### Date: September 24, 2015

To: Sharon Nizich, EPA/OAQPS/SPPD

From: Gabrielle Raymond and Kristin Sroka, RTI International

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

Brick and Structural Cl ay Products Manufacturing

I. Introduction

In accordance with section 112 of the Clean Air Act (CAA), the U.S. Environmental Protection Agency (EPA) established national em ission standards for hazardous air pollutants (NESHAP) on May 16, 2003, for the brick and struct ural clay products (B SCP) 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 manu facturing 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 standa rds for BSCP manufacturing, including standards for HF, HCl, chlorine (Cl 2 

### ), 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 affect ed 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 tec hnology (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 MA CT floor cannot be less stringent than the

emission control that is achieved in practice by the best controlle d similar source. For existing sources, the MACT floor cannot be less stringent than the av erage 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 fe wer 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 Manufacturi ng source category. This MACT floor analysis uses data collected in a survey of BSCP owne rs 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 oper ators 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, organi c 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 Cl 2 

### ; the metals antimony (Sb), arsenic (As), beryllium (Be), cadmium (Cd), chromium (C r), cobalt (Co), lead (Pb), manga nese (Mn), Hg, nickel (Ni), and selenium (Se); and dioxins a nd furans (D/F). MACT floor le vels 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 sect ion IV.B of the preamble to the proposed BSCP Manufacturing NESHAP (79 FR 75633) for more information aboutfilterable PM as a surrogate for total nonHg HAP metals).

MACT floors were not developed for acid gase s 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 fina l BSCP Manufacturing NESHAP.

III. MACT Floor Analysis Subcategories

Under CAA section 112(d)(1), the EPA ha s the discretion to “...distinguish among classes, types, and sizes of sour ces within a category or subcategor y 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 th ere are significant design and operational differences in BSCP tunnel kilns that a ffect the levels of emissions of certain HAP to justify subcategorizing BSCP tunnel kilns for th e purpose of establishing MACT floors. For the BSCP Manufacturing source category, the follo wing two subcategorie s were identified:

 Large tunnel kilns: New and existing BSCP tunnel kiln s 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 kiln s 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 limita tion achieved by those best performing sources. The EPA uses a UPL approach in its MACT floo r analyses because it incorporates the average performance of the best performi ng 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 pe rcent level of confidence means that a facility whose emissions are in line with the best perf ormers has one chance in 100 of exceeding the floor limit. A prediction interval for a single fu ture 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 ta ken. The UPL approach encompasses all the data point-to-data point variability. The predic tions derive from the dataset to which it is applied, and, thus, can be a pplied to any type of data.

There are different equations for calculati ng a UPL based on the distribution of the dataset. Data can be normally distributed, logno rmally distributed, or neither and thus have a skewed/unknown distribution. The EPA implemen ted 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 exte nding towards negative values. The value of S can be approximated using the followi ng equation (which is implemen ted 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 x i 

### = individual source mean

stdev = 

#     

# 

 

1 2



### n x x i



### As part of determining whether a data distri bution 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:



#         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 skewne ss of the data can be considered normal.

The kurtosis statistic (K) characterizes the degree of p eakedness or flatness of a given data distribution in comparison to a normal dist ribution. Normally distributed data have a K

value of zero. A K value that is greater than zero indi cates a relatively peak ed distribution. A K

value that is less than zero indicates a relativel y 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

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 s econd term. Instead, for 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 distri bution 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: 

#          5 3 3 2 1 24 2



### 

 

 



n n n n n 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 hypothesi s 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 re sults from both the skewness and kurtosis hypothesis tests indicated the dataset was norma lly 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 lo g-transformed, and the lo g-transformed dataset

was evaluated for kurtosis and skewness. If both tests of the log-transformed data indicated the log-transformed dataset was normally distribut ed, the dataset was treated as lognormally distributed in subsequent UPL calcu lations. If either of these te sts indicated the log-transformed dataset was not normally distributed, the datase t was treated as skewed /unknown distribution in subsequent UPL calculations.

For datasets with only thr ee 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 l og-transformed data. Th e smaller skewness/SES value was selected as an indication of a larg er likelihood of the data to come from the corresponding distribution.

After completing the determination of the type of data distribution fo r each dataset, the UPL was calculated using the corresponding equation for the distribution for that dataset. The UPL equations for normal, lognormal, and skew ed/unknown distribution da tasets are provided

below.

Normally Distributed Dataset



###      

  

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 = number of test runs = 

# 

 N

i i 

### n 1


### m = number of future test runs in the compliance average

N = number of sources

### 6 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 per cent level of confiden ce with degrees of freedom (df); this value can be calculate d 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 

### n df

Lognormally Distributed Dataset (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         



### where:

 ˆ 

### =

n y log n

i i 

# 

 1 

### ) ( 

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

2 

### ˆ  

### = 

#    

1 ˆ

1 2



###   

# 





### n y log n

i i 

###  

### = variance estimate of the log transformed data

Z 0.99 

### = the 99 th 

### -percentile of the log-normal di stribution 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 

###   

Skewed/Unknown Distribution (Non-N ormal/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

### 7 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 spec ified 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 test method measurements is another component of data variability. At very low emissions levels, as encountered in some of the da ta in the BSCP dataset, the inherent imprecision in the pollutant measuremen t method has a large influence on the reliability of the data underlying a MACT floor emission limit. Of particular concer n are those data that are reported near or below a test method’s pollu tant detection capability . Because of matrix effects, laboratory techniques, sample volum e, and other factors, method detection limits normally vary from test to test. The guideli nes 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 th e test-specific method detection limit.

