**Date:** September 15 , 2011

**Subject:** Technical Approach for Mineral Wool 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, E PA/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 Achievable C ontrol 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 achi eved 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 ource s, 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 Mineral Wool Production NESHAP source catego ry . This anal ys is 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 analy sis is also being performed in response to a petition for rulemaking by the Natural Resources Def ense Council and Sierra Club that states EPA failed to set emission limits for COS and other HAP s emitted by mineral wool facilities and challenges HAP surrogacies claimed in the current Mineral Wool NESHAP
. This MACT floor anal ys is uses data collected fro m a nationwide voluntary Information Collection Request (I CR) of mineral wool manufacturer s conducted by EPA in 2010. Data on process o perati ons, emission controls, and air emissions data reported by respondents to the IC R were compiled into a Microsoft A ccess data base that serves as the data set used for this MACT floor anal ys is (referred to in this memorandum as the “I CR data set”). **Background Information** The current Mineral Wool Production NESHAP was promulgated on June 1, 1999 and applies to existing, new, and reconstruct ed cupolas and curing ovens at mineral wool productionfacilities that are major source s of HAP emissions. The 1999 Mineral Wool Production NESHAP

sets particulate matter (PM) emission limits for new and existing cupolas and carbon mon oxide (CO) limits for new cupolas. The NESHAP also established emission limits for formaldehyde from new and existing curing ovens. Based on the 1999 NESHAP, these regulated pollutants currentl y serve as surrogates for other HAP s as follows : PM serves as a surrogate for HAP metals, CO for carbonylsulfide ( COS ) , and formaldehyde for phenol and methanol. The mineral wool production source category currently co nsists of 7 facilities in the U S; c ombined, these 7 facilities operate 11 cupolas and 3 curing ov ens. The three f acilities that operate curing ovens produce bonded mineral wool products . In addition to curing ovens, sources of HAP emissions associated with bonded product manufacturing include c ollection operations . There were no MACT emission limits established for collection operations in the 1999 Mineral Wool NESHAP. Bonded lines use HAP containing binders that result in formaldeh yde, phenol, and methanol emissions from curing ovens and collection sources. The stack configurations of curing and col lection operations vary at the three facilities operating bonded lines. The proposed amendments to the rule as a result of this review will include formaldeh yde, methanol, and phenol limits for collection operations ; h owever, due to the difference s in proc esses, associated exhaust streams , and stack configurations at the three bonded lines, EPA is proposing pollutant
- specific emission limits for both curing ovens and collection operations combined. The specific chemicals, compounds, or groups of compounds designated as HAP are listed in CAA section 112(b). From this list, the following additional HAP s were identified as be ing emitted from cupolas and w ould be regulated for new and existing source s in the proposed rule : carbonylsulfide (COS), hydrogen fluo ride (HF), and hydrogen chloride (HCl). **MACT Floor Analysis -**  **Subcategories** Under CAA section 112(d)(1), EPA has the discretion to “.. .distinguish among classes, ty pes, 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 mineral wool production facilities warrant subcategorization for the MACT floor anal ys is, EPA reviewed unit and process desi gn s , operating information , and air emissions data compiled in the I CR 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 significant design and operational differences in the collection operations at each of the three facilities that operate a bonded line. These three collection subcategories are listed below. Vertical Collection : In this design, the molten rock/slag mixture is poured from the cupola spout onto a group of stainless steel drums spinning in opposite directions. The spinning drums form fine fibers of the mineral mixture. High air volume directs the fibers off the fiberization spinners , toward a fast
- moving porous vertical conveyor belt. A strong vacuum is drawn on the opposite side of the belt , causing the fibers to lie against the vertical belt as it moves upward. At the top of the conveyance, the belt travels around a curve, the vacuum is released , and the fibers are removed o n a second belt that convey s the layer of binder
- sprayed mineral wool fibers into the curing oven.The vertical conveyer belt requires high volumes of air to be drawn through the belt and

results in the collection of a thin fiber layer upon the belt
. In this design, ‘shot’ , BB
- sized black granules that are high in iron (a result of using slag from the iron and steel industry) , fall out of the fiber layer. The vertical design is used to produce a specific typ e of mineral wool that is low in ‘shot’ and may be used in the hydroponic gardening market , as well as , in a specialized market of insulation products in which shot is undesirable. Horizontal Collection : This process is similar to vertical collection, except that the conveyor belt works with gravitati onal forces and results in a thicker layer of mineral wool collected upon the horizontal belt. This method also requires lower air volume drawn through the fiber layer than in the vertical design , and the ‘sho t’ is not selectively removed. The air stream is conducive to thermal oxidation at the hottest part of the cupola exhaust stack or at the existing thermal oxidizer on the curing oven. Drum Collection : In this design, fibers are drawn using a very high volume air flow into the center of a rotating dr um. The sides of the rotating drum have small holes through which the air flow may

exit but the fibers are caught. The angle of the drum, the vacuum, and centrifugal force s pull the fibers against the inside wal l of the drum and out the end. The entire drum is enclosed and the air flow may be vented to the hottest part of the cupola exhaust stack or to an existing thermal oxidizer on the curing oven. **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 Cupolas PM Current PM limit will remain the same . No MACT floor analysis performed. CO EPA is proposing to remove the current CO limit sinc e it was/is a surrogate for COS in the

