**Date:** February 7 , 2013 **Subject:** Technical Approach for Mineral Wool MACT Floor Calculations

40 CFR 63, Subpart DDD

– Supplemental Proposal EPA Contract No. EP - D - 11 - 084 ; EPA Work Assignment No. 1 - 07 RTIProject No. 021 3199 .00 1.07 **From:** Cindy

H ancy 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 ) f

or 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 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 achieved 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 Mineral Wool Production NESHAP source category . 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. This MACT floor anal ys is uses data collected from a voluntary , nationwide 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 ICR were compiled into a Microsoft Access data base that ser ves as the data set used for this MACT floor anal ys is (referred to in this memorandum as the “ICR data set ”). On November 25, 2011 EPA proposed revisions to the Mineral Wool Production NESHAP, 40 CFR part 63, subpart DDD. This memorandum incorporates chan ges made since the November 2011 proposal to reflect public comments regarding facility information and emissions data
. **Background Information** The current Mineral Wool Production NESHAP was promulgated on June 1, 1999 and applies to existing, new, and reco nstruct ed cupolas and curing ovens at mineral wool production facilitiesthat are major source s of HAP emissions. The 1999 Mineral Wool Production NESHAP has

particulate matter (PM) emission limits for new and existing cupolas and carbon monoxide (CO) limi ts for new cupolas. The NESHAP also established emission limits for formaldeh yde 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 formaldehyd e 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 1 1 cupolas and 3 curing ovens. The three f acilities that operate curing ovens produce both bonded and non
- bonded mineral wool products
. One new facility is currentl y under construction and is planned to operate 2 cupolas and 2 curing ovens
. This new facility under construction is not included in the MACT floor analy sis (it is, however, included in the cost anal yses for this source category)
. In addition to curing ovens, sources of HAP emissions associated with existing bonded product manufacturing include c ollection operations . There were no emis sion limits established for collection operations in the 1999 Mineral Wool NESHAP. Bonded lines use HAP - containing binders that generate formaldeh yd e, phenol, and methanol emissions from curing ovens and collection sources. The processes and stack configur ations of the curing and collection operations vary at the three facilities operating bonded lines. In the November 2011 proposal , EPA proposed subcategoriz ing bonded lines b y collection process type with separate MACT floor emission limits for formaldehyd e, phenol, and methanol. As part of the public comments on the proposal, EPA received additional formaldeh yde, phenol, and methanol emissions (test) data from 2 of the 3 facilities that operate bonded lines and revised the MACT floor calculations t o includ e this data. The EPA continues to propose subcategorizing bonded lines by collection process and combined limits for curing oven and collection operations. The specific chemicals, compounds, or groups of compounds designated as HAP are listed in CAA secti on 112(b). From this list, the following additional HAP s were identified as be ing emitted from cupolas and w ere proposed to be regulated for new and existing source s : carbonyl sulfide (COS), hydrogen fluoride (HF), and hydrogen chloride (HCl). In the November 2011 proposal , EPA developed MACT floor emission limit s for COS , HF, and HCl emissions f rom cupolas
. As part of the public comments on the proposed emission limits for cupolas, commenters provided i nformation regarding potential subcategorization appro aches for cupolas. After reviewing this data, EPA has decided that two different subcategorizations are appropriate when considering cupola emissions for COS, HF, and HCl
. The docket for this rulemaking is (docket # EPA
- HQ - OAR - 2010 - 1041) has been compile d at the EPA Air Docket and contains information that is referenced in this and other memos. **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 cat egory 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 MAC T floor anal ys is, EPA reviewed unit and process design 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 (1)the cupola design and raw materials used; and (2) the collection operations at each of the three

facilities that operate a bonded line. (1) Cupolas After the November 2011 pro posal , industry submitted comments and recommendations on cupola subcategorization. One commenters’ recommendation was to take into account the design differences between open
- top and closed
- top cupolas. Open - top cupolas are open to the atmosphere and are not under negative pressure at the top of the cupola where raw materials and coke are typicall y charged. Closed
- top cupolas are essentiall y completel y enclosed at the top and are under negative pressure to pull combustion air emissions directly from the v essel to the appropriate pollution control devices. In closed
- top designs, raw materials and coke also enter the cupola near the top, but a mechanical device ( i.e. , door, gate, or other separation mechanism) keeps the cupola virtually enclosed except for the brief moments when raw materials or coke are charged. Open
- top cupola designs can also be exposed to the environmental elements; when it rains or snows, the moisture goes through the top. As part of EPA ’s evaluat ion of this information and review of th e various unit and process design s , operating information , and air emissions data, EPA determined that the design difference between open
- top and closed
- top cupolas warrant subcategorization when determining COS MACT floors. Additionally , EPA received raw mat erial content information from 7 faci lities producing mineral wool . Four facilities reported using slag as a raw material and three reported only using minerals (rock) and coke (e.g., “no slag”). Slag is a waste by
- product and is location
- specific depending on the ty pe of facility

/process generating the slag. Some slag ha s residual fluorides or chlorides which vary

from location to location and from process to process and can therefore affect emissions of HF and HCl . In response to this information, EPA decided to subcategorize cupolas based on slag usage for the purposes of setting HF and HCl emission limits
. (2) Collection Operations The three proposed 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
- mov ing 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 , an d the fibers are removed on 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 gardeningmarket , 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 gravitational 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 selectivel y 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 drum. 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 co mpleted for each regulated pollutant as summarized in Table 1 .

