Appendix 5d- BART determination Report for Alcoa, Inc. - Warrick 

Operations 
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BART Determination Report 

for 

Alcoa, Inc. – Warrick Operations 

December 2008 

Amended July 2010 

Prepared for: 

Alcoa, Inc. – Warrick Operations 

Newburgh, Indiana 
BART DETERMINATION REPORT 

FOR 

ALCOA, INC. – WARRICK OPERATIONS 

NEWBURGH, INDIANA 

Prepared for: 

Alcoa, Inc. – Warrick Operations 

Newburgh, Indiana 

Prepared by: 

URS Corporation 

1093 Commerce Park Drive, Suite 100 

Oak Ridge, Tennessee 37830 

and 

CH2M HILL 

1095 Lakeside Centre Way, Suite 200 

Knoxville, Tennessee 37922 

December 2008 (Amended July 2010)
 i July 2008 

TABLE OF CONTENTS 

LIST OF FIGURES ....................................................................................................................... iv 

LIST OF TABLES ......................................................................................................................... iv 

ACRONYMS ...................................................................................................................................v 

1.0 EXECUTIVE SUMMARY ............................................................................................. 1-1 

2.0 INTRODUCTION ........................................................................................................... 2-1 

3.0 IDENTIFICATION OF BART-ELIGIBLE UNITS AT ALCOA WARRICK 

OPERATIONS ................................................................................................................. 3-1 

4.0 BART–ELIGIBLE EMISSION UNIT GROUP DESCRIPTION ................................... 4-1 

4.1 Primary Aluminum Reduction Process ................................................................ 4-1 

4.1.1 Existing Potline Emissions Control ..................................................................... 4-1 

4.2 Ingot Furnaces ...................................................................................................... 4-2 

4.3 Coal Fired Boilers ................................................................................................ 4-3 

5.0 BASELINE CONDITIONS AND VISIBILITY IMPACTS FOR BART-ELIGIBLE 

UNITS .............................................................................................................................. 5-1 

5.1 Refined Modeling Analysis ................................................................................. 5-3 

6.0 BART ANALYSIS FOR BART-ELIGIBLE EMISSION UNITS .................................. 6-1 

6.1 Potline Emission Controls.................................................................................... 6-1 

6.1.1 Potentially Applicable BART Control Options for Potlines ................................ 6-2 

6.1.1.1 Potentially Applicable SO2 Emission Controls for Potlines ............................ 6-2 

6.1.1.1.1 Wet Scrubbing for Potlines ............................................................................ 6-3 

6.1.1.1.1.1 Seawater Scrubbing ............................................................................ 6-5 

6.1.1.1.1.2 Limestone Slurry Forced Oxidation .................................................... 6-5 

6.1.1.1.1.3 Limestone Slurry Natural Oxidation ................................................... 6-6 

6.1.1.1.1.4 Conventional Lime Wet Scrubbing .................................................... 6-6 

6.1.1.1.1.5 Dual Alkali Sodium/Lime Scrubbing (Dilute Mode) ......................... 6-6 

6.1.1.1.1.6 Conventional Sodium Scrubbing ........................................................ 6-7 

6.1.1.1.2 Dry Scrubbing for Potlines ............................................................................ 6-7 

6.1.1.1.2.1 Dry Injection ....................................................................................... 6-7 

6.1.1.1.2.2 Semi-dry Scrubbing (Spray Dryer) ..................................................... 6-8 

6.1.1.1.3 Pollution Prevention for Potlines ................................................................... 6-8 

6.1.1.1.4 Potline Control Options from RBLC Database ........................................... 6-10 

6.1.1.2 Potentially Applicable PM Emission Controls for Potlines ........................... 6-12 

6.1.1.2.1 Fabric Filters ................................................................................................ 6-12 

6.1.1.2.2 Electrostatic Precipitators ............................................................................ 6-12 

6.1.1.2.3 Cyclones, Inertial Separators, and Wet Scrubbers ....................................... 6-13 

6.1.1.3 Potentially Applicable NOx Emission Controls for Potlines ......................... 6-13 

6.1.1.3.1 Selective Non-Catalytic Reduction .............................................................. 6-13 

6.1.1.3.2 Selective Catalytic Reduction ...................................................................... 6-14 

6.1.2 Summary of Technically Feasible BART Control Options for Potlines ........... 6-14 

6.1.2.1 Feasible BART Control Options for Potline SO2 .......................................... 6-14 

6.1.2.2 Feasible BART Control Options for Potline PM ........................................... 6-14 

6.1.2.3 Feasible BART Control Options for Potline NOx.......................................... 6-15 

6.1.3 Control Effectiveness for Feasible BART Control Options for Potlines ........... 6-15 

6.1.3.1 Control Effectiveness for Potline SO2 ........................................................... 6-15 

6.1.3.1.1 SO2 Wet Scrubbing ...................................................................................... 6-15 
 ii July 2008 

6.1.4 Evaluation of Costs and Other Impacts for Potline Feasible BART Control 

Options ............................................................................................................... 6-18 

6.1.4.1 Cost Analysis for SO2 Wet Scrubber Control Options .................................. 6-18 

6.1.4.2 Energy Impact Analysis ................................................................................. 6-20 

6.1.4.3 Non-Air Quality Environmental Impacts for Feasible Potline BART Control 

Options 6-20 

6.1.4.4 Remaining Useful Life ................................................................................... 6-21 

6.2 Coal Fired Industrial Boiler Emission Controls ................................................. 6-21 

6.2.1 Potentially Applicable BART Control Options for Industrial Boilers ............... 6-21 

6.2.1.1 Potentially Applicable SO2 Emission Controls for Industrial Boilers ........... 6-21 

6.2.1.1.1 Wet Scrubbing for Industrial Boilers ........................................................... 6-21 

6.2.1.1.1.1 Seawater Scrubbing .......................................................................... 6-23 

6.2.1.1.1.2 Limestone Slurry Forced Oxidation .................................................. 6-23 

6.2.1.1.1.3 Limestone Slurry Natural Oxidation ................................................. 6-24 

6.2.1.1.1.4 Conventional Limestone Wet Scrubbing .......................................... 6-24 

6.2.1.1.1.5 Dual Alkali Sodium/Lime Scrubbing (Dilute Mode) ....................... 6-24 

6.2.1.1.1.6 Conventional Sodium Scrubbing ...................................................... 6-25 

6.2.1.1.2 Dry Scrubbing for Industrial Boilers ........................................................... 6-25 

6.2.1.1.2.1 Dry Injection ..................................................................................... 6-25 

6.2.1.1.2.2 Semi-dry Scrubbing (Spray Dryer) ................................................... 6-25 

6.2.1.1.3 Pollution Prevention for Industrial Boilers .................................................. 6-26 

6.2.1.1.4 Industrial Boiler SO2 Control Options from RBLC Database ..................... 6-27 

6.2.1.2 Potentially Applicable BART Control Options for PM ................................. 6-29 

6.2.1.2.1 Fabric Filters ................................................................................................ 6-29 

6.2.1.2.2 Electrostatic Precipitators ............................................................................ 6-29 

6.2.1.2.3 Cyclones, Inertial Separators, and Wet Scrubbers ....................................... 6-30 

6.2.1.3 Potentially Applicable BART Control Options for NOx ............................... 6-30 

6.2.1.3.1 Low NOx Burners& Overfire Air ................................................................ 6-31 

6.2.1.3.2 Selective Non-Catalytic Reduction .............................................................. 6-32 

6.2.1.3.3 Selective Catalytic Reduction ...................................................................... 6-34 

6.2.1.3.4 Industrial Boiler NOx Control Options from RBLC Database .................... 6-36 

6.2.2 Summary of Technically Feasible BART Control Options for Industrial Boilers6-38 

6.2.2.1 Feasible BART Control Options for Industrial Boiler SO2 ........................... 6-38 

6.2.2.2 Feasible BART Control Options for Industrial and Utility Boiler PM .......... 6-38 

6.2.2.3 Feasible BART Control Options for Industrial Boiler NOx........................... 6-38 

6.2.3 Control Effectiveness for Feasible BART Control Options for Industrial Boilers6-39 

6.2.3.1 Control Effectiveness for Industrial Boiler SO2 ............................................ 6-39 

6.2.3.1.1 SO2 Wet Scrubbing ...................................................................................... 6-39 

6.2.3.2 Control Effectiveness for Industrial Boiler NOx ............................................ 6-40 

6.2.4 Evaluation of Cost and Other Impacts for Feasible BART Control Options .... 6-44 

6.2.4.1 Cost Analysis for SO2 Wet Scrubber Control Options .................................. 6-44 

6.2.4.2 Cost Analysis for NOx Control Options ......................................................... 6-44 

6.2.4.3 Energy Impact Analysis ................................................................................. 6-47 

6.2.4.4 Non-air Quality Environmental Impacts for Feasible Industrial Boiler BART 

Control Options .............................................................................................................. 6-47

 

7.0 EVALUATE VISIBILITY IMPACTS ............................................................................ 7-1 

8.0 DETERMINATION OF BART ....................................................................................... 8-1 
 iii July 2008 

8.1 Aluminum Potlines .............................................................................................. 8-1 

8.2 Coal Fired Boilers ................................................................................................ 8-1 

8.3 BART Visibility Modeling Analysis ................................................................... 8-1 

9.0 PROPOSED BART ALTERNATIVE ............................................................................. 9-1 

9.1 Alternative Controls ............................................................................................. 9-1 

9.2 Visibility Impact of Proposed Alternative to BART versus BART .................... 9-5 

10.0 REFERENCES .............................................................................................................. 10-1 

Appendix A: ALCOA BART MODELING PROTOCOL 

Appendix B: ALCOA BART MODELING REPORT 

Appendix C: CONTROL TECHNOLOGY COST DATA 

Appendix D: BUSINESS CONFIDENTIAL INFORMATION 
 iv July 2008 

LIST OF FIGURES 

1 Wet Scrubber ................................................................................................................... 6-4 

LIST OF TABLES 

Table 1-1 - Summary of Baseline, BART, and Alternative to BART Visibility Impact at MCNP.1-4 

Table 3-1 BART-eligible Emission Units ................................................................................... 3-1

Table 5-1 Baseline Conditions Modeling Input Data ................................................................. 5-2 

Table 5-2 Baseline Visibility Modeling Results ......................................................................... 5-4 

Table 6 -1 RBLC Database Search Results for Primary Aluminum Facilities ......................... 6-11 

Table 6-2 SO2 Post-Control Emission Rates ............................................................................ 6-17 

Table 6-3 Summary of the Impacts Analysis for SO2 Control Scenarios ................................. 6-20 

Table 6-4 RBLC Database SO2 Search Results for Industrial Boilers ..................................... 6-28 

Table 6-5 RBLC Database NOx Search Results for Industrial Boilers .................................... 6-37 

Table 6-6 SO2 Post-Control Emission Rates ............................................................................. 6-41 

Table 6-6A PM Post-Control Emission Rates from Unit 4........................................6-41 

Table 6-7 NOx Post-Control Emission Rates ............................................................................ 6-43 

Table 6-8 Summary of the Impacts Analysis for NOx Control Scenarios ................................ 6-46 

Table 7-1 SO2 & NOx Controls – Visibility Modeling Results at MCNP ................................. 7-3 

Table 8-1 BART Conditions Modeling Input Data .................................................................... 8-3 

Table 8-2 BART Visibility Modeling Results ............................................................................. 8-4 

Table 8-3 BART Visibility Improvement .................................................................................... 8-4 

Table 9-1 Proposed Alternative to BART Controls....................................................9-1 

Table 9-2 Baseline Including Boiler Unit 1 Conditions Modeling Input Data ............................ 9-3 

Table 9-3 Alternative to BART Conditions Modeling Input Data .............................................. 9-4 

Table 9-4 Summary of Baseline, BART and Alternative to BART Visibility Impact at MCNP 9-6 
 v July 2008 

ACRONYMS 

acfm actual cubic feet per minute 

Alcoa Alcoa, Inc. – Warrick Operations 

AWMA Air and Waste Management Association 

BACT Best Available Control Technology 

BART Best Available Retrofit Technology 

CAA Clean Air Act 

dv deciview 

EPA U.S. Environmental Protection Agency 

ESP Electrostatic Precipitator 

FGD Flue Gas Desulfurization 

LAER Lowest Achievable Emissions Rate 

LSFO Limestone Slurry Forced Oxidation 

LSNO Limestone Slurry Natural Oxidation 

MCNP Mammoth Cave National Park 

NOx Nitrogen Oxides 

PM Particulate Matter 

PM2.5 Particulate Matter less than 2.5 micrometers in diameter 

PM10 Particulate Matter less than 10 micrometers in diameter 

ppm parts per million 

ppmv parts per million by volume 

RACT Reasonably Available Control Technology 

RBLC RACT/BACT/LAER Clearinghouse 

SCR Selective Catalytic Reduction 

SNCR Selective Non-Catalytic Reduction 

SO2 Sulfur Dioxide 

UBC Used Beverage Can 
 1-1 July 2008 

1.0 EXECUTIVE SUMMARY 

 The Clean Air Act (CAA) requires the protection of visibility in 156 scenic areas across 

the United States. Under CAA Section 169A(b)(2)(A), States must require certain existing 

stationary sources to install Best Available Retrofit Technology (BART). Alcoa, Inc. – Warrick 

Operations (Alcoa) is a “BART-eligible” source. A BART determination is required because 

Alcoa emits air pollutants that may reasonably be anticipated to contribute to impairment of 

visibility in a Class I area. 

The analysis contained herein assesses the individual and collective visibility impact attributable 

to the BART-eligible emission units at Warrick Operations. It analyzes pollution prevention and 

add-on control options for the BART-eligible emission units. The BART determination and 

proposed alternative to BART were rendered based on the predicted visibility improvement and 

cost effectiveness associated with the technically feasible control options. The analyses involved 

in this BART determination were performed in accordance with Appendix Y to Part 51 – 

“Guidelines for BART Determinations Under the regional Haze Rule,1

” 

 The baseline visibility conditions were determined in accordance with a facility specific 

BART modeling protocol, developed by TRC and submitted to IDEM for approval in May, 

2006. These sources include 3 coal fired boilers, 5 aluminum reduction potlines, and 18 ingot 

furnaces. 

 Initial BART modeling projected the highest visibility impact to be in Mammoth Cave 

National Park (MCNP). Other Class 1 areas that were screened included Mingo, Sipsey, Great 

Smokey Mountains, Joyce Kilmer, Cohutta, and Shinning Rock. The BART analysis in this 

document was based solely on visibility impacts at MCNP, since the change in visibility in this 

Class 1 area would dictate the BART determination. 

 

1

 70 FR 39161 
 1-2 July 2008 

 The baseline modeled or projected 98th percentile visibility impact from the BART 

eligible sources at Warrick Operations range from approximately 1.8 to 1.9 deciviews (dv) at 

MCNP for the three modeled years (2001, 2002 and 2003). Approximately 93% to 97% of the 

total visibility impact is attributed to the coal fired boilers, with 3% to 7% from the potlines. 

Negligible visibility change during the baseline period was attributed to the ingot furnaces. 

The baseline modeled or projected maximum 98th percentile visibility impact from the 

three coal fired boilers is 1.9 dv at MCNP for 2002. On average, 85% of the boiler visibility 

impact is attributable to SO2 emissions, 12% is attributable to NOx emissions and the remaining 

31 percent is associated with particulate matter (PM). Results from the BART analysis for the 

coal fired boilers are as follows: 

 BART for SO2 emissions control was determined to be wet SO2 scrubbing on Units 2 and 

3 at 92% control efficiency. 

 BART for NOx emissions control was determined to be low NOx burners on Units 2 

and 3. 

 BART for PM emissions was determined to be the existing electrostatic precipitators 

(ESPs) on Units 2, 3, and 4. 

The baseline modeled or projected 98th percentile visibility impact from the potlines is 0.13 dv at 

MCNP in 2001. Of the 0.13 dv, approximately 92% (0.12 dv) is attributable to emissions from 

the primary control devices on the potlines. Ninety-four percent of the potline primary control 

device projected impact (0.11 dv) was from SO2 emissions and the remainder was from PM 

emissions. 

The modeling results revealed the maximum projected change in visibility to be 

approximately 0.01 dv for the potroom roofs and 0.005 dv for the ingot furnaces. The projected 

change in visibility attributed to each of these sources is less than 4% of the facility-wide 

threshold suggested by USEPA in Appendix Y that represents a contribution to visibility 

impairment. The further reduction in emissions from these sources would not result in 
 1-3 July 2008 

significant visibility improvement at MCNP. Therefore, these sources were excluded from 

further analysis. BART for the potroom roofs and ingot furnaces was determined to be no 

additional controls. 

 The analysis of potroom emissions resulted in a determination that BART for potline SO2

is a pollution prevention limit of 3% sulfur in the calcined petroleum coke (CPC) used to 

manufacture anodes (i.e., coke). BART for other pollutants emitted from the potlines 

[particulate matter (PM) and nitrogen oxides (NOx)] was determined to be the existing level of 

emission control. 

The BART analysis revealed the unsupportable high cost associated with potline add-on 

SO2 controls and raised concerns about the long-term viability of lower sulfur anode grade coke 

as a pollution prevention measure for minimizing potline SO2 emissions. Since Alcoa intends 

for Warrick Operations to be in operation throughout the period of the Regional Haze Program, it 

evaluated an alternative emission reduction strategy that minimized the future cost impacts of 

add-on controls and availability of low sulfur content raw materials. The alternative emission 

reduction strategy includes the wet SO2 scrubbing of its Unit 1 coal fired boiler, which is not a 

BART-eligible source, and the use of up to 3.5% sulfur coke at the potlines. 

The visibility benefit associated with the alternative emission reduction strategy is 

summarized in the Table 1. As shown in Table 1, implementation of an “Alternative to BART” 

control strategy, that includes the scrubbing of Unit 1 and 3.5% sulfur coke, will result in a 

“better than BART” visibility improvement. On average, the BART Alternative results in an 

additional 0.50 dv improvement over a BART-eligible source only scenario. Because the 

“Alternative to BART” provides Alcoa with more business certainty, and provides greater 

visibility improvement at MCNP, Alcoa requests IDEM to determine that the alternative 

emission reduction strategy described in Section No. 9.0 fulfills the best available retrofit 

technology requirements of Section 169A(b)(2)(A), of the 1990 Clean Air Act for this facility. 
 1-4 July 2008 

Table 1 – 1 Summary of Baseline, BART, and Alternative to BART Visibility Impact at MCNP. 

BART Option 

Baseline Visibility Impact (98 

Percentile Delta Deciview (dv) 

Post-BART Visibility Impact (98 

Percentile Delta Deciview (dv) 

Average 

Visibility 

Improvement 

(dv) 

 2001 2002 2003 Average 2001 2002 2003 Average BART Eligible Sources Onlya 1.852 1.906 1.788 1.849 0.444 0.299 0.402 0.382 1.467 Alternative to BART (BART Eligible Plus Unit 1 Controlled)b 2.311 2.774 2.549 2.545 0.686 0.463 0.595 0.581 1.964 

a Based on wet SO2 scrubbing on Units 2, and 3 with 3% sulfur coke for potlines b Based on wet SO2 scrubbing on Units 1, 2, and 3 with 3.5% sulfur coke for potlines. 
 December 2008 2-1

. 

2.0 INTRODUCTION 

The Clean Air Act (CAA) requires the protection of visibility in 156 scenic areas across 

the United States. Under CAA Section 169A(b)(2)(A), States must require certain 

existing stationary sources to install Best Available Retrofit Technology (BART). A 

“BART-eligible” source is 1 of 26 identified source categories that has the potential to 

emit ≥ 250 tons/year of any air pollutant and was put in place during the 15-year interval 

between August 7, 1962, and August 7, 1977. BART is required when any source 

meeting this definition emits any air pollutant that may reasonably be anticipated to cause 

or contribute to any impairment of visibility in any Class I area. 
 December 2008 3-1

3.0 IDENTIFICATION OF BART-ELIGIBLE UNITS AT ALCOA WARRICK 

OPERATIONS 

Alcoa, Inc. – Warrick Operations (Alcoa) operates emission units that fall within the 

categories of fossil-fuel fired steam electric plants of more than 250 MMBtu per hour heat input, 

primary aluminum ore reduction plants, and secondary metal production facilities – 3 of the 26 

identified source categories to which BART is applicable. Three boilers, 5 potlines, and 18 

furnaces within these categories were brought on-line between August 7, 1962 and August 7, 

1977. The following table identifies these emission units. 

Table 3-1. BART-eligible Emission Units 

EMISSION UNIT START-UP DATE 

Boiler # 2 1964 

Boiler # 3 1965 

Boiler # 4 1968 

Potline # 2 1962 

Potline # 3 1965 

Potline # 4 1965 

Potline # 5 1968 

Potline # 6 1968 

#1 Casting Complex 1M1 1973 

#1 Casting Complex 1M2 1973 

#1 Casting Complex East Holder 1EH 1973 

#1 Casting Complex West Holder 1WH 1973 

# 5 Furnace Complex Melter 5M1 1966 

# 5 Furnace Complex Melter 5M2 1966 

# 5 Furnace Complex Melter 5M3 1966 

# 5 HDC Complex East Holder 5EH 1966 

# 5 HDC Complex West Holder 5WH 1966 

# 6 Furnace Complex Melter 6M1 1966 

# 6 Furnace Complex Melter 6M2 1966 

# 6 Furnace Complex Melter 6M3 1966 

# 6 Furnace Complex East Holder 6EH 1966 

# 6 Furnace Complex West Holder 6WH 1966 

# 2 Offline East Melter 1976 

# 2 Offline West Melter 1976 

# 2 Offline East Holder 1976 

# 2 Offline West Holder 1976
 December 2008 3-2

The fossil-fuel fired steam electric plants of more than 250 MMBtu per hour heat input emission 

unit group has the potential to emit ≥250 tons/year of sulfur dioxide (SO2), a visibility impairing 

pollutant. As such, the Alcoa facility is defined as a BART-eligible source. Emission units within 

the fossil-fuel fired steam electric plants of more than 250 MMBtu per hour heat input and 

primary aluminum ore reduction plants that were in existence between August 7, 1962 and 

August 7, 1977, are the emission units at Alcoa that are BART-eligible. 
 December 2008 4-1

4.0 BART–ELIGIBLE EMISSION UNIT GROUP DESCRIPTION 

4.1 Primary Aluminum Reduction Process

Alcoa’s primary aluminum reduction operations include five BART-eligible potlines. 

The potline operations manufacture metallic aluminum by the electrolytic reduction of alumina 

in center-worked prebake cells. Direct electrical current, passing between anodes and the 

cathode, electrolytically reduces the alumina to aluminum and oxygen. Molten aluminum is 

deposited and accumulates over time at the cathode beneath a layer of molten cryolite bath. 

