1 

MEMORANDUM 

To: David Putney, U.S. Environmental Protection Agency (EPA), OAQPS 

From: David Green and Matt Hakos, RTI International 

Date: November 13, 2014 

Subject: Revised Draft MACT Floor Analysis for the Primary Aluminum Production Source 

Category 

I. Introduction 

Section 112 of the Clean Air Act (CAA) requires that the U.S. Environmental Protection Agency 

(EPA) 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 HAP emissions that is 

achievable. The minimum required 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 percent 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, methodology, and results of the MACT 

floor analysis for the Primary Aluminum Production source category. This analysis was performed to 

establish the MACT floors for the previously unregulated pollutants, listed below: 

1. Polycyclic organic matter (POM) emissions from: 

a. New and existing prebake potlines 

2. Particulate matter (PM) (as a surrogate for HAP metals) emissions from: 

a. New and existing potlines 

b. New and existing anode bake furnaces 

c. New and existing paste plants. 

II. Data Set 

On December 6, 2011, the EPA proposed revisions to the NESHAP for Primary Aluminum 

Reduction Plants. This memorandum details the new emissions data obtained and the proposed MACT 

standards that were developed following the December 2011 proposal for the forthcoming supplemental 

proposal. MACT floor determinations supporting proposed standards for carbonyl sulfide emissions 

from potlines and POM emissions from existing pitch storage tanks are unchanged from the December 

2011 proposal (and not reopened for comment) and are detailed in docket item number EPA-HQ-OAR2011-0797-0145. 

This MACT floor analysis used data gathered via an information request sent to the primary 

aluminum production industry in March of 2013. Data on process operations, emission controls, and air 

emissions data reported by respondents were compiled and serve as the data set used for this MACT 
2 

floor analysis (referred to in this memorandum as the “MACT floor data set”). PM and POM emissions 

test data was collected for the following:

Table 1. Summary of New Data Set

Facility 

Identifier Facility Name Potline Category 

Potline 

SubCategory 

PM Data POM 

Data 

Potline 

Paste 

Plant 

Anode 

Bake 

Furnace Potline 

SPPD_FAC_01 Alcoa - Massena West Prebake CWPB1    

SPPD_FAC_02 Alcoa - Warrick Prebake CWPB1    

SPPD_FAC_03 Alcoa - Wenatchee Prebake CWPB1    a

SPPD_FAC_04 Alumax - Mt. Holly Prebake CWPB1    

SPPD_FAC_05 Noranda Aluminum Prebake CWPB1  - - -

SPPD_FAC_06 Rio Tinto Alcan - Sebree Works b Prebake CWPB1    

SPPD_FAC_07 Ormet Primary Aluminum Prebake CWPB2  N/A N/A 

SPPD_FAC_11 Century Aluminum Of WV Prebake CWPB2 - - - -

SPPD_FAC_12 Alcoa – Rockdale Prebake CWPB2 - - - -

SPPD_FAC_08 Century Aluminum Of KY Prebake CWPB3  -  

SPPD_FAC_09 Intalco Aluminum Prebake SWPB    c

SPPD_FAC_10 Alcoa - Massena East d Soderberg HSS  N/A N/A -

SPPD_FAC_13 Columbia Falls Aluminum Soderberg VSS2 - - N/A -

SPPD_FAC_14 Lake Charles Carbon N/A N/A N/A - - N/A

 New emissions test data were provided. 

- No emissions data were provided. 

N/A No affected sources are located at the plant. 

a

 POM data were rejected due to damaged samples. 

b

 Plant is presently owned by Century Aluminum and referred to as Century Aluminum - Sebree. 

c

 PM data were rejected as testing was conducted under non-representative conditions. 

d

 Plant was permanently closed as a Soderberg facility in March of 2014. 

It is important to note the current operational status of several of the primary aluminum 

production facilities in the data set, as follows: 

1. Ormet Primary Aluminum (SPPD_FAC_07) – this facility is currently shutdown and in 

bankruptcy proceedings; 

2. Alcoa - Massena East (SPPD_FAC_10) – this facility is shutdown permanently as a Soderberg 

facility and is considering reopening as a prebake facility; 

3. Century Aluminum Of WV (SPPD_FAC_11) – this facility is currently idle, but intends to 

reopen when market conditions improve; 

4. Alcoa – Rockdale (SPPD_FAC_12) – this facility is currently idle, but intends to reopen when 

market conditions improve; and 
3 

5. Columbia Falls Aluminum (SPPD_FAC_13) – this facility has been shut down for about five 

years and is not expected to reopen due to its less efficient aluminum production technology. 