Variability of data due to measurement imprecision is inhere ntly and reasonably addressed in calculating a MACT floor emission limit when most of the data are significantly

above the method detection limit. For datasets w ith a large number of test results below the method detection limit (reported as method detecti on limit values), other techniques need to be

used to account for data variab ility. Indeed, under such a shif t, the data distribution becomes truncated on the lower end, leading to an arti ficial 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 variabi lity, 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. Relati ve pollutant measuremen t imprecision decreases to a consistent 10 to 15 percent for values m easured at a level about three times the method detection limit (ASME, 2001).

The approach taken to account for measurem ent variability include s 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 detecti on levels (RDL) from ava ilable pollutant-specific method detection levels (Westlin and Merrill, 20 11). These RDL values are then multiplied by three to decrease measurement imprecision to aro und 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 measurem ent variability is adequately addressed. This check was part of the variability analysis for all MACT floors.

For more information regarding the general us e 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) coordinate d 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 th e 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 ra w 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) fo r 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 facili ties 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 opera tes the kilns in the Sm all 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 th e data to character ize the geological history of the clay deposits and de termined 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 av eraging the facility averages. Next, the standard deviation of the facility averages was calculated. Th en 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 RS D, 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 

### x RSD IQV  

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 = IQV s 

2



### Lognormal UPL Template

Adjusted Variance = 

#     IQV

n n e m e me                 

  

   

### 1 2 ˆ ˆ 1 4 2

ˆ ˆ 2 2 ˆ ˆ ˆ 2 2 2 2 

###       



### 3. Incorporate Adjusted Variance into UPL equation

Normal UPL Template



#        

   

m n IQV s t x UPL df 

### 1 1 2

99

. 0

,



### Skewed/Unknown UPL Template



#        

   

m n IQV s t x UPL

p df 

### 1 1 2

,



### Lognormal UPL Template


#     IQV

n n e m e me

m z
e UPL                 

  

     



### 1 2 ˆ ˆ 1 4 2

ˆ ˆ 2 2 ˆ ˆ ˆ 2 99

. 0 2 ˆ

ˆ 2 2 2 2 

###         



### Please see the Appendix B Microsoft Excel® f iles 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% O 2 

### ).

### 10 V. MACT Floor Analysis Methodology

Step 1.

The first step in the MACT floor analysis wa s to calculate an average emission value for each source per pollutant and per unit of measure ba sed on the available test data. Averages were

calculated in terms of lb/ton a nd 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 de tection 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 calculate d for each source, in each subcategory and pollutant, all of the individual average emission valu es 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 sour ce was identified from the sources that had

individual source test run data in the survey dataset. For th e 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 Pool a

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 an alysis 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 subcateg ory 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 distribut ion for the dataset, the UPL was calculated using the corresponding equation fo r the distribution for that data set, as described in Section IV.A of this memorandum. See Appendix B fo r UPL summary tables for new and existing

sources.

Step 6.

The results of the UPL calculation were comp ared 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 measuremen t 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 fina l 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% O 2 

### ). The final non-Hg HAP metals emi ssion 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% O 2 

### ), 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 mo re details about the c onversion of the 3xRDL

values to the units of meas ure 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 le ss than the 3xRDL value, the 3xRDL value was

used as the basis for the standard because th e 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 so urce 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-0 5 0.035 0.016 0.036 lb/ton

Equivalent PM 0.0011 7.8E-07 0. 0029 0.0012 0.0029 gr/dscf @ 17% O 2

Small Kilns PM 0.063 0.00 57 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% O 2 Large Kilns Non-Hg HAP Metals 0.00 13 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%
O 2 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%
O 2 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-0 5 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% O 2

Small Kilns PM 0.0093 3.0E-0 5 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% O 2 Large Kilns Non-Hg HAP Metals 0.00 12 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%
O 2 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%
O 2 Equivalent Mercury 0.0010 1.8E-09 0.0019 2.0E-04 0.0019 lb/hr

### 13 VII. References

ASME (founded as the American Societ y 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 Uppe r 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, EP A/OAQPS/SPPD, to Docket ID No. EPAHQ-OAR-2013-0291. September 23, 2015.

Gayen, A. K. 1949. “The Distribution of Stude nt’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 Pred iction Limit to Limited Datasets

. Memorandum from Sharon Nizi ch, 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/OAQ PS/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 Lim it for Calculating MACT Floors

