1

Date: September 26, 2014

Subject: Revised Technical Approach for Mineral Wool Production MACT Floor Calculations

40 CFR 63, Subpart DDD – Supplemental Proposal

EPA Contract No. EP-D-11-084; EPA Work Assignment No. 2-09

RTI Project No. 0213199.002.009

From: Cindy Hancy

Dave Reeves

To: Susan Fairchild, EPA/OAQPS/SPPD/MMG

I. Introduction

Section 112 of the Clean Air Act (CAA) requires that the U.S. Environmental Protection Agency 

(EPA) establish National Emission Standards for Hazardous Air Pollutants (NESHAP) for the control of

hazardous air pollutants (HAP) emitted from both new and existing major sources in a source category.

These standards must reflect the “Maximum Achievable Control Technology (MACT) floor” for HAP 

emitted by these sources. The method for determining the MACT floor for a NESHAP is defined for 

both new and existing sources in 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 five sources for source categories with fewer than 30 sources.

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

floor analysis for the Mineral Wool Production NESHAP source category. This MACT floor analysis 

uses data collected from a voluntary, nationwide Information Collection Request (ICR) of mineral wool 

manufacturers conducted by EPA in 2010. Data on process operations, emission controls, and air 

emissions data reported by respondents to the ICR were compiled into a Microsoft Access data base that 

serves as the data set used for this MACT floor analysis (referred to in this memorandum as the “ICR 

data set”).

On November 25, 2011 EPA proposed revisions to the Mineral Wool Manufacturing NESHAP, 

40 CFR part 63, subpart DDD. Based on comments received on the November 2011 proposal and 

additional data received from industry, EPA published a supplemental proposal on April 15, 2013 with 

additional revisions to Subpart DDD. This memorandum incorporates changes made since the April 

2013 supplemental proposal including changes made as a result of public comments regarding facility 

information and emissions data.

II. Background Information

The Mineral Wool Production source category consists of 7 facilities operating in the United 

States. The 7 facilities operate 11 cupolas and 3 bonded manufacturing lines. Since the April 2013 
2

supplemental proposal, one additional plant has begun pre-production operations; this plant operates 2

mineral wool cupolas and 2 bonded manufacturing lines. The specific chemicals, compounds, or groups 

of compounds designated as HAP are listed in CAA section 112(b). From this list, the following 

additional HAPs were identified as being emitted from cupolas and were proposed to be regulated for 

new and existing sources: carbonyl sulfide (COS), hydrogen fluoride (HF), and hydrogen chloride (HCl) 

for cupolas and formaldehyde, phenol, and methanol from bonded manufacturing lines. 

III. Overview of the Proposed MACT Floor Limits in the 2011 Proposal and 2013 

Supplemental Proposal

This section provides an overview of the MACT floor limits that were revised in the 2011

proposal and the 2013 supplemental proposal. Table 1 provides an overview of the limits that have been 

proposed for mineral wool since the November 2011 proposal. Detailed information on 

subcategorization can be found in previous Technical Approach for Mineral Wool MACT Floor 

Calculations memoranda (EPA-HQ-OAR-2010-1041-0019 and EPA-HQ-OAR-2010-1041-0109).

A. Carbon Monoxide (CO) and Carbonyl Sulfide (COS)

The current mineral wool NESHAP sets limits for CO that serve as a surrogate for COS. In the 

November 2011 proposal, EPA proposed to remove the CO limits in the current rule and set COS 

MACT floor limits for all new and existing cupolas. In response to comments and additional information

submitted regarding cupola design, EPA proposed to subcategorize cupolas and set COS limits for both 

closed-top and open-top cupolas in the 2013 supplemental proposal. 

