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Date: February 7, 2013

Subject: Technical Approach for Wool Fiberglass MACT Floor Calculations

40 CFR 63, Subpart NNN – Supplemental Proposal

EPA Contract No. EP-D-11-084; EPA Work Assignment No. 1-07

RTI Project No. 0213199.001.007

From: Cindy Hancy

Dave Reeves

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

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 the 

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

These standards must reflect the maximum degree of reduction in HAP emissions that is achievable. 

The minimum level of control is referred to as the “Maximum Achievable Control Technology (MACT)

floor.” The method for determining the MACT floor 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 Wool Fiberglass Manufacturing NESHAP, 40 CFR 63, Subpart NNN source category. 

This analysis is part of EPA's obligation under CAA section 112(f)(2) and 112(d)(6) to conduct a 

residual risk and technology review. The MACT floor analysis is also being performed in response to a 

petition for rulemaking by the Natural Resources Defense Council and Sierra Club that states EPA failed to 

set emission limits for HAPs (phenol and methanol) emitted by wool fiberglass facilities and challenges 

some HAP surrogacies used in the current wool fiberglass NESHAP. This MACT floor analysis uses data 

collected from a nationwide voluntary survey of wool fiberglass manufacturers conducted by EPA in 

2010 and an Information Collection Request (ICR) sent out to the wool fiberglass industry in November 

2011. Data on process operations, emission controls, and air emissions data reported by respondents to 

the survey and 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 Wool Fiberglass Manufacturing NESHAP, 40 

CFR part 63, subpart NNN. This memorandum incorporates changes made since the November 2011

proposal to reflect public comments regarding facility information and emissions data.
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Background Information

The current Wool Fiberglass Production NESHAP (subpart NNN) was promulgated on June 14, 1999

and applies to each of the following existing and newly constructed major sources located at a wool 

fiberglass manufacturing facility: glass-melting furnaces, rotary spin (RS) manufacturing lines that 

produce bonded building insulation, and flame attenuation (FA) manufacturing lines producing bonded 

pipe insulation. The current rule also applies to new FA manufacturing lines producing bonded heavydensity and pipe products. Currently, subpart NNN defines “bonded” as wool fiberglass to which a 

phenol-formaldehyde binder has been applied. The use of these types of HAP binders results in 

formaldehyde, phenol, and methanol emissions from sources at bonded RS and FA lines which generally

consist of forming, curing, and collection operations. RS and FA manufacturing lines that produce 

nonbonded products are not currently subject to the standards. The 1999 Wool Fiberglass Production 

NESHAP (subpart NNN) sets particulate matter (PM) emission limits for new and existing furnaces and 

sets formaldehyde limits for new and existing RS lines and for new FA manufacturing lines. The 

original NESHAP also uses the surrogate approach, where PM serves as a surrogate for HAP metals and 

formaldehyde serves as a surrogate for organic HAP.

The wool fiberglass manufacturing source category currently consists of 30 facilities operating in the 

United States; 10 of these facilities are major sources and operate 29 glass-melting furnaces. The 

remaining 20 facilities are listed as area sources or synthetic minors. The North American Insulation 

Manufacturers Association (NAIMA) announced that by the end of 2012, they predict no major sources 

subject to Subpart NNN1 will exist in this source category (see docket items 0040 and 0052) by phasing 

out the use of phenol-formaldehyde binders. Once a facility has phased out its use of these HAP binders 

on bonded lines, it may apply to the appropriate permitting authority to no longer be subject to the 

MACT Subpart NNN standard under two definitions of the MACT rule: the applicability definition and 

the definition of ‘bonded’.

The specific chemicals, compounds, or groups of compounds designated as HAP are listed in CAA 

section 112(b). From this list, chromium compounds, hydrogen fluoride (HF) and hydrogen chloride 

(HCl) were identified as being emitted from furnaces; and formaldehyde, phenol, and methanol were 

identified as being emitted from bonded FA and RS lines. In the November 2011 proposal, EPA set 

MACT floor limits for HF and HCl. The Agency received comments on the proposed HF and HCl 

emission limits and upon reexamination of our analysis of the acid gas test data, we found that up to 80 

percent of the HF and HCl test data in the floor were below detection limit (BDL) of the required test 

method. Based on this information, EPA has decided to set work practice standards for HF and HCl 

instead of MACT floor emission limits under section 112(h) of the CAA. The 2011 proposal also set 

emission limits for chromium compounds based on both section 112(d)(6) technology review and 

112(f)(2) residual risk ample margin of safety. The Agency is not revising the chromium emission limit 

in the 2011 proposal, but is correcting the basis for proposed limit being technology review (and not a 

calculated MACT floor). Details regarding chromium compound emission limits and particulate matter 

(PM) limits for glass-melting furnaces are discussed in the Section 112(d)(6) Technology Review for 

Wool Fiberglass NESHAP memorandum and in the Draft Risk Report for the Wool Fiberglass 

Manufacturing RTR available in the docket for this rulemaking (docket # EPA-HQ-OAR-2010-1042). 