Periodically the molten aluminum is siphoned from beneath the cryolite bath and processed to 

achieve specific metal properties or is retained as pure aluminum. The product aluminum is 

solidified into intermediate or final products. The BART-eligible Potlines, No. 2 through No. 6 

emit SO2, NOX, and particulate matter (PM). These emission units are currently equipped with 

sophisticated emission control equipment for PM. 

 

4.1.1 Existing Potline Emissions Control 

 The potlines at Alcoa consist of groups of electrolytic reduction cells connected in series 

that produce molten aluminum. Each potline is comprised of 150 Alcoa technology reduction 

cells with 26 anodes per cell. Emissions from each potline group are captured and controlled 

with a primary control system. Any uncaptured fume is emitted as secondary fugitive emissions 

through the roof monitor atop the potline buildings. 

 There are two different types of primary control systems employed at the Alcoa potlines. 

Potlines 2, 5, and 6 utilize a fluid-bed reactor type system with fabric filtration downstream of 

the reactor beds. Smelting grade alumina is introduced into one end of the Alcoa designed A-398 

reactor. The alumina is fluidized by potline fume exhausted into the reactor through a series of 

perforated plates. Gaseous fluoride and a limited amount of SO2 are adsorbed onto the alumina 

surface. Fabric filtration devices are positioned atop the reactor compartments to collect 
 December 2008 4-2

entrained alumina particles and other PM present in the gas stream. Total fluoride and particulate 

removal efficiencies >99% are achieved by the control system. 

 Potlines 3 and 4 utilize a gas treatment system (GTS) consisting of an alumina injection 

system followed by fabric filtration. The alumina coats the fabric filters and adsorbs gaseous 

fluoride while simultaneously collecting other PM present in the gas stream. Removal 

efficiencies are again >99% with this control system. 

4.2 Ingot Furnaces

Alcoa’s Ingot plant includes seventeen (17) BART-eligible group 1 and group 2 furnaces. 

The # 1 Coil Casting Complex includes four (4) group 1 furnaces. Two (2) group 1 furnaces, 

identified as #1 Casting Complex 1M1 and 1M2, were constructed in 1973 with a maximum 

aluminum production rate of 6.85 tons per hour, each, when used for producing cast coils and 49 

tons per hour when used as off-line melters. Emissions are uncontrolled and exhaust through 

stacks 134.62 and 134.64 respectively. Two (2) group 1 furnaces, identified as #1 Casting 

Complex East Holder 1EH and West Holder 1WH were constructed in 1973 with maximum 

aluminum production rates of 10.27 tons per hour, each, when used for producing cast coils and 

49 tons per hour each, when used as off-line holders. Emissions are uncontrolled and exhaust 

through stacks 134.63 and 134.66, respectively. 

The #5 Furnace Complex also includes five (5) group 1 furnaces. Three (3) group 1 

furnaces are identified as Melters 5M1, 5M2 and 5M3, were constructed in 1966 with a 

maximum aluminum production rate of 97.5 tons per hour each. Emissions are uncontrolled and 

exhaust at stacks 134.33, 134.36, and 134.39, respectively. Two (2) group 1 furnaces are 

identified as #5 HDC Complex East Holder 5EH and West Holder 5WH, were constructed in 

1966 with maximum aluminum production rate of 97.5 tons per hour each. Emissions are 

uncontrolled and exhaust through stacks 134.35 and 134.38, respectively. 
 December 2008 4-3

The #6 Furnace Complex contains 5 group 1 furnaces. Three (3) group 1 furnaces are 

identified as Melters 6M1, 6M2, and 6M3. These furnaces were constructed in 1966 and have a 

maximum aluminum production rate of 12 tons per hour each. Emissions are uncontrolled and 

exhaust through stacks 134.40, 134.42, and 134.44, respectively. Two (2) group 1 furnaces 

identified as #6 Furnace Complex East Holder 6EH and West Holder 6WH were constructed in 

1966 with maximum aluminum production rate of 16 tons per hour each. Emissions are 

uncontrolled and exhaust through stacks 134.41 and 134.43, respectively. 

The #2 Offline Furnace Complex contains four (4) group 2 furnaces. Two (2) group 2 

furnaces are identified as #2 Offline East Melter and West Melter. These furnaces were 

constructed in 1976, each with a maximum aluminum production rate of 12 tons per hour. 

Emissions are uncontrolled and exhaust through stacks 134.71 and 134.76 respectively. Two (2) 

group 2 furnaces identified as #2 Offline East Holder and West Holder were constructed in 1976 

each with a maximum aluminum production rate of 12 tons per hour. Emissions are uncontrolled 

and exhaust through stacks 134.73 and 134.75, respectively. 

4.3 Coal Fired Boilers

Alcoa’s three (3) coal fired boilers that are BART-eligible are dry bottom, pulverized coal-fired 

boilers. They are identified as Boiler No. 2, 3, and 4. Construction of boilers 2 and 3 

commenced on July 26, 1956. Boiler 2 came on-line in January 1964. Boiler 3 came on-line in 

October 1965. Boilers 2 and 3 each had a nominal heat input capacity of 1,357 million Btu per 

hour (MMBtu/hr) prior to their recent upgrade to a nominal heat input capacity of 1,589 million 

Btu per hour. Construction of boiler 4 started on March 16, 1968 and has a nominal heat input 

capacity of 2,958 MMBtu/hr. Each of the boilers is equipped with an electrostatic precipitator 

(ESP) for control of particulate matter. Boiler 3 was equipped with a low NOx burner and overfire air in 2002 and Boiler 2 was equipped with a low NOx burner and over-fire air in 2004. 

Boiler 4 was equipped with a low- NOx burner in 1998 and a selective catalytic reduction system 

(SCR) in 2004. Wet flue gas desulfurization scrubbers were installed and began controlling 

emissions from boilers 2 and 3 in May and July, 2008 respectively. 
 5-1 December 2008 

5.0 BASELINE CONDITIONS AND VISIBILITY IMPACTS FOR BART-ELIGIBLE 

UNITS 

 Before beginning the five step case-by-case BART analysis, CALPUFF modeling was 

performed to evaluate the overall change in visibility attributable to Warrick’s BART-eligible 

emission units and to quantify their individual relative contribution to the total visibility impact of 

baseline conditions. A modeling protocol was developed by TRC Environmental Corporation and 

submitted to the IDEM. The protocol is included as Appendix B to this report. All modeling 

performed in association with this BART determination was done by TRC Environmental 

Corporation. 

 Table 5-1 presents the baseline modeling source input data that were used in the 

CALPUFF model to forecast the visibility impacts. Per Section IV of Part 51 Appendix Y, 

baseline emission rates used in the model were based on 24-hour average actual emissions from 

the highest emitting day. CALMET and CALPUFF simulations were conducted for 2001–2003. 

MM5 data at a resolution of 12 km was used for 2001 and 2002 and 20 km resolution RUC data 

were used for 2003 due to the unavailability of the 12 km MM5 data for 2003. This data was 

supplemented with available surface observations and upper air soundings within and 

surrounding the CALMET modeling domain. Initial BART modeling projected the highest 

visibility impact to be in Mammoth Cave National Park (MCNP), with minimal or no impact in 

more distant Class 1 areas. Other Class 1 areas that were screened included Mingo, Sipsey, 

Great Smokey Mountains, Joyce Kilmer, Cohutta, and Shinning Rock. The BART analysis in 

this document was based solely on visibility impacts at MCNP, since the change in visibility in 

this Class 1 area would dictate the BART determination. The results of the screening run show 

that visibility impacts within MCNP exceeded the 0.5 dv contribution to visibility impairment 

threshold suggested by USEPA; therefore, a refined modeling analysis was performed. 
 5-2 December 2008 

Table 5-1. Baseline Conditions Modeling Input Data 

Index Emission Unit ID # Stack Name Release Height (m) Monitor Width (m) Exit Veloc. (m/s) Delta T (K) Beginning UTM E/N (km) Ending UTM E/N (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

L01 103M.1 Potline #2, Room 103 14.02 1.52 2.93 24.95 

471.119, 

4196.702 

471.198, 

4196.984 0.535 0.753 

L02 104M.1 Potline #2, Room 104 14.02 1.52 2.93 24.95 

471.087, 

4196.711 

471.166, 

4196.993 0.535 0.753 

L03 105M.1 Potline #3, Room 105 14.02 1.52 2.93 24.95 

471.024, 

4196.728 

471.103, 

4197.010 0.569 0.802 

L04 106M.1 Potline #3, Room 106 14.02 1.52 2.93 24.95 

470.992, 

4196.737 

471.070, 

4197.019 0.569 0.802 

L05 107M.1 Potline #4, Room 107 14.02 1.52 2.93 24.95 

470.961, 

4196.745 

471.038, 

4197.027 0.567 0.799 

L06 108M.1 Potline #4, Room 108 14.02 1.52 2.93 24.95 

470.929, 

4196.754 

471.007, 

4197.036 0.567 0.799 

L07 109M.1 Potline #5 , Room 109 14.02 1.52 2.31 23.18 

470.900, 

4196.770 

471.976, 

4197.052 0.470 0.663 

L08 110M.1 Potline #5, Room 110 14.02 1.52 2.31 23.18 

470.868, 

4196.778 

471.943, 

4197.061 0.470 0.663 

L09 111M.1 Potline #6 , Room 111 14.02 1.52 2.31 23.18 

470.803, 

4196.796 

471.881, 

4197.078 0.532 0.749 

L10 112M.1 Potline #6, Room 112 14.02 1.52 2.31 23.18 

470.771, 

4196.804 

471.848, 

4197.086 0.532 0.749 

Index Emission Unit ID # Stack Name Stack Height (m) Stack diameter (m) Exit Veloc. (m/s) Exit Temperature (K) UTM Easting (km) UTM Northing (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

P01 GTC 

Potlines #3 & #4 GTC Pollution 

Controls 60.66 6.10 16.46 350 470.668 4196.863 0.986 0.116 

P02 160C1.1-160C1.36 Potline #2 A-398 14.94 3.70 21.12 366 471.118 4196.953 0.393 0.046 P03 161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.555 0.065 P04 161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 4196.888 0.563 0.066 P23 134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 P24 134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 P25 134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 P26 134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 P28 134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 P29 134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 P30 134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 P31 134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 P32 134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 P33 134.4 Melter 6M1 38.40 1.22 3.80 583 470.933 4197.145 0.062 0.029 P34 134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 P35 134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 P36 134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 P37 134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 P39 134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245 0.007 0.003 P41 134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 

WPP01 WPP01 

Warrick Power Plant Stack 1 Unit 2 

Only 115.82 5.91 12.88 423 470.810 4196.399 * 8.6 

WPP02 WPP02 

Warrick Power Plant Stack 2 Units 2 

and 3 115.82 5.91 12.59 428 470.731 4196.443 * 22.01 

WPP03 WPP03 Warrick Power Plant Stack 3 Unit 4 115.82 4.45 34.91 425 470.668 4196.433 * 49.525 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5
 5-3 July 2010 

5.2 Refined Modeling Analysis

 The CALPUFF modeling system was used for the BART analysis for the Class I areas 

within a 300-km radius of Alcoa. CALPUFF and its meteorological model CALMET are 

designed to handle the complexities posed by complex terrain, long source receptor distances, 

chemical transformation and deposition, and other issues related to Class I impacts. EPA adopted 

the CALPUFF modeling system as a guideline model for source-receptor distances >50 km and 

for use on a case-by-case basis in complex flow situations for shorter distances (Federal Register, 

April 15, 2003). CALPUFF was recommended for Class I impact assessments by the Federal 

Land Managers Workgroup in 2000 and the Interagency Workgroup on Air Quality Modeling in 

1998. CALPUFF is recommended by EPA for BART analyses2

 (Federal Register, July 6, 2005). 

 Calculation of the impact on light extinction is carried out in the CALPOST 

postprocessor. CALPOST Method 6 is used to compute the extinction change in deciviews. 

Refined modeling forecasts were prepared for visibility impacts at the Class I area where the 

combined emissions from the BART-eligible emission units were forecast to be equal to or greater 

than the screening threshold limit of 0.5 dv. The complete Alcoa BART modeling report is 

contained in Appendix C. The refined modeling predicted visibility impacts from Alcoa emission 

units to be at a level equal to or greater than the threshold limit of 0.5 dv at MCNP. 

Table 5-2 presents the modeled 98th percentile total source visibility impact reported as 

deciviews for 2001, 2002, and 2003 at the MCNP Class I area. The most significant modeled or 

projected visibility impact at MCNP was associated with emissions from stack 2 (50% of unit 2 and 

unit 3 with the maximum 98th percentile impact being 1.379 dv occurring in 2002. Of this projected 

impact from stack 2 (50% of unit 2 and unit 3), 74.2% was due to emissions of SO2 and 24.6% was 

due to NOx emissions. 0.6 percent of the projected visibility impact from stack 2 (50% of unit 2 

and unit 3) was attributable to emissions of particulate matter and organics combined. 

 

2

 70 FR 39122 
 5-4 July 2010 

The modeled or projected maximum 98th percentile visibility impact at MCNP associated 

with emissions from stack 1 (50% of coal fired boiler unit 2) was 0.434 dv occurring in 2002. Of 

this projected impact from 50% of unit 2, 71.2 % was due to emissions of SO2 and 27.3% was due 

to NOx emissions. 1.5% of the projected visibility impact from stack 1(50% of unit 2) was 

attributable to emissions of particulate matter and organics combined. 

Table 5-2. Baseline Visibility Modeling Results 

Year Source Group 

Modeled 

98th 

Percentile 

deciview 

Calculated 

98th 

Percentile 

deciview 

Percentage of Species Contribution

SO4

% 

NO3

% 

Filterable 

PM2.5% 

Filterable 

PM10 

% 

Organic 

Condensable PM 

% 

2001 Total of Sources 1.852 

2001 Unit 2, Stack 1 0.392 96.3 2.5 0.7 0.0 0.5 

2001 Unit 2 & 3, Stack 2 1.306 96.6 2.2 0.6 0.0 0.6 

2001 Unit 4, Stack 3 0.023 0.0 0.0 65.5 0.0 34.5 

2001 Potroom 0.010 28.0 0.0 28.0 8.0 36.0 

2001 A398s 0.070 94.0 0.0 2.2 0.0 3.8 

2001 GTC 0.049 94.5 0.0 2.4 0.0 3.1 

2001 Ingot Furnaces 0.001 0.0 66.7 33.3 0.0 0.0 

 

2002 Total of Sources 1.906 

2002 Unit 2, Stack 1 0.434 71.3 27.3 0.8 0.0 0.6 

2002 Unit 2 & 3, Stack 2 1.379 74.1 24.6 0.7 0.0 0.6 

2002 Unit 4, Stack 3 0.032 0.0 0.0 67.9 0.0 32.1 

2002 Potroom 0.004 20.0 0.0 30.0 10.0 40.0 

2002 A398s 0.030 87.3 2.5 3.9 0.0 6.3 

2002 GTC 0.026 90.0 1.4 2.9 0.0 5.7 

2002 Ingot Furnaces 0.001 0.0 100 0.0 0.0 0.0 

 

2003 Total of Sources 1.788 

2003 Unit 2, Stack 1 0.380 88.9 9.9 0.7 0.0 0.5 

2003 Unit 2 & 3, Stack 2 1.261 89.5 9.3 0.6 0.0 0.6 

2003 Unit 4, Stack 3 0.023 0.0 0.0 65.0 0.0 35.0 

2003 Potroom 0.007 23.5 0.0 29.4 6.0 41.1 

2003 A398s 0.068 92.7 0.6 3.9 0.0 2.8 

2003 GTC 0.046 92.5 0.8 4.2 0.0 2.5 

2003 Ingot Furnace 0.003 0.0 87.5 12.5 0.0 0.0 

All other BART-eligible sources (unit 4 PM, potlines, and ingot furnaces) at Alcoa Warrick 

and Alcoa Power Generating Inc. – Warrick Power Plant projected individual visibility impacts of 

less than 0.5 dv. The modeled or projected maximum 98th percentile visibility impact from the 
 5-5 July 2010 

potlines was approximately 0.13 dv at MCNP occurring in 2001. Approximately 93% of the 

projected impact from the potlines or 0.12 dv was attributable to emissions from the potline 

primary control devices, with the remainder, 0.01 dv, from the potroom roofs. Approximately 

94.2% of the potroom primary control device estimated impact or 0.112 dv was from emissions 

of SO2, 3.6% or 0.004 dv was from condensable organics, and 2.3% or 0.003 dv was due to 

emissions of fine particulates. The modeled or projected maximum 98th percentile visibility 

impact from unit 4 PM was approximately 0.032 dv at MCNP occurring in 2002. 

The refined modeling results in Table 5-2 show visibility impacts less than 0.02 dv for 

the potroom roofs and less than 0.005 dv for the ingot furnaces. The impact from each of these 

sources is less than 4% of the facility-wide contribution to visibility impairment threshold (0.5 

dv) for BART applicability suggested by USEPA in Appendix Y to Part 51- Regional Haze 

Regulations and Guidelines for Best Available Retrofit Technology (BART) Determinations; 

Final Rule. Reduction in emissions from these sources would not result in any significant 

visibility improvement at MCNP. 

The scope and cost analysis for the Alcoa BART determination was focused on the 

emission units predicted to contribute greater than 0.05 dv to MCNP visibility impairment. 

Coal-fired boiler units 2, 3, and 4 and the potline primary control devices (A398s and GTC) 

showed modeled 98th percentile visibility impacts of 1.8 dv and 0.12 dv, respectively. Given 

these potential impacts, a detailed retrofit control assessment was performed for boilers 2, 3, and 

4 and the reduction of SO2 emissions emanating from the potline primary control devices (A398s 

and GTC). Modeling data indicates that SO2 from these sources is the primary pollutant 

potentially impacting visibility at MCNP. 
 6-1 July 2010 

6.0 BART ANALYSIS FOR BART-ELIGIBLE EMISSION UNITS 

 The results of the refined CALPUF modeling indicate that emissions from Alcoa’s 

boilers 2, 3, and 4 and potline reactors 2 – 6 contribute to visibility impairment in at least one 

Class 1 area. The BART analysis was completed for these emissions sources. The analysis 

included a review of the available and technically feasible retrofit control technologies (Steps 1 

and 2), a determination of control effectiveness for the feasible options (Step 3), an evaluation of 

the cost and secondary impacts for feasible alternatives (Step 4), and an analysis of visibility 

impact and improvements (Step 5). 

The present controls for the potline reactors and the coal fired boilers are described by 

pollutant in the following sections, followed by the control options that are available for 

reduction of visibility impairing pollutants. 

6.1 Potline Emission Controls

The major pollutants emitted from the potlines are PM, hydrogen fluoride, SO2, and 

carbon monoxide. PM includes particulate fluoride, carbon dust, and alumina. SO2 comes from 

the sulfur in the components used to make the anodes. NOx emissions are minimal since there is 

no external fuel used by the potline reduction cells, there are no burners with combustion zones 

and there are no large sources of nitrogen in the raw materials. 

 Emissions from the pots are collected by capture a system that employs hooding over 

each pot. The hoods enclose the pot and divert smelting fume to ducting connected to emission 

control equipment. During normal operation of the potlines select hoods are temporarily 

removed to allow anodes to be changed. The temperature of the exhaust gases entering the 

control equipment is typically 150–300°F [Air and Waste Management Association (AWMA) 

2000]. Emissions from Potlines 2, 5, and 6 at Alcoa are each controlled using A-398 pollution 

control systems. The gas flow of each of the A-398 pollution control systems is approximately 

480,000 acfm at 200 o

F. Emissions from Potlines 3 and 4 are abated by the Gas Treatment 
 6-2 July 2010 

Center (GTC) emission control device. It is an alumina injection system equipped with a fabric 

filtration system to collect the injected alumina and other particulates. The gas flow rate of the 

GTC is approximately 1,000,000 acfm at 170 o

F. Secondary emissions from all of the potlines 

are uncontrolled and exhaust through the potroom roof monitors. 

6.1.1 Potentially Applicable BART Control Options for Potlines 

6.1.1.1 Potentially Applicable SO2 Emission Controls for Potlines 

Sulfur in the anodes is oxidized, releasing SO2 from the potlines as the anodes are 

consumed. Options for controlling SO2 include both add-on controls and pollution prevention. 

Absorption and adsorption have been used for the control of SO2 emissions from numerous 

industrial processes. As a result many commercialized control technologies have been used for 

SO2 control. While such technologies have been proven in the power utility industry, the 

practical application of these controls systems down stream of the potline reactors is limited by 

the very low inlet SO2 levels, in the range of 100 parts per million by volume (ppmv), and the 

expected range of gas conditions, including temperature, oxygen content, humidity, SO2/O2 ratio, 

and gas impurities. 

 

 Eight different SO2 control options were considered as having potential practical 

application as part of the BART analysis. Two of these technologies have been applied to the 

control of SO2 emissions at aluminum smelters. Six of the control options use wet scrubbing and 

two use dry scrubbing technology. The eight potentially applicable control options are: 

 Seawater scrubbing 

 Limestone slurry scrubbing with natural oxidation 

 Limestone slurry scrubbing with forced oxidation 

 Conventional lime wet scrubbing 

 Dual alkali sodium/lime scrubbing (dilute mode) 

 Conventional sodium scrubbing 

 Dry injection 

 Semi-dry scrubbing 
 6-3 July 2010 

6.1.1.1.1 Wet Scrubbing for Potlines 

 The primary development of SO2 control technology occurred because of the need to 

control emissions from the coal-fired, electric utility power industry (AWMA 2000). The large 

volumetric size of the potroom exhaust (500,000 to 1,000,000 acfm) would require a system 

similar to those used in the electric utility power industry. 

 The typical temperature range for wet scrubbers is 300–700°F. For utility combustion 

units, wet scrubbing systems have been installed on systems as large as 1,500 MW. Sodium 

compounds, lime, or limestone can be used. However, the high solubility of sodium complicates 

disposal of waste and wastewater. The typical sorbent material is lime or limestone. Lime is 

generally easier to manage on-site but is significantly more costly. Wet limestone scrubbing has 

a high capital and operating cost due to the handling of liquid reagent and waste, but is the 

preferred process for coal-fired utility power plants burning coal due to the low cost of limestone 

and high removal efficiencies. Typical removal efficiencies are 80–95%. Approximately 85% of 

the flue gas desulfurization (FGD) systems installed in the United States are wet scrubber 

systems (EPA 2003c). 

 In wet scrubbers, the waste gas enters a large vessel (spray tower or absorber), where it is 

sprayed with water slurry. Figure 1 is a simplified process flow diagram of a conventional wet 

scrubber. 
 6-4 July 2010 

Inlet

Gas

Particulate Control

Clean gas out

Spray tower/absorber

Fly Ash

Lime (stone)

and Water

Reaction

Tank

Calcium-based

sorbent spray

Thickener

Filter

Solids

Stabilized Waste

Lime

Blending

Pugmill

Reagent

Supply

Liquid Waste

Stream

Figure 1. Wet Scrubber 

 The calcium in the slurry reacts with SO2 to form CaSO3. A portion of the slurry from the 

reaction tank is pumped into the thickener, where the solids settle before going to a filter for final 

dewatering to about 50% solids. In the utility industry, the CaSO3 waste product is usually mixed 

with fly ash (approximately 1:1) and fixative lime (approximately 5%) and typically disposed of 

in landfills. Alternately, the forced oxidation process oxidizes the spent slurry to gypsum. 