III. MACT Floor Analysis – Subcategories 

Under CAA section 112(d)(1), the 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. The 

following subcategories are defined for existing primary aluminum potlines, under 40 CFR part 63, 

Subpart LL: 

1. Center-worked prebake one (CWPB1) means all existing center-worked prebake potlines not 

defined as center-worked prebake two (CWPB2) or center-worked prebake three (CWPB3) 

potlines. 

2. Center-worked prebake two (CWPB2) means all existing center-worked prebake potlines located 

at Alcoa in Rockdale, Texas; Kaiser Aluminum in Mead, Washington; Ormet Corporation in 

Hannibal, Ohio; Ravenswood Aluminum in Ravenswood, West Virginia; Reynolds Metals in 

Troutdale, Oregon; and Vanalco Aluminum in Vancouver, Washington. 

3. Center-worked prebake three (CWPB3) means all existing center-worked prebake potlines that 

produce very high purity aluminum, have a wet scrubber for the primary control system, and are 

located at the NSA primary aluminum plant in Hawesville, Kentucky. 

4. Side-worked prebake (SWPB) process means a method of primary aluminum reduction using the 

prebake process, in which the alumina is added along the sides of the reduction cell. 

5. Horizontal stud Soderberg (HSS) process means a method of primary aluminum reduction using

the Soderberg process in which the electrical current is introduced to the anode by steel rods 

(studs) inserted into the side of a monolithic anode. 

6. Vertical stud Soderberg two (VSS2) means all existing vertical stud Soderberg potlines located at 

Columbia Falls Aluminum in Columbia Falls, Montana.

There are no subcategories for new source potline emission limits for POM or PM, as new sources 

would be expected to utilize the lowest emitting potline configuration. By definition, there can be no

new CWPB1, CWPB2, CWPB3, or VSS2 potlines. All new potlines of any type are required to meet the 

TF limits for new sources, and all new potlines would be required to meet the proposed POM and PM 

limits for potlines. Further, all new Soderberg potlines would be required to meet the risk based standard 

for nickel and arsenic emissions. 

Any new potline designed to produce very high purity aluminum would be expected to comply with the 

new source POM emission standard either by using a suitably designed wet scrubber, or a dry alumina 

scrubber that is not integrated with their alumina feed system. In the latter case, the TF, POM and HAP 

metal laden alumina could be used in a non-high purity aluminum potline or discarded, as dictated by 

financial considerations. A wet roof vent scrubber could be added, if necessary for additional control. 

There are no subcategories (existing or new) for anode bake furnaces. 
4 

IV. MACT Floor Analysis – Concepts 

A. Upper Prediction Limit 

The EPA determined the pool of best performers considering both the test results of each source 

and a determination of each source’s performance over time. Performers are then ranked from lowest 

emitters to highest and a pool of best performers (referred to as the MACT floor pool) selected, based on 

the results of this analysis. For determining performance over time, the EPA used the upper prediction

limit (UPL) statistical methodology. That is, the best performers, and their level of performance, are

determined after accounting for sources’ normal operating variability. The UPL represents the value 

which one can expect the mean of a specified number of future observations (e.g., 3-run average) to fall 

below for the specified level of confidence, based upon the results of an independent sample from the 

same population. 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 UPL estimates what the upper bound of future values will be, based upon present or 

past background samples taken. The UPL approach encompasses all the data point-to-data point 

variability. 

There are different equations for calculating a UPL based on the distribution of the data set. Data 

can be normally distributed, lognormally distributed, or neither and thus have a skewed/unknown 

distribution. For this MACT floor analysis, the EPA implemented the statistical tests of skewness and 

kurtosis to determine the distribution of each source’s data. 

The skewness statistic (S) characterizes the degree of asymmetry of a given data distribution. 

Normally distributed data have an S value of zero. An S value that is greater than zero indicates that the 

data are asymmetrically distributed with a right tail extending towards positive values; similarly, an S 

value that is less than zero indicates that the data are asymmetrically distributed with a left tail extending 

towards negative values. The value of S can be approximated using the following equation (which is 

implemented in Microsoft Excel® using the “SKEW” function): 

( )( )

3

1 2 1

∑=











 −

− −

=

n

i

i

stdev

x x

n n

n

Skewness

Where: 

 n = sample size 

x = mean of MACT floor pool 

 xi = individual source mean 

 stdev = ( )

( ) ∑ −

−

1

2

n

x x i
5 

As part of determining whether a data distribution can be considered normal, the S value must be 

compared to the standard error of the skewness statistic (SES). The SES value can be approximated 

using the following equation: 

( )( )

( )( )( ) 2 1 3

6 1

− + +

× −

=

n n n

n n

SES

According to the skewness hypothesis test, if the absolute value of S is less than two times the absolute 

value of SES, the skewness of the data can be considered normal. 