With regards to formaldehyde, phenol, and methanol at RS and FA bonded lines, EPA proposed to 

remove the surrogacy relationship in the rule and establish limits for phenol and methanol and correct 

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

effort of 2010. After the 2011 proposal, EPA received information from industry clarifying that the 

 

1 Letters from A. Crane, NAIMA to C. Hancy, RTI (June 8. 2011) and S. Fairchild, U.S. EPA, (August 2, 2011). 
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proposed limits for formaldehyde, phenol and methanol were based on a data set which included test 

data for lines that had phased out use of phenol/formaldehyde binders and were therefore no longer 

subject to the rule. The Agency removed the erroneous data from the dataset and recalculated the MACT 

floor for RS lines based on the bonded lines at major sources and synthetic minor sources. The limits in 

the supplemental proposal for RS lines differ from the proposed limits due to the removal of erroneous 

data from the data set used to calculate the MACT floor.

MACT Floor Analysis - Subcategories

Under CAA section 112(d)(1), EPA has the discretion to “...distinguish among classes, types, and sizes 

of sources within a category or subcategory in establishing...” standards. When separate subcategories 

are established, a MACT floor is determined separately for each subcategory. To determine whether the 

wool fiberglass manufacturing facilities warrant subcategorization for the MACT floor analysis, EPA 

reviewed unit and process designs, operating information, and air emissions data compiled in the ICR 

data set and other information collected by the Agency for development of the NESHAP for this source 

category. The EPA also analyzed several subcategorization recommendations submitted by industry in 

their public comments on the proposed rule (76 FR 72770, November 25, 2011). Based on this review, 

EPA concluded that sufficient information exists to continue subcategorization of bonded lines into both 

FA and RS lines, but that beyond this level, there are no significant design or operational differences at 

wool fiberglass facilities that warrant further subcategorization. Specifically, the original/current wool 

fiberglass NESHAP (subpart NNN) contains separate emission limits for FA manufacturing lines that 

produce heavy-density wool fiberglass and FA manufacturing lines that produce pipe product wool 

fiberglass. According to recent industry information, there is only one company that runs FA lines at 

their facilities. These facilities provided test data in response to the voluntary survey that was to 

represent all FA lines. The EPA received data for three FA lines that were running heavy-density 

product and no data on FA lines that were running pipe products. In their May 5, 2010 letter to EPA (see 

Docket EPA-OAR-HQ-2010-1042), industry stated that the testing at pot & marble flame attenuated 

(FA) process units was representative of all products made on FA lines based on the following: “all remelt borosilicate glass marbles; all are pot & marble flame attenuation; and all are operated by Johns 

Manville.” The letter also stated that Johns Manville is the only NAIMA member with a pot & marble 

melting process and the FA process is “a completely different process than rotary (spin) and was 

subcategorized in the original MACT standard.” We therefore concluded that the limits developed for 

FA lines were representative of all products made on FA lines and that further subcategorization was no 

longer supportable under the standard. We proposed only limits for FA lines without regard to further 

subcategorization, and all products made on an FA line using phenol/formaldehyde binders would be 

subject to those limits. Although we received comment suggesting subcategorization of up to four

subcategories on FA lines, we received no additional test data from industry to support further 

subcategorization beyond the general FA line subcategory. Consequently, we propose limits for FA 

lines such that all products made on an FA line using phenol/formaldehyde binders are subject to the 

proposed emission limits.

MACT Floor Analysis Methodology

Existing Sources 

A MACT floor analysis was completed for formaldehyde, phenol, and methanol emissions from RS and 

FA lines. The majority of the data (e.g., production and equipment throughput rates) used to calculate 

the MACT floors was submitted as confidential business information (CBI) and therefore, the data and 

calculations are not publicly available (and not included in this memorandum). 
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The first step in the MACT floor analysis for each regulated source and HAP was to array all the data 

and rank each unit (for which emissions data was provided) by emission level (lowest to highest) for 

each pollutant. From this ranking, a MACT floor pool of sources was identified for determining the 

minimum control level allowed for the MACT floor, consistent with the criteria defined for new and 

existing sources by CAA section 112(d)(3). For the new source MACT floors, the best-controlled 

source was identified for which there were individual source test run data in the ICR data set. For the 

existing source MACT floors, selection of the MACT floor pool size (i.e., number of emission units to 

be included in the determination of the average emission limitation value) was determined on an 

individual unit category basis as described below. 