1999 NESHAP COS X X HF X X HCl X X Curing & Collection (comb ined) Formaldehyde X X Phenol X X Methanol X X A MACT floor anal ys is was not performed for PM since EPA is not proposing anychanges to the current PM limits. The current formaldehyde limit only applies to curing ovens. As previously

mentioned, EPA is now developing new MACT emission limits for collection operations . Therefore, a MACT floor anal ys is that includes both curing and collection was perform ed for new and existing sources . N o current emission limits exist for COS, HF, HCl, phenol, or methanol; in order to propose limits for each pollutant, a MACT floor anal ys is was performed for each of these pollutant s for new and existing source s . The fi rst 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) by emission level (lowest to highest) for each pollutant
. From this ranking, a MACT floor pool of sources was identified fo r 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. Cupolas **.** This category includes fewer than 30 sources. Therefore, the existing source MACT floors for COS, HF, and HCl emissions were based on the top 5 best performing cupolas . For new sources , th e MACT floor was based on the best performing cupola for each pollutant. Curing &Vertical Collection
. Currently , onl y one facility operates this typ e of collection
. Formaldeh yd e, phenol, and methanol MACT floors for new and existing sources were based on emission test runs for combined curing and collection operation s from this facility
. Curing &Horizontal Collection
. Currently , onl y one facility operates this type of collection. Formaldeh yd e, phenol, and methanol MACT floors for new and existing so urces were based on emission test runs for combined curing and collection operations from this facility
. Curing &Drum Collection
. Currently , onl y one facility operates this ty

pe of collection. Formaldeh yd e, phenol, and methanol MACT floors for new and e xisting sources were based on emission test runs for combined curing and collection operations from this facility
. The next step in the MACT floor anal ys is was to account for data variability in the c alculations of the applicable MACT 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 UPLapproach 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 vari ability 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 fac ility 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 (orthe average of some other pre
- specified number) of randoml y selected observation (s) from a

population. Inother words, the upper prediction limit estimates what the upper bound of future values will be, based up on 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 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 include s a flow diagram that summarizes the UPLapproaches used. To th is end, the data sets were evaluated for each HAP to ascertain whether the data were normall y distributed, or fit another typ e 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 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 mineral wool data sets used t o calculate MACT floors for each pollutant all contained less than 15 sources. 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 t est 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 asy mmetry 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 normal ity 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 (le ss) 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 s ets 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 tes t 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 indi cate 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 normally 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 statis tic 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].
Mean 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 2bIf the raw dat a and the log
- transformed data were not normally distributed and n ≥ 13, the UPL was calculated using the UPLpooled variance with skewness adjustment in Equation 3. Note this adjustment cannot be us ed 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 Sk ew = 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 TI NV 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 b y 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 BDL values, the UPLw 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 UPL calculations
. The second step was to identify

the largest BDL value of the dataset that was no greater than the mean of the entire dataset. This value was the RDLfor 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 RDL value was greater than the calculated UPLvalue, the 3x RDLvalue was used as the proposed MACT Floor Limit. 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 curing and collection subcategories for formaldehyd e, phenol, and methanol were the same for existing and new sources since there is onl y one source in each subcategory . If the new source MACT floor was less stringent than the MACT floor calculated for existing sources, the existing MACT floor was used for both new and existing sources. Table2 present s the new source and existing source MACT floor values determined for the Mineral

Wool Production source category. Table 2. Summary

of Proposed MACT floors for the Mineral Wool Source Category Total Sources in Industry Mean of

Sources Used in UPL Analy sis 99% UPL

Caclulated for Existing Sources 99% UPL

Caclulated for New Sources Cupolas 11

Carbonyl Sulfide 1.07 3.30 0.017 Hydrogen Flouride 0.0089 0.014 0.014 Hydrogen Chloride 0.0066 0.0096 0 .0 096 Curing & Drum Collection 1

Formaldeh yd e 0.045 0.067 0.067 Phenol 0.00039 0.0023 0.0023 Methanol 0.00011 0.00077 0.00077 Curing & Vertical Collection 1

Formaldeh yd e 0.45 0.46 0.46 Phenol 0.50 0.52 0.52 Methanol 0.62 0.63 0.63 Curing & Horizontal Collection 1

Formaldeh yd e 0.054 0.054 0.054 Phenol 0.013 0.15 0.15 Methanol 0.0081 0.022 0.0229 

## Attachment A10 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