Gypsum crystals dewater more efficiently and reduce the size of waste handling equipment. 

Depending on quality and demand, the gypsum may be commercially sold, eliminating the need 

for landfilling the waste product. 

 Note that “mist eliminators,” installed at the spray tower outlet or downstream ductwork, 

remove droplets from the gas. In some power plant installations, the gas is reheated to avoid 
 6-5 July 2010 

corrosion downstream. Many scrubbers have gas bypassing capability, which can be used for gas 

reheating. If the wet scrubber is downstream of a high-efficiency particulate removal device 

[fabric filter or electrostatic precipitator (ESP)], the particulate concentration may be higher 

leaving the scrubber than entering due to the solids in mist droplets that are carried out of the 

scrubber. 

 Some disadvantages of using wet scrubbing techniques in many applications are the 

requirement to treat wastewater, components must be constructed from expensive alloys to resist 

corrosion, and energy use is much higher. A practical issue associated with a wet scrubber 

system is the complexity of the system. The space required for a wet system is substantial (i.e., 

large footprint), the systems require more maintenance due to their complexity, and more 

personnel are required for their operation. 

6.1.1.1.1.1 Seawater Scrubbing 

 Globally, once-through seawater scrubbing has been installed at seven aluminum 

smelters, none of which are in the United States. Seawater scrubbing has been implemented in 

the coal fired power industry, recently at the Mawan Power Station in China and the Paiton 

Project in Indonesia. Seawater, which has a natural alkalinity, is pumped directly into a 

scrubbing tower through a system of spray nozzles where the atomized droplets make contact 

with the gas. The liquid effluent is discharged back into the ocean. Seawater scrubbing was 

automatically rejected as feasible because of Alcoa’s physical location. 

6.1.1.1.1.2 Limestone Slurry Forced Oxidation 

 Limestone slurry forced oxidation (LSFO) is used extensively in the utility flue gas 

desulphurization market. The raw material is finely ground limestone. There are a number of 

suppliers of LSFO technology. The most commonly used equipment is an open, multi-level, 

countercurrent spray tower scrubber equipped with spray nozzles to inject the limestone slurry 

droplets into the gas stream. Liquor is collected at the bottom of the tower and sparged with air 
 6-6 July 2010 

to oxidize the calcium sulfite to calcium sulfate to enhance the settling properties of the calcium 

sulfate. Recirculation pumps circulate the scrubbing liquor to the spray nozzles. SO2 removal 

efficiencies of 90% have been achievable. The bleed from the scrubber is sent to a dewatering 

system to remove excess moisture. For an aluminum smelter, the process will produce either 

solid gypsum waste or commercial-grade gypsum suitable for reuse as a cement additive. Only a 

very small purge or blowdown stream is required. 

 LSFO was determined to be a technically feasible retrofit control option for the potroom 

reactor even though it is not ideally suited for wet scrubbing due to low SO2 concentrations 

(<100 ppm). 

6.1.1.1.1.3 Limestone Slurry Natural Oxidation 

 Limestone slurry natural oxidation (LSNO) is very similar to LSFO. The major 

difference is the absence of an oxidation stage. The gypsum/calcium sulfite product is essentially 

a waste product with limited possibilities of being used for agricultural purposes. 

6.1.1.1.1.4 Conventional Lime Wet Scrubbing 

 Conventional lime wet scrubbing is also similar to LSFO except that the raw material is 

hydrated lime or quick lime that is either slaked on-site or purchased in the slaked form. The 

system typically uses forced oxidation, although natural oxidation is possible. The process will 

produce either solid gypsum waste or commercial-grade gypsum suitable for reuse as a cement 

additive. 

6.1.1.1.1.5 Dual Alkali Sodium/Lime Scrubbing (Dilute Mode) 

 Dual alkali sodium/lime scrubbing (dilute mode) uses a caustic sodium solution in the 

scrubber tower. A portion of the scrubbing liquid is discharged to a neutralization stage where 
 6-7 July 2010 

lime slurry is used to regenerate the caustic, which is returned to the scrubber. The bleed from 

the scrubber is sent to a dewatering system to produce a gypsum byproduct. The process will 

produce either solid gypsum waste or commercial-grade gypsum suitable for reuse as a cement 

additive. It should be noted, however, that dual alkali sodium/lime scrubbing (dilute mode) is not 

marketed today by major FGD vendors because the system is too complicated and expensive. 

6.1.1.1.1.6 Conventional Sodium Scrubbing 

 This technology has been successfully utilized in the power industry and globally, has 

been installed in at least 12 aluminum smelters. An alkaline solution of either soda ash or sodium 

hydroxide is pumped into the scrubbing tower and recirculated through a network of spray 

nozzles. Atomized droplets contact the up-flowing gas containing SO2. Where this technology 

has been deployed, the liquid effluent containing dissolved salts, including sodium and fluorides, 

has been discharged into a large receiving stream or an open body of water without treatment. 

6.1.1.1.2 Dry Scrubbing for Potlines 

6.1.1.1.2.1 Dry Injection 

 In dry injection, a reactive alkaline powder is injected into a furnace, ductwork, or a dry 

reactor. Typical removal efficiencies with calcium adsorbents are 50–60% and up to 80% with 

sodium base adsorbents. However, as with wet scrubbing, disposal of waste using sodium 

adsorbents must consider their high solubility in water compared to those from calcium 

adsorbents. The temperature range where dry scrubbing has been used is 300–1,800°F; the 

minimum temperature is 300–350°F. Dry systems are rarely used and according to EPA only 3% 

of FGD systems installed in the United States are dry systems (EPA 2003c). The dry waste 

material is removed using particulate control devices such a fabric filter or an ESP. 
 6-8 July 2010 

 Dry scrubbing downstream of the potline reactors is not technically feasible because of 

the low temperatures (<300°F) and low SO2 concentrations (<100 ppm). 

6.1.1.1.2.2 Semi-dry Scrubbing (Spray Dryer) 

 Semi-dry scrubbing is more commonly referred to as spray drying. Calcium hydroxide 

slurry (lime mixed with water) is introduced into a spray dryer tower. Sodium compounds can be 

used, but as with the dry scrubber, the high solubility of the sodium-based waste products in 

water complicates disposal of the waste. The slurry is atomized and injected into a reactor with 

the exhaust gases, where droplets react with SO2 as the liquid evaporates. This system is 

categorized as a semi-dry system because the end product of the SO2 conversion reaction is a dry 

material. The dry waste product is collected in the bottom of the spray dryer reactor, and a fabric 

filter or ESP downstream of the spray dryer removes the CaSO3, CaSO4, and unreacted lime. 

This air pollution control system uses water for evaporative cooling and for the SO2 reaction. It 

operates in a temperature range of 300–350°F because the temperature of the gases must be high 

enough to evaporate the water portion of the slurry. Approximately 12% of the FGD systems 

installed in the United States are spray dry systems (EPA 2003c) with typical SO2 removal 

efficiencies in the range of 80–90%. Unlike a wet scrubbing system there is no liquid blow-down 

stream from the dry system, and the collected solids are typically landfilled. 

Spray dry scrubbing downstream of the potline reactors is not technically feasible 

because of the low temperatures (<300°F) and low SO2 concentrations (<100 ppm). 

6.1.1.1.3 Pollution Prevention for Potlines 

 The guidelines for BART determinations under the Regional Haze Rule recommend 

consideration of pollution prevention options in addition to add-on controls. The primary 

opportunity for pollution prevention in the smelting process to minimize SO2 emissions is 

normally through limitations on the sulfur content in the incoming coke. Coke is a major raw 
 6-9 July 2010 

material used in the manufacture of green anodes. Green anodes are subsequently baked in a 

furnace prior to their use in the smelting process. Alcoa’s current specification for incoming coke 

sulfur content is 2% which is significantly lower than what is required for most primary 

aluminum facilities. Alcoa has current SO2 emission limits in their Title V permit that were 

established based on SIP modeling that supported uncontrolled SO2 emissions of 5.11 lbs./mm 

Btu from the power plant boilers (Unit 1 and BART eligible units 2-4) that translate to this 2% 

sulfur content specification for coke used to manufacture anodes. In order to fully evaluate the 

potential for pollution prevention in this BART analysis, Alcoa undertook a low sulfur coke 

availability analysis to determine what sulfur content in coke would be available beyond 2013 

when BART controls requirements are anticipated. Confidential research information belonging 

to the market analysts assisting with the preparation with the coke availability analysis is 

included in Appendix D. The coke availability and market analysis has been submitted 

separately pursuant to the procedures of the State of Indiana. The primary conclusions from this 

analysis indicate that: 

 Coke is a byproduct of the oil refining process. The sulfur content of the world’s 

crude oil supply has been and will continue increasing in sulfur content. Those 

refiners with coking capacity are minimizing their raw material costs by maximizing 

use of high sulfur crude oils to the optimal extent for their overall refinery design. 

The result will be a continuing increase in the sulfur content of available coke. 

 Coke is a relatively small, low revenue component of the refinery’s product profile. 

As such, the aluminum industry has little influence in controlling the quantity, 

quality, and price of the coke produced by refineries. 

 Growth in the aluminum industry has increased the demand for the limited quantities 

of coke and has driven prices for coke to unprecedented levels. 

 Prices for coke nearly doubled from 1994 to 2006. 

 The increased global growth in aluminum production will continue to outpace the 

production of coke. 

 Primary aluminum production is expected to grow at the rate of 3% to 4% annually 

resulting in a commensurate growth in demand for coke. 

 Coke providers are blending imported, high cost, lower sulfur coke with domestically 

sourced coke in attempts to meet the current specification requirements for coke. 

 Removal or reduction of the sulfur content of the coke once it has been received is not 

feasible. 
 6-10 July 2010 

 Aluminum smelters are experimenting with alternative cokes and technologies that 

are outside of the traditional specifications to ensure continued aluminum production 

in the face of the changing characteristics of this key raw material. 

 The deterioration in coke quality and the tightness of supply is expected to continue 

for the foreseeable future. 

 The increased demand for coke will force the aluminum industry to accept lower 

quality coke with higher sulfur contents. 

 Thus, based on the market and availability analysis of the future coke supply, Alcoa 

determined that it is infeasible to consider coke at sulfur contents below 3% as BART pollution 

prevention option because a supply of coke with sulfur contents below 3% cannot be ensured 

beyond 2013 when BART control requirements are anticipated. These market pressures are 

expected to force Alcoa to begin using higher sulfur content coke in the future. Because of this 

finding, Alcoa is seeking separate revision to the Indiana SIP and Title V operating permits to 

address this issue. Also, as a result of this analysis, pollution prevention is not technically 

feasible as an option to reduce SO2 emissions from the potlines. 

6.1.1.1.4 Potline Control Options from RBLC Database 

 A review or EPA’s RACT/BACT/LAER Clearinghouse (RBLC) database was also 

completed to determine which control technologies or techniques have been utilized by primary 

aluminum ore reduction plants. Results from searching the RBLC are summarized in Table 6-1.
 6-11 July 2010 

Table 6-1. RBLC Database Search Results for Primary Aluminum Facilities 

RBLC 

ID Facility 

Last 

Update Process Pollutant Control Option 

Percent 

Efficient 

Emission 

Limit 

KY-0070 NSA-A 

DIVISION OF 

SOUTHWIRE 

COMPANY 

3/2/2004 POTLINE 5 SO2 WET 

SCRUBBER a 

93% 25.51 lb/hour 

SC-0037 ALUMAX OF 

SOUTH 

CAROLINA 

9/17/2002 POTROOM 

GROUPS (4) 

PM EXISTING DRY 

ALUMINA 

SCRUBBERS 

(FABRIC 

FILTER) 

 5.9 lb/hour 

SC-0037 ALUMAX OF 

SOUTH 

CAROLINA 

9/17/2002 POTROOM 

GROUPS (4) 

SO2 LIMIT MAX % 

SULFUR OF 

ANODE COKE 

TO 2.95% LIMIT 

MAX % SULFUR 

OF ANODE 

PITCH TO 1.2% 

 271 lb/hour 

KY-0041 ARCO METALS 

CO. 

12/18/2001 PRIMARY 

ALUMINUM 

REDUCTION 

POTLINE 

SO2 FUEL SPEC: 

LOW S COKE 

AND PITCH (calc. 

3% sulfur) 

 388 lb/hour 

OR-0002 ALUMAX 

PACIFIC CORP. 

12/18/2001 ANODE 

COKE 

SO2 3% S in coke 

WA-0003 ALCOA 12/18/2001 POTLINES 

1,2,3 

SO2 FUEL SPEC: 

LIMIT S 

CONTENT IN 

COKE, RAW 

 3% S in coke 

NC-0003 ALCOA 1/28/2002 POT LINE 3 PM FABRIC FILTER 26 lb/hour 

NC-0003 ALCOA 1/28/2002 POT LINE 3 SO2 321 lb/hour 

MO-0036 NORANDA 

ALUMINUM, 

INC. 

5/9/2006 POTLINE 1 

AND 3 

PM10 Dry Scrubber 56.76/68.8 

tons/year 

a This wet scrubber is not actually used or required by permit. 

 The data in the RBLC database support the approach of limiting raw material sulfur 

content as a control option for potlines. Two facilities have limits of 3% sulfur content in coke 

and one has a 2.95% sulfur content limit. As previously noted, Alcoa currently operates below 

these limits. One facility is shown in the RBLC to have a wet scrubber to control SO2 emissions; 

however, an investigation revealed that the wet scrubber was not required as part of a BACT 

determination and that the facility currently does not operate a wet scrubber to control SO2
 6-12 July 2010 

emissions. The facility’s current Title V permit for “Potline 5” simply limits coke sulfur content 

to 3% and coal tar pitch sulfur to 0.8%. 

 Dry alumina scrubbers (with fabric filters) are the controls that have been considered 

BACT for PM. 

6.1.1.2 Potentially Applicable PM Emission Controls for Potlines 

 Potentially applicable PM emission controls are discussed in the following sections. 

6.1.1.2.1 Fabric Filters 

 Fabric filters generally provide high collection efficiencies for both coarse and fine 

(submicron) particles. They are relatively insensitive to fluctuations in gas stream conditions. 

Efficiency is relatively unaffected by large changes in inlet dust loadings. Filter outlet air is very 

clean (EPA 2003b). Collected material is dry, which usually simplifies processing or disposal. 

Fabric filters are currently applied for controlling PM emissions from the potrooms. 

6.1.1.2.2 Electrostatic Precipitators 

 ESPs are capable of very high removal efficiencies for large and small particles (EPA 

2003a). They offer control efficiencies that are comparable to fabric filters. Because of their 

modular design, ESPs, like fabric filters, can be applied to a wide range of system sizes. The 

operating parameters that influence ESP performance include fly ash mass loading, particle size 

distribution, fly ash electrical resistivity, and precipitator voltage and current. Dusts with high 

resistivities are not well-suited for collection in dry ESPs because the particles are not easily 

charged. This also affects the ash layers on the collecting electrodes. An ESP is technically 

feasible for control of PM from potrooms. 
 6-13 July 2010 

6.1.1.2.3 Cyclones, Inertial Separators, and Wet Scrubbers 

 Cyclones and inertial separators are used for collection of medium-sized and coarse 

particles. Wet scrubbers generally remove large particles but can remove small particles with the 

use of high pressure drops. However, none of these devices are as effective at removing small 

and submicron particles as fabric filters and ESPs (AWMA 2000). 

6.1.1.3 Potentially Applicable NOx Emission Controls for Potlines 

 Potentially applicable NOx emission controls for the potlines include only postcombustion controls since there is no external fuel or combustion zone and there are no large 

sources of nitrogen in the raw materials. 

6.1.1.3.1 Selective Non-Catalytic Reduction 

 SNCR is an add-on technique that involves injecting ammonia or urea into a specific 

temperature zone in a furnace or boiler. The ammonia or urea reacts with NOx in the gas to 

produce nitrogen and water. SNCR typically provides 30–50% NOx reduction. The effectiveness 

of SNCR depends on the temperature where reagents are injected, mixing of the reagent in the 

gas, residence time of the reagent within the required temperature window, and the ratio of 

reagent to NOx. The required temperature window is 1,600–2,100°F. Typical uncontrolled NOx

levels where this technology has been applied vary from 200 to 400 ppm. SNCR is less effective 

at lower levels of uncontrolled NOx (EPA 2003e). 

 The temperature of the potroom emission exhaust (<300°F) and NOx concentration 

(<1 ppm) are well outside the levels where SNCR could be used. Thus, SNCR is not technically 

feasible for the potroom exhaust. 
 6-14 July 2010 

6.1.1.3.2 Selective Catalytic Reduction 

 SCR is an add-on technique similar to SNCR that involves injecting ammonia into flue 

gas in the presence of a metal-based catalyst to convert NOx emissions to elemental nitrogen and 

water. The catalyst allows SCR systems to operate at much lower temperatures than SNCR; 

typical temperatures for SCR are 500–800°F, compared with 1,600–2,100°F for SNCR. The 

optimum temperature range is 700–750°F (EPA 2002). SCR is capable of NOx reduction 

efficiencies in the range of 70–90% and can be used with NOx concentrations as low as 20 ppm. 

However, higher NOx levels result in increased performance (EPA 2003d). 

 The temperature of the potroom emission exhaust (<300°F) and NOx concentration 

(<1 ppm) are outside the levels where SCR could be used. Thus, SCR is not technically feasible 

for the potroom exhaust. 

6.1.2 Summary of Technically Feasible BART Control Options for Potlines 

6.1.2.1 Feasible BART Control Options for Potline SO2

One technically feasible option, adding a wet scrubber to the potline reactor exhausts, 

was identified for controlling SO2 emissions from the potlines. This option was evaluated 

further as part of the BART determination analysis. 

6.1.2.2 Feasible BART Control Options for Potline PM 

 Cyclones, inertial separators, wet scrubbers, ESPs, and fabric filters are all technically 

feasible for controlling potroom PM emissions. However, ESPs and fabric filters are superior 

devices for controlling fine PM. 
 6-15 July 2010 

 Fabric filtration with dry alumina scrubbing has been widely used in the primary 

aluminum industry. Most smelters constructed within the past 20 years have used dry alumina 

scrubbing with fabric filters to control emissions from potlines. A few plants use control systems 

consisting of ESPs to collect PM followed by spray towers to scrub gaseous fluoride. Wet 

systems have many disadvantages, such as corrosion by hydrofluoric acid, scaling, and the 

requirement to treat wastewater. ESPs and wet systems are no longer installed on new smelters 

(AWMA 2000). 

 Given that fabric filters are already used for PM control and that these high-efficiency 

devices are superior or equal to other feasible control options, no further analysis of PM controls 

was performed. 

6.1.2.3 Feasible BART Control Options for Potline NOx

 Since there is no external fuel or combustion zone in the smelting cells, there are no 

technically feasible pre-combustion NOx controls. Likewise, there are no technically feasible 

add-on control options because of the temperature of the potroom exhaust (<300°F) and low NOx

concentration (<1 ppm). 

6.1.3 Control Effectiveness for Feasible BART Control Options for Potlines 

 Step 3 of the BART analysis is to evaluate the control effectiveness of the technically 

feasible control technologies. 

6.1.3.1 Control Effectiveness for Potline SO2

6.1.3.1.1 SO2 Wet Scrubbing 

 A wet scrubber was identified as a technically feasible add-on pollution control option to 

reduce SO2 from the potline reactors. Typical removal efficiencies are 80–95%. Two vendors of 
 6-16 July 2010 

this type of equipment provided control equipment quotes. One vendor provided preliminary 

equipment costs for two 100% absorbers for potline 2 and two 100% absorbers for potlines 3 - 6. 

The second vendor provided preliminary costs for two 100% absorber systems for the potlines at 

a similar Alcoa facility – Tennessee Operations. This system was sized for a total flow rate of 

1,920,000 acfm at Tennessee operations. For the purposes of this BART analysis, the 

information provided by the second vendor for the potlines at Alcoa – Tennessee Operations was 

scaled, based on exhaust gas volumes, to represent controls for Alcoa – Warrick Operations. The 

responding vendors reported that 95% SO2 removal was technically feasible. Accordingly, an 

SO2 removal efficiency of 95% was used in the BART analysis for the wet scrubber control 

option. 

 Mist droplets will be a component of the gas stream emitted from the scrubber. Solids in 

the droplets will become airborne PM when the water in the droplets evaporates. The PM 

concentration in the outlet of the wet scrubber was predicted to be 20 mg/Nm3

 by one of the 

vendors. Consequently, the wet scrubber option would cause an increase in PM from the 

potlines, as demonstrated in Table 6-2. 

 Table 6-2 summarizes the SO2 emission levels under the control scenario considered for 

BART. The emissions represent the combined total emissions from the potline roof vents and the 

potline reactors for each scenario. Based on the analysis of feasible add on controls and pollution 

prevention actions, the BART control scenario identified as feasible is the utilization of 3% 

sulfur coke and addition of a wet scrubber to the potlines reactors. The emissions 

reductions/increases achievable by these scenarios were compared to baseline. 
 6-17 July 2010 

Table 6-2. SO2 Post-Control Emission Ratesa

Control 

Scenario 

SO2

Control 

Technology 

SO2 NOX PM2.5 PM10 Organics 

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)b

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)b

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)c

Emissions 

(tons/year) 

% 

Reduction 

(Increase)e

Emissions 

(tons/year) 

% 

Reductio

(Increase

1 

3.0% 

Sulfur 

Coke with 

Potlines 

Wet 

Scrubber 

407 95.0 50.5 0 710 d c. 536 f e. 254 h G 

Current 

Potential 

Emissions 

2.0% 

Sulfur 

Coke 

Potlines 

4,052 50.5 777 d 398 f 292 h

aEmission rates include the potline primary control system and the potline roof emissions. bCompared with current potential emissions from the dry scrubbers, and excluding 127 tons/yr. from the roof vents. cBased on condensable PM10 removal listed in the 10/14/09 amendments letter for the #2 and 3 boiler scrubbers, i.e. 75%, the condensable inorganic 

emissions at the scrubber outlet will be 291 tons/yr. 39 tons/yr. will thus be solid PM2.5. The scrubber would add 194 tons of solid PM2.5 to what the fabric 

filter portion of the dry scrubber would remove. 

dIncludes 122 tons of inorganic condensables and 258 tons/yr. solid PM2.5 from the roof.eBased on information provided by the scrubber vendor, solid coarse PM will be 186 tons/yr. Includes 122 tons of inorganic condensables.fIncludes 350 tons/yr. solid PM10 from the roof.gBased on condensable PM10 removal measured at the Units 1,2,and 3 boiler scrubbers, i.e. 25%, or 116 tons/yr. for the captured emissions.hIncludes 138 tons/yr. of organic condensables from the roof vents.
 6-18 July 2010 

6.1.4 Evaluation of Costs and Other Impacts for Potline Feasible BART Control Options 

6.1.4.1 Cost Analysis for SO2 Wet Scrubber Control Options 

The exhaust gases from potlines 2, 5, and 6 are each routed to individual Alcoa A-398 

dry alumina reactors located in the courtyards between the potrooms or adjacent to the western 

most potroom. The exhaust gases from potlines 3 and 4 are routed to one GTC control system. 