B. Hydrogen Fluoride (HF) and Hydrogen Chloride (HCl)

In the November 2011 proposal, EPA proposed new and existing MACT floor limits for HF and 

HCl for all cupolas. Similar to the COS issue, EPA received comments, additional test data and

information regarding cupola design and raw materials. The EPA reviewed its analysis of acid gas test 

data and in 2013 proposed to subcategorize cupolas by whether or not slag is used as a raw material 

since it can contain residual fluorides and chlorides. The EPA proposed HF and HCl limits for both slag

and non-slag processing cupolas in the 2013 supplemental proposal. 

C. Formaldehyde, Phenol and Methanol

The mineral wool production industry currently includes three facilities that make bonded 

mineral wool. The current mineral wool NESHAP sets formaldehyde limits for curing ovens that also 

serve as a surrogate for methanol and phenol. In the November 2011 proposal, the EPA proposed to 

remove the surrogacy relationship in the rule and proposed MACT Floor limits for phenol, methanol and 

formaldehyde based on data submitted by the industry in their voluntary information collection. The 

proposed 2011emissions limits applied to curing and collection operations in aggregate at bonded 

mineral wool lines. After the 2011 proposal, EPA received information from industry on the process 

designs of the three bonded mineral wool operations; specific information was provided on the different 

collection processes at each facility. After reviewing this information, EPA concluded that the 

differences in collection operations warranted subcategorization, and in April 2013 EPA proposed to 

subcategorize combined collection operations and curing ovens into three separate types: vertical, 

horizontal, and drum curing and collection bonded lines. The 2013 supplemental proposal set separate 

formaldehyde, phenol, and methanol emission limits for each subcategory of bonded mineral wool lines

based on test data of each type of bonded line. 
3

IV. Proposed MACT Floor Changes in the 2014 Supplemental Proposal

A. Revisions to MACT Floor Methodology

Since the April 2013 supplemental proposal, the EPA has updated the MACT floor approach for 

existing and new sources that are based on limited datasets (fewer than 7 data points) in order to address 

questions raised in the D .C. Circuit Court of Appeals decision in National Association of Clean Water 

Agencies v. EPA (NACWA). This updated approach affected all of the new and existing source limits for 

formaldehyde, methanol, and phenol for each collection and curing subcategory. The limited dataset 

revisions also affected the new source HF, HCl, and COS limits for cupolas which were based on the 

best performing source and whose MACT floor consisted of limited datasets. The details of the updated 

MACT floor approach for limited data sets can be found in the memorandum “Approach for Applying 

the Upper Prediction Limit to Limited Datasets” (Fairchild, 2014). Table 1 provides an overview of the 

limits that are being revised in the October 2014 Supplemental proposal. Sections IV-VII of this 

memorandum presents the methodology of the mineral wool MACT floor analysis for non-limited 

datasets.

In addition to our updated approach for determining the MACT floor limits based on limited data 

sets, EPA has, in an effort to standardize the UPL calculations, updated the method it uses to calculate 

the standard error of kurtosis (SEK) since the April 2013 supplemental proposal. The updated method of 

calculating SEK is described in detail in Section V of this memorandum. 

B. Additional Revisions to MACT Floor Limits for Cupolas

In the April 2013 supplemental proposal, the EPA proposed limits for HF and HCl for both slag 

and no-slag subcategories of cupolas. The proposed limits for new and reconstructed sources were 

erroneously set equal to the HF and HCl limits for existing sources. The EPA is proposing to correct this 

error and set separate MACT floor HF and HCl emission limits for new and reconstructed sources based 

on the best performing source in each subcategory. 

The EPA is also revising the COS emissions limit for new and reconstructed closed-top mineral 

wool cupolas. The proposed COS emission limit of 0.025 lb/ton of melt (April 2013 proposal) was based 

on the best performing closed-top cupola. Upon further examination EPA realized that this source’s 

testing was below the test method detection limit (BDL) and thus calculated the appropriate 

representative detection limit for the COS test method based on the COS testing conducted at mineral

wool facilities (see “3 x RDL” Values for Carbonyl Sulfide memorandum for more information). The 