. Memorandum from Jeff Telander, EPA/OAQ PS/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 po llutant 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 ar e 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-2Table A-1. Final Standards for Large Kilns – PM lb/ton RankingKiln IDAPCD TypeSizeClassAverage PM(lb/ton)VarianceBelow 1mg ValuenRank byAverage514 DIFF Large Area Source (synthetic) 0.00757 7.68E-06 2 1538 DIFF Large Major Source 0.00868 1.09E-05 yes 5 2508 DIFF Large Major Source 0.01003 1.71E-05 5 3695 None Large Major Source 0.01278 1.26E-06 2 4503 DIFF Large Area Source (synthetic) 0.01399 3.67E-07 3 5568 DIFF Large Area Source (synthetic) 0.01709 5.99E-05 2 6696 DLA Large Major Source 0.01761 1.38E-04 3 7600 DIFF Large Area Source (synthetic) 0.01799 2.98E-04 yes 6 8604 DLS Large Area Source (synthetic) 0.01843 3.98E-05 3 9688 DIFF Large Area Source (synthetic) 0.02899 1.41E-04 5 10603 DLS Large Area Source (synthetic) 0.03278 2.23E-04 3 11558 DIFF Large Major Source 0.03471 1.05E-03 yes 6 12610 DIFF Large Area Source (synthetic) 0.03602 7.97E-05 5 13673 DLA Large Major Source 0.03627 1.23E-04 6 14674 DLA Large Major Source 0.03627 1.23E-04 6 15662 DLA Large Major Source 0.03784 6.66E-04 3 16543 DIFF Large Area Source (synthetic) 0.03790 1.10E-03 yes 5 17606 DIFF Large Major Source 0.03901 1.80E-03 yes 3 18502 DLS Large Major Source 0.04255 1.48E-03 yes 6 19544 DIFF Large Area Source (synthetic) 0.04487 1.09E-03 yes 14 20654 DIFF Large Area Source (synthetic) 0.04500 3.28E-05 3 21583 DLA Large Major Source 0.04765 3.08E-04 3 22680 DLA Large Major Source 0.04959 6.83E-05 3 23653 DIFF Large Major Source 0.05149 4.00E-05 5 24566 DIFF Large Major Source 0.06024 3.28E-03 yes 8 25506 DLS Large Area Source (synthetic) 0.06262 4.10E-04 5 26770 DLA Large Major Source 0.06884 1.92E-04 3 27526 DIFF Large Major Source 0.06969 1.05E-03 9 28547 DIFF Large Major Source 0.07636 5.17E-04 3 29A-3Kiln IDAPCD TypeSizeClassAverage PM(lb/ton)VarianceBelow 1mg ValuenRank byAverage548 DIFF Large Major Source 0.07636 5.17E-04 3 30527 DIFF Large Major Source 0.07699 6.23E-03 yes 9 31725 DLA Large Area Source (synthetic) 0.07840 1.93E-03 3 32691 DLA Large Area Source (synthetic) 0.08227 4.29E-04 3 33769 DLA Large Major Source 0.08635 4.66E-04 3 34625 DLA Large Major Source 0.09099 5.79E-04 3 35567 DIFF Large Major Source 0.09304 5.67E-04 3 36721 WS Large Area Source (synthetic) 0.09565 1.82E-03 5 37724 DLA Large Area Source (synthetic) 0.09599 7.78E-04 3 38641 DLA Large Area Source (synthetic) 0.09977 1.64E-03 3 39518 DLA Large Major Source 0.10624 5.28E-04 3 40679 DLA Large Major Source 0.10847 3.80E-03 3 41738 DIFF Large Area Source (synthetic) 0.11217 8.58E-03 6 42573 DLA, FCA Large Area Source (synthetic) 0.13228 2.02E-04 3 43730 DLA Large Major Source 0.13851 2.63E-03 6 44577 DLA Large Major Source 0.14145 3.56E-02 13 45578 DLA Large Major Source 0.14145 3.56E-02 13 46649 DLA Large Major Source 0.14213 9.04E-03 6 47646 DLA Large Area Source (synthetic) 0.14327 1.01E-02 6 48675 DIFF Large Area Source (synthetic) 0.14825 1.72E-03 3 49740 DLA Large Area Source (synthetic) 0.15802 2.68E-03 3 50729 DLA Large Major Source 0.17786 1.91E-03 3 51644 DLA Large Major Source 0.17806 9.79E-04 3 52676 DIFF Large Area Source (synthetic) 0.18995 3.55E-02 6 53736 DLA Large Area source (synthetic) 0.20060 7.15E-03 3 54647 DLA Large Area Source (synthetic) 0.23418 3.68E-02 7 55655 DIFF Large Area Source (synthetic) 0.23971 5.23E-02 5 56645 DLA Large Major Source 0.26210 6.74E-03 6 57539 None Large Major Source 0.28166 5.73E-03 2 58720 WS Large Area Source (synthetic) 0.32413 1.33E-01 5 59768 DLA Large Major Source 0.37699 1.40E-02 3 60A-4Kiln IDAPCD TypeSizeClassAverage PM(lb/ton)VarianceBelow 1mg ValuenRank byAverage643 WS Large Area Source (synthetic) 0.37757 5.25E-02 7 61612 DLA Large Major Source 0.41284 1.27E-02 3 62613 