 As stated previously, two vendors of this type of equipment provided control equipment 

quotes. One vendor provided preliminary equipment costs for two 100% wet scrubbers for 

potline # 2 and two 100% wet scrubbers for potlines # 3 - 6. The second vendor provided 

preliminary costs for two 100% wet scrubber systems for the potlines at a similar Alcoa facility – 

Tennessee Operations. This system was sized for a total flow rate of 1,920,000 acfm at 

Tennessee operations. For the purposes of this BART analysis, the information provided by the 

second vendor for the potlines at Alcoa – Tennessee Operations was scaled, based on exhaust gas 

volumes, to represent controls for Alcoa – Warrick Operations. Sodium-based scrubbers could 

also be used, but sodium is a less desirable reagent considering that these reagents are much 

more expensive. The high solubility of sodium compounds also would have higher solid and 

liquid waste disposal cost because there is no receiving stream near the Alcoa facility where 

sodium-containing wastewater could be discharged directly without pre-treatment. Other types of 

limestone-based scrubbers could also be used and costs for these systems would be similar. An 

advantage of the forced oxidation process is that the spent slurry is oxidized to gypsum, which 

dewaters more efficiently, resulting in less waste materials requiring disposal. Thus, a LSFO 

scrubber was determined to be the most appropriate control device for the cost analysis. 

 Neither of the two vendors provided a comprehensive installed cost estimate. Both 

preliminary designs were based on a central scrubbing center as the least cost approach, where 

exhaust from the alumina dry scrubbing systems would be ducted to a centralized scrubbing 

system. Both design estimates were based on systems that would provide 100% availability of 
 6-19 July 2010 

emissions control on each day of the year, given that potlines cannot be easily shutdown and 

restarted for control system outages. 

 One vendor provided an estimate of the scrubber equipment only. The other provided an 

“indicative price,” as an installed cost based on the scrubber equipment with installation assumed 

to be equal to the equipment cost. Important retrofit considerations are (1) that gases must be 

collected from individual dry reactor stacks, (2) the system must simultaneously maintain 

balanced flow from multiple potline control devices, and (3) the system installation would also 

require transport of new components through narrow passages in the existing potline. 

Coordination of the equipment delivery and the daily work schedule of the potline operation 

would also affect the control system installation. 

 One of the vendors recognized the complexity of this project, pointing out in their 

proposal that an extensive engineering effort was needed because of space limitations, access 

limitations, uncertainty as to laydown areas, and uncertainty of ductwork and supports. 

 For Alcoa’s BART determination, the factored cost procedures in the EPA Cost Manual 

(EPA 2002) were used to estimate an installed cost using the equipment costs provided by the 

vendors. The cost estimates are included in Appendix C. 

 Table 6-3 summarizes the cost of installing and operating a LSFO wet scrubber on the 

potlines to remove 95% of the SO2. The cost is based on an average of the two proposals. The 

capital and total annualized costs are high at >$300,000,000 and $55,000,000 per year, 

respectively. The wet scrubber cost effectiveness is also high at $15,000 per ton of SO2 removed, 

assuming use of coke with 3.0% sulfur. 
 6-20 July 2010 

Table 6-3. Summary of the Impacts Analysis for SO2 Control Scenarios 

Control 

Scenario 

Control 

Technology 

Evaluated 

Emission 

Rate 

(tons/year) 

Emissions 

Reductions 

(tons/year)a

Installed 

Capital 

Cost 

($000) 

Total 

Annualized 

Control 

Costs 

($000) 

Cost 

Effectiveness 

($ per ton of 

pollutant 

removed) 

Energy 

Impact 

(000 kWhour/ 

year) 

Collateral 

Increase 

in other 

Pollutants 

Non-Air 

Quality 

Environmental 

Impacts 

1 

3.0% Sulfur 

Coke with 

Potlines 

Wet 

Scrubber 

393 3,662 $305,000 $55,000 $15,000 41,800 PM2.5 58 

tons/year 

21,633 

tons/year of 

solid waste for 

disposal 

312 million 

gallons/year 

makeup water 

usage 

Current 

Potential 

Emissions 

2.0% 

Sulfur 

Coke 

Potlines

4,055 

6.1.4.2 Energy Impact Analysis 

 A wet scrubber removes SO2 by forcing the exhaust gas through a spray tower or 

absorber where it contacts water droplets that contain the unreacted lime or limestone. Energy is 

required to overcome the resistance of the scrubber components as well as falling water droplets. 

A substantial amount of energy is associated with a fan to move approximately 2,440,000 acfm 

through the scrubber. The fan alone would require 2,800 kW. Other energy is required for the 

slurry pumps, instrumentation, and miscellaneous items (e.g., lighting). The total energy 

required, based on an average of the two proposals, would be approximately 4,775 kW. As listed 

in Table 7, this is equivalent to 41,800,000 kW-hours of electricity per year. 

6.1.4.3 Non-Air Quality Environmental Impacts for Feasible Potline BART Control 

Options 

The two wet scrubber proposals were based on using limestone. This process oxidizes the 

spent slurry to gypsum, which may be landfilled or commercially sold. There is no way to know 

at this time whether the gypsum would have commercial value or whether there would be any 

demand for it. Therefore, it must be assumed that 21,600 tons of waste from the potlines wet 

scrubber would be landfilled each year. 
 6-21 July 2010 

 It is estimated that 312 million gallons of water will be required annually to operate the 

potline wet scrubber at a cost of $468,000. This will significantly impact the community 

infrastructure in that this will increase daily water demand. There will be relatively no impact 

due to water discharge, this being approximately 13 gallons/minute. 

 It is also estimated that 41 million kWh would be needed to operate the scrubbers 

annually. This would impact power demand on the current generating capacity and therefore also 

have an environmental impact due to power production equivalent to adding over 3,500 new 

households in the community. 

6.1.4.4 Remaining Useful Life 

 Alcoa has been in operation since 1960 when potline 1 and boiler unit # 1 were first 

brought on line. Alcoa has produced many different products for the construction, aerospace, 

military, consumer, and other markets. Since its inception, Warrick Operations has evolved into 

one of the most modern integrated aluminum production facilities in the world. The facility 

intends to be in operation throughout the period of the Regional Haze Program. 

6.2 Coal Fired Industrial Boiler Emission Controls

6.2.1 Potentially Applicable BART Control Options for Industrial Boilers 

6.2.1.1 Potentially Applicable SO2 Emission Controls for Industrial Boilers 

Sulfur in the coal burned to create steam in the boilers is released during the 

combustion process as SO2. 

6.2.1.1.1 Wet Scrubbing for Industrial Boilers 

 The primary development of SO2 control technology occurred because of the need to 

control emissions from the coal-fired, electric utility power industry (AWMA 2000). 

 The typical temperature range for wet scrubbers is 300–700°F. For utility combustion 

units, wet scrubbing systems have been installed on systems as large as 1,500 MW. Sodium 
 6-22 July 2010 

compounds, lime, or limestone can be used. However, the high solubility of sodium complicates 

disposal of waste and wastewater. The typical sorbent material is lime or limestone. Lime is 

generally easier to manage on-site but is significantly more costly. Wet limestone scrubbing has 

a high capital and operating cost due to the handling of liquid reagent and waste, but is the 

preferred process for coal-fired utility power plants burning coal due to the low cost of limestone 

and high removal efficiencies. Typical removal efficiencies are 80–95%. Approximately 85% of 

the flue gas desulfurization (FGD) systems installed in the United States are wet scrubber 

systems (EPA 2003c). 

 In wet scrubbers, the waste gas enters a large vessel (spray tower or absorber), where it is 

sprayed with water slurry. Figure 1, previously presented, is a simplified process flow diagram of 

a conventional wet scrubber. 

 The calcium in the slurry reacts with SO2 to form CaSO3. A portion of the slurry from the 

reaction tank is pumped into the thickener, where the solids settle before going to a filter for final 

dewatering to about 50% solids. In the utility industry, the CaSO3 waste product is usually mixed 

with fly ash (approximately 1:1) and fixative lime (approximately 5%) and typically disposed of 

in landfills. Alternately, the forced oxidation process oxidizes the spent slurry to gypsum. 

Gypsum crystals dewater more efficiently and reduce the size of waste handling equipment. 

Depending on quality and demand, the gypsum may be commercially sold, eliminating the need 

for landfilling the waste product. 

 Note that “mist eliminators,” installed at the spray tower outlet or downstream ductwork, 

remove droplets from the gas. In some power plant installations, the gas is reheated to avoid 

corrosion downstream. Many scrubbers have gas bypassing capability, which can be used for gas 

reheating. If the wet scrubber is downstream of a high-efficiency particulate removal device 

[fabric filter or electrostatic precipitator (ESP)], the particulate concentration may be higher 

leaving the scrubber than entering due to the solids in mist droplets that are carried out of the 

scrubber. 
 6-23 July 2010 

 Some disadvantages of using wet scrubbing techniques in many applications are the 

requirement to treat wastewater, components must be constructed from expensive alloys to resist 

corrosion, and energy use is much higher. A practical issue associated with a wet scrubber 

system is the complexity of the system. The space required for a wet system is substantial (i.e., 

large footprint), the systems require more maintenance due to their complexity, and more 

personnel are required for their operation. 

6.2.1.1.1.1 Seawater Scrubbing 

Seawater scrubbing has also been implemented in the coal fired power industry, most 

recently at the Mawan Power Station in China and the Paiton Project in Indonesia. Seawater, 

which has a natural alkalinity, is pumped directly into a scrubbing tower through a system of 

spray nozzles where the atomized droplets make contact with the effluent gas stream. The liquid 

effluent is discharged back into the ocean. Seawater scrubbing was automatically rejected as 

infeasible because of Alcoa’s physical location. 

6.2.1.1.1.2 Limestone Slurry Forced Oxidation 

Limestone slurry forced oxidation (LSFO) is used extensively in the utility flue gas 

desulphurization market. The raw material is finely ground limestone. There are a number of 

suppliers of LSFO technology. The most commonly used equipment is an open, multi-level, 

countercurrent spray tower scrubber equipped with spray nozzles to inject the limestone slurry 

droplets into the gas stream. Liquor is collected at the bottom of the tower and sparged with air 

to oxidize the calcium sulfite to calcium sulfate to enhance the settling properties of the calcium 

sulfate. Recirculation pumps circulate the scrubbing liquor to the spray nozzles. SO2 removal 

efficiencies of 90% have been achievable. The bleed from the scrubber is sent to a dewatering 

system to remove excess moisture. For a coal fired boiler, the process will produce either solid 

gypsum waste or commercial-grade gypsum suitable for reuse as a cement additive. Only a very 

small purge or blowdown stream is required. 
 6-24 July 2010 

 LSFO was determined to be a technically feasible retrofit control option for the coal fired 

boilers. 

6.2.1.1.1.3 Limestone Slurry Natural Oxidation 

 Limestone slurry natural oxidation (LSNO) is very similar to LSFO. The major 

difference is the absence of an oxidation stage. The gypsum/calcium sulfite product is essentially 

a waste product with limited possibilities of being used for agricultural purposes. 

6.2.1.1.1.4 Conventional Limestone Wet Scrubbing 

 Conventional lime wet scrubbing is also similar to LSFO except that the raw material is 

hydrated lime or quick lime that is either slaked on-site or purchased in the slaked form. The 

system typically uses forced oxidation, although natural oxidation is possible. The process will 

produce either solid gypsum waste or commercial-grade gypsum suitable for reuse as a cement 

additive. 

6.2.1.1.1.5 Dual Alkali Sodium/Lime Scrubbing (Dilute Mode) 

 Dual alkali sodium/lime scrubbing (dilute mode) uses a caustic sodium solution in the 

scrubber tower. A portion of the scrubbing liquid is discharged to a neutralization stage where 

lime slurry is used to regenerate the caustic, which is returned to the scrubber. The bleed from 

the scrubber is sent to a dewatering system to produce a gypsum byproduct. The process will 

produce either solid gypsum waste or commercial-grade gypsum suitable for reuse as a cement 

additive. It should be noted, however, that dual alkali sodium/lime scrubbing (dilute mode) is not 

marketed today by major FGD vendors because the system is too complicated and expensive. 
 6-25 July 2010 

6.2.1.1.1.6 Conventional Sodium Scrubbing 

 This technology has been successfully utilized in the power industry. An alkaline solution 

of either soda ash or sodium hydroxide is pumped into the scrubbing tower and recirculated 

through a network of spray nozzles. Atomized droplets contact the up-flowing gas containing 

SO2. Where this technology has been deployed, the liquid effluent containing dissolved salts, 

including sodium and fluorides, has been discharged into a large receiving stream or an open 

body of water without treatment. 

6.2.1.1.2 Dry Scrubbing for Industrial Boilers 

6.2.1.1.2.1 Dry Injection 

 In dry injection, a reactive alkaline powder is injected into a furnace, ductwork, or a dry 

reactor. Typical removal efficiencies with calcium adsorbents are 50–60% and up to 80% with 

sodium base adsorbents. However, as with wet scrubbing, disposal of waste using sodium 

adsorbents must consider their high solubility in water compared to those from calcium 

adsorbents. The temperature range where dry scrubbing has been used is 300–1,800°F; the 

minimum temperature is 300–350°F. Dry systems are rarely used and according to EPA only 3% 

of FGD systems installed in the United States are dry systems (EPA 2003c). The dry waste 

material is removed using particulate control devices such a fabric filter or an ESP. 

 

6.2.1.1.2.2 Semi-dry Scrubbing (Spray Dryer) 

 Semi-dry scrubbing is more commonly referred to as spray drying. Calcium hydroxide 

slurry (lime mixed with water) is introduced into a spray dryer tower. Sodium compounds can be 

used, but as with the dry scrubber, the high solubility of the sodium-based waste products in 

water complicates disposal of the waste. The slurry is atomized and injected into a reactor with 

the exhaust gases, where droplets react with SO2 as the liquid evaporates. This system is 
 6-26 July 2010 

categorized as a semi-dry system because the end product of the SO2 conversion reaction is a dry 

material. The dry waste product is collected in the bottom of the spray dryer reactor, and a fabric 

filter or ESP downstream of the spray dryer removes the CaSO3, CaSO4, and unreacted lime. 

This air pollution control system uses water for evaporative cooling and for the SO2 reaction. It 

operates in a temperature range of 300–350°F because the temperature of the gases must be high 

enough to evaporate the water portion of the slurry. Approximately 12% of the FGD systems 

installed in the United States are spray dry systems (EPA 2003c) with typical SO2 removal 

efficiencies in the range of 80–90%. Unlike a wet scrubbing system there is no liquid blow-down 

stream from the dry system, and the collected solids are typically landfilled. 

6.2.1.1.3 Pollution Prevention for Industrial Boilers 

Several techniques may be used to reduce SO2 emissions from coal combustion. One 

way is to switch to lower sulfur coals, since SO2 emissions are proportional to the sulfur content 

of the coal. This alternative may not be possible where lower sulfur coal is not readily available 

or where a different grade of coal cannot be satisfactorily fired. In some cases, various coal 

cleaning processes may be employed to reduce the fuel sulfur content. Physical coal cleaning 

removes mineral sulfur such as pyrite but is not effective in removing organic sulfur. Chemical 

cleaning and solvent refining processes are being developed to remove organic sulfur. 

It is not reliably known what the sulfur content of coals will be that are available to Alcoa 

in the future. Low sulfur coals are currently in demand as utilities comply with Acid Rain Rules 

and other Federal and State programs. Availability has decreased and cost has increased. Since 

Alcoa intends to operate the Warrick facility throughout the period of the Regional Haze 

Program, it is not feasible to rely on the long-term availability of low sulfur coals. Use of lowsulfur coals was rejected as a BART option. 
 6-27 July 2010 

6.2.1.1.4 Industrial Boiler SO2 Control Options from RBLC Database 

A review or EPA’s RACT/BACT/LAER Clearinghouse (RBLC) database was also 

completed to determine which control technologies or techniques have been utilized by industrial 

boilers. Results from searching the RBLC are summarized in Table 6-4.
 6-28 July 2010 

Table 6-4. RBLC Database Search Results for SO2 Control Industrial Boilers 

RBLC ID Facility Last Update Process Control Option ND-0021 GASCOYNE GENERATING STATION 8/16/2005 BOILER, COAL-FIRED LIMESTONE INJECTION WITH A SPRAY DRYER. NV-0036 TS POWER PLANT 8/31/2006 200 MW PC COAL BOILER LIME SPRAY SPRAY DRY SCRUBBER MO-0071 KANSAS CITY POWER & LIGHT COMPANY - IATAN STATION 5/7/2007 PULVERIZED COAL BOILER - UNIT 2 

KCPL SHALL INSTALL SCR UNIT FOR THE UNIT 2 BOILER NOX EMISSIONS AND ALSO SHALL INSTALL WET SCRUBREDUCE SOX EMISSIONS. BOTH CONTROLS ARE NOT BAND SOX 

NE-0031 OPPD - NEBRASKA CITY STATION 8/30/2006 UNIT 2 BOILER DRY FLUE GAS DESULFURIZATION & FABRIC FILTER MO-0060 CITY UTILITIES OF SPRINGFIELD - SOUTHWEST POWER STATION 3/8/2007 PULVERIZED COAL FIRED BOILER DRY FLUE GAS DESULFURIZATION > 90% UT-0053 DESERET GENERATION AND TRANSMISSION COMPANY 12/18/2001 COAL FIRED BOILER WET SCRUBBER UT-0065 INTERMOUNTAIN POWER GENERATING STATION - UNIT #3 3/22/2006 PULVERIZED COAL FIRED ELECTRIC GENERATING UNIT WET FLUE GAS DESULPHURIZATION, LOW SULFER COAWI-0228 WPS - WESTON PLANT 8/31/2006 SUPER CRITICAL PULVERIZED COAL ELECTRIC STEAM BOILER (S04, P04) DRY FGD, LIMIT ON EMISSIONS ENTERING CONTROL SY

LBS/MMBTU 30 DAY AVG. 

MO-0071 KANSAS CITY POWER & LIGHT COMPANY - IATAN STATION 5/7/2007 PULVERIZED COAL BOILER - UNIT 1 WY-0057 WYGEN 2 9/23/2003 BOILER, 500 MW PC SEMI-DRY LIME SPRAY DRYER ABSORBER KS-0026 HOLCOMB UNIT #2 1/16/2004 BOILER, PULVERIZED COAL DRY FLUE GAS DESULFURIZATION NE-0018 WHELAN ENERGY CENTER 8/10/2004 BOILER, UNIT 2 UTILITY SPRAY DRYER ABSORBER (SDA) SC-0104 SANTEE COOPER CROSS GENERATING STATION 8/31/2006 BOILER, NO. 3 AND NO. 4 FLUE GAS DESULFURIZATION (WET SCRUBBING) MT-0027 HARDIN GENERATOR PROJECT 7/1/2004 BOILER, PULVERIZED COAL-FIRED WET VENTURI SCRUBBER PA-0183 AES BEAVER VALLEY, LLC 9/4/2003 COAL FIRED BOILER HYDRATED ASH RE-INJECTION SYSTEM AR-0074 PLUM POINT ENERGY 3/2/2004 BOILER , UNIT 1 - SN-01 DRY FLUE GAS DESULFURIZATION AR-0079 PLUM POINT ENERGY 5/2/2006 BOILER - SN-01 DRY FLUE GAS DESULFURIZATION VA-0296 VIRGINIA TECH 2/7/2006 OPERATION OF BOILER 11 DRY SCRUBBER FLUE GAS DESULFURIZATION SYSTEM KY-0084 THOROUGHBRED GENERATING STATION 8/30/2006 BOILER, COAL, (2) WET FLUE GAS DESULFURIZATION (FGD), WESP, AND P

DESIGN 

WY-0039 

TWO ELK GENERATION PARTNERS, LIMITED PARTNERSHIP 

3/11/2004 BOILER, STEAM ELECTRIC POWER GENERATING LIME SPRAY DRY SCRUBBER 

PA-0162 EDISON MISSION ENERGY 6/12/2006 BOILER, COAL, PULVERIZED BITUMINOUS, UNIT 3 WET LIMESTONE SCRUBBER VA-0268 THERMAL VENTURES 9/5/2003 BOILER, STEAM GOOD COMBUSTION PRACTICES, CLEAN BURNING FUE

CONTINUOUS EMISSION MONITORING DEVICE. 

OH-0314 SMART PAPERS HOLDINGS, LLC 4/29/2008 PULVERIZED DRY BOTTOM BOILER LA-0122 MANSFIELD MILL 3/17/2005 POWER BOILER #1 & #2, COMBINED FUEL LIMIT SULFUR CONTENT OF FUEL NOTES: The RBLC search was performed for industrial coal-fired boilers with capacities greater than 250 MMBtu/hr. Facilities that operate circulating fluidized bed boilers were not includstill under construction were also excluded from the search results. 
 6-29 July 2010 

Twenty-four units were identified in the RBLC database that could be consider similar to 

the boiler units at Alcoa. Of these 24 units, approximately half utilized a form of dry flue gas 

desulfurization to control SO2 emissions, seven used wet scrubbing to control SO2 emissions, 

and the remaining units used other means such as low sulfur coal and good combustion practices. 

Of the 24 units in the database, 10 listed an SO2 removal efficiency in the range of 90% to 95% 

with an average of 91.8%. 

Both wet scrubbing and dry scrubbing have been considered BACT for SO2. 

6.2.1.2 Potentially Applicable BART Control Options for PM 

The Indiana CAIR rules do not remove utility boilers from the requirement to perform a BART 

analysis for PM control. Industrial boilers 2 and 3 are also subject to PM BART. The sections 

that follow for PM are applicable for boilers 2, 3, and 4. 

6.2.1.2.1 Fabric Filters 

 Fabric filters generally provide high collection efficiencies for both coarse and fine 

(submicron) particles. They are relatively insensitive to fluctuations in gas stream conditions. 

Efficiency is relatively unaffected by large changes in inlet dust loadings. Filter outlet air is very 

clean (EPA 2003b). Collected material is dry, which usually simplifies processing or disposal. 