EPA then compared the method detection level to the calculated MACT floor limit and found that the 

proposed emission limit was very close to the representative detection limit (RDL). Based on EPA 

guidance for handling MACT floor limits calculated using BDL data (Westlin and Merrill, 2011), EPA 

multiplied the minimum detection level for the analytic method by a factor of three in order to account 

for measurement variability and used this 3x RDL as the MACT floor limit for new and reconstructed 

closed-top mineral wool cupolas. This represents the lowest level that can be reliably measured using 

this test method, and EPA therefore believes that it is the lowest level that can be set as the MACT limit 

taking the appropriate measurement variability into account. Additional discussion on the RDL is in 

Section VI of this memorandum.
4

C. Additional Revisions to MACT Floor Limits for Bonded Mineral Wool Manufacturing Lines

After the April 2013 supplemental proposal, EPA received new formaldehyde, phenol and 

methanol emissions test measurements for horizontal collection/curing lines. The EPA conducted a 

thorough review of the original emission test report which was the basis for the November 2011 

proposed limits, and the new testing the facility submitted. The EPA found that emissions were 

measured at significantly different production rates in the second test than during the first test. After

discussions with both the company and testing contractors to obtain additional information that would 

explain the widely divergent results from the first and second tests (which varied up to an order of 

magnitude), the EPA concluded that the proper action would be to abandon the first test in its entirety 

due to the sample collection and reporting errors, and use the second test in its place because those 

samples were collected and reported correctly. The use of the second test results in the MACT floor 

UPL calculation changed the proposed emission limits for the horizontal collection/curing subcategory. 

(See Rockwool Formaldehyde Emission Testing, Flywool Stack, 9/2010 and 3/2012, August 8, 2013, 

Johnson, S. to Fairchild, S.).
5

Table 1 – Overview of New and Existing Source MACT Limits for Mineral Wool Production

Process Subpart DDD 

Subcategory HAP

Existing Source MACT Floor Limits 

(lb/ton of glass pulled)

New Source MACT Floor Limits 

(lb/ton of glass pulled)

Current 

Rule

2011 

Proposal

2013 

Supp. 

Proposal

2014 

Supp. 

Proposal

Current 

Rule

2011 

Proposal

2013 

Supp. 

Proposal

2014 

Supp. 

Proposal

Cupolas

Processing Slag

HF NA 0.014 0.16 No 

Change NA 0.014 0.16 0.015

HCl NA 0.0096 0.21 0.44 NA 0.0096 0.21 0.012

Not Processing

Slag

HF NA 0.014 0.13 No 

Change NA 0.014 0.13 0.018

HCl NA 0.0096 0.43 No 

Change NA 0.0096 0.43 0.015

Closed-Top COS NA 3.3 3.4 No 

Change NA 0.017 0.025 0.062

Open-Top COS NA 3.3 6.8 No 

Change NA 0.017 4.3 3.2

Combined 

Collection and 

Curing

Vertical 

Collection*

Formaldehyde 0.061 0.46 2.7 2.4 Same as 

Existing

Same as 

Existing

Same as 

Existing

Phenol NA 0.52 0.74 0.71 NA Same as 

Existing

Same as 

Existing

Same as 

Existing

Methanol NA 0.63 1.0 0.92 NA Same as 

Existing

Same as 

Existing

Same as 

Existing

Horizontal 

Collection*

Formaldehyde 0.061 0.054 0.054 0.63 Same as 

Existing

Same as 

Existing

Same as 

Existing

Phenol NA 0.15 0.15 0.12 NA Same as 

Existing

Same as 

Existing

Same as 

Existing

Methanol NA 0.022 0.022 0.049 NA Same as 

Existing

Same as 

Existing

Same as 

Existing

Drum Collection*

Formaldehyde 0.061 0.067 0.18 0.17 Same as 

Existing

Same as 

Existing

Same as 

Existing

Phenol NA 0.0023 1.3 0.85 NA Same as 

Existing

Same as 

Existing

Same as 

Existing

Methanol NA 0.00077 0.48 0.28 NA Same as 

Existing

Same as 

Existing

Same as 

Existing

1Current formaldehyde limits apply to curing ovens only. 
6

V. MACT Floor Approach

A. Upper Prediction Limit (UPL)

The MACT floor analysis for mineral wool manufacturing uses a UPL approach to identify the 

average emission limitation achieved by those best performing sources because this approach

incorporates the average performance of the sources and the variability of the performance during 

testing conditions.1 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 data set 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 data set. 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 each source’s data.