DLA Large Major Source 0.41284 1.27E-02 3 63551 DLA Large Major Source 0.57684 5.15E-02 16 64552 DLA Large Major Source 0.57684 5.15E-02 16 65775 None Large Major Source 0.64068 4.38E-02 6 66766 DLA Large Major Source 0.82067 7.89E-01 6 67767 DLA Large Major Source 0.82067 7.89E-01 6 68A-5Table A-2. Final Standards for Large Kilns – PM gr/dscf @ 17% O2RankingKiln IDAPCD TypeSizeClassAverage PM(gr/dscf @17% O2)VarianceBelow 1mg ValuenRank byAverage508 DIFF Large Major Source 0.000614 7.83E-08 5 1695 None Large Major Source 0.000648 4.18E-08 2 2514 DIFF Large Area Source (synthetic) 0.000697 7.72E-08 2 3503 DIFF Large Area Source (synthetic) 0.000767 9.80E-09 3 4568 DIFF Large Area Source (synthetic) 0.001337 3.04E-07 2 5600 DIFF Large Area Source (synthetic) 0.001558 2.25E-06 yes 6 6604 DLS Large Area Source (synthetic) 0.001728 2.37E-07 3 7543 DIFF Large Area Source (synthetic) 0.001882 1.99E-06 yes 5 8662 DLA Large Major Source 0.002669 4.05E-06 3 9603 DLS Large Area Source (synthetic) 0.002695 1.16E-06 3 10544 DIFF Large Area Source (synthetic) 0.002717 4.55E-06 yes 14 11654 DIFF Large Area Source (synthetic) 0.002767 4.40E-08 3 12606 DIFF Large Major Source 0.002868 9.96E-06 yes 3 13566 DIFF Large Major Source 0.003060 7.11E-06 yes 8 14502 DLS Large Major Source 0.003358 9.86E-06 yes 6 15688 DIFF Large Area Source (synthetic) 0.003431 2.17E-06 5 16769 DLA Large Major Source 0.003624 2.20E-07 3 17653 DIFF Large Major Source 0.003729 1.18E-06 5 18610 DIFF Large Area Source (synthetic) 0.003753 2.53E-06 5 19527 DIFF Large Major Source 0.003902 1.29E-05 yes 9 20526 DIFF Large Major Source 0.004072 4.72E-06 9 21538 DIFF Large Major Source 0.004107 1.33E-05 yes 5 22680 DLA Large Major Source 0.004332 3.07E-07 3 23547 DIFF Large Major Source 0.004486 1.69E-06 3 24548 DIFF Large Major Source 0.004486 1.69E-06 3 25506 DLS Large Area Source (synthetic) 0.004710 1.64E-06 5 26721 WS Large Area Source (synthetic) 0.004760 3.68E-06 5 27567 DIFF Large Major Source 0.005333 2.00E-06 3 28558 DIFF Large Major Source 0.005418 2.49E-05 yes 6 29A-6Kiln IDAPCD TypeSizeClassAverage PM(gr/dscf @17% O2)VarianceBelow 1mg ValuenRank byAverage641 DLA Large Area Source (synthetic) 0.005652 5.11E-06 3 30518 DLA Large Major Source 0.006929 2.17E-06 3 31770 DLA Large Major Source 0.007347 4.92E-06 3 32725 DLA Large Area Source (synthetic) 0.007843 2.07E-05 3 33724 DLA Large Area Source (synthetic) 0.008930 1.77E-05 3 34675 DIFF Large Area Source (synthetic) 0.010095 3.12E-05 3 35646 DLA Large Area Source (synthetic) 0.010943 5.19E-05 6 36649 DLA Large Major Source 0.011338 5.89E-05 6 37720 WS Large Area Source (synthetic) 0.011467 1.28E-04 5 38730 DLA Large Major Source 0.012457 2.12E-05 6 39740 DLA Large Area Source (synthetic) 0.012769 2.11E-05 3 40679 DLA Large Major Source 0.013785 4.40E-05 3 41644 DLA Large Major Source 0.014006 6.72E-06 3 42655 DIFF Large Area Source (synthetic) 0.015596 2.35E-04 5 43577 DLA Large Major Source 0.016035 5.14E-04 13 44578 DLA Large Major Source 0.016035 5.14E-04 13 45729 DLA Large Major Source 0.016105 1.28E-05 3 46647 DLA Large Area Source (synthetic) 0.017307 1.94E-04 7 47676 DIFF Large Area Source (synthetic) 0.018290 3.63E-04 6 48645 DLA Large Major Source 0.025039 9.03E-05 6 49551 DLA Large Major Source 0.026017 9.22E-05 16 50552 DLA Large Major Source 0.026017 9.22E-05 16 51539 None Large Major Source 0.026224 4.43E-05 2 52768 DLA Large Major Source 0.028201 8.93E-05 3 53612 DLA Large Major Source 0.032152 1.05E-04 3 54613 DLA Large Major Source 0.032152 1.05E-04 3 55643 WS Large Area Source (synthetic) 0.038993 8.70E-04 7 56775 None Large Major Source 0.042195 6.60E-05 6 57A-7Table A-3. Final Standards for Small Kilns – PM lb/ton RankingKiln IDAPCD TypeSizeClassAverage PM(lb/ton)VarianceBelow 1mg ValuenRank byAverage599 DIFF Small Major Source 0.00930 2.99E-05 3 1549 None Small Major Source 