Date:	 September 29, 2011

Subject: 	Technical Approach for Wool Fiberglass MACT Floor Calculations

	EPA Contract No. EP-D-06-118; EPA Work Assignment No. 4-10

	RTI Project No. 0210426.004.010

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) to 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 the HAP emissions that is achievable.  The
minimum level of control is referred to as the “Maximum Achievable
Control Technology (MACT) floor.”  The method for determining the MACT
floor 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% 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, the methodology,
and the results of the MACT floor analysis for the Wool Fiberglass
Production NESHAP 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 Information Collection Request
(ICR) of wool fiberglass 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”).

Background Information

The current Wool Fiberglass Production NESHAP was promulgated on June
14, 1999 and applies to each of the following existing and newly
constructed sources located at a wool fiberglass manufacturing facility:
All glass-melting furnaces, rotary spin (RS) manufacturing lines that
produce bonded building insulation, and flame attenuation (FA)
manufacturing lines producing bonded pipe insulation. The rule also
applies to new FA manufacturing lines producing bonded heavy-density
products. RS and FA manufacturing lines that produce nonbonded products
are not currently subject to the standards.  The 1999 Wool Fiberglass
Production NESHAP sets particulate matter (PM) emission limits for new
and existing furnaces and sets formaldehyde limits for new and existing
RS and FA manufacturing lines.  The current NESHAP also uses the
surrogate approach, where PM serves as a surrogate for HAP metals and
formaldehyde serves as a surrogate for organic HAPs.

The wool fiberglass production source category currently consists of 29
facilities in the US; combined, these 29 facilities operate
approximately 79 furnaces and listed over 100 process lines. This
furnace count does not include pot & marble furnaces and not all RS and
FA manufacturing lines produce a bonded product.  By definition in the
current rule Bonded refers to wool fiberglass to which a
phenol-formaldehyde binder has been applied. The use of these types of
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. The stack configurations of RS and FA
bonded lines vary at facilities, as it is common industry practice to
vent more than one process unit to common ductwork/controls. The
proposed amendments to the rule, as a result of this review, will
include the addition of methanol and phenol limits for RS and FA bonded
lines, as well as, a revision to formaldehyde limits in order to reflect
the emission levels achieved by the current best performing sources.

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 furnaces and will
be regulated for new and existing sources in the proposed rule: hydrogen
fluoride (HF) and hydrogen chloride (HCl).  The current PM limit is also
being revised and a new chromium limit is being proposed as a result of
the technology review on the wool fiberglass industry. Because PM and
Chromium limits will be proposed as a technology review finding, the
details of these limits are discussed in the Section 112(d)(6)
Technology Review for Wool Fiberglass NESHAP memorandum.

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 production
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.  Based on this review, EPA concluded that there are no
significant design and operational differences at wool fiberglass
facilities that would warrant proposing subcategorization. However, EPA
did find large differences in chrome contents of refractory bricks used
in some glass melting furnaces. 

MACT Floor Analysis Methodology 

Existing Sources 

A MACT floor analysis was completed for each proposed regulated
pollutant as summarized in Table 1.  

Table 1 – Summary of Proposed Limits

	Existing Sources	New Sources

Furnaces

HF	EPA is proposing new limit (No current limit exists)	EPA is proposing
new limit (No current limit exists)

HCl	EPA is proposing new limit (No current limit exists)	EPA is
proposing new limit (No current limit exists)

RS Bonded lines

Formaldehyde	Revising existing limit	Revising existing limit

Phenol	EPA is proposing new limit (No current limit exists)	EPA is
proposing new limit (No current limit exists)

Methanol	EPA is proposing new limit (No current limit exists)	EPA is
proposing new limit (No current limit exists)

FA Bonded Lines

Formaldehyde	Revising existing limit	Revising existing limit

Phenol	EPA is proposing new limit (No current limit exists)	EPA is
proposing new limit (No current limit exists)

Methanol	EPA is proposing new limit (No current limit exists)	EPA is
proposing new limit (No current limit exists)



The first step in the MACT floor analysis for each regulated source and
HAP was to 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. 

Furnaces.   This category includes more than 30 sources and therefore
the top 12% of furnaces where used to calculate the UPL.  Since there
are 80 furnaces industry wide, the top 10 best performing furnaces for
which we had data for were used in calculating the MACT floor for HF and
 HCl.  At some facilities, multiple furnaces are routed to one stack and
emission testing was performed at the combined stack. In these cases,
the lb/ton emission rate from the test report was applied to all the
sources routed to the stack. 

Bonded RS Manufacturing Lines.  Industry wide, this category includes
more than 30 sources and therefore the top 12% of furnaces where used to
calculate the UPL. There are approximately __ bonded RS manufacturing
lines, therefore, the top 7 best performing furnaces for which emission
test data was provided were used in calculating the MACT floor for
formaldehyde, phenol, and methanol. 

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 3 sources 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
used to support the normality assumption.  Statistical test of the
kurtosis, skewness, and goodness of fit test 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;

	s2	=  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:

 							    Equation 1a

Mean calculated by: 

                                                                        
               Equation 1b

Pooled variance calculated by:

                                                      		    Equation 1c

If the kurtosis or skewness tests indicate the data was not normally
distributed, the data were log-transformed. 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.  

                     Equation 2

where:

	μ	=  the average of the best performing existing sources;

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

 	=  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:

                                                                        
                        Equation 2a

Variance is calculated by:

                                                                        
           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.  

                                                                        
    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;

	s2	=  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 static that gives a 99 percent confidence level by
correcting the probability values  (p) using Equation 4

λ3(t) – Kurtosis x Pλ4(t) + λ32xP λ3/2(t)       Equation 4

Adjustment for Below Detection Level Emissions Data

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MACT Floor Analysis Results

The MACT floors for new and existing sources are summarized in Table 2.
When calculated MACT floors for new sources are less stringent than the
MACT floor calculated for existing sources, the existing MACT floor was
used for both new and existing sources. 

	Mean of Sources

Used to Calculate UPL (lb/ton)	99% UPL Calculated for Existing Sources
(lb/ton)	99% UPL Calculated for New Sources (lb/ton)

Furnaces

Hydrogen Fluoride	0.00079	0.0020	0.00078

Hydrogen Chloride	0.00071	0.0015	0.00078

RS Lines

Formaldehyde	0.090	0.17	0.020

Phenol	0.057	0.19	0.0011

Methanol	0.16	0.48	0.00067

FA Lines

Formaldehyde	3.53	5.55	3.32

Phenol	0.51	1.36	0.46

Methanol	0.30	0.50	0.50

Attachment A

 

	

DRAFT 3-1-11

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