Bonded RS Manufacturing Lines. There are less than 30 RS lines located at the 10 major 

sources; therefore the top 5 best performing RS lines for which emission test data was provided 

were used in calculating the MACT floor for formaldehyde, phenol, and methanol. For new 

sources, the best performing source was used to calculate the MACT floor for each pollutant. 

Bonded FA Manufacturing Lines. This category includes less than 30 sources and emission test 

data was submitted for three FA lines. Therefore, all of these three FA lines were used to 

calculate formaldehyde, phenol, and methanol limits for existing sources. For new sources, the 

best performing source was used to calculate the MACT floor for each pollutant. 

The next step in the MACT floor analysis was to account for data variability in the calculations of the

applicable MACT floor limits for the subcategories using the data’s 99% upper prediction limit (UPL). 

Specifically, the MACT floor limit was determined as the UPL calculated with the Student’s t-test using 

the “TINV” function in Microsoft Excel software. The UPL approach has also been used in other EPA 

rulemakings (e.g., NESHAP for Portland Cement, NSPS for Hospital/Medical/Infectious Waste 

Incinerators, NESHAP for Industrial, Commercial, Institutional Boilers and Process Heaters, and 

NESHAP for Electric Generating Units) to account for variability in emissions data for a specified level 

of confidence. 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% level of confidence means that a 

facility whose emissions are consistent 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 upper prediction limit estimates what the upper bound of future values will be, based 

upon present or past background samples taken. The UPL consequently represents the value at which 

we can expect the mean of future observations for the HAP emissions to fall within a specified level of 

confidence, based upon the results of an independent sample from the same population. This method 

accounts for the point-to-point variability in the data. 

The form of the UPL equation differs somewhat depending upon the number of data points and data 

distribution to which it is applied. Attachment A includes a flow diagram that summarizes the UPL

approaches used. To this end, the data sets were evaluated for each HAP to ascertain whether the data 

were normally distributed, or fit another type of distribution (e.g., log normal distribution). According 

to the Central Limit Theorem (Durrett, 1996), when a data set includes 15 or more sources, the UPL is

based on the assumption that the data fit a normal distribution. The Central Limit Theorem states that 

regardless of the shape of the original distribution, if the distribution has a finite mean (μ) and variance 

(σ2), the sampling distribution of the mean approaches a normal distribution with a mean of (μ) and a 

variance of σ2/N as N, the sample size, increases (Durrett, 1996).

The wool fiberglass data sets used to calculate MACT floors varied for each pollutant. When the sample 

size is smaller than 15 and the distribution of the data is unknown, the Central Limit Theorem cannot be 
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used to support the normality assumption. Statistical test of the kurtosis and skewness are then used to 

evaluate the normality assumption. The skewness statistic (S) characterizes the degree of asymmetry of 

a given data distribution. Normally distributed data have an S value of 0. An S value that is greater 

(less) than 0 indicates that the data are asymmetrically distributed with a right (left) tail extending 

towards positive (negative) values. The standard error of the skewness statistic (SES) was also used in 

determining the normality of the data distribution. 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 0. A K value that is greater (less) than 0 indicates a relatively peaked 

(flat) distribution. The standard error of the kurtosis statistic (SEK) was also used in determining the 

normality of the data distribution.

For each data set to which the UPL was applied (i.e., the separate data sets for each HAP applicable to a 

source), the S and K values were calculated using the reported test values. If both kurtosis and skewness 

tests indicate the data is normally distributed, the UPL was calculated using the UPL pooled variance 

Equation 1. 

 = 

 + (, ) × 

 





+





 Equation 1

where:



 = the average (mean) of the best performing existing sources;

t(p,df) = the t statistic for a confidence level p, and df degrees of freedom;

s

2

= the pooled variance;

n = the total number of test runs (all sources) used in the analysis; and

m = the number of (future) compliance test runs [for run-by-run data, m=3].

Degrees of freedom calculated by:

1

1

 











 

N

i

df ni

 Equation 1a

Mean calculated by:

 



N

i

n

j

ij

i

x

n

X

1 1

1

 Equation 1b

Pooled variance calculated by:

 









n

i

xi X

n

s

1

2

2

1

1

 Equation 1c

If the kurtosis or skewness tests indicate the data was not normally distributed, the data were logtransformed. Once the logs of all the test runs were calculated, new kurtosis and skewness tests were

performed on the log-transformed data. If both kurtosis and skewness tests indicated the log-transformed 

data were normally distributed, the UPL can be calculated using the Equation 2. 
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  

















    

 



2( 1)

ˆ ˆ

1

2 4

.99 2 ˆ ˆ ˆ 2 2 ˆ ˆ 2

ˆ

ˆ 2 2 2

2

n n

me e m e

m

Z

UPL e

      





 Equation 2

where:

μ = the average of the best performing existing sources;

Z.99 = the z statistic for a lognormal distribution at 99 percent;

2 ˆ = the variance;

n = the total number of test runs (all sources) used in the analysis; and

m = the number of (future) compliance test runs [for run-by-run data m=3].