0.01960 1.36E-05 3 2531 SD/ESP Small Major Source 0.11149 6.80E-03 6 3532 SD/ESP Small Major Source 0.11149 6.80E-03 6 4533 SD/ESP Small Major Source 0.18153 1.96E-03 3 5180 None Small Major Source 0.18290 1.06E-03 3 6521 None Small Major Source 0.23121 1.31E-03 3 7178 None Small Major Source 0.24311 5.22E-03 3 8650 None Small Major Source 0.25022 4.06E-03 3 9516 None Small Major Source 0.29156 7.25E-03 6 10179 None Small Major Source 0.31288 1.06E-04 3 11669 None Small Major Source 0.37566 2.73E-04 3 12529 None Small Major Source 0.38192 1.95E-02 3 13530 None Small Major Source 0.39455 1.49E-02 9 14535 None Small Major Source 0.66397 1.98E-02 3 15706 None Small Major Source 0.74622 2.61E-01 6 16704 None Small Major Source 1.18767 6.79E-02 3 17705 None Small Major Source 1.18767 6.79E-02 3 18A-8Table A-4. Final Standards for Small Kilns – PM gr/dscf @ 17% O2RankingKiln IDAPCD TypeSizeClassAverage PM(gr/dscf @ 17%O2)VarianceBelow 1mg ValuenRank byAverage599 DIFF Small Major Source 0.000647 1.43E-07 3 1549 None Small Major Source 0.001046 7.72E-08 3 2531 SD/ESP Small Major Source 0.006673 3.07E-05 6 3532 SD/ESP Small Major Source 0.006673 3.07E-05 6 4180 None Small Major Source 0.009619 3.02E-06 3 5530 None Small Major Source 0.010404 1.21E-05 9 6178 None Small Major Source 0.011154 1.61E-05 3 7533 SD/ESP Small Major Source 0.011596 3.31E-06 3 8521 None Small Major Source 0.012629 3.03E-06 3 9529 None Small Major Source 0.012911 1.29E-05 3 10179 None Small Major Source 0.014582 3.62E-07 3 11516 None Small Major Source 0.023365 4.50E-05 6 12535 None Small Major Source 0.024064 1.72E-05 3 13650 None Small Major Source 0.025025 7.14E-05 3 14A-9Table A-5. Final Standards for Large Kilns – Non-Hg Metal HAP lb/hr RankingKiln IDAPCDTypeSizeClassAverage TotalNon-Hg Metals(lb/hr)VarianceOverall StatusnRank526 DIFF Large Major Source 1.15E-03 7.10E-08 DLL 3 1653 DIFF Large Major Source 1.48E-03 2.04E-07 DLL 2 2600 DIFF Large Area Source (synthetic) 1.69E-03 5.79E-08 DLL 3 3558 DIFF Large Major Source 1.79E-03 2.33E-06 DLL 3 4544 DIFF Large Area Source (synthetic) 1.93E-03 5.98E-08 DLL 3 5543 DIFF Large Area Source (synthetic) 2.14E-03 1.60E-08 DLL 2 6508 DIFF Large Major Source 2.71E-03 1.76E-06 DLL 3 7606 DIFF Large Major Source 3.35E-03 8.32E-10 DLL 2 8527 DIFF Large Major Source 3.72E-03 4.65E-07 DLL 3 9676 DIFF Large Area Source (synthetic) 4.33E-03 1.09E-08 DLL 2 10566 DIFF Large Major Source 4.42E-03 4.27E-06 DLL 2 11655 DIFF Large Area Source (synthetic) 4.91E-03 1.41E-07 DLL 3 12720 WS Large Area Source (synthetic) 9.91E-03 4.87E-07 DLL 2 13721 WS Large Area Source (synthetic) 2.89E-02 7.88E-04 DLL 2 14Table A-6. Final Standards for Small Kilns – Non-Hg Metal HAP lb/hr RankingKiln IDAPCDTypeSizeClassAverage TotalNon-Hg Metals(lb/hr)VarianceOverall StatusnRank531 SD/ESP Small Major Source 2.84E-02 6.15E-05 DLL 3 1532 SD/ESP Small Major Source 2.84E-02 6.15E-05 DLL 3 2A-10Table A-7. Final Standards for Large Kilns – Hg lb/ton RankingaKiln IDAPCDTypeSizeClassAverage Hg(lb/ton)VarianceOverallStatusnRank byAverage568 DIFF Large Area Source (synthetic) 1.48E-05 8.83E-13 BDL 3 1558 DIFF Large Major Source 1.70E-05 1.43E-12 DLL 3 2655 DIFF Large Area Source (synthetic) 1.72E-05 3.10E-11 ADL 3 3547 DIFF Large Major Source 2.31E-05 2.33E-11 DLL 3 4548 DIFF Large Major Source 2.31E-05 2.33E-11 DLL 3 5676 DIFF Large Area Source (synthetic) 2.70E-05 8.99E-12 DLL 3 6503 DIFF Large Area Source (synthetic) 2.91E-05 7.63E-12 DLL 3 7566 DIFF Large Major Source 3.27E-05 2.37E-12 BDL 3 8606 DIFF Large Major Source 3.85E-05 3.30E-11 DLL 3 9721 WS Large Area Source (synthetic) 3.93E-05 4.84E-10 DLL 2 10720 WS Large Area Source (synthetic) 6.22E-05 2.92E-10 DLL 2 11543 DIFF Large Area Source (synthetic) 7.66E-05 7.09E-12 DLL 3 12775 None Large Major Source 7.79E-05 1.60E-09 DLL 3 13526 DIFF Large Major Source 8.50E-05 7.47E-10 ADL 3 