Date: September 24, 2015 

To: Sharon Nizich, EPA/OAQPS/SPPD 

From: Gabrielle Raymond and Kristin Sroka, RTI International 

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

Brick and Structural Clay Products Manufacturing 

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 brick and structural clay products (BSCP) manufacturing 

industry. The NESHAP regulated emissions of hydrogen fluoride (HF), hydrogen chloride 

(HCl), and particulate matter (PM)—a surrogate for hazardous air pollutant (HAP) metals—from 

tunnel kilns located at BSCP facilities. On March 13, 2007, the D.C. Circuit Court vacated the 

emission standards for BSCP manufacturing due to issues associated with the methodology used 

to determine the minimum regulatory “floors” for new and existing units.1 Therefore, on 

December 18, 2014, the EPA proposed new standards for BSCP manufacturing, including 

standards for HF, HCl, chlorine (Cl2), mercury (Hg), and non-Hg HAP metals (or PM surrogate). 

The EPA provided a 90-day public comment period following proposal of the BSCP 

Manufacturing NESHAP, during which all affected parties were given the opportunity to 

comment on the proposed rule. The EPA has considered the comments received and, as 

appropriate, incorporated them into the final rule. 

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. 

 

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

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

MACT floor analysis for the BSCP Manufacturing source category. This MACT floor analysis 

uses data collected in a survey of BSCP owners and operators conducted by the EPA in 2008 and 

2010 under section 114 of the CAA and data received during the public comment period. The 

emissions data supplied by BSCP owners and operators in response to the survey and the public 

comment period 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 BSCP Final Rule (Raymond, 2015). 

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 BSCP 

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 BSCP facilities (see section IV.B of the preamble to the proposed BSCP Manufacturing 

NESHAP (79 FR 75633) for more information about filterable PM as a surrogate for total nonHg HAP metals). 

MACT floors were not developed for acid gases or D/F. A health-based emission limit 

was developed for acid gases under CAA section 112(d)(4), and work practice standards were 

developed for D/F under CAA section 112(h). The rationale behind these standards is discussed 

in the preamble to the final BSCP Manufacturing NESHAP. 

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 BSCP Manufacturing source category warrants 

subcategorization for the MACT floor analysis, the EPA reviewed BSCP tunnel kiln 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 et. 

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

operational differences in BSCP tunnel kilns that affect the levels of emissions of certain HAP to 

justify subcategorizing BSCP tunnel kilns for the purpose of establishing MACT floors. For the 

BSCP Manufacturing source category, the following two subcategories were identified: 

 Large tunnel kilns: New and existing BSCP tunnel kilns with a design capacity equal to 

or greater than 10 tons per hour (tph) of fired product. 

 Small tunnel kilns: New and existing BSCP tunnel kilns with a design capacity less than 

10 tph of fired product. 
3 

For the final standards, these subcategories were used for the MACT floors for Hg, PM, 

and non-Hg HAP metals. 

IV. MACT Floor Analysis Concepts 

A. Upper Prediction Limit 

The MACT floor analysis for BSCP 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. 

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 
4 

 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 nn 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 n

n

stdev

x x

n n n

n n Kurtosis

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)) 
5 

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. 

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 
6 

 s2 = 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         

where: 

ˆ = 

n

log y n

i  i 1 ( )

 = the average of the log transformed data from the data 

2 ˆ = 

   

1

ˆ 1

2



  

n

log y n

i i  = 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   

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 
7 

 s2 = 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 BSCP 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 BSCP 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 

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 
8 

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

check was part of the variability analysis for all MACT floors. 

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, 2014). 

C. Mercury Raw Material Variability Factor 

The Brick Industry Association (BIA) coordinated with several BSCP facilities to test the 

Hg content of the raw materials used in their kilns and provided the summarized data to the EPA 

(Miller, 2015). The EPA mapped the facilities and quarry locations provided by BIA to identify 

samples collected from the sources in the MACT floor pool, as identified by Step 3 in Section V 

of this memorandum, as well as samples of raw materials from the same geologic deposit as 

those sources in the MACT floor pool, for use in the development of a Hg raw material 

variability factor. 

The BIA provided the Hg content (ppb) for over 160 samples from around the country 

(see Appendix E for data provided by the BIA). Two groups of samples were identified, one in 

Oklahoma/Arkansas (including Boral Bricks facilities in Union City and Muskogee, OK, each of 

which operates a kiln in the Large Tunnel Kiln MACT floor pool) and one in Ohio (including 

Belden Bricks in Sugarcreek, OH, which operates the kilns in the Small Tunnel Kiln MACT 

floor pool). As discussed in Mercury Content of Oklahoma and Ohio Shale Deposits Supplying 

the Brick Industry (Fairchild, 2015), the EPA reviewed the data to characterize the geological 

history of the clay deposits and determined that it is appropriate to use the raw material data from 

the two deposits in the development of the Hg raw material variability factor. 

For each deposit, a facility average of the raw material data was calculated, then the 

deposit average was calculated by averaging the facility averages. Next, the standard deviation 

of the facility averages was calculated. Then the relative standard deviation (RSD) was 

calculated for each deposit by dividing the deposit average by the deposit standard deviation for 

each deposit. The overall RSD is the Oklahoma RSD, as this was the higher of the two RSD 

values. Please see Appendix E for the calculation of the overall RSD. 

The overall RSD, or Hg Raw Material RSD, was then used to calculate the Hg Raw 

Material Variability factor, which was incorporated into each UPL template (Normal, 

Lognormal, and Skewed/Unknown) as described below. 