The UPL is a value derived from widely accepted and commonly used statistical principles, and 

represents the upper end of a prediction interval. The UPL is used in a wide variety of industries and 

professions, such as manufacturing, finance, healthcare, etc. and is calculated using one of several 

equations that must be selected based on certain characteristics of each dataset. The most important 

parameters in the UPL calculation are the mean (average) performance of the unit or units, the 

distribution of the dataset, the variance in the measured emission values (that is, the individual data 

points), and the sample size. The equations that are used to calculate the UPL are explained in more 

detail below.

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):

 

1 See the July 2014 memorandum Use of the Upper Prediction Limit for Calculating MACT Floors and the October 2014 

memorandum Approach for Applying the Upper Prediction Limit to Limited Datasets.
7

  

3

1 2 1













 

 



n

i

i

stdev

x x

n n

n

Skewness

where:

n = sample size

x = mean of MACT floor pool

xi = individual source mean

stdev =

     



1

2

n

x x i

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

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

using the following equation:

  

 2 1 3

6 1

  

 



n n n

n n

SES

Using the standard 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 three. A 

K value that is greater than three indicates a relatively peaked distribution. A K value that is less than 

three indicates a relatively flat distribution. The estimate of K can be calculated using one of two ways

depending on the number of data points in the data set. For data sets 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

The kurtosis equation cannot be used for data sets with three run values (n=3) because there will 

be a zero in the denominator of the first and second terms. The kurtosis estimated with the “KURT” 

function is called excess kurtosis. It is equal to the kurtosis – 3, so for a normal distribution, excess 

kurtosis = 0. Instead, for data sets with three run values, the excess kurtosis is estimated using the 

following equation:

 

  

3

1

4

1

4











n stdev

x x

Kurtosis

n

i

i
8

As part of determining whether the distribution of the data 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 n

n n

SEK

for datasets with n>3, or

n

SEK 24

for datasets with n=3

According to the standard 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 data set was normally distributed, the data were treated as normally distributed in 

subsequent UPL calculations. If either of these tests indicated the data set was not normally distributed, 

the data set was log-transformed, and the log-transformed data set was evaluated for kurtosis and 

skewness. If both tests of the log-transformed data indicated the log-transformed data were normally 

distributed, the data were treated as lognormally distributed in subsequent UPL calculations. If either of 

these tests indicated the log-transformed data were not normally distributed, the data were treated as 

skewed/unknown distribution in subsequent UPL calculations.

For data sets with only three run values, the result of both the skewness and kurtosis hypothesis 

tests always indicate the data set is normally distributed. Therefore, to determine the appropriate data 

distribution for those data sets, 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 data set, the UPL was 

calculated using the corresponding equation for the distribution for that data set. The UPL equations for 

normal, lognormal, and skewed/unknown distribution data sets are provided below.

Normally Distributed Data Set













  

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

ni 1
9

m = number of future test runs in the compliance average

N = number of sources

s

2 = pooled variance calculated as 

  



 

n

i

i

x x

n

s

1

2 1 2

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

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

using the “TINV” function in Microsoft Excel® software

df = degrees of freedom calculated as 

  1

1

  



N

i

i df n

Lognormally Distributed Data Set (Bhaumik and Gibbons, 2004)

 

 



















    

 



2 1

ˆ ˆ

1

2 4

9 9 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

0.9 9

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
10

n = number of test runs = 



N

i

ni 1

m = number of future test runs in the compliance average

N = number of sources

s

2 = pooled variance calculated as 

  



 

n

i

i

x x

n

s

1

2 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 (RDL)

The imprecision of test method measurements can be a significant component of data variability. 

