**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 RTIProject 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 . The se standards must reflect the maximum degree of reduction in the HAP emissions that is achievable. Th e minimum level of control is referred to as the “Maximum Achievabl e Control T echnology (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 a chieved in practice b y the best - controlled 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% of existing sources for source categories with 30 or more s ources, 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 anal ys is for the Wool Fiberglass Production NESHAP source category . This analy sis 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 anal ys is is also being performed in response to a petition for rulemaking by the Natural Resourc es 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 anal ys is u ses data collected from a nationwide voluntary Information Collection Request (I CR) of wool fiberglass manufactur er s conducted by EPA in 2010. Data on process o perati ons, emission controls, and air emissions data reported by respondents to the ICR were co mpiled 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 attenu ation (FA) manufacturing lines producing bonded pipe insulation. The rule also applies to new FA manufacturing lines producing bonded heav y- density products. RS and FAmanufacturing lines that produce nonbonded products are not currentl y 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 appr oach, where PM serves as a surrogate for HAP metals and formaldeh yd e serves as a surrogate for organic HAPs. The wool fiberglass production source category currentl y co nsists of 29 facilities in the U S; c ombined, these 29 facilities operate approximately 79 furnaces and listed over 100 process lines. Th is furnace count do es 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 phen ol formaldeh yde binder has been applied . The use of these ty pes of binders result s 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 confi gurations of RS and FA bonded lines vary at facil ities, 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 formaldeh yde 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 wi thin 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 subcategorizatio n for the MACT floor anal ys is, EPA reviewed unit and process design s , operating information , and air emissions data compiled in the ICR data set and other information collected b y 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 anal ys is was completed for each proposed regulated pollutant as summarized in Table 1 .Table 1

– Summary of Propose d Li mits 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 Formal dehyde 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 anal ys is for each regulated source and HAP was to rank each unit ( for which emissions data was provided) b y emission level (lowest to highe st) 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 b y 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 . In dustry 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 formaldeh yd e, 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 formaldeh yde, 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 anal ys is was to account for data variability in the c alculations of the applicable MAC T floor limit s for the subcategories using the data’s 99% upper prediction limit (UPL) . Specificall y, the MACT floor limi t was determined as the UPL calculated with the Student’s t - test using the “ TI NV ” function in Microsoft Excel software. The UPLappro ach has also been used in other EPA rulemakings (e.g., NESHAP for Portland Cement, NSPS for Hospital/Medical/Infectious Waste In cinerators, NESHAP for Industrial, Commercial, Institutional Boilers and Process Heaters , and NESHAP for Electric Generating Uni ts ) 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 conf idence 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 v alues will be, based upon present or past background samples taken . The UPLconsequentl y 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 resul ts 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 applie d. Attachment A includes a flow diagram that summarizes the UPL approaches used. To th is 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 distribut ion) . 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 C entral 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 f

iberglass data sets used to calculate MACT floors varied for each p ollutant . When the sample size is smaller than 15 and the distribution of the data is unknown, the Central L imit Theorem cannot be used to support the normality assumption. Statistical tes t 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 as ymmetry

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 as ymmetrically 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) ch aracterizes the degree of peaked ness 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 UPLwas applied (i.e. , the separate data set s 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 1where:
= 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 anal ys is; 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 i n df Equation 1a Mean calculated b y: 

##  

   N i n j ij i x n X 1 1 1 Equation 1b Pooled variance calculated by :



#   

 

### 

  n

i i 

### X 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 w ere log transformed . Once the log s of all the test runs w ere calculated , new kurtosis and skewness test s w ere performed on the log - transformed data. If both kurtosis and skewness tests indicate d the log - transformed data w ere normall y distributed, the UPLcan be calculated using the Equation 2 .



#          

         ) 1 ( 2 ˆ ˆ 1 4 2
ˆ ˆ 2 2 ˆ ˆ ˆ 2 99 . 2 ˆ ˆ 2 2 2 2 n n e m e me m Z e UPL          Equation 2 where: μ = the average of the best performing existing sources ;

99 . Z = the z statisti c for a lognormal distribution at 99 percent; 2 ˆ  = the variance; n = the total number of test runs (all sources) used in the anal ys is; and m = the number of (future) compliance test runs [for run - by- run data m=3]. Me an is calculated b y:

n x n i i 

## 

  1  Equation 2a Variance is calculated b y:

##   1 ˆ 1 2 2



  

## 

 n x x n i i  Equation 2b If the raw dat a 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.                   m n s t n s Skew X p df 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 anal ys is; 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 anal ys is. 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 stati sti c 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 E quation 4 Corrected Probability

= P 0 (t) + Skewness x P λ3 (t)

– Kurtosis x P λ4 (t) + λ3 2 xP λ3 /2 (t) Equation 4 **Adjustment for Below**  **Detection Level Em**  **issions Data**  Prior to calculating the UPL s, test runs that were below detection limit (BDL) were identified. If a dataset contained any BDLvalues, the UPL w as calculated using BDL values as reported in the test report. After the UPL was completed for a particular source and pollutant , a comparison of the UPL and the representative m ethod d etection l evel (RDL) was performed. The first step in the comparison w as to, f or a particular emissions unit category , find the mean of the emissions data set, which was calculated during the UPLcalculations . The second step was to identify the largest BDLvalue of the dataset that was no greater than the mean of the entire dataset. This value was the RDL for the pollutant data set of the emission unit category . The RDL was then multiplied by 3 and the product is compared to the UPL . If the 3x RDLvalue was less than or equal to the calculated UPL value, the UPLvalue w as u sed as the proposed MACT Floor Limit. If the 3x RDLvalue was greater than the calculated UPLvalue, the 3x RDLvalue was used as the proposed MACT Floor L imit. If no B DL values were included in the pollutant data set for a particular unit ty pe, these step s were not performed. **MACT Floor Analysis Results**The MACT floors for new and existing source s are summarized in Table 2. When calculated MACT

floor s 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 L ines Formaldeh yd e 0.090 0.17 0 .020

Phenol 0.057 0.19 0 .0011 Methanol 0.16 0.48 0 .00067 FA Lines Formaldeh yd e 3.53 5.55 3.32

Phenol 0.51 1.36 0.46 Methanol 0.30 0.50 0.508 

## Attachment A9 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