1. Calculate Intra Quarry Variance (IQV) 

 

2 IQV  RSD x

Where: 

RSD = Relative standard deviation 

x = mean of the raw data 
9 

2. Incorporate IQV into pooled variance to adjust the variance of the floor pool 

Normal and Skewed/Unknown UPL Template 

 Adjusted Variance = s  IQV 2

Lognormal UPL Template 

 Adjusted Variance =     IQV

n n

me e m e 































     

2 1

ˆ ˆ 1

2 4

2 ˆ ˆ ˆ 2 2 ˆ ˆ  2 2  2  

3. Incorporate Adjusted Variance into UPL equation 

Normal UPL Template 

  



 



    

n m

UPL x tdf s IQV 2 1 1 ,0.99

Skewed/Unknown UPL Template 

  



 



    

n m

UPL x tdf p s IQV 2 1 1 ,

Lognormal UPL Template 

    IQV

n n

me e m e

m

z UPL e 































        

2 1

ˆ ˆ 1

2 4

0.99 2 ˆ ˆ ˆ 2 2 ˆ ˆ 2

ˆ ˆ 2 2 2

2

        

Please see the Appendix B Microsoft Excel® files for the specific UPL calculation and 

how the Hg raw material variability factor was incorporated for Large and Small Tunnel Kiln Hg 

floors (lb/ton, lb/hr, and μg/dscm @ 17% O2). 
10 

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 and per unit of measure based on the available test data. Averages were 

calculated in terms of lb/ton and concentration for PM and Hg, as well as lb/hr for non-Hg HAP 

metals and Hg. 

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 (i.e., lb/ton, μg/dscm, and lb/hr). 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, 2015). 

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. 

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. 

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

Pollutant Subcategory 

No. Sources 

Nationwide 

No. Sources with 

Data 

No. Sources in 

MACT Floor Pool 

PM Large Kilns 122 68 9 

PM Small Kilns 98 18 3 

Non-Hg HAP Metals Large Kilns 122 14 2 

Non-Hg HAP Metals Small Kilns 98 2 1 

Hg Large Kilns 122 19 3 

Hg Small Kilns 98 2 1 

a Each MACT floor pool is based on 12 percent of the sources with data. 

 

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. 
11 

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. 

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. 

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 (micrograms per dry standard cubic meter [μg/dscm] with no oxygen 

correction). The PM emission limits for the final BSCP Manufacturing NESHAP are in units of 

pound per ton (lb/ton) of brick and grains per dry standard cubic foot at 17 percent oxygen 

(gr/dscf @ 17% O2). The final non-Hg HAP metals emission limit is in units of pounds per hour 

(lb/hr). The final Hg emission limits are in units of lb/ton of brick, micrograms per dry standard 

cubic meter at 17 percent oxygen (μg/dscm @ 7% O2), and lb/hr. 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 brick) to the emission data in 

μg/dscm (uncorrected). 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 (Nizich, 

2015) 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 BSCP Manufacturing source category. 
12 

Table 2. Final Existing Source MACT Floors 

Subcategory Pollutant Avg. Var. 

99% 

UPL 3xRDL 

MACT 

Floor 

Rounded Unit of Measure

Large Kilns PM 0.014 8.5E-05 0.035 0.016 0.036 lb/ton 

 Equivalent PM 0.0011 7.8E-07 0.0029 0.0012 0.0029 gr/dscf @ 17% O2

Small Kilns PM 0.063 0.0057 0.36 0.016 0.37 lb/ton 

 Equivalent PM 8.5E-04 1.4E-07 0.0021 0.0010 0.0021 gr/dscf @ 17% O2

Large Kilns Non-Hg HAP Metals 0.0013 1.2E-07 0.0022 0.0057 0.0057 lb/hr 

Small Kilns Non-Hg HAP Metals 0.057 2.5E-04 0.10 0.0031 0.11 lb/hr 

Large Kilns Mercury 1.6E-05 9.7E-12 4.1E-05 8.0E-06 4.1E-05 lb/ton 

Equivalent Mercury 3.0 0.65 7.7 1.5 7.7 μg/dscm @ 17% 

O2

Equivalent Mercury 1.7E-04 1.2E-09 5.4E-04 8.0E-05 5.5E-04 lb/hr 

Small Kilns Mercury 1.8E-04 5.5E-11 3.3E-04 1.7E-05 3.3E-04 lb/ton 

Equivalent Mercury 17 0.17 91 1.7 91 μg/dscm @ 17% 

O2

Equivalent Mercury 0.0010 1.8E-09 0.0019 2.0E-04 0.0019 lb/hr 

Table 3. Final New Source MACT Floors 

Subcategory Pollutant Avg. Var. 

99% 

UPL 3xRDL 

MACT 

Floor 

Rounded Unit of Measure

Large Kilns PM 0.0087 1.1E-05 0.018 0.016 0.018 lb/ton 

Equivalent PM 6.1E-04 7.8E-08 0.0014 0.0012 0.0014 gr/dscf @ 17% O2

Small Kilns PM 0.0093 3.0E-05 0.029 0.016 0.030 lb/ton 

 Equivalent PM 6.5E-04 1.4E-07 0.0020 0.0010 0.0021 gr/dscf @ 17% O2

Large Kilns Non-Hg HAP Metals 0.0012 7.1E-08 0.0027 0.0057 0.0057 lb/hr 

Small Kilns Non-Hg HAP Metals 0.057 2.5E-04 0.10 0.0031 0.11 lb/hr 

Large Kilns Mercury 1.5E-05 8.8E-13 2.8E-05 8.0E-06 2.8E-05 lb/ton 

Equivalent Mercury 2.5 0.68 6.1 1.5 6.2 μg/dscm @ 17% 

O2

Equivalent Mercury 1.4E-04 2.0E-09 3.3E-04 8.0E-05 3.4E-04 lb/hr 

Small Kilns Mercury 1.8E-04 5.5E-11 3.3E-04 1.7E-05 3.3E-04 lb/ton 

Equivalent Mercury 17 0.17 91 1.7 91 μg/dscm @ 17% 

O2

Equivalent Mercury 0.0010 1.8E-09 0.0019 2.0E-04 0.0019 lb/hr 
13 

VII. 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 R.D. Gibbons. 2004. “An Upper Prediction Limit for the Arithmetic Mean 

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

Fairchild, S. 2015. Mercury Content of Oklahoma and Ohio Shale Deposits Supplying the Brick 

Industry. Memorandum from Susan Fairchild, EPA/OAQPS/SPPD, to Docket ID No. EPAHQ-OAR-2013-0291. September 23, 2015. 