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 three. A 

K value that is greater than three indicates a relatively peaked distribution. A K value that is less than 

three indicates a relatively flat distribution. The estimate of K can be calculated one of two ways. For 

data sets with more than three run values, kurtosis can be estimated using the following equation (which 

is implemented in Microsoft Excel® using the “KURT” function): 

( )

( )( )( )

( )

( )( ) 2 3

3 1

1 2 3

1

4 2

− −

−

−



























 −

− − −

+

= ∑ n n

n

stdev

x x

n n n

n n

Kurtosis

This equation cannot be used for data sets with three run values (n=3) because there will be a 

zero in the denominator of the first and second term. Instead, for data sets with three run values, kurtosis 

is estimated using the following equation: 

( )

( )( ) 3

1

4

1

4

−

−

+

=

∑=

n stdev

x x

Kurtosis

n

i

i

As part of determining whether a data distribution can be considered normal, the K value must 

be compared to the standard error of the kurtosis statistic (SEK). The SEK value, for n > 3, can be 

approximated using the following equation: 

. 

Where n = 3, the SEK value can be approximated as √8. According to the kurtosis hypothesis test, if the 

absolute value of K is less than two times the absolute value of SEK, the kurtosis of the data can be 

considered normal. 

For this MACT floor analysis, if the results from both the skewness and kurtosis hypothesis tests 

indicated the data set was normally distributed, the data set was treated as normally distributed in 

subsequent UPL calculations. If either of these tests indicated the data set was not normally distributed, 

the data set was log-transformed, and the log-transformed data set was evaluated for kurtosis and 

skewness. If both tests of the log-transformed data indicated the log-transformed data set was normally 

distributed, the data set was treated as lognormally distributed in subsequent UPL calculations. If either 

( )

( )(2 )3 ( )( ) 3 5

24 ( )1

2

− + − +

−

=

n n n n

n n

SEK
6 

of these tests indicated the log-transformed data set was not normally distributed, the data set was 

treated as skewed/unknown distribution in subsequent UPL calculations. 

For data sets with only three run values, the result of both the skewness and kurtosis hypothesis 

tests always indicate the data set is normally distributed. Therefore, to determine the appropriate data 

distribution for those data sets, the skewness/SES values from raw data were compared to the 

skewness/SES values from log-transformed data. The smaller skewness/SES value was selected as an 

indication of a larger likelihood of the data to come from the corresponding distribution. 

After completing the determination of the type of data distribution for each source’s data set, the 

UPL was calculated using the corresponding equation for the distribution for that source. The UPL 

equations for normal, lognormal, and skewed/unknown distribution data sets are provided below. 

Normally Distributed Data Set 













= + +

n m

UPL x t s df

2 1 1

99.0,

Where: 

 UPL = upper prediction limit 

x = mean of the data calculated as ∑ ∑= =

=

N

i

n

j

ij

i

x

n

x

1 1

1

 n = number of test runs = ∑ =

N

i

i

n

1

 m = number of future test runs in the compliance average 

 N = number of sources 

 s2 = pooled variance calculated as ∑ ( )

=

= −

n

i

i

x x

n

s

1

2 1 2

 tdf,0.99 = quantile of t-distribution at the 99 percent level of confidence with degrees of 

freedom (df); this value can be calculated with the Student’s t-test statistical method, 

using the “TINV” function in Microsoft Excel® software 

 df = degrees of freedom calculated as ( ) 1

1

= ∑ −

=

N

i

i

df n

Lognormally Distributed Data Set (Bhaumik and Gibbons, 2004) 

( ) ( )















−

= + − + +

+ +

+

2 1

ˆ ˆ

1

2 4

99.0 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

μ σ σ μ σ σ σ

σ

μ
7 

Where: 

μˆ = 

n

log y

n

i ∑ i =1

( )

 = the average of the log transformed data from the data 

2 σˆ = 

( ( ) )

1

ˆ

1

2

−

∑ − =

n

log y

n

i

i μ

 = variance estimate of the log transformed data 

 z0.99 = the 99th-percentile of the log-normal distribution estimated using the trapezoidal rule 

approach from the following equation:

