E

- 01 44 44 UPL ng/dscm @ 7% O 2 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% O 2 Wall tile spray dryers D/F TEQ 1.21E

- 01 0.14 0.14 UPL ng/dscm @ 7% O 2 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% O 2 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 T able C

- 5

. New Source Floors

Subcategory Pollutant Converted
3xRDL Value a 

### 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% O 2 Floor tile press dryers DF/TEQ 1.88E

- 01 0.012 0.19 3xRDL ng/dscm @ 7% O 2 Floor tile spray dryers DF/TEQ 1.68E

- 01 0.015 0.17 3xRDL ng/dscm @ 7% O 2 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% O 2 Wall tile spray dryers D/F TEQ 1.21E

- 01 0.12 0.12 3xRDL ng/dscm @ 7% O 2 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% O 2 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 Data s ets

## 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 cal culate 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 t o 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 o ur standard floor calculation procedure were warranted and are proposing the MACT floor limits as calculated (Telander, 2014b).