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. 

Docket Item No. EPA-HQ-OAR-2013-0291-0171. 

Miller, S. 2015. “RE: Green brick mercury data.” E-mail and attachment from Susan Miller, 

Brick Industry Association, to Sharon Nizich, USEPA. May 21, 2015. 

Nizich, S. 2015. Approach for Applying the Upper Prediction Limit to Limited Datasets. 

Memorandum from Sharon Nizich, EPA/OAQPS/SPPD, to Docket ID No. EPA-HQ-OAR2013-0291. September 24, 2015. 

Raymond, G. 2015. Test Data Used in BSCP Manufacturing Final Rule. Memorandum from 

Gabrielle Raymond, RTI International, to Sharon Nizich, EPA/OAQPS/SPPD. September 

24, 2015. 

Raymond, G., K. Sroka, and B. Munoz. 2014. Analysis of Potential Subcategories in the BSCP 

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

November 6, 2014. 

Telander, J. 2014. 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. Docket Item No. EPA-HQ-OAR-2013-0291-0128. 

Westlin, P., and R. Merrill. 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. Docket Item No. EPAHQ-OAR-2013-0291-0133. 
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. Final Standards for Large Kilns – PM lb/ton Ranking 

Kiln ID APCD Type Size Class 

Average PM 

(lb/ton) Variance 

Below 1 

mg Value 

514 DIFF Large Area Source (synthetic) 0.00757 7.68E-06 538 DIFF Large Major Source 0.00868 1.09E-05 yes 508 DIFF Large Major Source 0.01003 1.71E-05 695 None Large Major Source 0.01278 1.26E-06 503 DIFF Large Area Source (synthetic) 0.01399 3.67E-07 568 DIFF Large Area Source (synthetic) 0.01709 5.99E-05 696 DLA Large Major Source 0.01761 1.38E-04 600 DIFF Large Area Source (synthetic) 0.01799 2.98E-04 yes 604 DLS Large Area Source (synthetic) 0.01843 3.98E-05 688 DIFF Large Area Source (synthetic) 0.02899 1.41E-04 603 DLS Large Area Source (synthetic) 0.03278 2.23E-04 558 DIFF Large Major Source 0.03471 1.05E-03 yes 610 DIFF Large Area Source (synthetic) 0.03602 7.97E-05 673 DLA Large Major Source 0.03627 1.23E-04 674 DLA Large Major Source 0.03627 1.23E-04 662 DLA Large Major Source 0.03784 6.66E-04 543 DIFF Large Area Source (synthetic) 0.03790 1.10E-03 yes 606 DIFF Large Major Source 0.03901 1.80E-03 yes 502 DLS Large Major Source 0.04255 1.48E-03 yes 544 DIFF Large Area Source (synthetic) 0.04487 1.09E-03 yes 654 DIFF Large Area Source (synthetic) 0.04500 3.28E-05 583 DLA Large Major Source 0.04765 3.08E-04 680 DLA Large Major Source 0.04959 6.83E-05 653 DIFF Large Major Source 0.05149 4.00E-05 566 DIFF Large Major Source 0.06024 3.28E-03 yes 506 DLS Large Area Source (synthetic) 0.06262 4.10E-04 770 DLA Large Major Source 0.06884 1.92E-04 526 DIFF Large Major Source 0.06969 1.05E-03 547 DIFF Large Major Source 0.07636 5.17E-04 
A-3 

Kiln ID APCD Type Size Class 

Average PM 

(lb/ton) Variance 

Below 1 

mg Value 

548 DIFF Large Major Source 0.07636 5.17E-04 527 DIFF Large Major Source 0.07699 6.23E-03 yes 725 DLA Large Area Source (synthetic) 0.07840 1.93E-03 691 DLA Large Area Source (synthetic) 0.08227 4.29E-04 769 DLA Large Major Source 0.08635 4.66E-04 625 DLA Large Major Source 0.09099 5.79E-04 567 DIFF Large Major Source 0.09304 5.67E-04 721 WS Large Area Source (synthetic) 0.09565 1.82E-03 724 DLA Large Area Source (synthetic) 0.09599 7.78E-04 641 DLA Large Area Source (synthetic) 0.09977 1.64E-03 518 DLA Large Major Source 0.10624 5.28E-04 679 DLA Large Major Source 0.10847 3.80E-03 738 DIFF Large Area Source (synthetic) 0.11217 8.58E-03 573 DLA, FCA Large Area Source (synthetic) 0.13228 2.02E-04 730 DLA Large Major Source 0.13851 2.63E-03 577 DLA Large Major Source 0.14145 3.56E-02 578 DLA Large Major Source 0.14145 3.56E-02 649 DLA Large Major Source 0.14213 9.04E-03 646 DLA Large Area Source (synthetic) 0.14327 1.01E-02 675 DIFF Large Area Source (synthetic) 0.14825 1.72E-03 740 DLA Large Area Source (synthetic) 0.15802 2.68E-03 729 DLA Large Major Source 0.17786 1.91E-03 644 DLA Large Major Source 0.17806 9.79E-04 676 DIFF Large Area Source (synthetic) 0.18995 3.55E-02 736 DLA Large Area source (synthetic) 0.20060 7.15E-03 647 DLA Large Area Source (synthetic) 0.23418 3.68E-02 655 DIFF Large Area Source (synthetic) 0.23971 5.23E-02 645 DLA Large Major Source 0.26210 6.74E-03 539 None Large Major Source 0.28166 5.73E-03 720 WS Large Area Source (synthetic) 0.32413 1.33E-01 768 DLA Large Major Source 0.37699 1.40E-02 
A-4 