14600 DIFF Large Area Source (synthetic) 8.94E-05 1.08E-10 ADL 3 15508 DIFF Large Major Source 9.08E-05 1.21E-10 DLL 3 16527 DIFF Large Major Source 9.08E-05 5.98E-11 ADL 3 17544 DIFF Large Area Source (synthetic) 9.78E-05 1.02E-10 DLL 3 18653 DIFF Large Major Source 1.02E-04 9.35E-12 DLL 3 19aADL = above detection level; WS = wet scrubber; NA = not applicable.A-11Table A-8. Final Standards for Large Kilns – Hg μg/dscm @ 17% O2RankingaKiln IDAPCDTypeSizeClassAverage Hg(μg/dscm @17% O2)VarianceOverallStatusnRank byAverage655 DIFF Large Area Source (synthetic) 2.51 6.81E-01 ADL 3 1568 DIFF Large Area Source (synthetic) 2.93 8.86E-02 BDL 3 2547 DIFF Large Major Source 3.67 7.83E-01 DLL 3 3548 DIFF Large Major Source 3.67 7.83E-01 DLL 3 4503 DIFF Large Area Source (synthetic) 3.71 7.82E-02 DLL 3 5566 DIFF Large Major Source 4.53 7.43E-02 BDL 3 6721 WS Large Area Source (synthetic) 4.54 7.95E+00 DLL 2 7720 WS Large Area Source (synthetic) 4.68 1.49E+00 DLL 2 8676 DIFF Large Area Source (synthetic) 6.17 5.94E-01 DLL 3 9606 DIFF Large Major Source 6.22 2.01E+00 DLL 3 10558 DIFF Large Major Source 6.73 5.28E-01 DLL 3 11526 DIFF Large Major Source 9.36 1.26E+01 ADL 3 12527 DIFF Large Major Source 9.81 6.20E-01 ADL 3 13543 DIFF Large Area Source (synthetic) 12.25 2.90E-02 DLL 3 14508 DIFF Large Major Source 13.40 3.12E+00 DLL 3 15775 None Large Major Source 13.81 4.96E+01 DLL 3 16544 DIFF Large Area Source (synthetic) 14.44 5.67E+00 DLL 3 17653 DIFF Large Major Source 14.48 2.28E-02 DLL 3 18600 DIFF Large Area Source (synthetic) 16.84 5.77E-01 ADL 3 19aADL = above detection level; WS = wet scrubber; NA = not applicable.A-12Table A-9. Final Standards for Large Kilns – Hg lb/hr RankingaKiln IDAPCDTypeSizeClassAverage Hg(lb/hr)VarianceOverallStatusnRank byAverage655 DIFF Large Area Source (synthetic) 1.37E-04 1.97E-09 ADL 3 1568 DIFF Large Area Source (synthetic) 1.75E-04 1.25E-10 BDL 3 2558 DIFF Large Major Source 1.94E-04 1.86E-10 DLL 3 3676 DIFF Large Area Source (synthetic) 2.08E-04 5.33E-10 DLL 3 4503 DIFF Large Area Source (synthetic) 2.77E-04 6.93E-10 DLL 3 5547 DIFF Large Major Source 2.83E-04 1.21E-08 DLL 3 6548 DIFF Large Major Source 2.83E-04 1.21E-08 DLL 3 7720 WS Large Area Source (synthetic) 4.03E-04 1.22E-08 DLL 2 8526 DIFF Large Major Source 4.41E-04 2.01E-08 ADL 3 9721 WS Large Area Source (synthetic) 5.74E-04 1.03E-07 DLL 2 10775 None Large Major Source 6.20E-04 1.01E-07 DLL 3 11527 DIFF Large Major Source 6.41E-04 2.98E-09 ADL 3 12606 DIFF Large Major Source 6.48E-04 9.32E-09 DLL 3 13544 DIFF Large Area Source (synthetic) 6.60E-04 4.63E-09 DLL 3 14566 DIFF Large Major Source 6.62E-04 9.71E-10 BDL 3 15653 DIFF Large Major Source 6.78E-04 4.16E-10 DLL 3 16600 DIFF Large Area Source (synthetic) 1.07E-03 1.55E-08 ADL 3 17543 DIFF Large Area Source (synthetic) 1.12E-03 1.52E-09 DLL 3 18508 DIFF Large Major Source 1.33E-03 2.59E-08 DLL 3 19aADL = above detection level; WS = wet scrubber; NA = not applicable.A-13Table A-10. Final Standards for Small Kilns – Hg lb/ton RankingaKiln NoAPCDTypeSizeClassAverage(lb/ton)VarianceOverallStatusnRank byAverage531 SD/ESP Small Major Source 1.76E-04 5.51E-11 DLL 3 1532 SD/ESP Small Major Source 1.76E-04 5.51E-11 DLL 3 2aSD/ESP = spray dryer/electrostatic precipitator.Table A-11. Final Standards for Small Kilns – Hg μg/dscm @ 17% O2RankingaKiln IDAPCDTypeSizeClassAverage Hg(μg/dscm @ 17%O2)VarianceOverallStatusnRank byAverage531 SD/ESP Small Major Source 17.36 1.71E-01 DLL 3 1532 SD/ESP Small Major Source 17.36 1.71E-01 DLL 3 2aSD/ESP = spray dryer/electrostatic precipitator.Table A-12. Final Standards for Small Kilns – Hg lb/hr RankingaKiln IDAPCDTypeSizeClassAverage Hg (lb/hr)VarianceOverallStatusnRank byAverage531 SD/ESP Small Major Source 9.97E-04 7.05E-09 DLL 3 1532 SD/ESP Small Major Source 9.97E-04 7.05E-09 DLL 3 2aSD/ESP = spray dryer/electrostatic precipitator.