( ) ( )( )( ) 99.0

24

3 3 6

3

6

1

99.0

0

2 4

1 3 2 =















 − − +

− − + ∫z

z z

z z

z

z z φ

β β

Skewed/Unknown Distribution (Non-Normal/Non-Lognormal) (Gayen, 1949) 













= + +

n m

UPL x t s df p

2 1 1

,

Where: 

 UPL = upper prediction limit 

x = mean of the data calculated as ∑ ∑= =

=

N

i

n

j

ij

i

x

n

x

1 1

1

 n = number of test runs = ∑ =

N

i

i

n

1

 m = number of future test runs in the compliance average 

 N = number of sources 

 s2 = pooled variance calculated as ∑ ( )

=

= −

n

i

i

x x

n

s

1

2 1 2

 tdf,p = recalculated quantile of t-distribution based on specified level of confidence (i.e., 

99%) 

 df = degrees of freedom calculated as ( ) 1

1

= ∑ −

=

N

i

i

df n
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V. MACT Floor Analysis Methodology 

Step 1. 

The first step in the MACT floor analysis was to calculate the mean emission rate for each 

source. Table A-1 (Appendix A) details the dataset used for each individual source calculation. 

Step 2. 

Once the means were calculated for each source, subcategory, and pollutant, they were ranked 

from lowest to highest value. Table A-1 (Appendix A) details the rankings for each pollutant and 

subcategory. 

Step 3. 

From the rankings shown in Table A-1 (Appendix A), the best performing sources were 

identified consistent with the criteria in CAA section 112(d)(3) for determining MACT floors for new 

and existing sources. These sources are referred to as the “MACT floor pool”. For the new source 

MACT floors, the best controlled similar source was identified for each pollutant and emission source 

type, as detailed in Table A-1 (Appendix A). Note that the EPA is not proposing subcategories for the 

new source MACT standards. For the existing source subcategorized MACT floors, the best-performing 

five sources of a subcategory were identified when five or more sources for which we had emissions 

data existed in the subcategory. If a subcategory included fewer than five sources, or if emissions data 

was only available for fewer than five sources in a subcategory, then all of the sources for which we had 

emissions data were included in the MACT floor pool for that subcategory. All existing source 

subcategories had fewer than thirty sources. 

Step 4. 

Each existing MACT floor pool for each subcategory and pollutant was evaluated for kurtosis 

and skewness to determine the distribution, as described in Section IV of this memorandum. Note that 

each test run was treated as a separate data point in this MACT floor analysis. After determining the 

type of data distribution for the data set, the UPL was calculated using the corresponding equation for 

the distribution for that data set, as previously described. 

For more information regarding the general use of the UPL and why it is appropriate for 

calculating MACT floors, see the memorandum titled Use of the Upper Prediction Limit for Calculating 

MACT Floors, which is available in the docket for this action (Docket ID No. EPA-HQ-OAR-2011-

0797). Furthermore, with regard to calculation of MACT floor limits based on limited datasets, we 

considered additional factors as described in the memorandum titled, Approach for Applying the Upper 

Prediction Limit to Limited Datasets for the Primary Aluminum Production Source Category, which is 

available in the docket for this action. 

VI. MACT Floor Analysis Results 

Tables 2 and 3 present the existing source and new source MACT floor limit values determined 

for the Primary Aluminum Production source category. The data and algorithms used to calculate the 

MACT floor limits are presented in MACT Floor Calculation Details for Primary Aluminum 

Supplemental Proposal, available in the docket. Refer to Appendix B for more detail. 
Table 2. Proposed Existing and New Source MACT Floor Limits for Polycyclic Organic Matte

Polycyclic Organic Matter (POM) Standards 

Category Source Type Subcategory Distribution N n Average 

Existing Source StandardsPotline Prebake CWPB1 Normal 4 14 0.67 lb/ton Al Potline Prebake CWPB2 Normal 1 6 5.48 lb/ton Al Potline Prebake CWPB3 Normal 1 6 1.31 lb/ton Al Potline Prebake SWPB Normal 1 6 9.31 lb/ton Al New Source StandardsPotline All types N/A Normal 1 4 0.54 lb/ton Al 

Table 3. Proposed Existing and New Source MACT Floor Limits for Particulate Matter (