Kiln ID APCD Type Size Class 

Average PM 

(lb/ton) Variance 

Below 1 

mg Value 

643 WS Large Area Source (synthetic) 0.37757 5.25E-02 612 DLA Large Major Source 0.41284 1.27E-02 613 DLA Large Major Source 0.41284 1.27E-02 551 DLA Large Major Source 0.57684 5.15E-02 552 DLA Large Major Source 0.57684 5.15E-02 775 None Large Major Source 0.64068 4.38E-02 766 DLA Large Major Source 0.82067 7.89E-01 767 DLA Large Major Source 0.82067 7.89E-01 
A-5 

Table A-2. Final Standards for Large Kilns – PM gr/dscf @ 17% O2 Ranking 

Kiln ID APCD Type Size Class 

Average PM 

(gr/dscf @ 

17% O2) Variance 

Below 1 

mg Value 

508 DIFF Large Major Source 0.000614 7.83E-08 695 None Large Major Source 0.000648 4.18E-08 514 DIFF Large Area Source (synthetic) 0.000697 7.72E-08 503 DIFF Large Area Source (synthetic) 0.000767 9.80E-09 568 DIFF Large Area Source (synthetic) 0.001337 3.04E-07 600 DIFF Large Area Source (synthetic) 0.001558 2.25E-06 yes 604 DLS Large Area Source (synthetic) 0.001728 2.37E-07 543 DIFF Large Area Source (synthetic) 0.001882 1.99E-06 yes 662 DLA Large Major Source 0.002669 4.05E-06 603 DLS Large Area Source (synthetic) 0.002695 1.16E-06 544 DIFF Large Area Source (synthetic) 0.002717 4.55E-06 yes 654 DIFF Large Area Source (synthetic) 0.002767 4.40E-08 606 DIFF Large Major Source 0.002868 9.96E-06 yes 566 DIFF Large Major Source 0.003060 7.11E-06 yes 502 DLS Large Major Source 0.003358 9.86E-06 yes 688 DIFF Large Area Source (synthetic) 0.003431 2.17E-06 769 DLA Large Major Source 0.003624 2.20E-07 653 DIFF Large Major Source 0.003729 1.18E-06 610 DIFF Large Area Source (synthetic) 0.003753 2.53E-06 527 DIFF Large Major Source 0.003902 1.29E-05 yes 526 DIFF Large Major Source 0.004072 4.72E-06 538 DIFF Large Major Source 0.004107 1.33E-05 yes 680 DLA Large Major Source 0.004332 3.07E-07 547 DIFF Large Major Source 0.004486 1.69E-06 548 DIFF Large Major Source 0.004486 1.69E-06 506 DLS Large Area Source (synthetic) 0.004710 1.64E-06 721 WS Large Area Source (synthetic) 0.004760 3.68E-06 567 DIFF Large Major Source 0.005333 2.00E-06 558 DIFF Large Major Source 0.005418 2.49E-05 yes 
A-6 

Kiln ID APCD Type Size Class 

Average PM 

(gr/dscf @ 

17% O2) Variance 

Below 1 

mg Value 

641 DLA Large Area Source (synthetic) 0.005652 5.11E-06 518 DLA Large Major Source 0.006929 2.17E-06 770 DLA Large Major Source 0.007347 4.92E-06 725 DLA Large Area Source (synthetic) 0.007843 2.07E-05 724 DLA Large Area Source (synthetic) 0.008930 1.77E-05 675 DIFF Large Area Source (synthetic) 0.010095 3.12E-05 646 DLA Large Area Source (synthetic) 0.010943 5.19E-05 649 DLA Large Major Source 0.011338 5.89E-05 720 WS Large Area Source (synthetic) 0.011467 1.28E-04 730 DLA Large Major Source 0.012457 2.12E-05 740 DLA Large Area Source (synthetic) 0.012769 2.11E-05 679 DLA Large Major Source 0.013785 4.40E-05 644 DLA Large Major Source 0.014006 6.72E-06 655 DIFF Large Area Source (synthetic) 0.015596 2.35E-04 577 DLA Large Major Source 0.016035 5.14E-04 578 DLA Large Major Source 0.016035 5.14E-04 729 DLA Large Major Source 0.016105 1.28E-05 647 DLA Large Area Source (synthetic) 0.017307 1.94E-04 676 DIFF Large Area Source (synthetic) 0.018290 3.63E-04 645 DLA Large Major Source 0.025039 9.03E-05 551 DLA Large Major Source 0.026017 9.22E-05 552 DLA Large Major Source 0.026017 9.22E-05 539 None Large Major Source 0.026224 4.43E-05 768 DLA Large Major Source 0.028201 8.93E-05 612 DLA Large Major Source 0.032152 1.05E-04 613 DLA Large Major Source 0.032152 1.05E-04 643 WS Large Area Source (synthetic) 0.038993 8.70E-04 775 None Large Major Source 0.042195 6.60E-05 
A-7 