### Appendix B

UPL Tables

### B-1 UPL Tables

Once the best performing sources were iden tified per pollutant and subcategory, the existing and new source UPL values were calcu lated. 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-2Table B-1. Final Standards Existing Source UPL SummarySubcategoryPollutantNo. ofSourcesIndustrywideNo. ofSourceswith DataDeterminationof No. ofSources inMACT FloorNo. ofSourcesin MACTFloor (N)No. DataPoints inMACTFloor (n)Averageof TopSourcesVarianceof TopSourcesUPLUnit ofMeasureDataDistributionLarge Kilns PM 122 6812% Sourceswith Data9 31 0.014 8.5E-05 0.035 lb/tonlognormalEquivalent PM 122 5712% Sourceswith Data7 23 0.0011 7.8E-07 0.0029gr/dscf @17% O2lognormalSmall Kilns PM 98 1812% Sourceswith Data3 12 0.063 0.0057 0.36 lb/tonlognormalEquivalent PM 98 1412% Sourceswith Data2 6 8.5E-04 1.4E-07 0.0021gr/dscf @17% O2lognormalLarge KilnsNon-Hg HAPMetals122 1412% Sourceswith Data2 5 0.0013 1.2E-07 0.0022 lb/hr normalSmall KilnsNon-Hg HAPMetals98 212% Sourceswith Data1 3 0.057 2.5E-04 0.10 lb/hr lognormalLarge KilnsMercury1221912% Sourceswith Data391.6E-059.7E-124.1E-05lb/tonnormalEquivalentMercury1221912% Sourceswith Data393.00.657.7μg/dscm @17% O2normalEquivalentMercury1221912% Sourceswith Data391.7E-041.2E-095.4E-04lb/hrskewed/unknownSmall KilnsMercury98212% Sourceswith Data131.8E-045.5E-113.3E-04lb/tonlognormalEquivalentMercury98212% Sourceswith Data13170.1791μg/dscm @17% O2normalEquivalentMercury98212% Sourceswith Data130.00101.8E-090.0019lb/hrlognormalB-3Table B-2. Final Standards New Source UPL SummarySubcategoryPollutantNo. ofSourcesIndustrywideNo. ofSourceswithDataDeterminationof No. ofSources inMACT FloorNo. ofSourcesin MACTFloor (N)No. DataPoints inMACTFloor (n)Averageof TopSourcesVarianceof TopSourcesUPLUnit ofMeasureDataDistributionLarge Kilns PM 122 6812% Sourceswith Data1 5 0.0087 1.1E-05 0.018 lb/ton normalEquivalent PM 122 5712% Sourceswith Data1 5 6.1E-04 7.8E-08 0.0014gr/dscf @17% O2normalSmall Kilns PM 98 1812% Sourceswith Data1 3 0.0093 3.0E-05 0.029 lb/ton lognormalEquivalent PM 98 1412% Sourceswith Data1 3 6.5E-04 1.4E-07 0.0020gr/dscf @17% O2lognormalLarge KilnsNon-Hg HAPMetals122 1412% Sourceswith Data1 3 0.0012 7.1E-08 0.0027 lb/hr normalSmall KilnsNon-Hg HAPMetals98 212% Sourceswith Data1 3 0.057 2.5E-04 0.10 lb/hr lognormalLarge KilnsMercury1221912% Sourceswith Data131.5E-058.8E-132.8E-05lb/tonlognormalEquivalentMercury1221912% Sourceswith Data132.50.686.1μg/dscm @17% O2lognormalEquivalentMercury1221912% Sourceswith Data131.4E-042.0E-093.3E-04lb/hrlognormalSmall KilnsMercury98212% Sourceswith Data131.8E-045.5E-113.3E-04lb/tonlognormalEquivalentMercury98212% Sourceswith Data13170.1791μg/dscm @17% O2normalEquivalentMercury98212% Sourceswith Data130.00101.8E-090.0019lb/hrlognormal

### Appendix C

Conversion of 3xRDL Values to Units Other Th an Concentration to Facilitate Comparison

with UPL Values

### C-1 Conversion of 3xRDL Values to Units Other Th an Concentration to Facilitate Comparison

with UPL Values

The standard 3xRDL values developed for sp ecific pollutants at certain sample volumes are presented in a guidance document develo ped by the EPA (Westlin and Merrill, 2011).

For the BSCP Manufacturing MACT floors, th e units of measure used to develop the

UPL values were lb/ton bric k, lb/hr, gr/dscf @ 17% O 2 

### , and μg/dscm @ 17% O 2 

### . However, the 3xRDL values from the guidance document are gi ven in units of concen tration, specifically μg/dscm for metals and PM. In order to comp are the calculated UPL with the 3xRDL for a particular pollutant, we needed to convert the 3xR DL value to the units of measure used in the UPL calculation. This appendix describes th e procedure used for that conversion.

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

calculations used to convert the 3xRDL values fo r each pollutant and subcategory. The tables in this appendix are summary excerpts of the in formation from that Microsoft Excel® file.

1. For all of the sources in th e MACT floor pool, we looked at each test run that was flagged by respondents to the BSCP survey as below detection leve l (BDL), detection level limited (DLL), or above detection level (ADL). We proceeded with the following steps to convert the 3xRDL value to th e 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, a nd lb/hr values for those sources and noted the sample volume (d scm) 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% O 2 

### / μg/dscm; Non-Hg Metal HAP lb/hr / μg/dscm; Hg lb/ton / μg/dscm; Hg μg/dscm @ 17% O 2 

### / μg/dscm; and Hg lb/hr / μg/dscm.

4. We calculated the average of all the ratio values. Table C-1 pr ovides 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% O 2 / μg/dscm

Small Kilns PM 5.30E-06 lb/ton / μg/dscm
PM (equivalent) 3.22E-07 gr/dscf @ 17% O 2 / μg/dscm

Large Kilns Hg 4.70E-06 lb/ton / μg/dscm
Hg (equivalent) 9.07E-01 μg/dscm @ 17% O 2 / 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% O 2 / 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, th e typical sample volume was equal to 1 dscm for most

BSCP tests.

