1

Date: September 2 6

, 201 4

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

- 0 9 RTI Project No. 021 3199 .00 2 .00 9

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

. The se standards must reflect the “Maximum Achievable Control T echnology (MACT) floor” for HAP emitted by these sour ces. 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 c ontrolled simil ar source.
F or 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

s ources, or the best performin g five sources for source categories with fewer than 30 sources.

The purpose of this memora ndum 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

manufact urers conducted by EPA in 2010. Data on process operations, emission controls, and air emissions data reported by respondents to the ICR were comp iled 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 6 3, 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

a dditional 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 co nsists of 7 facilities operating in the U nited

States

. The 7 facilities operate 11 cupolas and 3 bonded manufacturing lines

. Since the April 20132

supplemental proposal

, one additional plant has begun pre

- production operation s ; this plant operate s 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 pr oposed 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

p roposal and the 2013 supplemental proposal. Table 1 provides an overview of the limits that have been proposed fo r 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 limit s 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. Simil ar 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

- s l ag 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 su rrogate for methanol and phenol

. In the November 2011 proposal

, the EPA proposed to

remove the surrogacy relationship in the rule and proposed MACT Floor limit s for phenol, methanol and formaldehyde based on data submitted by the industry in their voluntary information collection

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

mineral wool lines. After the 20 11 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 conclude d that the differences in collection operations warranted subcategorization

, and i n April 2013 EPA proposed to subcategorize combined collection operations and curing ovens into three separate types: vertical, horizontal, and drum curing and collection bon ded 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 MA CT floor approach for existing and new sources that are based on limited dataset s ( fewer than 7 data points ) in order to addre ss 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 coll ection and curing subcategory. The limited data set 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 Supplementa l 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 memorandu m.

B. A dditional 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

errone ously 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 source s based on the best performing source in each subcategory.

Th e EPA is also revising the COS emissions limit for new and r econs tructed 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 c upola. 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 conduc ted at miner al wool facilities ( see “3 x RDL” Values for Carbonyl Sulfide memorandum for more information)

. T he

EPA then compared the method detection level to the calculate d MACT floor limit and found that the proposed emiss ion limit was very close to the representativ e 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 i n order to accou nt
for measurement variability and used this 3x RDL as the MACT floor limit for new and r econstructed

closed

- top mineral wool cupolas . This represents the lowest level that can be reliably measured using this test method, and EPA therefore believe s that it is the lowest lev el 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, ph enol 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

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

discussion s with bo th the company and testing contractors to obtain additional information that would explain the widely divergent results from the first and second tests (which varied u p to an order of magnitude)

, t he 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 change d 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

No t 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

Op en

- Top COS NA 3.3 6.8 No Change NA 0.017 4.3 3.2

Com bined
Collection and Curing Vertical

Collection* Formaldehyde 0.06 1 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 0.06 1 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 C ollection* Formaldehyde 0.06 1 0.067 0.18 0.17 Same as Existing Same as

Existing Same as

Existing

Pheno l 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

1 Current 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 th os e best performing sources because this approach

i ncorporates the average performance of the sources and the variability of the perform ance 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 facil ities 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 f or 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

obs ervation(s) from a pop ulation. 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 po int

- to

- data point variability. The predictions derive from the data s et to which it is applied, and, thus, can be applied to any type of data.

The re are different equations for calculating a UPL based on the distribution of the data set

. Data can be normally distributed, lognormally distributed, or neither and thus have a s kewed/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 sa mple 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 tha t 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 ext endin g 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

where:

n = sample size

= mean of MACT floor pool

x i = individual source mean

stdev =

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

. The SES value can be approxim ated using the following equation :

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 compa rison 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 es timated using the following equation (which is implemented in Microsoft Excel ® using the “ KURT ” function ) :

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

be a zero in the denominato r of the first and second term s

. 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 kurtosi s is estimated using the following equation:8

As part of determining whether the distribution of the data can be considered normal, the K value must be compared to t he standard error of the kurtosis statistic (SEK)