Table A-3. Final Standards for Small Kilns – PM lb/ton Ranking 

Kiln ID APCD Type Size Class 

Average PM 

(lb/ton) Variance 

Below 1 

mg Value 

599 DIFF Small Major Source 0.00930 2.99E-05 549 None Small Major Source 0.01960 1.36E-05 531 SD/ESP Small Major Source 0.11149 6.80E-03 532 SD/ESP Small Major Source 0.11149 6.80E-03 533 SD/ESP Small Major Source 0.18153 1.96E-03 180 None Small Major Source 0.18290 1.06E-03 521 None Small Major Source 0.23121 1.31E-03 178 None Small Major Source 0.24311 5.22E-03 650 None Small Major Source 0.25022 4.06E-03 516 None Small Major Source 0.29156 7.25E-03 179 None Small Major Source 0.31288 1.06E-04 669 None Small Major Source 0.37566 2.73E-04 529 None Small Major Source 0.38192 1.95E-02 530 None Small Major Source 0.39455 1.49E-02 535 None Small Major Source 0.66397 1.98E-02 706 None Small Major Source 0.74622 2.61E-01 704 None Small Major Source 1.18767 6.79E-02 705 None Small Major Source 1.18767 6.79E-02 
A-8 

Table A-4. Final Standards for Small Kilns – PM gr/dscf @ 17% O2 Ranking 

Kiln ID APCD Type Size Class 

Average PM 

(gr/dscf @ 17% 

O2) Variance 

Below 1 

mg Value 

599 DIFF Small Major Source 0.000647 1.43E-07 549 None Small Major Source 0.001046 7.72E-08 531 SD/ESP Small Major Source 0.006673 3.07E-05 532 SD/ESP Small Major Source 0.006673 3.07E-05 180 None Small Major Source 0.009619 3.02E-06 530 None Small Major Source 0.010404 1.21E-05 178 None Small Major Source 0.011154 1.61E-05 533 SD/ESP Small Major Source 0.011596 3.31E-06 521 None Small Major Source 0.012629 3.03E-06 529 None Small Major Source 0.012911 1.29E-05 179 None Small Major Source 0.014582 3.62E-07 516 None Small Major Source 0.023365 4.50E-05 535 None Small Major Source 0.024064 1.72E-05 650 None Small Major Source 0.025025 7.14E-05 
A-9 

Table A-5. Final Standards for Large Kilns – Non-Hg Metal HAP lb/hr Ranking 

Kiln ID 

APCD 

Type Size Class 

Average Total 

Non-Hg Metals 

(lb/hr) Variance Overall Statu

526 DIFF Large Major Source 1.15E-03 7.10E-08 DLL 653 DIFF Large Major Source 1.48E-03 2.04E-07 DLL 600 DIFF Large Area Source (synthetic) 1.69E-03 5.79E-08 DLL 558 DIFF Large Major Source 1.79E-03 2.33E-06 DLL 544 DIFF Large Area Source (synthetic) 1.93E-03 5.98E-08 DLL 543 DIFF Large Area Source (synthetic) 2.14E-03 1.60E-08 DLL 508 DIFF Large Major Source 2.71E-03 1.76E-06 DLL 606 DIFF Large Major Source 3.35E-03 8.32E-10 DLL 527 DIFF Large Major Source 3.72E-03 4.65E-07 DLL 676 DIFF Large Area Source (synthetic) 4.33E-03 1.09E-08 DLL 566 DIFF Large Major Source 4.42E-03 4.27E-06 DLL 655 DIFF Large Area Source (synthetic) 4.91E-03 1.41E-07 DLL 720 WS Large Area Source (synthetic) 9.91E-03 4.87E-07 DLL 721 WS Large Area Source (synthetic) 2.89E-02 7.88E-04 DLL 

Table A-6. Final Standards for Small Kilns – Non-Hg Metal HAP lb/hr Ranking 

Kiln ID 

APCD 

Type Size Class 

Average Total 

Non-Hg Metals 

(lb/hr) Variance Overall Statu

531 SD/ESP Small Major Source 2.84E-02 6.15E-05 DLL 532 SD/ESP Small Major Source 2.84E-02 6.15E-05 DLL 
A-10 

Table A-7. Final Standards for Large Kilns – Hg lb/ton Rankinga 

Kiln ID 

APCD 

Type Size Class 

Average Hg 

(lb/ton) Variance 

Overall 

Status 

568 DIFF Large Area Source (synthetic) 1.48E-05 8.83E-13 BDL 558 DIFF Large Major Source 1.70E-05 1.43E-12 DLL 655 DIFF Large Area Source (synthetic) 1.72E-05 3.10E-11 ADL 547 DIFF Large Major Source 2.31E-05 2.33E-11 DLL 548 DIFF Large Major Source 2.31E-05 2.33E-11 DLL 676 DIFF Large Area Source (synthetic) 2.70E-05 8.99E-12 DLL 503 DIFF Large Area Source (synthetic) 2.91E-05 7.63E-12 DLL 566 DIFF Large Major Source 3.27E-05 2.37E-12 BDL 606 DIFF Large Major Source 3.85E-05 3.30E-11 DLL 721 WS Large Area Source (synthetic) 3.93E-05 4.84E-10 DLL 720 WS Large Area Source (synthetic) 6.22E-05 2.92E-10 DLL 543 DIFF Large Area Source (synthetic) 7.66E-05 7.09E-12 DLL 775 None Large Major Source 7.79E-05 1.60E-09 DLL 526 DIFF Large Major Source 8.50E-05 7.47E-10 ADL 600 DIFF Large Area Source (synthetic) 8.94E-05 1.08E-10 ADL 508 DIFF Large Major Source 9.08E-05 1.21E-10 DLL 527 DIFF Large Major Source 9.08E-05 5.98E-11 ADL 544 DIFF Large Area Source (synthetic) 9.78E-05 1.02E-10 DLL 653 DIFF Large Major Source 1.02E-04 9.35E-12 DLL 