6.2.1.2.2 Electrostatic Precipitators 

 ESPs are capable of very high removal efficiencies for large and small particles (EPA 

2003a). They offer control efficiencies that are comparable to fabric filters. Because of their 

modular design, ESPs, like fabric filters, can be applied to a wide range of system sizes. The 

operating parameters that influence ESP performance include fly ash mass loading, particle size 

distribution, fly ash electrical resistivity, and precipitator voltage and current. Dusts with high 

resistivities are not well-suited for collection in dry ESPs because the particles are not easily 

charged. This also affects the ash layers on the collecting electrodes. 
 6-30 July 2010 

6.2.1.2.3 Cyclones, Inertial Separators, and Wet Scrubbers 

 Cyclones and inertial separators are used for collection of medium-sized and coarse 

particles. Wet scrubbers generally remove large particles but can remove small particles with the 

use of high pressure drops. However, none of these devices are as effective at removing small 

and submicron particles as fabric filters and ESPs (AWMA 2000). 

6.2.1.3 Potentially Applicable BART Control Options for NOx

Combustion controls and post-combustion controls are the two potential ways to reduce 

NOx emissions from industrial coal-fired boilers. Combustion control methods seek to suppress 

the formation of NOx during the combustion process by controlling the flame temperature and 

the fuel/oxygen ratio. Combustion control methods typically include low NOx burners (LNBs), 

overfire air (OFA), combustion optimization, and natural gas reburn. Post-combustion controls 

capture a portion of the NOx after formation. Post-combustion controls typically include 

selective non-catalytic reduction (SCR) and selective catalytic reduction systems (SCR). 

Technologies such as Mobotec and NOXStar are also examples of emerging post-combustion 

control technologies. Post-combustion NOx control technologies use either ammonia or urea as a 

reagent. The SCR technology also requires multiple layers of reduction catalyst. Seven different 

NOx control options were considered as having potential practical application as part of the 

BART analysis. 

 Low NOx Burners 

 Natural Gas Reburn 

 Combustion Optimization (Neural Network) 

 Selective Non-catalytic Reduction (SNCR) 

 SNCR/SCR Hybrid (Cascade Process) 

 Selective Catalytic Reduction (SCR) 

 Mobotec ROFA/ROTAMIX 
 6-31 July 2010 

 Mitsui Babcock NOXStar 

For this BART analysis, emphasis was placed on evaluating technically proven and 

commercially available NOx control technologies. The Mobotec ROFA/ROTAMIX, the Mitsui 

Babcock NOXStar, and the SNCR/SCR Hybrid systems are considered emerging postcombustion control technologies and have a limited number of installations in operation in the 

U.S. Natural gas reburn technology requires sufficient residence time (adequate furnace height) 

to successfully reduce NOx; therefore, it is difficult to use as a retrofit technology in existing 

coal-fired boilers. Combustion optimization is also limited in effectiveness in a retrofit case 

depending on how well the existing boilers are operated and maintained. The commercially 

proven NOx control technologies evaluated in the BART analysis include LNB with OFA, 

SNCR, and SCR systems. 

6.2.1.3.1 Low NOx Burners& Overfire Air 

LNBs limit NOx formation by controlling the stoichiometric and temperature profiles of the 

combustion process in each burner zone. The unique design of features of an LNB may create (1) a 

reduced oxygen level in the combustion zone to limit fuel NOx formation, (2) a reduced flame temperature 

that limits thermal NOx formation, and/or (3) a reduced residence time at peak temperature which also 

limits thermal NOx formation. 

LNBs are applicable to tangential and wall-fired boilers of various sizes but are not applicable to 

other boiler types such as cyclone furnaces or stokers. They have been used as a retrofit NOx control for 

existing boilers and can achieve approximately 35 to 55 percent reduction from uncontrolled levels. They 

are also used in new boilers to meet New Source Performance Standards (NSPS) limits. LNBs can be 

combined with OFA to achieve even greater NOx reduction (40 to 60 percent reduction from uncontrolled 

levels).
 6-32 July 2010 

6.2.1.3.2 Selective Non-Catalytic Reduction 

 SNCR is an add-on technique that involves injecting ammonia or urea into a specific 

temperature zone in a furnace or boiler. The ammonia or urea reacts with NOx in the gas to 

produce nitrogen and water. SNCR typically provides 30–50% NOx reduction. The effectiveness 

of SNCR depends on the temperature where reagents are injected, mixing of the reagent in the 

gas, residence time of the reagent within the required temperature window, and the ratio of 

reagent to NOx. The required temperature window is 1,600–2,100°F. The furnace of a pulverized 

coal fired boiler operates at temperature between 2,500 and 3,000 OF. Therefore, the optimum 

temperature window at Warrick will most likely occur somewhere at the top of the furnace and 

in the forward section of the pendent area backpass. Typical uncontrolled NOx levels where this 

technology has been applied vary from 200 to 400 ppm. SNCR is less effective at lower levels of 

uncontrolled NOx (EPA 2003e). 

SNCR systems are capable of achieving a NOx emission reduction as high as 50 to 60 

percent in optimum conditions (adequate reaction time, temperature, and reagent/flue gas 

mixing; high baseline NOx conditions; and multiple levels of injectors) with ammonia slips of 10 

to 50 ppmvd. Lower ammonia slip values can be achieved with lower NOx reduction 

capabilities. Typically, optimum conditions are difficult to achieve, resulting in emission 

reduction levels of 20 to 40 percent. Potential performance is very site-specific and varies with 

fuel type, steam generator size, allowable ammonia slip, furnace CO concentrations, and steam 

generator heat transfer characteristics. Due to the low inlet NOx conditions of the Warrick units 

and small boiler height, an SNCR system is expected to only achieve around 20 to 25 percent 

reduction, while maintaining an ammonia slip of 2 ppmvd to 5 ppmvd. As the ammonia slip 

value is controlled closer to 2 ppmvd, then the NOx reduction efficiency will be 20 percent or 

less. 

SNCR systems reduce NOx emissions using the same reduction mechanism as SCR 

systems. Most of the undesirable chemical reactions occur when a reagent is injected at 

temperatures above or below the optimum range. At best, these undesired reactions consume 

reagent with no reduction in NOx emissions while, at worst, the oxidation of ammonia can 
 6-33 July 2010 

actually generate NOx. Accordingly, NOx reductions and overall reaction stoichiometry are very 

sensitive to the temperature of the flue gas at the reagent injection point. This complicates the 

application of SNCR for boilers larger than 50 to 100 MW. 

Reagent injection lances are usually located between the boiler soot blowers in the 

pendent superheat section. Optimum injector location is mainly a function of temperature and 

residence time. To accommodate SNCR reaction temperature and boiler turndown requirements, 

several levels (four to five) of injection lances are normally installed if sufficient boiler height 

and residence time is available. It is estimated that only one level of nozzles would be installed 

for the Warrick units due to design limitations. A second level of multiple lance nozzles could 

be installed in the boiler backpass for a 5 to 10 percent increase in NOx removal capability, but 

the capital cost increases significantly and there is potential that ammonia slip would exceed 5 

ppmvd. 

A flue gas residence time of at least 0.3 seconds in the optimum temperature range is 

desired to ensure adequate SNCR performance. Residence times in excess of 1 second yield 

high NOx reduction levels, even under less than ideal mixing conditions. 

Both ammonia- and urea-based SNCR processes typically require three to eight times the 

theoretical amount of reagent to achieve NOx reductions, as compared to SCR systems. 

Considering that aqueous ammonia cost about $100/ton and urea costs about $280/ton, there is a 

significant economic consideration in selecting a suitable reagent. The increased reagent 

consumption is due to reagent thermal decomposition, varying temperature, and the lack of a true 

steady-state controlled environment, which tends to increase ammonia slip emissions. Even with 

best efforts (multiple levels of injection, conscientious operator attention, etc.) ammonia slip 

emissions from SNCR systems will be highly variable during load changes. This can result in 

excess or inadequate reagent injection, the increased potential for exceeding allowable NOx

emission limits, or increased ammonia slip with associated air heater pluggage and fly ash 

contamination. 
 6-34 July 2010 

The use of anhydrous ammonia would require the same safety systems, storage tanks, and 

vaporizers as those required for SCR systems. A urea-based process would have a pumping skid 

in lieu of a vaporizer or blower. The urea is pumped and injected as a liquid (typically a 50:50 

solution of urea and water). The 50:50 solution is further diluted, prior to injection, by mixing it 

with either steam or air. These high-pressure gases act as the carrier gas as well as providing the 

pressure drop that leads to atomization upon injection into the boiler. If steam is used, there may 

be an impact to the boiler heat rate. If air is used, an air compressor is usually required to 

provide adequate constant supply of high-pressure flow. 

6.2.1.3.3 Selective Catalytic Reduction 

 SCR is an add-on technique similar to SNCR that involves injecting ammonia into flue 

gas in the presence of a metal-based catalyst to convert NOx emissions to elemental nitrogen and 

water. The catalyst allows SCR systems to operate at much lower temperatures than SNCR; 

typical temperatures for SCR are 500–800°F, compared with 1,600–2,100°F for SNCR. The 

optimum temperature range is 700–750°F (EPA 2002). SCR is capable of NOx reduction 

efficiencies in the range of 70–90% and can be used with NOx concentrations as low as 20 ppm. 

However, higher NOx levels result in increased performance (EPA 2003d). 

Current U.S. SCR experience demonstrates that a coal fired boiler can be retrofitted with 

an SCR; however, oxidation of SO2 to SO3 could require moderate air heater modifications since 

the acid dew point temperature of the flue gas is directly related to SO3 concentrations. As the 

SO3 concentration increases, the acid dew point of the flue gas increases, potentially increasing 

corrosion in downstream equipment or possibly requiring an increase in the air heater gas outlet 

temperature. The undesired reactions described cannot be eliminated completely. However, 

prudent design and appropriate operation can minimize the effect of the SCR system on the 

existing plant. These design considerations have some impact on the capital cost of an SCR 

system. Limiting the ammonia slip to a level that avoids air heater washing and contamination 

of the fly ash is very important. Long-term operations experience has shown that a level of 2 to 

3 ppmvd ammonia slip is appropriate when burning most coal types. 
 6-35 July 2010 

The ammonia injection rate is controlled by the inlet NOx concentration, flue gas flow 

rate, and outlet NOx emission rate. The ammonia injection rate is based on stoichiometric ratio, 

typically very close to 1.0. 

The SCR reactor is the housing for the catalyst. The reactor is basically a widened 

section of ductwork modified by the addition of catalyst, catalyst support structures, access 

doors, and soot blowers. SCR systems have been installed in three different arrangements, highdust, low-dust, and tail-end. In a high-dust arrangement, the catalyst is located between the 

outlet of the economizer and the inlet of the air heater. A low-dust arrangement typically 

positions the catalyst between the outlet of a hot-side electrostatic precipitator and the inlet of the 

air heater; however, the catalyst could be positioned at the outlet of a cold-side precipitator with 

supplemental heating of the flue gas. In a tail-end arrangement, the catalyst is located between 

the outlet of a flue gas desulfurization system and upstream of the stack which also requires 

supplemental heating of the flue gas. Most installations in the U.S. have been the high-dust 

arrangement which, in most circumstances, is the most economical arrangement alternative. The 

Warrick units employ a cold side ESP for particulate control and there is adequate space between 

the ESP and the air heater inlet; therefore, the low-dust arrangement is the most feasible 

arrangement. 

The ammonia reagent for the SCR systems can be supplied by anhydrous ammonia, a 19 

or 29 percent aqueous ammonia/water solution, or by conversion of urea to ammonia. Since the 

ammonia is vaporized prior to contact with the catalyst, the selection of ammonia type does not 

influence the catalyst performance. However, the selection of ammonia type does affect all other 

subsystem components, including reagent storage, vaporization, injection control, and balanceof-plant requirements. The majority of worldwide installations use anhydrous ammonia. 
 6-36 July 2010 

6.2.1.3.4 Industrial Boiler NOx Control Options from RBLC Database 

A review or EPA’s RACT/BACT/LAER Clearinghouse (RBLC) database was also 

completed to determine which control technologies or techniques have been utilized by industrial 

boilers. Results from searching the RBLC are summarized in Table 6-5.
 6-37 July 2010 

Table 6-5. RBLC Database Search Results for NOX Control Industrial Boilers 

RBLC ID Facility Last Update Process Control Option 

NV-0036 TS POWER PLANT 8/31/2006 200 MW PC COAL BOILER SCR & LOW NOX BURNERS 

UT-0065 INTERMOUNTAIN POWER GENERATING STATION - UNIT #3 3/22/2006 PULVERIZED COAL FIRED ELECTRIC GENERATING UNIT LOW NOX BURNERS, OVER FIRE AIR, SCR 

WI-0228 WPS - WESTON PLANT 8/31/2006 SUPER CRITICAL PULVERIZED COAL ELECTRIC STEAM BOILER (S04, P04) LOW NOX BURNERS, GOOD COMBUSTION PRACTICES S

CATALYTIC REDUCTION (SCR) 

NE-0031 OPPD - NEBRASKA CITY STATION 8/30/2006 UNIT 2 BOILER SELECTIVE CATALYTIC REDUCTION (SCR) 

WY-0057 WYGEN 2 9/23/2003 BOILER, 500 MW PC LOW NOX BURNERS/SCR 

OK-0118 HUGO GENERATING STA 9/27/2007 COAL-FIRED STEAM EGU BOILER (HU-UNIT 2) LOW NOX BURNERS (LNB) W/ OVERFIRE AIR (OFA) AND 

CATALYTIC REDUCTION (SCR) 

SC-0104 SANTEE COOPER CROSS GENERATING STATION 8/31/2006 BOILER, NO. 3 AND NO. 4 LOW NOX BURNERS AND SCR 

MO-0060 CITY UTILITIES OF SPRINGFIELD - SOUTHWEST POWER STATION 3/8/2007 PULVERIZED COAL FIRED BOILER 

IT WAS DETERMINED THAT THE BACT FOR NOX FROM TPULVERIZED COAL FIRED BOILER IS GOOD COMBUSTIOALONG WITH SCR HAVING A NOX EMISSION LIMIT OF 0.ON A 30-DAY ROOLING AVERAGE. 

KY-0084 THOROUGHBRED GENERATING STATION 8/30/2006 BOILER, COAL, (2) PROPER BOILER DESIGN, LOW NOX BURNERS, AND SC

MO-0071 KANSAS CITY POWER & LIGHT COMPANY - IATAN STATION 5/7/2007 PULVERIZED COAL BOILER - UNIT 2 

KCPL SHALL INSTALL SCR UNIT FOR THE UNIT 2 BOILER NOX EMISSIONS AND ALSO SHALL INSTALL WET SCRUBREDUCE SOX EMISSIONS. BOTH CONTROLS ARE NOT BAND SOX 

NE-0018 WHELAN ENERGY CENTER 8/10/2004 BOILER, UNIT 2 UTILITY SELECTIVE CATALYTIC REDUCTION 

MT-0027 HARDIN GENERATOR PROJECT 7/1/2004 BOILER, PULVERIZED COAL-FIRED SELECTIVE CATALYTIC REDUCTION 

AR-0074 PLUM POINT ENERGY 3/2/2004 BOILER , UNIT 1 - SN-01 LOW NOX BURNERS AR-0079 PLUM POINT ENERGY 5/2/2006 BOILER - SN-01 LOW NOX BURNERS 

MO-0071 KANSAS CITY POWER & LIGHT COMPANY - IATAN STATION 5/7/2007 PULVERIZED COAL BOILER - UNIT 1 

KS-0026 HOLCOMB UNIT #2 1/16/2004 BOILER, PULVERIZED COAL SCR, LOW NOX BURNERS, SEPARATED OVERFIRE AIR (PA-0162 EDISON MISSION ENERGY 6/12/2006 BOILER, COAL, PULVERIZED BITUMINOUS, UNITS 1, 2 &3 SCR. SEE COMMENT ABOUT NOX EMISSION LIMITS IN F

REGULATORY BASIS IS STATE IMPLEMENTATION PLAN

WY-0039 TWO ELK GENERATION PARTNERS, LIMITED PARTNERSHIP 3/11/2004 BOILER, STEAM ELECTRIC POWER GENERATING LOW NOX BURNERS WITH OVER FIRE AIR AND SELECT

REDUCTION 

VA-0296 VIRGINIA TECH 2/7/2006 OPERATION OF BOILER 11 EMISSIONS CONTROLLED BY A MASS-FEED STOKER CO

WITH LOW EXCESS AIR/STAGED COMBUSTION 

TX-0489 SOUTHWESTERN PUBLIC SERVICE COMPANY- HARRINGTON STATION 3/20/2007 UNIT 3 BOILER LOW NOX BURNERS, SEPARATED OVERFIRE AIR WINDB

ADDITIONAL YAW CONTROL OF THE BURNERS FOR ADCONTROL 

VA-0268 THERMAL VENTURES 9/5/2003 BOILER, STEAM GOOD COMBUSTION PRACTICES, CLEAN BURNING FUE

CONTINUOUS EMISSION MONITORING DEVICE. 

PA-0176 ORION POWER MIDWEST LP 8/15/2006 BOILERS, COAL (3) OVERFIRE AIR, LOW NOX BURNERS UT-0053 DESERET GENERATION AND TRANSMISSION COMPANY 12/18/2001 COAL FIRED BOILER BOILER DESIGN 

NOTES

The RBLC search was performed for industrial coal-fired boilers with capacities greater than 250 MMBtu/hr. Facilities that operate circulating fluidized bed boilers were not included in the search. Fa

search results. No facilities with SNCR controls were found in the RBLC database using this search criterion. 
 6-38 July 2010 

Twenty-three units in the RBLC database were identified as potentially similar to Alcoa’s 

boiler units. The NOx control technologies used on these units included boiler design, low NOx 

burners, low NOx burners combined with over-fire air, SCR, and a combination of low NOx 

burners, over-fire air and SCR. Each of these technologies or a combination of these 

technologies were considered BACT for NOx. 

 

6.2.2 Summary of Technically Feasible BART Control Options for Industrial Boilers 

6.2.2.1 Feasible BART Control Options for Industrial Boiler SO2

One technically feasible option was identified for controlling SO2 emissions from the 

industrial boilers. This option includes installation of wet scrubbers and was evaluated further as 

part of the BART determination analysis. 

6.2.2.2 Feasible BART Control Options for Industrial and Utility Boiler PM 

While fabric filters would be considered a technically feasible option for controlling 

particulate emissions from the boilers 2, 3, and 4 at Alcoa – Warrick, these units currently have 

cold-side ESPs. Baseline modeling results indicate that modeled or projected visibility impact at 

MCNP associated with particulate and organic emissions combined from coal fired boiler units 2,3, 

and 4 was less than 0.06 dv. Based on these data, adding additional pollution controls for PM will 

not significantly reduce the already very low visibility impact due to units 2, 3 and 4 at Alcoa – 

Warrick. For this reason, no additional analysis associated with PM controls on these units was 

performed for this BART analysis. 

6.2.2.3 Feasible BART Control Options for Industrial Boiler NOx

Combustion control options that were determined to be feasible for NOx control on units 

2 and 3 include low NOx burners and overfire air. The post-combustion controls that were 

determined to be feasible for NOx control on units 2 and 3include SCR and SNCR. During 

portions of the baseline years 2001 through 2003, units 2 and 3 had no controls for NOx. 
 6-39 July 2010 

6.2.3 Control Effectiveness for Feasible BART Control Options for Industrial Boilers 

Step 3 of the BART analysis is to evaluate the control effectiveness of the technically 

feasible control technologies. 

6.2.3.1 Control Effectiveness for Industrial Boiler SO2

6.2.3.1.1 SO2 Wet Scrubbing 

Wet scrubbers were identified as a technically feasible add-on pollution control options to 

reduce SO2 from boiler units 2 and 3. Typical removal efficiencies are 80–95%. 

 Table 6-6 summarizes the SO2 emission levels under the control scenarios considered for 

BART. The emissions represent the combined total emissions from units 2 and 3 for each 

scenario. Control Scenario 1 is the utilization of two wet scrubbers to control SO2 emissions 

from each of units 2 and 3. The emissions reductions achievable by wet scrubbing at these units 

were compared to baseline. Pursuant to 326 IAC 7-4-10 (Warrick County Sulfur Dioxide 

Emission Limitations), SO2 emission limits were established for units 2 and 3 that resulted in an 

allowable SO2 emission rate of 5.11 lbs. /mm Btu. By virtue of Units 2 and 3 being modified to 

increase their heat input capacity, they have become subject to 40 CFR Subpart Db, and must 

meet a minimum SO2 removal efficiency of 90%. Based on the RBLC database analysis, which 

indicated an average control efficiency of 91.8% was BACT for SO2 from industrial boilers, and 

Standards of Performance for Industrial-Commercial-Institutional Steam Generating Units (40 

CFR 60 Subpart Db) requires a 92% removal efficiency for this type of source, if reconstructed, 

it was determined that 92% efficiency would be reasonable for units 2 and 3. (The NSPS 

provides an optional SO2 removal requirement of 90% minimum if the units are only modified.). 

 In the December, 2008 BART determination, SO2 and NOx emissions from utility boiler 

4 were also included. Since that time, it has been determined that utility boilers meet the BART 
 6-40 July 2010 

requirements for these pollutants by virtue of their required participation in the Indiana Clean Air 

Interstate Rule. PM emissions from utility boiler 4 remain subject to the BART analysis 

requirements. Table 6-6A shows post control PM emissions from boiler 4. 

Current potential emissions are based the highest 24 hour emission rate measured by the 

CEM systems on units 2 and 3. 

6.2.3.2 Control Effectiveness for Industrial Boiler NOx

Low NOx burners combined with overfire air were identified as feasible combustion 

control options to reduce NOx emissions from units 2 and 3. SCR and SNCR were determined 

to be feasible post-combustion NOx control options for units 2 and 3. 

 Table 6-7 summarizes the NOx emission levels under the control scenarios considered for 

BART. 
 6-41 July 2010 

Table 6-6. SO2 Post-Control Emission Rates

Control 

Scenario 

SO2

Control 

Technology 

SO2 NOX PM2.5 PM10 Organics 

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/year) 

% 

Reduction 

(Increase)a

Emissions 

(tons/year) 

% 

Reductio

(Increase

1 

Wet 

Scrubber on 

each of 

units 2 and 

3 

4,497 

92.0b 

9,551 

0 564 63.7 0 0 84 75.0 

Current 

Potential 

Emissions 

 56,215 9,551 1,552 0 334 

aCompared with current potential emissions. bBased on 92% removal efficiency on units 2 and 3. 