At very low emissions levels 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. 

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 data sets 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. Carbonyl sulfide (COS) was not part of the available pollutant-specific method 

detection levels list. Since the best performing COS closed-top cupola consisted of test data values that 

were below detection (BDL) EPA calculated the method detection values for COS based on all of the 

COS test data submitted by mineral wool facilities. The results of this are presented in the 
11

“Determination of Representative Detection Level (RDL) and 3 x RDL Values for Carbonyl Sulfide” 

memorandum available in the docket. 

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 are used for the MACT floor 

emission limit to ensure that measurement variability is adequately addressed. This check was part of the 

variability analysis for all existing MACT floors that had below detection level (BDL) or detection level 

limited (DLL) run data present in the best performing data sets. 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” (Fairchild, 2014).

VI. MACT Floor Analysis for Mineral Wool Manufacturing

A. MACT Floor Calculation Steps

Step 1. 

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

source, subcategory and pollutant. The limits for the mineral wool NESHAP are in pounds of pollutant 

per tons of glass pulled; because the majority of the data (e.g., production and equipment throughput 

rates) used to calculate the MACT floor limits are submitted as confidential business information (CBI) 

the data and calculations are not publicly available (and are not included in this memorandum).

Step 2.

Once an average emission value was calculated for each source, subcategory and pollutant, all of 

the individual average emission values were ranked from lowest to highest value. 

Step 3.

Based on the ranking in Step 2, 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 

source was identified. 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 Tables 2 and 3.

Table 2. Number of Sources in Existing Source MACT Floor Pool

Process

Subpart DDD 

Subcategory

No. 

Sources 

Nationwide HAP

No. 

Sources in 

MACT 

Floor Pool

No. of Data 

Points in 

MACT 

Floor Pool Based on

Cupolas

Processing Slag 4

HF

4

12

Best-performing 

five sources for source 

categories with fewer 

than 30 sources

HCl 12

Not Processing

Slag 4

HF

4

12

HCl 12

Closed-Top 5 COS 5 15

Open-Top 3 COS 3 9

Combined 

Collection and 

Curing

Vertical 

Collection* 1

Formaldehyde

1

3

Only one source 

industrywide Phenol 6

Methanol 6
12

Horizontal 

Collection* 1

Formaldehyde

1

3

Only one source 

industrywide Phenol 3

Methanol 3

Drum Collection* 1

Formaldehyde

1

3

Only one source 

industrywide Phenol 3

Methanol 3

Table 3. Number of Sources in New Source MACT Floor Pool

Process

Subpart DDD 

Subcategory

No. 

Sources 

Nationwide HAP

No. 

Sources in 

MACT 

Floor Pool

No. of Data 

Points in 

MACT 

Floor Pool Based on

Cupolas

Processing Slag 4

HF 1 3 Best-performing source

HCl 1 3 Best-performing source

Not Processing

Slag 4

HF 1 3 Best-performing source

HCl 1 3 Best-performing source

Closed-Top 5 COS 1 3 Best-performing source

Open-Top 3 COS 1 3 Best-performing source

Combined 

Collection and 

Curing

Vertical 

Collection 1

Formaldehyde

1

3 Best-performing source -

Only one source 

industry-wide

Phenol 6

Methanol 6

Horizontal 

Collection 1

Formaldehyde

1

3

Best-performing source -

Only one source 

industry-wide

Phenol 3

Methanol 3

Drum Collection 1

Formaldehyde

1

3

Best-performing source -

Only one source 

industry-wide

Phenol 3

Methanol 3

Step 4.

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

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

Step 5.

After determining the type of data distribution, the UPL was calculated using the corresponding 

equation for the distribution for those data, as previously described. See Section VII for UPL summary 

tables for new and existing sources.

Step 6.