a ADL = above detection level; WS = wet scrubber; NA = not applicable. 
A-11 

Table A-8. Final Standards for Large Kilns – Hg μg/dscm @ 17% O2 Rankinga 

Kiln ID 

APCD 

Type Size Class 

Average Hg 

(μg/dscm @ 

17% O2) Variance 

Overall 

Status 

655 DIFF Large Area Source (synthetic) 2.51 6.81E-01 ADL 568 DIFF Large Area Source (synthetic) 2.93 8.86E-02 BDL 547 DIFF Large Major Source 3.67 7.83E-01 DLL 548 DIFF Large Major Source 3.67 7.83E-01 DLL 503 DIFF Large Area Source (synthetic) 3.71 7.82E-02 DLL 566 DIFF Large Major Source 4.53 7.43E-02 BDL 721 WS Large Area Source (synthetic) 4.54 7.95E+00 DLL 720 WS Large Area Source (synthetic) 4.68 1.49E+00 DLL 676 DIFF Large Area Source (synthetic) 6.17 5.94E-01 DLL 606 DIFF Large Major Source 6.22 2.01E+00 DLL 558 DIFF Large Major Source 6.73 5.28E-01 DLL 526 DIFF Large Major Source 9.36 1.26E+01 ADL 527 DIFF Large Major Source 9.81 6.20E-01 ADL 543 DIFF Large Area Source (synthetic) 12.25 2.90E-02 DLL 508 DIFF Large Major Source 13.40 3.12E+00 DLL 775 None Large Major Source 13.81 4.96E+01 DLL 544 DIFF Large Area Source (synthetic) 14.44 5.67E+00 DLL 653 DIFF Large Major Source 14.48 2.28E-02 DLL 600 DIFF Large Area Source (synthetic) 16.84 5.77E-01 ADL 

a ADL = above detection level; WS = wet scrubber; NA = not applicable. 
A-12 

Table A-9. Final Standards for Large Kilns – Hg lb/hr Rankinga 

Kiln ID 

APCD 

Type Size Class 

Average Hg 

(lb/hr) Variance 

Overall 

Status 

655 DIFF Large Area Source (synthetic) 1.37E-04 1.97E-09 ADL 568 DIFF Large Area Source (synthetic) 1.75E-04 1.25E-10 BDL 558 DIFF Large Major Source 1.94E-04 1.86E-10 DLL 676 DIFF Large Area Source (synthetic) 2.08E-04 5.33E-10 DLL 503 DIFF Large Area Source (synthetic) 2.77E-04 6.93E-10 DLL 547 DIFF Large Major Source 2.83E-04 1.21E-08 DLL 548 DIFF Large Major Source 2.83E-04 1.21E-08 DLL 720 WS Large Area Source (synthetic) 4.03E-04 1.22E-08 DLL 526 DIFF Large Major Source 4.41E-04 2.01E-08 ADL 721 WS Large Area Source (synthetic) 5.74E-04 1.03E-07 DLL 775 None Large Major Source 6.20E-04 1.01E-07 DLL 527 DIFF Large Major Source 6.41E-04 2.98E-09 ADL 606 DIFF Large Major Source 6.48E-04 9.32E-09 DLL 544 DIFF Large Area Source (synthetic) 6.60E-04 4.63E-09 DLL 566 DIFF Large Major Source 6.62E-04 9.71E-10 BDL 653 DIFF Large Major Source 6.78E-04 4.16E-10 DLL 600 DIFF Large Area Source (synthetic) 1.07E-03 1.55E-08 ADL 543 DIFF Large Area Source (synthetic) 1.12E-03 1.52E-09 DLL 508 DIFF Large Major Source 1.33E-03 2.59E-08 DLL 

a ADL = above detection level; WS = wet scrubber; NA = not applicable. 
A-13 

Table A-10. Final Standards for Small Kilns – Hg lb/ton Rankinga

Kiln No 

APCD 

Type Size Class 

Average 

(lb/ton) Variance 

Overall 

Status 

531 SD/ESP Small Major Source 1.76E-04 5.51E-11 DLL 532 SD/ESP Small Major Source 1.76E-04 5.51E-11 DLL 

a SD/ESP = spray dryer/electrostatic precipitator. 

Table A-11. Final Standards for Small Kilns – Hg μg/dscm @ 17% O2 Rankinga 

Kiln ID 

APCD 

Type Size Class 

Average Hg 

(μg/dscm @ 17% 

O2) Variance 

Overall 

Status 

531 SD/ESP Small Major Source 17.36 1.71E-01 DLL 532 SD/ESP Small Major Source 17.36 1.71E-01 DLL 

a SD/ESP = spray dryer/electrostatic precipitator. 

Table A-12. Final Standards for Small Kilns – Hg lb/hr Rankinga 

Kiln ID 

APCD 

Type Size Class Average Hg (lb/hr) Variance 

Overall 

Status 

531 SD/ESP Small Major Source 9.97E-04 7.05E-09 DLL 532 SD/ESP Small Major Source 9.97E-04 7.05E-09 DLL 

a SD/ESP = spray dryer/electrostatic precipitator. 
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. Final 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

Variance 

of Top 

Sources 

Large Kilns PM 122 68 12% Sources with Data 9 31 0.014 8.5E-05  Equivalent PM 122 57 12% Sources with Data 7 23 0.0011 7.8E-07 Small Kilns PM 98 18 12% Sources with Data 3 12 0.063 0.0057  Equivalent PM 98 14 12% Sources with Data 2 6 8.5E-04 1.4E-07 Large Kilns Non-Hg HAP Metals 122 14 12% Sources with Data 2 5 0.0013 1.2E-07 Small Kilns Non-Hg HAP Metals 98 2 12% Sources with Data 1 3 0.057 2.5E-04 Large Kilns Mercury 122 19 12% Sources with Data 3 9 1.6E-05 9.7E-12 4