 

Mean is calculated by:

n

x

n

i

 i

 1 

 Equation 2a

Variance is calculated by:

 

1

ˆ

1

2

2









n

x x

n

i

i



 Equation 2b

If the raw data and the log-transformed data were not normally distributed and n ≥13, the UPL was

calculated using the UPL pooled variance with skewness adjustment in Equation 3. Note this 

adjustment cannot be used if the number of individual runs is less than 13. 













 















 



n m

t s

n

Skew s

X df p

1 1

6

2

,

2

 Equation 3

where:



 = the average of the best performing existing sources;

t(p,df) = the t statistic for a confidence level p, and df degrees of freedom;

s

2

= the pooled variance;

n = the total number of test runs (all sources) used in the analysis;

m = the number of (future) compliance test runs [for run-by-run data m=3]; and

Skew = the skewness of the test runs used in the analysis.

If the raw data and the log-transformed data were not normally distributed and n was less than 13 the 

UPL was calculated using the UPL pooled variance in Equation 1, but instead of using the Excel TINV 

formula to find the t statistic t(p,df), a trial and error method was used to find the t statistic that gives a 

99 percent confidence level by correcting the probability values (p) using Equation 4

Corrected Probability = P0(t) + Skewness x Pλ3(t) – Kurtosis x Pλ4(t) + λ3

2

xP λ3/2(t) Equation 4
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Adjustment for Below Detection Level Emissions Data

Prior to calculating the UPLs, test runs that were below detection level (BDL) were identified. If a 

dataset contained any BDL values, the UPL was calculated using BDL values as reported in the test 

report. The calculated floor or emissions limit was then compared to three times the RDL values 

provided by EPA. If the three times the RDL was less than the calculated floor or emissions limit (e.g., 

calculated from the UPL), we conclude that measurement variability was adequately addressed and the 

calculated floor or emissions limit would need no adjustment. If, on the other hand, the value equal to 

three times the RDL were greater than the UPL, we concluded that the calculated floor or emissions 

limit does not account entirely for measurement variability and used the three times RDL value instead. 

The RDL for each pollutant was determined using data from tests of all the best performers for all of the 

final regulatory subcategories (i.e., pooled test data). If no BDL values were included in the pollutant 

data set for a particular unit type, these steps were not performed.

MACT Floor Analysis Results

The MACT floors for new and existing sources were calculated using the 99% UPL approach described 

above and are summarized in Table 1. When calculated MACT floors for new sources are less stringent 

than the MACT floor calculated for existing sources, the existing MACT floor calculated value was used 

for both new and existing sources. 

Table 1 – Summary of MACT Floor Emission Limits

Data

Distribution

Mean of Sources

Used to Calculate 

UPL (lb/ton) for 

Existing Sources

MACT floor 

limits for 

Existing 

Sources 

(lb/ton)

MACT 

floor limits 

for New 

Sources 

(lb/ton)

RS Lines

Formaldehyde Normal 0.15 0.22 0.087

Phenol Normal 0.15 0.31 0.034

Methanol Normal 0.42 0.75 0.61

FA Lines

Formaldehyde Normal 3.53 5.55 3.32

Phenol Normal 0.51 1.36 0.46

Methanol Normal 0.30 0.50 0.50

References: 

Durrett, Richard (1996). Probability: Theory and Examples (Second edition).

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.

Johnson, Norman J., Modified t Tests and Confidence Intervals for Asymmetrical Populations. Journal 

of the American Statistical Association, Vol. 73, No. 363 (Sep., 1978), pp. 536-544.
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Attachment A
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Determine number of 

sources in MACT floor

Are 

there at least 15 

sources in MACT 

floor?

Assume normal 

distribution

Calculate MACT floor 

using UPL Pooled 

Variance Equation 1

Test for normal 

distribution using 

kurtosis and skewness

Does sample have 

normal distribution?

Calculate MACT floor 

using UPL pooled 

Variance with skewness 

adjustment Equation 3

Use UPL as MACT floor

Are any data 

BDL or DLL?

Log transform data

Test data for lognormal 

distribution using 

kurtosis and skewness

Does sample 

have lognormal 

distribution?

Calculate MACT floor 

using UPL Lognormal 

Equation 2

Determine RDL

Compare UPL to 3 x 

RDL

Use greater of UPL and 

3 x RDL as MACT floor

Yes

No

Yes

No

No

Yes

Yes

MACT Floor Flow Chart

Does the dataset 

contain 13 or more data 

points (n≥13)?

Calculate UPL by 

adjusting T statistic 

values using probability 

trial and error. 

No

No

Yes