For source data sets that included BDL data, there was an additional step taken after the 

subcategory UPL was calculated. As described in Section IV, the results of the UPL calculation were 
13

compared to the 3xRDL value of the relevant performance test method(s) to ensure 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]). The emission limits for the

proposed mineral wool NESHAP are in units of pound per ton (lb/ton) of glass. 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 glass) to the emission data in μg/dscm

(uncorrected). 

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 data sets with less than seven data points, the steps outlined in the memorandum 

“Approach for Applying the Upper Prediction Limit to Limited Datasets” (Fairchild, 2014) were 

followed. 

VII. MACT Floor Analysis Results

Tables 4 and 5 present the existing source and new source MACT floor values determined for the 

mineral wool source category.

Table 4. Proposed Existing Source MACT Floors- 2014 Supplemental Proposal

Process

Subpart DDD 

Subcategory HAP

Number of 

sources in 

floor

Emissions 

Avg of 

Existing 

MACT Floor 

Pool (lb/ton)

99% UPL 

MACT Floor 

(lb/ton)

Cupolas

Processing Slag

HF

4

0.058 0.16

HCl 0.053 0.44

Not Processing Slag

HF

4

0.033 0.13

HCl 0.055 0.43

Closed-Top COS 5 0.89 3.4

Open-Top COS 3 3.9 6.8

Combined Collection 

and Curing

Vertical Collection

Formaldehyde

1

1.1 2.4

Phenol 0.37 0.71

Methanol 0.44 0.92

Horizontal Collection

Formaldehyde

1

0.25 0.63

Phenol 0.067 0.12

Methanol 0.034 0.049

Drum Collection Formaldehyde 1 0.099 0.17
14

Phenol 0.62 0.85

Methanol 0.21 0.28

Table 5. Proposed New Source MACT Floors - 2014 Supplemental Proposal

Process

Subpart DDD 

Subcategory HAP

Number of 

sources in 

floor

Emissions 

Avg of 

Existing 

MACT Floor 

Pool (lb/ton)

99% UPL 

MACT Floor 

(lb/ton)

Cupolas

Processing Slag

HF

1

0.0071 0.015

HCl 0.0064 0.012

Not Processing Slag

HF

1

0.0096 0.018

HCl 0.0056 0.015

Closed-Top COS 1 0.0058 0.062

Open-Top COS 1 2.7 3.2

Combined Collection 

and Curing

Vertical Collection

Formaldehyde

1

1.1 2.4

Phenol 0.37 0.71

Methanol 0.44 0.92

Horizontal Collection

Formaldehyde

1

0.25 0.63

Phenol 0.067 0.12

Methanol 0.034 0.049

Drum Collection

Formaldehyde

1

0.099 0.17

Phenol 0.62 0.85

Methanol 0.21 0.28
15

References:

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

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

CRTD Vol. 60, February 2001.

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

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

Gayen, A. K. 1949. “The Distribution of Student’s t in Random Samples of any Size Drawn from NonNormal Universes.” Biometrika, Vol. 36, No. 3/4 (Dec. 1949), pp. 353-369.

Fairchild, S. 2014a. Use of the Upper Prediction Limit for Calculating MACT Floors. Memorandum 

from Susan Fairchild, EPA/OAQPS/SPPD, to Docket ID No. EPA-HQ-OAR-2010-1041. July 2014.

Fairchild, S. 2014b. Approach for Applying the Upper Prediction Limit to Limited Datasets. 

Memorandum from Susan Fairchild, EPA/OAQPS/SPPD, to Docket ID No. EPA-HQ-OAR-2010-

1041. July 2014.

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

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

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

management and MACT rule writers. December 13, 2011.

Hancy, C. and Reeves, D. 2014. Determination of Representative Detection Level (RDL) and “3 x 

RDL” Values for Carbonyl Sulfide. Memorandum from RTI Internation to Susan Fairchild, 

EPA/OAQPS/SPPD. July 2014.

Johnson, Steffan. Rockwool Formaldehyde Emission Testing, Flywool Stack, 9/2010 and 3/2012.

 August 2013.