Particulate Matter (surrogate for HAP metals) Standards 

Category Source Type Subcategory Distribution N n Average 

Existing Source StandardsPotline Prebake CWPB1 Lognormal 5 22 3.84 lb/ton Al Potline Prebake CWPB2 Normal 1 6 4.69 lb/ton Al Potline Prebake CWPB3 Normal 1 6 12.43 lb/ton Al Potline Prebake SWPB Normal 1 9 3.04 lb/ton Al Potline Soderberg VSS2 Lognormal 1 3 12.24 lb/ton Al Anode Bake Furnace N/A N/A Normal 5 24 0.0331 lb/ton Anode Paste Plant N/A N/A Lognormal 5 15 0.0143 lb/ton Anode New Source Standards Potline All types N/A Lognormal 1 9 3.04 lb/ton Al Anode Bake Furnace N/A N/A Normal 1 6 0.0134 lb/ton Anode Paste Plant N/A N/A Lognormal 1 3 0.0020 lb/ton Anode 
10 

VII. References 

Bhaumik, D.K. and Gibbons, R.D. 2004. “An Upper Prediction Limit for the Arithmetic Mean of a 

Lognormal Random Variable.” Technometrics, 46(2):239-248. 

Gayen, A. K. 1949. “The Distribution of Student’s t in Random Samples of any Size Drawn from NonNormal Universes.” Biometrika, Vol. 36, No. 3/4 (Dec. 1949), pp. 353-369. 
11 

Appendix A 

MACT Floor Data Tables 
Table A-1. MACT Floor Data Table

Rank Facility ID Facility Name n Mean Unit Of Measure Test Run Da

1 2 3 4 5 

POM (Potlines): CWPB11 a SPPD_FAC_04 Alumax - Mt. Holly 4 0.54 lb/ton Al 0.59 0.61 0.51 0.47 -- 2 SPPD_FAC_06 Rio Tinto Alcan - Sebree Works 3 0.55 lb/ton Al 0.24 0.73 0.68 -- -- 3 SPPD_FAC_02 Alcoa – Warrick 3 0.67 lb/ton Al 0.41 0.78 0.84 -- -- 4 SPPD_FAC_01 Alcoa - Massena West 4 0.88 lb/ton Al 1.15 0.72 0.75 0.89 -- POM (Potlines): CWPB21 SPPD_FAC_07 Ormet Primary Aluminum 6 5.48 lb/ton Al 4.67 1.87 4.99 4.49 8.59 POM (Potlines): CWPB31 SPPD_FAC_08 Century Aluminum Of KY 6 1.31 lb/ton Al 1.64 1.93 1.12 1.79 0.57 POM (Potlines): SWPB1 SPPD_FAC_09 Intalco Aluminum 6 9.31 lb/ton Al 6.07 4.31 13.42 13.52 6.80 PM (Potlines): CWPB1 1 SPPD_FAC_04 Alumax - Mt. Holly 3 2.62 lb/ton Al 3.74 2.13 2.00 -- -- 2 SPPD_FAC_03 Alcoa – Wenatchee 6 3.52 lb/ton Al 3.87 5.49 3.42 2.49 3.84 3 SPPD_FAC_01 Alcoa - Massena West 4 3.86 lb/ton Al 4.36 3.12 3.73 4.24 -- 4 SPPD_FAC_06 Rio Tinto Alcan - Sebree Works 6 4.36 lb/ton Al 1.94 8.12 5.01 2.22 5.55 5 SPPD_FAC_02 Alcoa – Warrick 3 4.63 lb/ton Al 3.55 6.30 4.04 -- -- 6 b SPPD_FAC_05 Noranda Aluminum 4 5.25 lb/ton Al c c 3.40 7.18 4.05 PM (Potlines): CWPB21 SPPD_FAC_07 Ormet Primary Aluminum 6 4.69 lb/ton Al 2.33 2.27 3.34 7.57 4.59 PM (Potlines): CWPB31 SPPD_FAC_08 Century Aluminum Of KY 6 12.43 lb/ton Al 13.11 9.55 13.49 9.22 12.30 
Rank Facility ID Facility Name n Mean Unit Of Measure Test Run Da