Table 6-6A. PM Post-Control Emission Rates for Utility Boiler 4

Control 

Scenario 

SO2

Control 

Technology 

SO2 NOX PM2.5 PM10 Organics 

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/year) 

% 

Reduction 

(Increase)a

Emissions 

(tons/year) 

% 

Reductio

(Increase

1 Wet Scrubber NA b NAb NA b 0 406 81.0 0 0 213 24.6 

Current 

Potential 

Emissions 

 NA b NA b 2,133 0 282 

aCompared with current potential emissions. b BART is not applicable for utility boilers, with respect to SO2 and NOx, due to their required participation in the Indiana Cle an Air Interstate rule 

( which is presumed to require a BART equivalent degree of control).
 6-42 July 2010 

This page left blank intentionally. 
 6-43 July 2010 

Table 6-7. NOx Post-Control Emission Rates for Boilers 2 and 3

Control 

Scenario 

NOx 

Control 

Technology 

NOx SO2 PM2.5 PM10 Organics 

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/yr) 

% 

Reduction 

(Increase)a

Emissions 

(tons/year) 

% 

Reduction 

(Increase)a

Emissions 

(tons/year) 

% 

Reduction 

(Increase)a

3 

Low NOx 

Burners /w 

Overfire 

Air and 

SCR on 

Units 2 & 3 

2,103 

78.0 

56,215 

0 564 63.7 0 84 75.0 

2 

Low NOx 

Burners /w 

Overfire 

Air and 

SNCR on 

Units 2 & 3 

3,463 63.7 

56,215 

0 564 63.7 0 84 75.0 

1 

Low NOx 

Burners w/ 

Overfire 

Air on 

Units 2 & 3 

4,700 50.8 56,215 0 564 63.7 0 84 75.0 

Current 

Potential 

Emissions 

Units 2 

and 3 

Low NOx 

Burners w/ 

Overfire 

Air and No 

Controls on 

Units 2 & 3 

9,551 56,215 

 1,552 0 334 

aCompared with current potential emissions. 
 6-44 July 2010 

6.2.4 Evaluation of Cost and Other Impacts for Feasible BART Control Options 6.2.4.1 Cost Analysis for SO2 Wet Scrubber Control Options 

Conventional wet scrubbers, which were determined to be one of the most effective technically feasible control options, 

are currently being installed to control SO2 emissions on units 2, 3, and 4. Scrubbers were connected to boilers 2 and 3 in May 

and July, 2008 respectively. The purpose of a control technology cost analysis in a BART determination is to evaluate which, if any, control option is feasible from a cost stand point. Since Alcoa has chosen to install the most effective technically feasible control option for SO2

removal on boilers 2 and 3, a cost analysis for controlling SO2 from the boilers was not deemed necessary for this BART 

determination. 6.2.4.2 Cost Analysis for NOx Control Options 

 The costs for Alcoa’s BART determination were based on an engineering evaluation of NOx controls for Units 2 and 3 

by Black & Veatch. The cost estimates are included in Appendix C. 

The approximate capital cost of adding low-NOx burners to Units 2 and 3 would be approximately $8,100,000. The 

nominal cost effectiveness would be approximately $160 per ton of NOx removed. The actual cost effectiveness would be higher because this assumes operating at 8,760 hours/year. Low NOx burners are a cost effective option for Units 2 and 3. 
 6-45 July 2010 

The cost of adding SNCR to Units 2 and 3 would primarily be the operating cost of injecting ammonia or urea. The 

approximate capital cost would be approximately $3,000,000 with an operating cost of $4,200,000 per year. The nominal cost effectiveness would be approximately $3,392 per ton of NOx removed. The actual cost effectiveness would be higher because this assumes operating at 8,760 hours/year. Adding SNCR is not a reliable option considering the technical difficulties discussed 

previously. Even if SNCR were a good technical option, it is not cost effective considering that 87% of the visibility impacts are 

associated with SO2 emissions rather than NOx. SNCR is not a cost effective or practical BART option for these units. 

The approximate capital cost of adding SCR to Units 2 and 3 would be approximately $70,100,000 with an operating 

cost of $13,400,000 per year. The nominal cost effectiveness would be approximately $5,148 per ton of NOx removed. As with the other options, the actual cost effectiveness would be much higher because this assumes operating at 8,760 hours/year. SCR is a technically feasible option but is not cost effective considering that 87% of the visibility impacts are associated SO2 emissions 

rather than NOx. SCR is not a cost effective BART option for these units. 

Table 6-8 summarizes the cost of installing and operating low NOx burners and over-fire air systems on units 2 and 3 

and the incremental cost of adding SNCR (though its technical feasibility is questionable) on units 2 and 3 as well as the incremental cost of adding SCR on units 2 and 3. 
 6-46 July 2010 

Table 6-8. Summary of the Impacts Analysis for NOx Control Scenarios 

Control 

Scenario 

Control Technology 

Evaluated 

Emission 

Rate 

(tons/year) 

Emissions 

Reductions 

(tons/year)a

Installed 

Capital 

Cost 

($000) 

Total 

Annualized 

Control 

Costs 

($000) 

Incremental 

Cost 

Effectiveness 

($ per ton of 

pollutant 

removed) 

Energy 

Impact 

(000 kWhour/ 

year) 

Non-Air 

Quality 

Environmental 

Impacts 

3 

Low NOx Burners 

/w Overfire Air 

and SCR on Unit 4 

and Low NOx 

Burners w/ 

Overfire Air and 

SCR on Units 2 & 

3 

4,049 2,597 $70,144 $13,371 $5,148 20,533 

Catalyst 

disposal, acid 

dew point 

corrosion, 

safety handling 

of ammonia 

2 

Low NOx Burners 

/w Overfire Air 

and SCR on Unit 4 

and Low NOx 

Burners w/ 

Overfire Air and 

SNCR on Units 2 

& 3 

5,409 1,237 $2,970 $4,196 $3,392 876 

Boiler tube 

fowling due to 

formation of 

ammonium 

sulfates 

1 

Low NOx Burners 

/w Overfire Air 

and SCR on Unit 4 

and Low NOx 

Burners w/ 

Overfire Air on 

Units 2 & 3

6,646 4,851 $8,100 $765 $158 0 

Current 

Potential 

Emissions 

11,506 

aCompared with baseline emissions.
 6-47 July 2010 

6.2.4.3 Energy Impact Analysis 

A wet scrubber removes SO2 by forcing the exhaust gas through a spray tower or absorber where it contacts water 

droplets that contain the unreacted lime or limestone. Energy is required to overcome the resistance of the scrubber componentsas well as falling water droplets. A substantial amount of energy is associated with operation of fans to move the exhaust air through the scrubbers, for the slurry pumps, instrumentation, and miscellaneous items (e.g., lighting). 

The energy impacts of operating an SNCR system are primarily due to pumping and atomizing the reagent. The 

estimated energy use would be 876,000 kWhr per year. 

The energy impacts of operating an SCR system include ammonia vaporization and the additional pressure drop of 

moving the gas stream through the catalyst. The estimated energy use would be 20,500,000 kWhr per year. 6.2.4.4 Non-air Quality Environmental Impacts for Feasible Industrial Boiler BART Control Options 

Wet scrubbers using limestone oxidizes the spent slurry to gypsum. This waste from the wet scrubbers would be 

landfilled each year. Several hundred million gallons of water will be required annually to operate the wet scrubbers. This will 

significantly impact the community infrastructure in that this will increase daily water demand. There will be relatively no impact due to water discharge. Several million kWh will be needed to operate the scrubbers annually. This would impact power 

demand on the current generating capacity and therefore also have an environmental impact due to power. 

With SNCR, urea or ammonia is injected directly into the boiler. There it combines with sulfur oxides to form 

ammonium bisulfate and ammonium sulfate. These compounds are often “sticky” and difficult to remove which leads to fouling of boiler tubes. Ultimately new soot blowers may be needed or additional maintenance time is required to remove these deposits.
 6-48 July 2010 

 SCR systems typically use ammonia. An issue with SCR systems is that the safety considerations of storing and 

handling ammonia (which is a toxic chemical) must be addressed. The SCR catalyst is gradually poisoned by flue gas constituents and must be replaced. Another issue that must be addressed is the disposal of the spent catalyst that contains active 

metals (e.g., vanadium and titanium). A portion of the SO2 can be oxidized to SO3 by the catalyst. This results in another issue that must be addressed where the additional SO3 causes a higher acid dew point downstream of the catalyst that can cause increased corrosion. 

1.0 
 7-1 July 2010 

7.0 EVALUATE VISIBILITY IMPACTS 

 Step 5 of the BART analysis involves evaluation of visibility impacts. More specifically, 

this is an evaluation of the potential improvement in visibility resulting from the application of 

feasible pollution prevention/add-on control options. Refined CALPUFF modeling of the 

individual emission units with the control options applied was performed. This modeling was 

accomplished according to the modeling protocol that was developed and submitted to IDEM 

(included as Appendix A). In general, this modeling was the same as the baseline modeling 

except stack data and emission data associated with the application of the feasible pollution 

prevention/add-on controls were used as model inputs. 

Based on the results of steps 1 through 4 of this BART analysis, two (2) feasible control 

scenarios were modeled. Scenario 1 included the use of 3% sulfur coke in the anodes and 

existing controls on the potlines and wet scrubber controls, low NOx burners and overfire air on 

each of boiler units 2 and 3. SNCR and SCR controls on boiler units 2 and 3 were not modeled 

because it was determined in the baseline modeling that the visibility impact at MCNP was 

primarily due to SO2 rather than NOx. It was also determined that the addition of SNCR or SCR 

to low NOx burners and over-fire air would not significantly increase the removal NOx. 

Scenario 2 included the use of 3% sulfur in coke in the anodes and wet scrubber control on the 

potlines and wet scrubber controls, low NOx burners and overfire air on each of boiler units 2, 3, 

and 4 and SCR on boiler unit 4. 

 Table 7-1 presents the results of modeling with the potline and boiler SO2 control 

scenarios and boiler NOx control scenarios. The baseline modeling results indicate that the 

average 98th percentile visibility impact from Alcoa’s BART-eligible sources at MCNP was 

1.849 dv. The post-control modeling results for Scenario 1 indicate that the average 98th

percentile visibility impact from Alcoa’s BART-eligible sources at MCNP was 0.382 dv. The 
 7-2 July 2010 

post-control modeling results for Scenario 2 indicate that the average 98th percentile visibility 

impact from Alcoa’s BART-eligible sources at MCNP was 0.289 dv.
 7-3 December 2008 

Table 7-1. SO2 & NOx Controls – Visibility Modeling Results at MCNP 

Control Scenario 

No. Control Technology

2001 2002 2003 Average 

Modeled 98th

Percentile Value 

(dv)

Modeled 98th

Percentile Value 

(dv)

Modeled 98th

Percentile Value 

(dv) 

Modeled 98th Percentile 

Value (dv)

Baseline 1.852 1.906 1.788 1.849 

Scenario 1 

3% sulfur coke in 

the anodes and 

existing controls on 

the potlines, ESP 

and wet scrubber 

controls, low NOx 

burners and overfire 

air on each of boiler 

units 2 and 3, and 

ESP and wet 

scrubber control on 

boiler unit 4

0.444 0.299 0.402 0.382 

Scenario 2 

3% sulfur in coke in 

the anodes and wet 

scrubber control on 

the potlines, ESP 

and wet scrubber 

controls, low NOx 

burners and overfire 

air on each of boiler 

units 2 and 3, and

ESP and wet 

scrubber control on 

boiler unit 4

0.374 0.218 0.268 0.289 
 8-1 December 2008 

8.0 DETERMINATION OF BART 

8.1 Aluminum Potlines

 For potline SO2 emissions, BART was determined to be a limit of 3% sulfur in the coke 

used to manufacture anodes. Use of wet scrubbing technology to reduce potline SO2 emission 

was rejected as BART due to excessive costs: total cost effectiveness of $15,000 per ton of SO2

removed and capital and total annualized costs of >$300,000,000 and $55,000,000 per year, 

respectively. 

 For PM emissions, BART was determined to be the current level of control, which is the 

use of baghouses to control PM emissions from the alumina dry scrubbers. 

There are no feasible technologies for the control of NOx from potlines; thus, BART for 

NOx was determined to be no controls. 

8.2 Coal Fired Boilers

For SO2 emissions from units 2, 3 and 4, BART was determined to be wet scrubbing with 

a 92% control efficiency on units 2 and 3. 

The existing ESP controls on units 2, 3, and 4 were determined to be BART for PM. 

For NOx emissions, BART was determined to be low NOx burners on units 2 and 3. 

8.3 BART Visibility Modeling Analysis

CALPUFF modeling was performed using input data based on controls that were 

identified as BART. Table 8-1 presents the BART modeling source input data that were used in 

the CALPUFF model to forecast the visibility impact. Table 8-2 presents the modeled 98th

percentile total source visibility impact reported as deciviews for 2001, 2002 and 2003 at 
 8-2 December 2008 

MCNP. Table 8-3 presents the average visibility improvement associated with implementing 

BART at Alcoa Inc. – Warrick Operations and APGI – Warrick Power Plant. 

Modeling indicates implementation of BART as determined above will reduce the 

potential impact on visibility at MCNP from an average 98th percentile value of 1.849 dv to an 

average 98th percentile value of 0.382 dv, or an improvement in visibility of 3.060 dv. 
December 2008 

8-3

Table 8-1. BART Conditions Modeling Input Data 

Index Emission Unit ID # Stack Name Release Height (m) Monitor Width (m) Exit Veloc. (m/s) Delta T (K) Beginning UTM E/N (km) Ending UTM E/N (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

L01 103M.1 Potline #2, Room 103 14.02 1.52 2.93 24.95 

471.119, 

4196.702 

471.198, 

4196.984 0.535 0.753 

L02 104M.1 Potline #2, Room 104 14.02 1.52 2.93 24.95 

471.087, 

4196.711 

471.166, 

4196.993 0.535 0.753 

L03 105M.1 Potline #3, Room 105 14.02 1.52 2.93 24.95

471.024, 

4196.728

471.103, 

4197.010 0.569 0.802 

L04 106M.1 Potline #3, Room 106 14.02 1.52 2.93 24.95

470.992, 

4196.737

471.070, 

4197.019 0.569 0.802 

L05 107M.1 Potline #4, Room 107 14.02 1.52 2.93 24.95 

470.961, 

4196.745 

471.038, 

4197.027 0.567 0.799 

L06 108M.1 Potline #4, Room 108 14.02 1.52 2.93 24.95 

470.929, 

4196.754 

471.007, 

4197.036 0.567 0.799 

L07 109M.1 Potline #5 , Room 109 14.02 1.52 2.31 23.18

470.900, 

4196.770

471.976, 

4197.052 0.470 0.663 

L08 110M.1 Potline #5, Room 110 14.02 1.52 2.31 23.18

470.868, 

4196.778

471.943, 

4197.061 0.470 0.663 

L09 111M.1 Potline #6 , Room 111 14.02 1.52 2.31 23.18 

470.803, 

4196.796 

471.881, 

4197.078 0.532 0.749 

L10 112M.1 Potline #6, Room 112 14.02 1.52 2.31 23.18 

470.771, 

4196.804 

471.848, 

4197.086 0.532 0.749 

Index Emission Unit ID # Stack Name Stack Height (m) Stack diameter (m) Exit Veloc. (m/s) Exit Temperature (K) UTM Easting (km) UTM Northing (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

P01 GTC 

Potlines #3 & #4 GTC Pollution 

Controls 60.66 6.10 16.46 350 470.668 4196.863 1.185 1.667 

P02 160C1.1-160C1.36 Potline #2 A-398 14.94 3.70 21.12 366 471.118 4196.953 0.535 0.753 P03 161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.541 0.760 P04 161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 4196.888 0.532 0.748 P23 134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 P24 134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 P25 134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 P26 134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 P28 134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 P29 134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 P30 134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 P31 134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 P32 134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 P33 134.4 Melter 6M1 38.40 1.22 3.80 583 470.933 4197.145 0.062 0.029 P34 134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 P35 134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 P36 134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 P37 134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 P39 134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245 0.007 0.003 P41 134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 

WPP02 

WPP Units 2 & 3 Units 2 and 3 115.82 5.91 12.59 428 470.727 4196.445 * 12.75 

WPP03 WPP Unit 4 Unit 4 115.82 4.45 34.91 425 470.720 4196.340 * 2.745 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5
 December 2008 8-4

Table 8-2. BART Visibility Modeling Results 

Year f(RH) Max RH (%) Rayleigh 

Maximum 

Delta 

Bext 

98th 

Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th Percentile 

Delta 

Deciview 

 (Mm-1) (%) (%) (dv) (dv) 

 

2001 EPA 95 10 9.34 4.60 0.868 0.444 

 

2002 EPA 95 10 10.35 3.07 0.949 0.299 

 

2003 EPA 95 10 10.87 4.17 1.002 0.402 

Table 8-3. BART Visibility Improvement 

BART 

Option 

Baseline Visibility Impact (98 

Percentile Delta Deciview 

(dv) 

Post-BART Visibility Impact 

(98 Percentile Delta Deciview 

(dv) 

Average 

Visibility 

Improvement 

(dv) 

 2001 2002 2003 Average 2001 2002 2003 Average 

BART 

Eligible 

Sources 

Onlya 1.852 1.906 1.788 1.849 0.444 0.299 0.402 0.382 1.467 
 December 2008 9-1

9.0 PROPOSED BART ALTERNATIVE 

The BART analysis and the associated coke availability study (see Appendix D) raised 

concerns for Alcoa Inc. – Warrick Operations regarding both the long-term availability of lower 

sulfur anode grade coke and the high costs associated with potline add-on SO2 controls. To 

address these concerns, Alcoa is proposing an alternative to BART that will result in greater 

visibility improvement compared to BART, while allowing Alcoa Inc. – Warrick Operations the 

long term flexibility needed for purchase and use of higher sulfur coke. The alternative emission 

reduction strategy includes the wet SO2 scrubbing of its Unit 1 coal fired boiler, which is not a 

BART-eligible source, and the use of up to 3.5% sulfur coke at the potlines. 

 

9.1 Alternative Controls

As an alternative to BART, Alcoa is proposing to install a SO2 wet scrubber on boiler unit 1 

which is a unit that is not a BART eligible source. In combination with installing this scrubber, 

Alcoa is proposing to change the sulfur content limit for coke used to produce anodes and reduce 

the SO2 removal efficiency for other wet scrubbers. Specifically, Table 9-1 lists changes in 

controls that are proposed, compared to BART. 

Table 9-1. Proposed Alternative to BART Controls 

Emission Unit BART Control Alternative Control 

Boiler 1 No required SO2 or NOx control ESP, Wet SO2 scrubber at 91% 

efficiency, LNBs with staged OFA 

Boilers 2 and 3 Wet SO2 scrubber at 92% efficiency 

LNBs with staged OFA

ESP, Wet SO2 scrubber at 90% 

efficiency, LNBs with staged OFA

Boiler 4 Wet SO2 scrubber and cold side ESP 

providing 0.015 lb./mm Btu PM 

control 

Wet SO2 scrubber and cold side 

ESP providing 0.10 lb./mm Btu PM 

control 

Potlines Anode grade coke < 3% sulfur Anode grade coke < 3% sulfur 
 December 2008 9-2

 

Table 9-2 presents the baseline modeling source input data that were used in the CALPUFF 

model to forecast the baseline visibility impact including boiler unit 1. Table 9-3 presents the 

alternative to BART modeling source input data that were used in the CALPUFF model to 

forecast the visibility impact. 
9-3

Table 9-2. Baseline Including Boiler Unit 1 Conditions Modeling Input Data 

Index Emission Unit ID # Stack Name Release Height (m) Monitor Width (m) Exit Veloc. (m/s) Delta T (K) Beginning UTM E/N (km) Ending UTM E/N (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

L01 103M.1 Potline #2, Room 103 14.02 1.52 2.93 24.95 

471.119, 

4196.702 

471.198, 

4196.984 0.535 0.753 

L02 104M.1 Potline #2, Room 104 14.02 1.52 2.93 24.95 

471.087, 

4196.711 

471.166, 

4196.993 0.535 0.753 

L03 105M.1 Potline #3, Room 105 14.02 1.52 2.93 24.95

471.024, 

4196.728

471.103, 

4197.010 0.569 0.802 

L04 106M.1 Potline #3, Room 106 14.02 1.52 2.93 24.95

470.992, 

4196.737

471.070, 

4197.019 0.569 0.802 

L05 107M.1 Potline #4, Room 107 14.02 1.52 2.93 24.95 

470.961, 

4196.745 

471.038, 

4197.027 0.567 0.799 

L06 108M.1 Potline #4, Room 108 14.02 1.52 2.93 24.95 

470.929, 

4196.754 

471.007, 

4197.036 0.567 0.799 

L07 109M.1 Potline #5 , Room 109 14.02 1.52 2.31 23.18

470.900, 

4196.770

471.976, 

4197.052 0.470 0.663 

L08 110M.1 Potline #5, Room 110 14.02 1.52 2.31 23.18

470.868, 

4196.778

471.943, 

4197.061 0.470 0.663 

L09 111M.1 Potline #6 , Room 111 14.02 1.52 2.31 23.18 

470.803, 

4196.796 

471.881, 

4197.078 0.532 0.749 

L10 112M.1 Potline #6, Room 112 14.02 1.52 2.31 23.18 

470.771, 

4196.804 

471.848, 

4197.086 0.532 0.749 

Index Emission Unit ID # Stack Name Stack Height (m) Stack diameter (m) Exit Veloc. (m/s) Exit Temperature (K) UTM Easting (km) UTM Northing (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 60.66 6.10 16.46 350 470.668 4196.863 0.986 0.116 P02 

160C1.1-

160C1.36 Potline #2 A-398 14.94 3.70 21.12 366 471.118 4196.953 0.393 0.046 

P03 

161B5.1-

161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.555 0.065 

P04 

161B6.1-

161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 4196.888 0.563 0.066 

P23 134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 P24 134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 P25 134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 P26 134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 P28 134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 P29 134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 P30 134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 P31 134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 P32 134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 P33 134.4 Melter 6M1 38.40 1.22 3.80 583 470.933 4197.145 0.062 0.029 P34 134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 P35 134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 P36 134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 P37 134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 P39 134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245 0.007 0.003 P41 134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 

WPP01 WPP01 Warrick Power Plant Stack 1 Unit 1 & 2 115.82 5.91 12.88 423 470.810 4196.399 * 24.18 WPP02 WPP02 Warrick Power Plant Stack 2 Unit 2 and 3 115.82 5.91 12.59 428 470.731 4196.443 * 22.01 WPP03 WPP03 Warrick Power Plant Stack 3 Unit 4 115.82 4.45 34.91 425 470.668 4196.433 * 49.525 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5
9-4

Table 9-3. Alternative to BART Conditions Modeling Input Data 

Index Emission Unit ID # Stack Name Release Height (m) Monitor Width (m) Exit Veloc. (m/s) Delta T (K) Beginning UTM E/N (km) Ending UTM E/N (km) Filterable PM10 - PM2.5 (g/s) Filterable PM2.5 (g/s) 

L01 103M.1 Potline #2, Room 103 14.02 1.52 2.93 24.95

471.119, 

4196.702

471.198, 

4196.984 0.535 0.753 

L02 104M.1 Potline #2, Room 104 14.02 1.52 2.93 24.95 

471.087, 

4196.711 

471.166, 

4196.993 0.535 0.753 

L03 105M.1 Potline #3, Room 105 14.02 1.52 2.93 24.95 

471.024, 

4196.728 

471.103, 

4197.010 0.569 0.802 

L04 106M.1 Potline #3, Room 106 14.02 1.52 2.93 24.95

470.992, 

4196.737

471.070, 

4197.019 0.569 0.802 

L05 107M.1 Potline #4, Room 107 14.02 1.52 2.93 24.95

470.961, 

4196.745

471.038, 

4197.027 0.567 0.799 

L06 108M.1 Potline #4, Room 108 14.02 1.52 2.93 24.95 

470.929, 

4196.754 

471.007, 

4197.036 0.567 0.799 

L07 109M.1 Potline #5 , Room 109 14.02 1.52 2.31 23.18 

470.900, 

4196.770 

471.976, 

4197.052 0.470 0.663 

L08 110M.1 Potline #5, Room 110 14.02 1.52 2.31 23.18

470.868, 

4196.778

471.943, 

4197.061 0.470 0.663 

L09 111M.1 Potline #6 , Room 111 14.02 1.52 2.31 23.18

470.803, 

4196.796

471.881, 

4197.078 0.532 0.749 

L10 112M.1 Potline #6, Room 112 14.02 1.52 2.31 23.18 

470.771, 

4196.804 

471.848, 

4197.086 0.532 0.749 

Emission Unit 

ID # Stack Name 

Stack 

Height 

(m) 

Stack 

diameter 

(m) 

Exit 

Veloc. 