Equivalent Mercury 122 19 12% Sources with Data 3 9 3.0 0.65 Equivalent Mercury 122 19 12% Sources with Data 3 9 1.7E-04 1.2E-09 5

Small Kilns Mercury 98 2 12% Sources with Data 1 3 1.8E-04 5.5E-11 3

Equivalent Mercury 98 2 12% Sources with Data 1 3 17 0.17 Equivalent Mercury 98 2 12% Sources with Data 1 3 0.0010 1.8E-09 
B-3 

Table B-2. Final 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 

Variance 

of Top 

Sources 

Large Kilns PM 122 68 12% Sources with Data 1 5 0.0087 1.1E-05  Equivalent PM 122 57 12% Sources with Data 1 5 6.1E-04 7.8E-08 Small Kilns PM 98 18 12% Sources with Data 1 3 0.0093 3.0E-05  Equivalent PM 98 14 12% Sources with Data 1 3 6.5E-04 1.4E-07 Large Kilns Non-Hg HAP Metals 122 14 12% Sources with Data 1 3 0.0012 7.1E-08 Small Kilns Non-Hg HAP Metals 98 2 12% Sources with Data 1 3 0.057 2.5E-04 Large Kilns Mercury 122 19 12% Sources with Data 1 3 1.5E-05 8.8E-13 2

Equivalent Mercury 122 19 12% Sources with Data 1 3 2.5 0.68 Equivalent Mercury 122 19 12% Sources with Data 1 3 1.4E-04 2.0E-09 3

Small Kilns Mercury 98 2 12% Sources with Data 1 3 1.8E-04 5.5E-11 3

Equivalent Mercury 98 2 12% Sources with Data 1 3 17 0.17 Equivalent Mercury 98 2 12% Sources with Data 1 3 0.0010 1.8E-09 
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 BSCP Manufacturing MACT floors, the units of measure used to develop the 

UPL values were lb/ton brick, lb/hr, gr/dscf @ 17% O2, and μg/dscm @ 17% O2. However, the 

3xRDL values from the guidance document are given in units of concentration, specifically 

μg/dscm for metals and PM. 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 BSCP survey as below detection level (BDL), detection 

level limited (DLL), or above detection level (ADL). We proceeded with the following 

steps to convert the 3xRDL value to the units of measure used in UPL. 

2. For all of the sources in the PM and Hg MACT existing source floor pools, we compiled 

the available concentration, oxygen-corrected concentration, lb/ton, and lb/hr 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; PM gr/dscf @ 

17% O2 / μg/dscm; Non-Hg Metal HAP lb/hr / μg/dscm; Hg lb/ton / μg/dscm; Hg 

μg/dscm @ 17% O2 / μg/dscm; and Hg lb/hr / μg/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 Units Of Measure 

Large Kilns PM 5.26E-06 lb/ton / μg/dscm 

 PM (equivalent) 3.99E-07 gr/dscf @ 17% O2 / μg/dscm 

Small Kilns PM 5.30E-06 lb/ton / μg/dscm 

 PM (equivalent) 3.22E-07 gr/dscf @ 17% O2 / μg/dscm 

Large Kilns Hg 4.70E-06 lb/ton / μg/dscm 

 Hg (equivalent) 9.07E-01 μg/dscm @ 17% O2 / μg/dscm 

 Hg (equivalent) 4.72E-05 lb/hr / μg/dscm 

Small Kilns Hg 1.02E-05 lb/ton / μg/dscm 

 Hg (equivalent) 1.01E+00 μg/dscm @ 17% O2 / μg/dscm 

 Hg (equivalent) 1.16E-04 lb/hr / μg/dscm 

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

Non-Hg HAP Metals, and Hg, the typical sample volume was equal to 1 dscm for most 

BSCP tests. 

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

of the test runs in this dataset (1 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 PM, Hg, and Total Non-Hg 

Metals at the typical sample volume of 1 dscm and other various dscm tests. 

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 

Total Non-Hg 

Metals (Method 29) 

analyzed by 

ICP/AES or AA 

8.6E+01 2.6E+02 2.6E+02 1.3E+02 8.6E+01 6.3E+01 

Total Non-Hg 

Metals (Method 29) 

analyzed by ICP/MS 

or GFAA 

9.0E+00 2.7E+01 2.7E+01 1.4E+01 9.0E+00 6.8E+00 
C-3 

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

convert the 3xRDL value into the units of measure used in the UPL calculation (e.g., lb/ton; lb/hr; gr/dscf 

μg/dscm @17% O2). Table C-3 displays a summary of the converted 3xRDL values. 

Table C-3. Converted 3xRDL Values 

Subcategory Pollutant 

Average 

Ratio 

Average Ratio Units Of 

Measure 

3xRDL at 

Typical 

Sample 

Volume 

(μg/dscm) 

Converted 

3xRDL 

Value 

Large Kilns PM 5.26E-06 lb/ton / μg/dscm 3.0E+03 0.016  PM (equivalent) 3.99E-07 gr/dscf @ 17% O2 / μg/dscm 3.0E+03 0.0012 Small Kilns PM 5.30E-06 lb/ton / μg/dscm 3.0E+03 0.016  PM (equivalent) 3.22E-07 gr/dscf @ 17% O2 / μg/dscm 3.0E+03 0.0010 Large Kilns Hg 4.70E-06 lb/ton / μg/dscm 1.7E+00 8.0E-06  Hg (equivalent) 9.07E-01 μg/dscm @ 17% O2 / μg/dscm 1.7E+00 1.5  Hg (equivalent) 4.72E-05 lb/hr / μg/dscm 1.7E+00 8.0E-05 Small Kilns Hg 1.02E-05 lb/ton / μg/dscm 1.7E+00 1.7E-05  Hg (equivalent) 1.01E+00 μg/dscm @ 17% O2 / μg/dscm 1.7E+00 1.7  Hg (equivalent) 1.16E-04 lb/hr / μg/dscm 1.7E+00 2.0E-04 