1 2 3 4 5 

PM (Potlines): SWPB1 a SPPD_FAC_09 Intalco Aluminum 9 3.04 lb/ton Al 2.87 1.92 2.88 4.03 3.92 PM (Potlines): Soderberg1 SPPD_FAC_10 Alcoa – Massena East 3 12.24 lb/ton Al 8.70 10.60 17.43 -- -- PM (Anode Bake Furnaces)1 a SPPD_FAC_02 Alcoa - Warrick 6 0.0134 lb/ton anode 0.0012 0.0026 0.0163 0.0261 0.0178 2 SPPD_FAC_04 Alumax - Mt. Holly 3 0.0217 lb/ton anode 0.0239 0.0236 0.0176 -- -- 3 SPPD_FAC_06 Rio Tinto Alcan - Sebree Works 3 0.0373 lb/ton anode 0.0330 0.0080 0.0710 -- -- 4 SPPD_FAC_01 Alcoa - Massena West 9 0.0439 lb/ton anode 0.0620 0.0170 0.0130 0.0740 0.0370 5 SPPD_FAC_09 Intalco Aluminum 3 0.0470 lb/ton anode 0.0340 0.0790 0.0280 -- -- 6 b SPPD_FAC_03 Alcoa - Wenatchee 3 0.0496 lb/ton anode 0.0477 0.0541 0.0469 -- -- PM (Paste Plants)1 a SPPD_FAC_04 Alumax - Mt. Holly 3 0.0020 lb/ton anode 0.0016 0.0011 0.0032 -- -- 2 SPPD_FAC_03 Alcoa - Wenatchee 3 0.0023 lb/ton anode 0.0027 0.0017 0.0025 -- -- 3 SPPD_FAC_01 Alcoa - Massena West 3 0.0146 lb/ton anode 0.0160 0.0123 0.0156 -- -- 4 SPPD_FAC_02 Alcoa - Warrick 3 0.0160 lb/ton anode 0.0091 0.0171 0.0219 -- -- 5 SPPD_FAC_06 Rio Tinto Alcan - Sebree Works 3 0.0363 lb/ton anode 0.0730 0.0210 0.0150 -- -- 6 d SPPD_FAC_09 Intalco Aluminum -- -- lb/ton anode -- -- -- -- -- a Indicates facility that established the new source MACT floor for emissions of applicable pollutant from applicable source. b The results of the testing at this facility were not part of the MACT floor pool in this instance since it was not one of the top 5 performers. c PM test results for runs 1 and 2 are statistical outliers and considered non-representative due to circumstances of the testing and were not used in the MACT d These tests were conducted under non-representative conditions and were not used in the MACT floor determination. 
14 

Appendix B 

Summary of UPL Calculation Sheets in MACT Floor Calculation Details for Primary 

Aluminum Supplemental Proposal (Available in Docket ID No. EPA-HQ-OAR-2011-0797) 
Table B-1. Summary of UPL Calculation Sheets in MACT Floor Calculation Details for Primary Alumi

Proposal (Available in Docket ID No. EPA-HQ-OAR-2011-0797) 

Polycyclic Organic Matter (POM) Standards 

Category Source Type Subcategory Distribution MACT Limit (99% UPL) File Name 

Existing Source StandardsPotline Prebake CWPB1 Normal 1.1 lb/ton Al 01_UPL_POM_Existing_PPotline Prebake CWPB2 Normal 12 lb/ton Al 02_UPL_POM_Existing_PPotline Prebake CWPB3 Normal 2.7 lb/ton Al 03_UPL_POM_Existing_PPotline Prebake SWPB Normal 19 lb/ton Al 04_UPL_POM_Existing_PNew Source Standards Potline All types N/A Normal 0.77 lb/ton Al 05_UPL_POM_New_PotlParticulate Matter (surrogate for HAP metals) Standards Existing Source StandardsPotline Prebake CWPB1 Lognormal 7.2 lb/ton Al 06_UPL_PM_Existing_PoPotline Prebake CWPB2 Normal 11 lb/ton Al 07_UPL_PM_Existing_PoPotline Prebake CWPB3 Normal 20 lb/ton Al 08_UPL_PM_Existing_PoPotline Prebake SWPB Normal 4.6 lb/ton Al 09_UPL_PM_Existing_PoPotline Soderberg -- Lognormal 26 lb/ton Al 10_UPL_PM_Existing_PoAnode Bake Furnace N/A N/A Normal 0.068 lb/ton Anode 11_UPL_PM_Existing_AnPaste Plant N/A N/A Lognormal 0.082 lb/ton Anode 12_UPL_PM_Existing_PaNew Source Standards Potline All types N/A Normal 4.6 lb/ton Al 13_UPL_PM_New_PotlinAnode Bake Furnace N/A N/A Normal 0.036 lb/ton Anode 14_UPL_PM_New_AnodPaste Plant N/A N/A Lognormal 0.0056 lb/ton Anode 15_UPL_PM_New_Paste_