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

for datasets with n>3, or

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 d istributed 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 k urtos is and

skewness. If both tests of the log

- tr ansformed data indicated the log

- transformed data were normally distributed, the data were treated as lognormally distributed i n subsequent UPL calculations. If either of these tests indicated the log

- transformed data were not normally distributed, the dat a 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 dat a set is normally distributed. Therefore, to determ ine the appropriate data distribution for those data sets, the skewness/SES values from raw data were compared to the

skewness/SES val ues 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

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

Normally Distributed Data Set

where:

UPL = upper prediction limit

= mean of the data calculated as

n = number of test runs =9

m = number of future test runs in the compliance average

N = number of sources

s 2

= pooled variance calculated as

t df, 0 .99 = quantile of t

- distribution at the 99 percent level of confi dence with degrees of freedom (df) ; this value can be calculated with the Student’s t

- test statistical method, using the “TINV” functi on in Microsoft Excel® software

df = degrees of freedom calculated as

Lognormally Distributed Data Set (Bhaumik and Gibbons, 2004)

where:

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

= = variance estimate of the log transformed data

z 0. 99 = the 99 th

- percentile of the log

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

Skewed/Unknown Distribution (Non

- Normal/Non

- Lognor mal) (Gayen, 1949)

where:

UPL = upper prediction limit

= mean of the data calculated as10

n = number of test runs =

m = number of future test runs in the complia nce average

N = number of sources

s 2

= pooled variance calculated as

t df,p = recalculated quantile of t

- distribution based on specified level of confidence ( i.e.

, 99%)

df = degrees of freedom calculated as

B. Representative Detection Limit (RDL)

The imprecision of t est method measurement s 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 r eliability 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 p ollutant detection capability. Because of matrix effects, la boratory techniques, sample volume , and other f actors, method detection limits

no rmally 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 ab ove 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 distribu tion 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 occurrin g at or near the detection

li mit is about 40 to 50 percent. Relative p ollutant 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 t o account for measurement variability includes def ining 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 detec tion limit value. Th e 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 v alues 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. T he results of this are presented in the11

“ Determination of Representative Detect ion 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 e ach pollutant and subcategory. The larger of the 3xRDL value and the calculated UPL valu e are used for the MACT floor

emission limit to ensure that measurement variab ility 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” ( Fairchil d , 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 pol lutant 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)

th e 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 l owest 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 subcategor y basis, as described in Table s 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

No t 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 612 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

No t 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) w as evaluated for kurtosis and skewness to determine the distribution, as described in Section IV of this memorandum

.

Step 5.

After determinin g 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 additio nal step taken after the subcategory UPL was calculated. As described in Section IV , t he results of the UPL calculation were13

compared to the 3xRDL value of the relevant performance test method(s) to ensure that data measurement variability is addressed.

Th e 3xRDL values in the guidance document (Westlin and Merrill , 2011) were given in units of concentration (micrograms per dry standard cubic meter [μ g/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 em ission rate that can be measured using the performance test method while maintaining a relative method precision on the order of 10 to 20 per cent of the measured value. If the UPL value was equal to or greater than the 3xRDL value, then

the UPL value was u sed 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 , 20 14 ) were

followed.

VII. MACT Floor Analysis Results

Table s 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 N umber of

sources in
floor Emissions

Avg of Existing
MACT F loor

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 0.1714 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 0.2815

References:

ASME (founded as the American Society of Mechanical Engineers). 2001. Reference Method Accuracy and Precision (ReMAP): Phase 1, Precision of Manual Stack Emission Measurements

. CRTD Vol. 60, February 2001.

Bhaumik, D.K. and Gibbons, R.D. 2004. “An Upper Prediction Limit for the Arithmetic Mean of a Lognormal Random Variable.” Technometrics , 46(2):239

- 248.

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

No rmal Universes.” Biometrika , Vol. 36, No. 3/4 (Dec. 1949), pp. 353

- 369.

Fairchild, S . 2014 a

. Use of the Upper Prediction Limit for Calculating MACT Floors . Memorandum from Susan Fairchild, EPA/OAQPS/SPPD, to Do cket 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 Do cket ID No. EPA

- HQ

- OAR

- 2010

- 1041

. July 2014

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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

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