Table 1

– Summary Current RTR MACT F loor Analy ses

Existing Sources New Sources Cupolas PM Current PM limit will remain the same . No MACT floor analysis performed. CO EPA remove d the current CO limit since it was/is a

surrogate for COS in the 1999 NESHAP
. COS EPA setting MACT floor limits and subcategorizing

by closed top/open top HF EPA setting MACT floor limits and subcategorizing by slag usage. HCl Curing & Collection (comb ined) Fo rmaldehyde EPA setting MACT floor limits and subcategorizing by collection process Phenol EPA setting MACT floor limits and subcategorizing by collection process Methanol EPA setting MACT floor limits and subcategorizing by collection process A MACT f

loor anal ys is was not performed for PM since EPA is not making any changes to the current PM limits. The current formaldehyde limit only applies to curing ovens. As previousl y mentioned, EPA is setting new MACT emission limits for collection operations . Th erefore, a MACT floor anal ys is that includes both curing and collection was performed for new and existing sources . N o current emission limits exist for COS, phenol, or methanol; in order to develop emission limits for each pollutant, a MACT floor anal ys i s was performed for each ofthese pollutant s for new and existing source s .

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 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 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 includ ed in the determination of the average emission limitation value ) was determined on an individual unit category basis as described below. Closed
- top c upolas **.** This category consists of 8 cupolas industry wide
. EPA has COS emission d ata on 3 out of the 8 cupolas, therefore , the new and existing source MACT floor for COS e missions consist of three cupolas
. Open
- top c upolas **.** This category consists of 3 cupolas industry wide
. EPA has COS emission data on all 3 of these cupolas, therefore, the new and ex isting source MACT floor for COS e missions consist of all of these three cupolas
. Cupolas using s lag as raw material
. This category consists of 5 cupolas industry wide
. EPA has HCl and HF emission data on 4 out of the 5 cupolas, therefore , the new and ex isting source MACT floor for HF and HCl emissions consist of 4 cupolas. Cupolas without s lag in raw material**.** This category consists of 6 cupolas industry wide
. EPA has HCl and HF emission data on 3 out of the 6 cupolas, therefore, the new and existing source MACT floor for HF and HCl emissions consist of 3 cupolas. 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 emis sion 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. Formaldehyd e, phenol, and methanol MACT floors for new and existing sources w ere 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 existing 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 subcate gories using the data’s 99% upper prediction limit (UPL)
. Specifically, 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 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 bestperformers. 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 pres ent 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 flo w diagram that summarizes the UPLapproaches 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 distribution)
. According to the Centra l 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 L imit Theorem states that regardless of the shape of the original distribution, if the di stribution 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 to calculate the MACT floor emission limit 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. St atistical 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 asy mmetry of a given data distribution. Normally distributed data have an S valu e 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 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 Equ ation 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 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 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 statistic 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 c annot 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 usin g 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 with results that were below detection l evel (BDL) were identified. If a data set contained any BDL values, the UPLwas calculated using BDL values as reported in the test report. The calculated floor or emissions limit wa s then compared to three times the RDL values provided by EPA . If the three times the RDL w as less than the calculated floor or emissi ons 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. I f, on the other hand, the value equal to three times the RDL were greater th an the UPL , we concluded that the calculated floor or emissions limit does not account entirely for measurement variability and used the three times RDLvalue instead
. The RDLfor each pollutant was determined using data from tests of all the best performe rs 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 ty

pe, these steps were not performed. **MACT Floor Analysis Results** Table 2 present s the new and existing source MACT floor values determined for the Mineral Wool Production source category.Table 2 . Summary of MACT floors for the Mineral Wool Production Source Category Process

- HAP Total Sources in Industry Mean of

Sources Used in UPL Analysis 99% UPL

Calculated for New and Existing Sources Open - Top Cupolas COS 3 3.9 6.8 Closed
- Top Cupolas COS 10 1.0 3.4 Cupolas using Slag HF 5 0.058 0.16 HCl 0.053 0.21 Cupolas without Slag HF 6 0.033 0.13 HCl 0.055 0.43 Curing & Drum Collection

Formaldehyde 1 0.10 0. 18 Phenol 0.62 1.3 Methanol 0.21 0. 48 Curing & Vertical Collection

Formaldehyde 1 1.1 2.7 Phenol 0.37 0.74 Methanol 0.44 1.0 Curing & Horizontal Collection Formaldehyde 1 0.05 0.054

Phenol 0.0 1 0.15 Methanol 0.01 0.02210 

## Attachment A11 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