(m/s) 

Exit 

Temperature 

(K) 

UTM Easting 

(km) 

UTM 

Northing 

(km) 

Filterable 

PM10 - 

PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

P01 GTC 

Potlines #3 & #4 GTC Pollution 

Controls 60.66 6.10 16.46 350 470.668 4196.863 1.185 1.667 

P02 160C1.1-160C1.36 Potline #2 A-398 14.94 3.70 21.12 366 471.118 4196.953 0.535 0.753 P03 161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.541 0.760 P04 161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 4196.888 0.532 0.748 P23 134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 P24 134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 P25 134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 P26 134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 P28 134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 P29 134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 P30 134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 P31 134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 P32 134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 P33 134.4 Melter 6M1 38.40 1.22 3.80 583 470.933 4197.145 0.062 0.029 P34 134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 P35 134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 P36 134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 P37 134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 P39 134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245 0.007 0.003 P41 134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 

WPP Units 1- 2 & 3 Units 1 - 3 115.82 5.79 12.33 329 470.727 4196.445 * 17.94 

WPP Unit 4 Unit 4 115.82 4.45 34.91 329 470.720 4196.340 * 18.303 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5
December 2008 9-5

9.2 Visibility Impact of Proposed Alternative to BART versus BART

Table 9-4 presents the results of modeling that was performed in association with 

Alcoa Inc. – Warrick Operations and APGI – Warrick Power Plant’s proposed Alternative to BART. In order to compare the visibility improvement associated with BART versus Alcoa’s proposed Alternative to BART, unit 1 was added as an emissions source to the BART-eligible sources. Even though unit 1 is not BART eligible, its baseline period uncontrolled emissions impacted visibility at MCNP. Installation of a wet scrubber for SO2 control, and LNB’s for NOx control on unit 1 will provide an improvement in visibility impact. These controls are not required by the Regional Haze Program, and serve as the basis for the alternative to BART. The unit 1 controls offset the impact of increasing petroleum coke sulfur content, and slightly reducethe SO2 removal efficiencies for boilers 2 and 3. Based on this modeling, it was determined that the proposed Alternative to BART would improve visibility at MCNP more than BART. The average visibility improvement due to Alcoa’s Alternative to BART was 1.947 dv while the average visibility improvement due to BART was 1.467 dv. 

Implementation of an “Alternative to BART” control strategy, that includes the scrubbing of Unit 1 and 3.5% sulfur 

coke, will result in a “better than BART” visibility improvement. On average, the BART Alternative results in an additional 0.50 dv improvement over a BART-eligible source only scenario. Because the “Alternative to BART” provides Alcoa with more business certainty, and provides greater visibility improvement at MCNP, Alcoa requests IDEM to determine that the alternative emission reduction strategy described herein fulfills the best available retrofit technology requirements of Section 169A(b)(2)(A), of the 1990 Clean Air Act for this facility. 
December 2008 9-6

Table 9 -4. Summary of Baseline, BART, and Alternative to BART Visibility Impact at MCNP.

BART Option 

Baseline Visibility Impact (98 

Percentile Delta Deciview (dv) 

Post-BART Visibility Impact (98 

Percentile Delta Deciview (dv) 

Average 

Visibility 

Improvement 

(dv) 

2001 2002 2003 Average 2001 2002 2003 Average 

BART Eligible Sources Onlya 1.852 1.906 1.788 1.849 0.444 0.299 0.402 0.382 1.467Alternative to BART (BART Eligible Plus Unit 1 Controlled)a 2.311 2.774 2.549 2.545 0.686 0.463 0.595 0.581 1.964

a Based on ESP and wet SO2 scrubbing on Units 2 - 3 and 4 with 3% sulfur coke for potlines b Based on ESP and wet SO2 scrubbing on Units 1, 2, 3, ESP and wet SO2 scrubbing on Unit 4 for PM control, and 3.5% sulfur 

coke for potlines. 
 December 2008 10-1

10.0 REFERENCES 

AWMA 2000. Air Pollution Engineering Manual, Second Edition (formerly document AP-40), 

Air & Waste Management Association, John Wiley & Sons, 2000. 

EPA 2003a. “Air Pollution Control Technology Fact Sheet – Dry Electrostatic Precipitator,” 

EPA-452/F-03-028, August 7. 

EPA 2003b. “Air Pollution Control Technology Fact Sheet – Fabric Filter,” EPA-452/F-03-025, 

August 7. 

EPA 2003c. “Air Pollution Control Technology Fact Sheet – Flue Gas Desulfurization,” EPA452/F-03-034, August 8. 

EPA 2003d. “Air Pollution Control Technology Fact Sheet – Selective Catalytic Reduction,” 

EPA-452/F-03-032, August 8. 

EPA 2003e. “Air Pollution Control Technology Fact Sheet – Selective Non-Catalytic 

Reduction,” EPA-452/F-03-031, August 8. 

EPA 2002. EPA Air Pollution Control Cost Manual, Sixth Edition, EPA/452/B-02-001, January 

2002 (and updates). 

Black & Veatch, “Alcoa Warrick Units 2 and 3 NOx Reduction Study,” September 2006. 
Appendix A to 

BART determination Report for Alcoa, Inc. - Warrick Operations 
This page intentionally left blank. 
Revisions to Appendix A, Alcoa BART Modeling Protocol

These revisions to Appendix A were submitted in September 2010 in a format not compatible with th

tables in this attachment replace the tables by the same numbers included in the original report. 
Table 2-3. Point and Line Source Emissions

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - PM2.5

 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s)

S

(

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0

P01 GTC 

Potlines #3 & #4 GTC 

Pollution Controls 0.986 0.116 1.757 4.409 

44

P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 2P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 2P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 

2

2

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 0P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 0P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 0P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 0P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 

0

0

P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 

0

0

P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 

0

0

P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 0P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 0P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 0P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 0P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 0P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0

WPP01 WPP stack 1 WPP Stack 1 Unit 2 Only * 8.6 1.949 2.852 3WPP02 WPP stack 2 WPP Stack 2 Units 2 and 3 * 22.01 21.96 7.629 5.73 11.236 8.384 1WPP03 WPP stack 3 WPP Stack 3 Unit 4 * 49.525 49.523 8.13 11.895 0.0 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5

2-5 Sour
Table 2-4. PM Speciation of Particulate Matter Emitted from Lines and Stacks

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

L01 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L02 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L03 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L04 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L05 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L06 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L07 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L08 0.470 0.6630 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L09 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 L10 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 

P01 0.986 0.116 1.757 4.409 0.493 0.493 0.029 0.029 2.234 2.234 0.879 P02 0.393 0.046 0.700 1.758 0.197 0.197 0.012 0.012 0.891 0.891 0.350 P03 0.555 0.065 0.989 2.482 0.278 0.278 0.016 0.016 1.257 1.257 0.495 P04 0.563 0.066 1.002 2.514 0.282 0.282 0.017 0.017 1.274 1.274 0.501 P23 0.056 0.027 0.001 0.001 0.028 0.028 0.007 0.007 0.007 0.007 2.50E-0P24 0.017 0.026 0.002 0.002 0.009 0.009 0.007 0.007 0.007 0.007 7.50E-0P25 0.065 0.030 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-0P26 0.011 0.016 0.002 0.002 0.006 0.006 0.004 0.004 0.005 0.005 7.50E-0P28 0.061 0.028 0.001 0.001 0.031 0.031 0.007 0.007 0.007 0.007 2.50E-0P29 0.110 0.167 0.015 0.015 0.055 0.055 0.042 0.042 0.049 0.049 7.50E-0P30 0.095 0.044 0.001 0.001 0.048 0.048 0.011 0.011 0.012 0.012 5.00E-0P31 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P32 0.066 0.031 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-0P33 0.062 0.029 0.001 0.005 0.031 0.031 0.007 0.007 0.010 0.010 2.50E-0P34 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P35 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-0P36 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P37 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-0

________ 1 Emissions are fine filterable plus inorganic condensables 

_____________________________________________________________________________________________________
2-6 So

Table 2-4. PM Speciation of Particulate Matter Emitted from Lines and Stacks, Continued

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

P39 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00 P41 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00 

WPP1 - 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 WPP2 

- 22.01

21.96

7.629

5.73

11.236

8.384

0.000 0.000 5.503

5.490

5.5035.490

11.1219.682

11.1215.490

3.814 2.865

WPP3 - 49.525 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.329 18.328 18.329 18.328 4.065 

________ 1 Emissions are fine filterable plus inorganic condensables 

_____________________________________________________________________________________________________

2-6A 
Modeling Protocol for a BART Assessment of the 

Alcoa Warrick Operations and Warrick Power 

Plant, Warrick County, Indiana 

Prepared For: 

Alcoa Warrick Operations 

Warrick County, Indiana 

Submitted By: 

TRC Environmental Corporation 

650 Suffolk Street, Wannalancit Mills 

Lowell, Massachusetts 01854 

(978) 970-5600 

November 2008 
i

TABLE OF CONTENTS 

Page

1.0 INTRODUCTION ......................................................................................................................1-1

2.0 SOURCE DESCRIPTION .........................................................................................................2-1

3.0 SCREENING MODELING .......................................................................................................3-1

4.0 GEOPHYSICAL AND METEOROLOGICAL DATA FOR REFINED MODELING ......4-1

4.1 Terrain ......................................................................................................................................4-1

4.2 Land Use...................................................................................................................................4-1

4.3 Meteorological Data Base ........................................................................................................4-4

4.4 Air Quality Monitoring Data ..................................................................................................4-13

5.0 AIR QUALITY MODELING METHODOLOGY..................................................................5-1

5.1 Model Selection........................................................................................................................5-1

5.1.1 Major Features of CALMET................................................................................................5-1

5.1.2 Major Features of CALPUFF...............................................................................................5-4

5.2 Modeling Domain Configuration .............................................................................................5-9

5.3 Meteorological Modeling Options............................................................................................5-9

5.4 CALPUFF Computational Domain and Receptors ..................................................................5-9

5.5 Dispersion Modeling Options.................................................................................................5-10

5.6 Visibility Calculations ............................................................................................................5-11

5.7 Modeling Products..................................................................................................................5-12

6.0 REFERENCES............................................................................................................................6-1
ii

LIST OF FIGURES 

Page

Figure 2-1. An aerial photo of the facility with the potrooms and other major buildings outlined. 2-2

Figure 3-1. Terrain elevations for the VISTAS CALMET 12-km regional domain. CALPUFF 

computational subdomain, the Class I areas and the locations of Warrick facilities are 

also shown. 3-3

Figure 4-1. Terrain contours (m MSL) at 1 km resolution for the 225 x 195 CALMET and 

CALPUFF computational domains. The Class I area, Mammoth Cave NP and the 

Alcoa Warrick facility are shown. 4-2

Figure 4-2. Dominant land use categories at 1 km resolution on the 225 km x 195 km CALMET 

and CALPUFF model domains. Mammoth Cave National Park and the facility are 

also shown. 4-3

Figure 4-3. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the 

refined 2001 modeling. Mammoth Cave National Park and the facility are also 

shown. 4-10

Figure 4-4. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the 

refined 2002 modeling. Mammoth Cave National Park and the facility are also 

shown. 4-11

Figure 4-5. Plot of all the surface, upper air, RUC data and precipitation stations to be used in the 

refined 2003 modeling. Mammoth Cave National Park and the facility are also 

shown. 4-12

Figure 4-6. Plot of all the ozone stations, both CASTNet and AIRS proposed for the refined 2001 

modeling. Mammoth Cave National Park and the facility are also shown. 4-15

Figure 4-7. Plot of all the ozone stations, both CASTNet and AIRS proposed for the refined 2002 

modeling. Mammoth Cave National Park and the facility are also shown. 4-16

Figure 4-8. Plot of all the ozone stations, both CASTNet and AIRS proposed for the refined 2003 

modeling. Mammoth Cave National Park and the facility are also shown. 4-17
iii

LIST OF TABLES 

Page

Table 2-1. Line Source Parameters used in CALPUFF 2-3

Table 2-2. Point Source Parameters used in CALPUFF 2-4

Table 2-3. Point and Line Source Emissions 2-5

Table 2-4. PM Speciation of Particulate Matter Emitted from Lines and Stacks 2-6

Table 3-1. Class I Areas in the Vicinity of Alcoa Warrick 3-2

Table 3-2. Monthly f(RH) Values Based on Area Centroids for Application with Visibility 

Method 6 3-2

Table 3-3. Average Natural Levels of Aerosol Components 3-2

Table 3-4. Results of the Screening Simulations 3-4

Table 4-1. U.S. Geological Survey Land Use and Land Cover Classification System 4-5

Table 4-2. Default CALMET Land Use Categories and Associated Geophysical Parameters 

Based on the U.S. Geological Survey Land Use Classification System (14-Category 

System) 4-6

Table 4-3. Meteorological Data Sources and Parameters Available 4-7

Table 4-4. NWS Hourly Surface Stations 4-8

Table 4-5. Upper Air Stations 4-8

Table 4-6. Hourly NWS Precipitation Stations 4-9

Table 4-7. Ozone Stations 4-14

Table 5-1. Major Features of the CALMET Meteorological Model 5-3

Table 5-2. Major Features of the CALPUFF Model 5-7

Table 5-2. Major Features of the CALPUFF Model (Cont’d) 5-8

Table 5-3. Background Natural Visibility Concentrations for the Eastern United States 5-12

Table 5-4. Monthly f(RH) Values for Mammoth Cave Based on the Area Centroid 5-12
1-1 Introduction

1.0 INTRODUCTION 

TRC Environmental Corporation is conducting a Best Available Retrofit Technology (BART) 

analysis for the Alcoa Warrick aluminum plant and Warrick Power Plant. This facility is situated 

in Warrick County, Indiana on the northern shores of the Ohio River along the Indiana/Kentucky 

border. It is approximately 23 km southeast of Evansville. The Alcoa Warrick Operations facility 

is a primary aluminum smelter. 

On July 6, 2005 the US Environment Protection Agency produced the Federal Register 

document, 40 CFR Part 51 in order to introduce new National Regional Haze Regulations for 

Best Available Retrofit Technology. The regional haze rule requires States to submit 

implementation plans (SIPs) to address regional haze visibility impairment in 156 Federallyprotected parks and wilderness areas, commonly referred to as “Class 1 Areas”. The final rule 

included a requirement for BART for certain large stationary sources that were put in place 

between 1962 and 1977. The regional haze rule uses the term “BART-eligible source” to describe 

those sources which have the potential to emit 250 tons or more of a visibility-impairing air 

pollutant, were put in place between August 7, 1962 and August 7, 1977 and whose operations 

fall within one or more of 26 specifically listed source categories, which includes primary 

aluminum ore reduction plants. 

BART review is required when the source ‘emits any air pollutant which may reasonably be 

anticipated to cause or contribute to any impairment of visibility in any Class 1 area. In 

identifying a level of control of BART, States are required by section 169A(g) of the CAA to 

consider; (a) the costs of compliance, (b) the energy and non-air quality environmental impacts of 

compliance, (c) any existing pollution control technology in use at the source, (d) the remaining 

useful life of the source and (e) the degree of visibility improvement which may reasonably be 

anticipated from the use of BART. 

The purpose of the modeling is to assess the ambient air quality impacts of sulfur dioxide (SO2), 

particulate matter (PM) and nitrogen oxides (NOx) emissions at Mammoth Cave National Park 

which is located in a south east direction approximately 120 km away. The impacts of the facility 

on visibility will be evaluated. 

The topography of the domain area consists of gentle rolling terrain where elevation of the land 

ranges from ~120m in the Ohio River Valley in the north and west of the model domain to 

~240m in the east. There is the potential for some terrain effects, both on the meteorological 

fields and in terms of plume-terrain interaction effects. The CALMET and CALPUFF nonsteady-state models (Scire et al., 2000a,b) are used for the modeling analysis. The U.S. 

Environmental Protection Agency (EPA) has recommended CALPUFF as the preferred model for 

BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline 
1-2 Introduction

Model for Class I impact assessments and other long range transport applications and on a caseby-case basis for near-field applications involving complex flows (U.S. EPA, 2003a). CALPUFF 

is also recommended by both the Federal Land Managers Air Quality Workgroup (FLAG, 2000) 

and the Interagency Workgroup on Air Quality Modeling (U.S. EPA, 1998). CALPUFF is 

recommended in the new draft proposed updated to FLAG (FLAG, 2008). 

CALMET is a diagnostic meteorological model that produces three-dimensional wind fields 

based on parameterized treatments of terrain effects such as slope flows, terrain blocking effects, 

and kinematic effects. Meteorological observations were used to determine the wind field in areas 

where the observations were representative. Hourly meteorological data produced by the 

Mesoscale Model, Version 5 (MM5) on a 12 km grid were used by CALMET for 2001 and 2002 

to help define the initial estimate of the wind fields. For 2003, RUC data, (Rapid Update Cycle) 

has been transformed into 3D.DAT format for its inclusion into CALMET. RUC is a high 

frequency weather forecast and data assimilation system which is supported and developed by 

NCEP. The RUC model provides high frequency mesoscale analyses and short range numerical 

forecasts. In this analysis the 50 original vertical levels were extracted and transformed into an 

MM5 data input file. The horizontal resolution of the data is 20 km Fine scale terrain effects (1 

km resolution) were determined by the diagnostic wind module in CALMET. It had been 

expected that spatial variability would occur in the wind fields over short distances due to the 

terrain channeling. 

CALPUFF is a non-steady-state puff dispersion model. It accounts for spatial changes in the 

CALMET-produced meteorological fields, variability in surface conditions (elevation, surface 

roughness, vegetation type, etc.), chemical transformation, wet removal due to rain and snow, dry 

deposition, and terrain influences on plume interaction with the surface. CALPUFF contains a 

module to compute visibility effects, based on a humidity-dependent relationship between 

particulate matter concentrations and light extinction, as well as wet and dry acid deposition 

fluxes. The refined meteorological and dispersion modeling simulations will be conducted for a 

three-year period (2001, 2002 and 2003). Visibility impacts from SO2, PM, and NOx, and their 

secondary products resulting from emissions from the proposed sources will be predicted by the 

model at receptors in the Class I area. 

The Lake Michigan Air Directors Consortium (LADCO) 2006 Document was used as a starting 

point for establishing the modeling procedures for the Warrick BART analysis. A few exceptions 

to the procedures from (LADCO, 2006) are proposed such as the use of the EPA-approved 

version of the model (Version 5.8), a more refined modeling domain with 1 km grid instead of 36 

km grid spacing, modeling of 2001-2003 using the different meteorological data set from what is 

specified in (LADCO, 2006) in order to allow the use of higher resolution meteorological data.
1-3 Introduction

In Section 2, a general description of the study area and the source configuration is provided. The 

results of a screening analysis that allows the identification of the primary Class I area controlling 

the BART analysis to be determined are presented in Section 3. Descriptions of the site 

characteristics and the data bases (meteorological, geophysical, and aerometric) used in the 

analysis are provided in Section 4. Section 5 includes an overview of the CALMET and 

CALPUFF models, and the importance of evaluating non-steady-state effects. 
 2-1 Source Description

2.0 SOURCE DESCRIPTION 

The Alcoa Warrick Operations facility is a primary aluminum smelter located in Warrick County, 

Indiana on the northern shore of the Ohio River along the Indiana/Kentucky border. It is 

approximately 23 km southeast of Evansville, IN. 

The potential BART-eligible facilities consists of five potlines (10 potrooms), and 16 melting 

and/or holding furnaces. Figure 2-1 shows an aerial photo of the facility with the potrooms and 

other major buildings outlined. In the existing facility configuration, there are 16 furnace stacks, 

and 108 stacks associated with the A-398 reactors for Lines 2, 5, and 6. Each A-398 has 36 

stacks. The common pollution control system for Potline 3 and 4 emissions exit through a 199 ft 

stack. 

Three stacks for the Warrick Power Plant will be modeled using the parameters listed in 

Table 2-2. 

For modeling purposes, banks of closely-spaced stacks of identical stack characteristics will be 

treated as a single effective stack. The effective stack uses the same exit velocity and exit 

temperature as the individual stacks, but the effective diameter was computed so that the 

volumetric flow of the effective stack is equal to the sum of the flows of the individual stacks in 

the bank. Therefore each bank of stacks is replaced by a single point source. 