6. We identified the appropriate 3xRDL concentr ation 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 concentra tion values for PM, Hg, and Total Non-Hg Metals at the typical samp le 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+00C-37.We multiplied the appropriate 3xRDL concentration value for the typical sample volume by the average ratio in Table C-1 toconvert the 3xRDL value into the units ofmeasure used in the UPL calculation (e.g., lb/ton; lb/hr; gr/dscf @17%O2; orμg/dscm @17%O2). Table C-3 displays a summary of the converted 3xRDL values.Table C-3. Converted 3xRDL ValuesSubcategoryPollutantAverageRatioAverage Ratio Units OfMeasure3xRDL atTypicalSampleVolume(μg/dscm)Converted3xRDLValueConverted 3xRDLValue Units OfMeasureLarge Kilns PM 5.26E-06 lb/ton / μg/dscm 3.0E+03 0.016 lb/tonPM (equivalent) 3.99E-07 gr/dscf @ 17% O2/ μg/dscm 3.0E+03 0.0012 gr/dscf @ 17% O2Small Kilns PM 5.30E-06 lb/ton / μg/dscm 3.0E+03 0.016 lb/tonPM (equivalent) 3.22E-07 gr/dscf @ 17% O2/ μg/dscm 3.0E+03 0.0010 gr/dscf @ 17% O2Large Kilns Hg 4.70E-06 lb/ton / μg/dscm 1.7E+00 8.0E-06 lb/tonHg (equivalent) 9.07E-01 μg/dscm @ 17% O2/ μg/dscm 1.7E+00 1.5 μg/dscm @ 17% O2Hg (equivalent) 4.72E-05 lb/hr / μg/dscm 1.7E+00 8.0E-05 lb/hrSmall Kilns Hg 1.02E-05 lb/ton / μg/dscm 1.7E+00 1.7E-05 lb/tonHg (equivalent) 1.01E+00 μg/dscm @ 17% O2/ μg/dscm 1.7E+00 1.7 μg/dscm @ 17% O2Hg (equivalent) 1.16E-04 lb/hr / μg/dscm 1.7E+00 2.0E-04 lb/hr8.For Non-Hg HAP Metals there are two setsof 3xRDL values provided by the guidance document per analytical methods forMethod 29: Inductively Coupled AtomicEmission Spectroscopy or Atomic Absorption Analysis (ICP/AES or AA) andInductively Coupled Plasma/Mass Spectrometry or Graphite Furnace Atomic Absorption Analysis (ICP/MS or GFAA). Wemultiplied the appropriate 3xRDL concentration value specific to the analytical method used by each run by run ratio. We thentook the average of those valuesfor the converted 3xRDL value.C-4SubcategoryPollutantRun by Run RatioUnits Of Measure3xRDL at Typical SampleVolume (μg/dscm)Converted3xRDL ValueConverted 3xRDLValue Units OfMeasureLarge Kilns Non-Hg HAP Metals lb/hr / μg/dscm2.6E+02[ICP/AES or AA]and2.7E+01[ICP/MS or GFAA]0.0057 lb/hrSmall Kilns Non-Hg HAP Metals lb/hr / μg/dscm2.6E+02[ICP/AES or AA]and2.7E+01[ICP/MS or GFAA]0.0031 lb/hr9.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 flooremission limit.b.If the 3xRDL value was greater than the calculated UPL value, we used the3xRDL value as the MACT floor emissionlimit.c.Table C-4 and C-5 summarize the results of the calculated UPL and 3xRDL comparison for existing and new sourcefloors.C-5Table C-4. Existing Source FloorsSubcategoryPollutantConverted3xRDL ValueUPLRoundedFloorFloor BasedOnUnits Of MeasureLarge Kilns PM 0.016 0.035 0.036 UPL lb/tonPM (equivalent) 0.0012 0.0029 0.0029 UPL gr/dscf @ 17% O2Small Kilns PM 0.016 0.36 0.37 UPL lb/tonPM (equivalent) 0.0010 0.0021 0.0021 UPL gr/dscf @ 17% O2Large KilnsNon-Hg HAPMetals0.0057 0.0022 0.0057 3xRDL lb/hrSmall KilnsNon-Hg HAPMetals0.0031 0.10 0.11 UPL lb/hrLarge Kilns Hg 8.0E-06 4.1E-05 4.1E-05 UPL lb/tonHg (equivalent) 1.5 7.7 7.7 UPL μg/dscm @ 17% O2Hg (equivalent) 8.0E-05 5.4E-04 5.5E-04 UPL lb/hrSmall Kilns Hg 1.7E-05 3.3E-04 3.3E-04 UPL lb/tonHg (equivalent) 1.7 91 91 UPL μg/dscm @ 17% O2Hg (equivalent) 2.0E-04 0.0019 0.0019 UPL lb/hrC-6Table C-5. New Source FloorsSubcategoryPollutantConverted3xRDL ValueUPLRoundedFloorFloor BasedOnUnits Of MeasureLarge Kilns PM 0.016 0.018 0.018 UPL lb/tonPM (equivalent) 0.0012 0.0014 0.0014 UPL gr/dscf @ 17% O2Small Kilns PM 0.016 0.029 0.030 UPL lb/tonPM (equivalent) 0.0010 0.0020 0.0021 UPL gr/dscf @ 17% O2Large KilnsNon-Hg HAPMetals0.0057 0.0027 0.0057 3xRDL lb/hrSmall KilnsNon-Hg HAPMetals0.0031 0.10 0.11 UPL lb/hrLarge Kilns Hg 8.0E-06 2.8E-05 2.8E-05 UPL lb/tonHg (equivalent) 1.5 6.1 6.2 UPL μg/dscm @ 17% O2Hg (equivalent) 8.0E-05 3.3E-04 3.4E-04 UPL lb/hrSmall Kilns Hg 1.7E-05 3.3E-04 3.3E-04 UPL lb/tonHg (equivalent) 1.7 91 91 UPL μg/dscm @ 17% O2Hg (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: par ticulate 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 kiln s. 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 st eps: ensuring that we selected the data distribution that best represents each datase t; ensuring that the correct equation for the distribution was then applied to the data; a nd comparing individual components of each limited

dataset to determine if the standards based on limited datasets r easonably 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 Equivale nt PM (gr/dscf @ 17% O 2 

### )

 Large Kilns New Hg (lb/ton)

 Large Kilns New Equivalent Hg (μg/dscm @ 17% O 2 

### )

 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 Equivale nt PM = 0.0021 gr/dscf @ 17% O 2



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

 Large Kilns New Equivalent Hg = 6.2 μg/dscm @ 17% O 2



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

### Appendix E

Development of Hg Raw Mat erial Variability Factor

### E-1 Development of Hg Raw Mat erial 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.