8. For Non-Hg HAP Metals there are two sets of 3xRDL values provided by the guidance document per ana

Method 29: Inductively Coupled Atomic Emission Spectroscopy or Atomic Absorption Analysis (ICP/AEInductively Coupled Plasma/Mass Spectrometry or Graphite Furnace Atomic Absorption Analysis (ICP/Mmultiplied the appropriate 3xRDL concentration value specific to the analytical method used by each run 

took the average of those values for the converted 3xRDL value. 
C-4 

Subcategory Pollutant 

Run by Run Ratio 

Units Of Measure 

3xRDL at Typical Sample 

Volume (μg/dscm) 

Converted 

3xRDL Value 

Large Kilns Non-Hg HAP Metals lb/hr / μg/dscm 

2.6E+02 

[ICP/AES or AA] 

and 

2.7E+01 

[ICP/MS or GFAA] 

0.0057 

Small Kilns Non-Hg HAP Metals lb/hr / μg/dscm 

2.6E+02 

[ICP/AES or AA] 

and 

2.7E+01 

[ICP/MS or GFAA] 

0.0031 

9. 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 

emission limit. 

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

limit. 

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

floors. 
C-5 

Table C-4. Existing Source Floors 

Subcategory Pollutant 

Converted 

3xRDL Value UPL 

Rounded 

Floor 

Floor Based 

On Units 

Large Kilns PM 0.016 0.035 0.036 UPL lb/ton  PM (equivalent) 0.0012 0.0029 0.0029 UPL gr/dscSmall Kilns PM 0.016 0.36 0.37 UPL lb/ton  PM (equivalent) 0.0010 0.0021 0.0021 UPL gr/dscLarge Kilns Non-Hg HAP Metals 0.0057 0.0022 0.0057 3xRDL lb/hr Small Kilns Non-Hg HAP Metals 0.0031 0.10 0.11 UPL lb/hr Large Kilns Hg 8.0E-06 4.1E-05 4.1E-05 UPL lb/ton  Hg (equivalent) 1.5 7.7 7.7 UPL μg/dsc Hg (equivalent) 8.0E-05 5.4E-04 5.5E-04 UPL lb/hr Small Kilns Hg 1.7E-05 3.3E-04 3.3E-04 UPL lb/ton  Hg (equivalent) 1.7 91 91 UPL μg/dsc Hg (equivalent) 2.0E-04 0.0019 0.0019 UPL lb/hr 
C-6 

Table C-5. New Source Floors 

Subcategory Pollutant 

Converted 

3xRDL Value UPL 

Rounded 

Floor 

Floor Based 

On Units Of Mea

Large Kilns PM 0.016 0.018 0.018 UPL lb/ton  PM (equivalent) 0.0012 0.0014 0.0014 UPL gr/dscf @ 17% Small Kilns PM 0.016 0.029 0.030 UPL lb/ton  PM (equivalent) 0.0010 0.0020 0.0021 UPL gr/dscf @ 17% Large Kilns Non-Hg HAP Metals 0.0057 0.0027 0.0057 3xRDL lb/hr Small Kilns Non-Hg HAP Metals 0.0031 0.10 0.11 UPL lb/hr Large Kilns Hg 8.0E-06 2.8E-05 2.8E-05 UPL lb/ton  Hg (equivalent) 1.5 6.1 6.2 UPL μg/dscm @ 17 Hg (equivalent) 8.0E-05 3.3E-04 3.4E-04 UPL lb/hr Small Kilns Hg 1.7E-05 3.3E-04 3.3E-04 UPL lb/ton  Hg (equivalent) 1.7 91 91 UPL μg/dscm @ 17 Hg (equivalent) 2.0E-04 0.0019 0.0019 UPL lb/hr 
Appendix D 

Limited Datasets 
D-1 

For the BSCP Manufacturing source category, we have limited datasets for the following 

pollutants and subcategories: particulate matter (PM) in units of concentration for existing small 

tunnel kilns, non-mercury (non-Hg) metal HAP for existing small and large tunnel kilns, 

mercury (Hg) for existing small tunnel kilns (all units of measurement); and PM, non-Hg metal 

HAP, and Hg for new small and large tunnel kilns. 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 (Nizich, 2015). 

We did determine that further evaluation of the approach used to calculate MACT floors 

for the following floors was needed: 

 Small Kilns Existing Equivalent PM (gr/dscf @ 17% O2) 

 Large Kilns New Hg (lb/ton) 

 Large Kilns New Equivalent Hg (μg/dscm @ 17% O2) 

 Large Kilns New Hg (lb/hr) 

See Approach for Applying the Upper Prediction Limit to Limited Datasets (Nizich, 

2015) for more information. We reevaluated the UPL methodology and as such, the MACT 

floors are: 

 Small Kilns Existing Equivalent PM = 0.0021 gr/dscf @ 17% O2

 Large Kilns New Hg = 2.8E-05 lb/ton 

 Large Kilns New Equivalent Hg = 6.2 μg/dscm @ 17% O2

 Large Kilns New Hg = 3.4E-04 lb/hr 
Appendix E 

Development of Hg Raw Material Variability Factor 
E-1 

Development of Hg Raw Material Variability Factor 

The corresponding Appendix E Microsoft Excel® files provide the Hg raw material 

provided by BIA and the determination of the overall RSD used in calculations for each existing 

and new source UPL per pollutant and subcategory. 

See “Mercury Content of Oklahoma and Ohio Shale Deposits Supplying the Brick 

Industry” (Fairchild 2015) for the determination of the two deposits (OK and OH) being used out 

of all data provided by the BIA.