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

RTI Project No. 0213199.001.07

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 Mineral Wool 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. This MACT floor analysis uses data collected from a voluntary,

nationwide Information Collection Request (ICR) of mineral wool 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”).

On November 25, 2011 EPA proposed revisions to the Mineral Wool Production NESHAP, 40 

CFR part 63, subpart DDD. This memorandum incorporates changes 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 reconstructed cupolas and curing ovens at mineral wool production facilities 
that are major sources of HAP emissions. The 1999 Mineral Wool Production NESHAP has

particulate matter (PM) emission limits for new and existing cupolas and carbon monoxide (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 currently 

serve as surrogates for other HAPs as follows: PM serves as a surrogate for HAP metals, CO for

carbonyl sulfide (COS), and formaldehyde for phenol and methanol. 

The mineral wool production source category currently consists of 7 facilities in the US; 

combined, these 7 facilities operate 11 cupolas and 3 curing ovens. The three facilities that 

operate curing ovens produce both bonded and non-bonded mineral wool products. One new 

facility is currently 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 analysis (it is, however, 

included in the cost analyses for this source category). In addition to curing ovens, sources of 

HAP emissions associated with existing bonded product manufacturing include collection 

operations. There were no emission limits established for collection operations in the 1999 

Mineral Wool NESHAP. Bonded lines use HAP-containing binders that generate formaldehyde, 

phenol, and methanol emissions from curing ovens and collection sources. The processes and 

stack configurations of the curing and collection operations vary at the three facilities operating 

bonded lines. In the November 2011 proposal, EPA proposed subcategorizing bonded lines by 

collection process type with separate MACT floor emission limits for formaldehyde, phenol, and 

methanol. As part of the public comments on the proposal, EPA received additional 

formaldehyde, phenol, and methanol emissions (test) data from 2 of the 3 facilities that operate 

bonded lines and revised the MACT floor calculations to include 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 section 112(b). From this list, the following additional HAPs were identified as being

emitted from cupolas and were proposed to be regulated for new and existing sources: carbonyl

sulfide (COS), hydrogen fluoride (HF), and hydrogen chloride (HCl). In the November 2011 

proposal, EPA developed MACT floor emission limits for COS, HF, and HCl emissions from

cupolas. As part of the public comments on the proposed emission limits for cupolas, 

commenters provided information regarding potential subcategorization approaches 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 compiled 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 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 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 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 proposal, 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 typically charged. Closed-top cupolas are essentially completely enclosed at the top 

and are under negative pressure to pull combustion air emissions directly from the vessel 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 evaluation of this 

information and review of the various unit and process designs, 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 material content information from 7 facilities 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 type of facility/process generating the slag. Some slag has 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-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 on a second belt that conveys

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 type 

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 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 ‘shot’ 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 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 forces pull the fibers against the inside wall 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 analysis was completed for each regulated pollutant as summarized in Table 1. 

Table 1 – Summary Current RTR MACT Floor Analyses

Existing Sources New Sources

Cupolas

PM Current PM limit will remain the same. No MACT 

floor analysis performed.

CO EPA removed 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 (combined)

Formaldehyde 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 floor analysis 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 previously 

mentioned, EPA is setting new MACT emission limits for collection operations. Therefore, a 

MACT floor analysis that includes both curing and collection was performed for new and 

existing sources. No current emission limits exist for COS, phenol, or methanol; in order to 

develop emission limits for each pollutant, a MACT floor analysis was performed for each of 
these pollutants for new and existing sources. 

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 bestcontrolled 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. 

Closed-top cupolas. This category consists of 8 cupolas industry wide. EPA has COS 

emission data on 3 out of the 8 cupolas, therefore, the new and existing source MACT 

floor for COS emissions consist of three cupolas. 

Open-top cupolas. This category consists of 3 cupolas industry wide. EPA has COS 

emission data on all 3 of these cupolas, therefore, the new and existing source MACT 

floor for COS emissions consist of all of these three cupolas. 

Cupolas using slag 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 

existing source MACT floor for HF and HCl emissions consist of 4 cupolas. 

Cupolas without slag 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, only one facility operates this type of 

collection. Formaldehyde, 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. 

Curing & Horizontal Collection. Currently, only one facility operates this type of 

collection. Formaldehyde, 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.

Curing & Drum Collection. Currently, only one facility operates this type of collection. 

Formaldehyde, 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 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 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. 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;
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. 

  

















    

 



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 

static 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

Adjustment for Below Detection Level Emissions Data

Prior to calculating the UPLs, test runs with results that were below detection level (BDL) were 

identified. If a data set 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

Table 2 presents 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 0.01 0.15

Methanol 0.01 0.022
10

Attachment A
11

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