Table 2-1 lists the line source parameters while Table 2-2 shows the source parameters for the 

point sources. Table 2-3 summarizes the line and point source emissions and Table 2-4 

summarizes the particulate speciation for all the sources. 
 2-2 Source Description

470.2 470.4 470.6 470.8 471.0 471.2 471.4 471.6 471.8 472.0

UTM Easting (km)

4195.6

4195.8

4196.0

4196.2

4196.4

4196.6

4196.8

4197.0

4197.2

4197.4

4197.6

4197.8

4198.0

UTM Northing (km)

 103M.1 104M.1 

 105M. 1 

 106M.1 107M.1 

 108M.1 

 109M.1 110M.1 111M.1 

 112M.1 

 60.3 60.8 

 61A.1 

 Tank 62 BC-24 

 61B.1 

 141A NW 141A SW 104. 1 141A NE 141A SE 

 144A 

 160C1.37 

 112A.1 

 16B6.16 161B5.37 

 166 

160C1.1-160C1

 GTC 

161B6.1-161B6 161B5.1-161B5

 110.2 

 134.62 134.64 134.67 134. 66 134.65 

 134.33 134.35 134.36 134.38 134.39 134.4 134. 41 134. 42 134.43 134.44 

 134.45 

 134.71 134. 73 

 134.75 134.76 134.68 134. 77 134. 69 134.7 

 379.1 

(UTM Zone = 16, Hemisphere = N, Datum = NAD83: GRS80/NAR-C)

ALCOA Warrick: Plant Layout

Figure 2-1. An aerial photo of the facility with the potrooms and other major buildings outlined. 
 2-3 

Table 2-1. Line Source Parameters used in CALPUFF 

Source 

ID 

Emission 

Unit ID # Stack Name 

Release 

Height 

(m) 

Monitor 

Width (m) 

Exit Velocity

(m/s) 

Delta Temp

(oK) 

Begin 

UTM 

E/N (km) 

E

U

E/

L01 103M.1 Potline #2, Room 103 14.02 1.52 2.93 24.95 471.119, 4196.702 471.19L02 104M.1 Potline #2, Room 104 14.02 1.52 2.93 24.95 471.087, 4196.711 471.16L03 105M.1 Potline #3, Room 105 14.02 1.52 2.93 24.95 471.024, 4196.728 471.10L04 106M.1 Potline #3, Room 106 14.02 1.52 2.93 24.95 470.992, 4196.737 471.07L05 107M.1 Potline #4, Room 107 14.02 1.52 2.93 24.95 470.961, 4196.745 471.03L06 108M.1 Potline #4, Room 108 14.02 1.52 2.93 24.95 470.929, 4196.754 471.00L07 109M.1 Potline #5 , Room 109 14.02 1.52 2.31 23.18 470.900, 4196.770 471.97L08 110M.1 Potline #5, Room 110 14.02 1.52 2.31 23.18 470.868, 4196.778 471.94L09 111M.1 Potline #6 , Room 111 14.02 1.52 2.31 23.18 470.803, 4196.796 471.88L10 112M.1 Potline #6, Room 112 14.02 1.52 2.31 23.18 470.771, 4196.804 471.84

Notes: L01-L02, L03-L04, L05-l06: F’ = 1002.186; Ave. line source width = 1.52m; Ave. building dimension = 292.6m; H = 13.61m, W = 16.0m; Ave. building separation L07-L08, L09-L10: F’ = 736.541; Ave. line source width = 1.52m; Ave. building dimension = 292.24m; H = 13.15m, W = 17.0m; Ave. building separation The release height (m), monitor width (m), exit velocity (m/s) and exit temperature (oK) were all taken from the 2002 Alcoa Warrick CO st

All the coordinates were digitized to match aerial photos in NAD83 datum 

L01-L06: Average Line Source Buoyancy Parameter (F') Calculation L07-L10: Average Line Source Buoyancy Param

F' = [gLW

mw(Ts-Ta)]/Ts = 1002.186 m4/s3 where F' = [gLW

mw(Ts-Ta)]/Ts = 736.541 m4/s3, where

g = acceleration of gravity = 9.81 m/s2 g = acceleration of gravity = 9.81 m/s2

L = line source length = 292.6 m L = line source length = 292.24 Wm = line source width = 1.52 m Wm = line source width = 1.52 m w = line source exit velocity = 2.93 m/s w = line source exit velocity = 2.31 m/s Ts = line source exit temperature = 318.3 K Ts = line source exit temperature = 316.8 K 

Ta = ambient air temperature = 293.3 K Ta = ambient air temperature = 293.6 K Ts - Ta = 

ΔT = 24.95 K Ts-Ta = 

ΔT = 23.18 K 
 2-4 

Table 2-2. Point Source Parameters used in CALPUFF 

Index Emission 

Unit ID # 

Stack Name Stack 

Height 

(m) 

Stack 

 Diameter 

(m) 

Exit Velocity

(m/s) 

Exit 

Temp

(oK) 

UTM 

Easting

 (km) 

U

Nor

 (

P01 GTC Potlines #3 & #4 GTC Pollution Controls 60.66 6.10 16.46 350 470.668 419P02 160C1.1-160C1.36 Potline #2 A-398 14.94 3.70 21.12 366 471.118 419P03 161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 419P04 161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 419P23 134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 419P24 134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 419P25 134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 419P26 134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 419P28 134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 419P29 134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 419P30 134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 419P31 134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 419P32 134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 419P33 134.4 Melter 6M1 38.40 1.22 3.80 583 470.933 419P34 134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 419P35 134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 419P36 134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 419P37 134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 419P39 134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 419P41 134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 419

WPP1 WPP stack 1 WPP Stack 1, Unit 2 only 115.82 5.91 12.88 423 470.810 419WPP2 WPP stack 2 WPP Stack 2, Units 2 and 3 115.82 5.91 12.59 428 470.731 419WPP3 WPP stack 3 WPP Stack 3, Unit 4 115.82 4.45 34.91 425 470.668 419
 2-5 

Table 2-3. Point and Line Source Emissions 

Source 

ID 

Emission 

Unit ID # Stack Name 

Filterable 

PM10-PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

Organic 

Condensable 

PM2.5

(g/s) 

Inorganic 

Condensable 

PM2.5

(g/s) 

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 9P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 1P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 2P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 3P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 4P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 1P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 4P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 1P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 4P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 2P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 1P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 2P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 1P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 2P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 6P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 2

WPP1 WPP stack 1 WPP Stack 1, Unit 2 only * 8.6 1.949 2.852 WPP2 WPP stack 2 WPP Stack 2, Units 2 and 3 * 21.96 5.73 8.384 WPP3 WPP stack 3 WPP Stack 3, Unit 4 * 49.523 8.13 11.895 
 2-6 

Table 2-4. PM Speciation of Particulate Matter Emitted from Lines and Stacks 

 Coarse PM Fine PM Organic Cond

Source 

Index 

PM10-

PM2.5 

(g/s) 

Solid 

PM2.5 

(g/s) 

Org. 

Cond 

(g/s) 

InOrg. 

Cond 

(g/s) 

6-10μm 

(g/s) 

2.5-

6.00μm 

(g/s) 

1.25-

2.5μm 

(g/s) 

1.00-

1.25μm 

(g/s) 

0.625-

1.00μm1 

(g/s) 

0.500-

0.625μm1 

(g/s) 

0.625-

1.00μm 

(g/s) 

0

L01 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L02 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L03 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L04 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L05 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L06 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L07 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L08 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L09 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 L10 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 

P01 0.986 0.116 1.757 4.409 0.493 0.493 0.029 0.029 2.234 2.234 0.879 P02 0.393 0.046 0.700 1.758 0.197 0.197 0.012 0.012 0.891 0.891 0.350 P03 0.555 0.065 0.989 2.482 0.278 0.278 0.016 0.016 1.257 1.257 0.495 P04 0.563 0.066 1.002 2.514 0.282 0.282 0.017 0.017 1.274 1.274 0.501 P23 0.056 0.027 0.001 0.001 0.028 0.028 0.007 0.007 0.007 0.007 2.50E-04 P24 0.017 0.026 0.002 0.002 0.009 0.009 0.007 0.007 0.007 0.007 7.50E-04 P25 0.065 0.030 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 P26 0.011 0.016 0.002 0.002 0.006 0.006 0.004 0.004 0.005 0.005 7.50E-04 P28 0.061 0.028 0.001 0.001 0.031 0.031 0.007 0.007 0.007 0.007 2.50E-04 P29 0.110 0.167 0.015 0.015 0.055 0.055 0.042 0.042 0.049 0.049 7.50E-03 P30 0.095 0.044 0.001 0.001 0.048 0.048 0.011 0.011 0.012 0.012 5.00E-04 P31 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 P32 0.066 0.031 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 P33 0.062 0.029 0.001 0.005 0.031 0.031 0.007 0.007 0.010 0.010 2.50E-04 P34 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 P35 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 P36 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 P37 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 P39 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00E+00 0P41 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00E+00 0

wpp1 - 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 wpp2 - 21.96 5.73 8.384 0.000 0.000 5.490 5.490 9.682 9.682 2.865 wpp3 - 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.328 18.328 4.065 

_______ 1 Emissions are fine filterable plus inorganic condensables.
 3-1 Screening Modeling

3.0 SCREENING MODELING 

As a first step into the BART analysis for Alcoa Warrick and Warrick Power Plant, screening 

simulations were made to analyze the influence of the facilities at Class I Areas located up to 500 km 

from the site (Table 2-1). For the screening simulations and BART analysis, VISTAS 12-km regional 

CALMET domain was used (VISTAS, 2005) with CALPUFF computational subdomain to cover the 

facility, all seven Class I areas and sufficient buffer zone of 100 km around the facility and Class I areas 

(Figure 3-1). This is a sufficient buffer zone at the boundaries which allows for the effects of flow 

curvature and possible small-scale recirculation to be evaluated. 

Method 6 visibility was used with monthly average relative humidity factors as listed in Table 2-2 and 

estimated natural concentrations for East United States as listed in Table 2-3. 

As indicated in the LADCO (2006) protocol, emission controls for the Warrick facility will be based on 

impacts at the Class I area with the highest predicted visibility impairment. The results of the screening 

simulations show that this will always be Mammoth Cave, which is by a large margin the closest Class I 

area to the facility (Table 2-4). Mammoth Cave is approximately 120 km from the facility while the next 

nearest Class I area (Mingo) is more than twice as far away. The other Class I areas on the list are all 

close to or beyond 400 km away from the facility. 

Results in Table 2-4 are presented for each of the modeled year separately (2001 to 2003) and for all 3 

years together. The 98th percentile value for a single year is the 8th highest values, while for three-year 

period is the 22nd highest. 

Since Mammoth Cave is the Class I area with the highest impacts and controls for Warrick facility will 

be based on the influence at Mammoth Cave, the refined modeling is proposed with the domain that is 

appropriate for refined modeling the visibility impacts from the Warrick sources on Mammoth Cave. 

The description of this domain, its characteristics and methodology used in the refined modeling is 

described in the next section 
 3-2 Screening Modeling

Table 3-1. Class I Areas within 500 km of Alcoa Warrick 

Class I Area Distance from 

Warrick (km) 

Mammoth Cave 120 

Mingo 268 

Sipsey 391 

Great Smoky Mountains 394 

Joyce Kilmer 401 

Cohutta 404 

Shining Rock 481 

Table 3-2. Monthly f(RH) Values Based on Area Centroids for Application with Visibility Method 6 

Class I area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Mammoth Cave 3.4 3.1 2.9 2.6 3.2 3.5 3.7 3.9 3.9 3.4 3.2 3.5 

Mingo 3.3 3.0 2.8 2.6 3.0 3.2 3.3 3.5 3.5 3.1 3.1 3.3 

Sipsey 3.4 3.1 2.9 2.8 3.3 3.7 3.9 3.9 3.9 3.6 3.3 3.4 

Great Smoky 3.3 3.0 2.9 2.7 3.2 3.9 3.8 4.0 4.2 3.8 3.3 3.4 

Joyce Kilmer 3.3 3.1 2.9 2.7 3.3 3.8 4.0 4.2 4.2 3.8 3.3 3.5 

Cohutta 3.3 3.1 3.0 2.8 3.4 3.8 4.0 4.2 4.2 3.8 3.4 3.5 

Shining Rock 3.3 3.0 2.9 2.7 3.4 3.9 4.1 4.5 4.4 3.8 3.3 3.4 

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (U.S EPA, 2003), Appendix A

Table 3-3. Average Natural Levels of Aerosol Components 

 East (μg/m3) 

Ammonium sulfate 0.23 

Ammonium nitrate 0.1 

Organic carbon 1.4 

Elemental carbon 0.02 

Soil 0.5 

Coarse Mass 3 

Source: Guidance for Estimating Natural Visibility Conditions 

Under the Regional Haze Rule (U.S EPA, 2003), Table 2-1
 3-3 Screening Modeling

Figure 3-1. Terrain elevations for the VISTAS CALMET 12-km regional domain. CALPUFF 

computational subdomain, the Class I areas and the locations of Warrick facilities are also 

shown. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

Sipsey

Cohutta

Mammoth Cave

Mingo

Great Smoky Mountains

Joyce Kilmer-Slickrock

Shining Rock

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Warrick

CALPUFF 

computational domain
 3-4 Screening Modeling

Table 3-4. Results of the Screening Simulations 

Class I Area 

(distance from 

Warrick (km)) Year 

Maximum 

Delta 

Bext 

98th 

Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th 

Percentile 

Delta 

Deciview 

 (%) 

(#days>5%, 

#days>10%) 

(%) (dv) 

(#days>0.5dv, 

#days>1dv) 

(dv) 

 

Mammoth Cave (120) 2001 94.68 (105,74) 60.12 6.662 (105,73) 4.708 

Mingo (268) 2001 71.84 (44,33) 39.44 5.414 (44,32) 3.325 

Sipsey (391) 2001 67.69 (53,25) 25.52 5.169 (52,24) 2.273 

Great Smoky (394) 2001 51.04 (40,20) 15.00 4.124 (37,18) 1.397 

Joyce Kilmer (401) 2001 43.27 (35,12) 11.66 3.596 (32,11) 1.103 

Cohutta (404) 2001 25.44 (37,11) 12.92 2.267 (35,10) 1.255 

Shining Rock (481) 2001 32.84 (21,10) 12.70 2.839 (20,10) 1.195 

 

Mammoth Cave (120) 2002 133.75 (89,62) 68.73 8.491 (87,59) 5.232 

Mingo (268) 2002 92.30 (67,47) 53.87 6.463 (66,47) 4.286 

Sipsey (391) 2002 67.10 (56,33) 31.72 5.134 (55,32) 2.755 

Great Smoky (394) 2002 32.51 (47,19) 16.46 2.815 (46,18) 1.524 

Joyce Kilmer (401) 2002 29.75 (38,18) 16.85 2.604 (37,17) 1.557 

Cohutta (404) 2002 82.52 (40,22) 20.89 6.017 (39,20) 1.903 

Shining Rock (481) 2002 13.97 (21,1) 7.49 1.307 (21,1) 0.725 

 

Mammoth Cave (120) 2003 150.13 (134,107) 85.01 9.168 (132,105) 6.153 

Mingo (268) 2003 142.82 (44,33) 30.98 8.872 (44,33) 2.699 

Sipsey (391) 2003 50.01 (61,38) 28.70 4.056 (61,38) 2.523 

Great Smoky (394) 2003 32.95 (59,29) 24.26 2.848 (58,28) 2.172 

Joyce Kilmer (401) 2003 37.78 (49,19) 22.79 3.205 (49,18) 2.053 

Cohutta (404) 2003 38.66 (57,24) 23.38 3.269 (56,22) 2.101 

Shining Rock (481) 2003 20.87 (30,13) 14.28 1.895 (30,12) 1.335 

 

Mammoth Cave (120) 2001-2003 150.13 (328,243) 72.38 9.168 (324,237 5.445 

Mingo (268) 2001-2003 142.82 (155,113) 43.39 8.872 (154,112) 3.604 

Sipsey (391) 2001-2003 67.69 (170,96) 29.31 5.169 (168,94) 2.570 

Great Smoky (394) 2001-2003 51.04 (146,68) 19.53 4.124 (141,64) 1.784 

Joyce Kilmer (401) 2001-2003 43.27 (122,49) 16.85 3.596 (118,46) 1.557 

Cohutta (404) 2001-2003 82.52 (134,57) 18.07 6.017 (130,52) 1.661 

Shining Rock (481) 2001-2003 32.84 (72,24) 11.70 2.839 (71,23) 1.107 
 4-1 Geophysical and Meteorological Data

4.0 GEOPHYSICAL AND METEOROLOGICAL DATA FOR REFINED MODELING 

4.1 Terrain 

Gridded terrain elevations for the proposed modeling domain are derived from 3 arc-second digital 

elevation models (DEMs) produced by the United States Geological Survey (USGS). Data are provided 

in files covering 1 degree by 1 degree blocks of latitude and longitude. The 1-degree DEMs are 

produced by the Defense Mapping Agency using cartographic and photographic sources. USGS 

1:250,000 scale topographic maps are the primary source of 1-degree DEMs. 

One degree DEM data consists of an array of 1201 by 1201 elevations referenced on the geographic 

(latitude/longitude) coordinate system of the World Geodetic System 1972 Datum. Elevations are in 

meters relative to mean sea level, and the spacing of the elevations along each profile is 3 arc-seconds, 

which corresponds to a spacing of approximately 90 meters. 

The proposed CALMET computational domain is located over Warrick County, Indiana. The modeling 

domain will cover an area of 225 km by 195 km (Figure 4-1) which includes Mammoth Cave National 

Park, located directly southeast of the source. The domain includes an adequate buffer of more than 

50 km in each direction both from the Class I area and the facility . The terrain is gently rolling, with 

terrain height increasing to the east of the model domain. A horizontal resolution of 1 km is proposed to 

represent the variations of the terrain elevations and land use in the area. Figure 4-1 shows contours of 

the terrain averaged to 1 km. The USGS elevation records located within each grid cell in the 

computational domain were averaged to produce a mean elevation at each grid point. Adequate 

representation of the important terrain features and valleys associated with the Class I area and the 

surrounding area are captured by the 225 x 195 grid cells, a workable number of cells. The CALPUFF 

computational domain will be the same as the CALMET domain. The domain extends beyond the Class 

I area in order to provide an adequate buffer zone at the boundaries, and to allow the effects of flow 

curvature and possible small-scale recirculation to be evaluated. 

4.2 Land Use 

The USGS Land Use data in the vicinity of the facility will be used to produce a gridded field of 

dominant Land Use categories. The land use data proposed for the analysis are the Composite Theme 

Grid land use data (CTG) from the USGS, at a resolution of 200 m. 

Land use data were processed to produce a 1 km resolution gridded field of fractional Land Use 

categories. The 37 USGS Land Use categories were then mapped into 14 CALMET LU categories. 

Surface properties such as albedo, Bowen ratio, roughness length, and leaf area index were computed 

proportionally to the fractional LU. The USGS Land Use categories are described in Table 4-1. 

Table 4-2 displays the 14 CALMET land use categories and their associated geophysical parameters. 

Figure 4-2 show the dominant land use categories to be used in the modeling. 
 4-2 Geophysical and Meteorological Data

Figure 4-1. Terrain contours (m MSL) at 1 km resolution for the 225 x 195 CALMET and CALPUFF 

computational domains. The Class I area, Mammoth Cave NP and the Alcoa Warrick 

facility are shown. 

400 450 500 550 600 650

UTM X Coordinate (km) - NAR-C

4050

4100

4150

4200

4250

UTM Y Coordinate (

km) - NAR-C

Alcoa Warrick Aluminum Plant

Mammoth Cave National Park

IN

TN

KY

IL

100

125

150

175

200

225

250

275

300

325

terrain

elevations

(m)
 4-3 Geophysical and Meteorological Data

Figure 4-2. Dominant land use categories at 1 km resolution on the 225 km x 195 km CALMET and 

CALPUFF model domains. Mammoth Cave National Park and the facility are also shown. 

400 450 500 550 600 650

UTM X Coordinate (km) - NAR-C

4050

4100

4150

4200

4250

UTM Y Coordinate (

km) - NAR-C

Alcoa Warrick Aluminum Plant

Mammoth Cave National Park

Urban land

Agricultural land

Range land

Forest land

Water

Wet land

Barren land

Tundra

Snow and Ice

10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

IN

TN

KY

IL
 4-4 Geophysical and Meteorological Data

4.3 Meteorological Data Base 

The wind fields in the modeling domain are expected to be variable. Depending on the location, some of 

the observational data is only representative of a small area around itself. The local terrain is expected to 

influence the local flow, much of the structure in the wind fields will be determined by CALMET using 

its diagnostic wind field module, rather than being driven by observations. 

The CALMET model requires meteorological information from the surface and upper air as well as 

geophysical information about the Land Use and terrain heights. Specifically, CALMET requires 

surface observations of wind speed, wind direction, temperature, cloud cover, ceiling height, surface 

pressure, relative humidity, and precipitation type (e.g., snow, rain, etc.). These variables are routinely 

measured at the National Weather Service (NWS) surface stations. The upper air data will include 

twice-daily observations of vertical profiles of wind speed, wind direction, temperature, and pressure. In 

addition, hourly precipitation measurements will be included in the modeling and are required for wet 

deposition calculations in CALPUFF. Three-dimensional gridded data from the prognostic numerical 

model MM5 are also included as well as RUC data for the 2003 modeling. Table 4-3 lists the types of 

observational and modeled data available that will be used in the modeling. There are ten surface 

meteorological stations that are proposed to be used, all located within or near the modeling domain 

(Table 4-4): Louisville Standiford, KY; Capitol City, KY; Louisville Bowman, KY; Owensboro, KY; 

Henderson City, KY; Fort Knox, KY; Evansville, KY; Huntingsburg, KY; Lawrenceville, KY; Fort 

Campbell, KY, and, Bowling Green, KY. The surface data will be extracted from the Integrated Surface 

Hourly Weather Observations (ISHWO) CD-roms (Volume 19 for 2001, Volume 23 for 2002) and 2003 

ISHWO DVD. Upper air data will be extracted from the FSL/NCDC Radiosonde Database at 

http://raob.fsl.noaa.gov/. The available upper air sites are Nashville, TN and Lincoln-Logan County, IL 

(Table 4-5). Both these sites are located well off the model domain. 

Approximately 16 precipitation stations are available for use in the modeling (Table 4-6). These data 

will be obtained from NCDC in TD3240 format. Figure 4-3, Figure 4-4 and Figure 4-5 show the 

locations and spatial coverage of all of these stations for 2001, 2002 and 2003. 
 4-5 Geophysical and Meteorological Data

Table 4-1. U.S. Geological Survey Land Use and Land Cover Classification System 

Level I Level II 

10 Urban or Built-up Land 11 

12 

13 

14 

15 

16 

17 

Residential 

Commercial and Services 

Industrial 

Transportation, Communications and Utilities 

Industrial and Commercial Complexes 

Mixed Urban or Built-up Land 

Other Urban or Built-up Land 

20 Agricultural Land 21 

22 

23 

24 

Cropland and Pasture 

Orchards, Groves, Vineyards, Nurseries, and 

 Ornamental Horticultural Areas 

Confined Feeding Operations 

Other Agricultural Land 

30 Rangeland 31 

32 

33 

Herbaceous Rangeland 

Shrub and Brush Rangeland 

Mixed Rangeland 

40 Forest Land 41 

42 

43 

Deciduous Forest Land 

Evergreen Forest Land 

Mixed Forest Land 

50 Water 51 

52 

53 

54 

55 

Streams and Canals 

Lakes 

Reservoirs 

Bays and Estuaries 

Oceans and Seas 

60 Wetland 61 

62 

Forested Wetland 

Nonforested Wetland 

70 Barren Land 71 

72 

73 

74 

75 

76 

77 

Dry Salt Flats 

Beaches 

Sandy Areas Other than Beaches 

Bare Exposed Rock 

Strip Mines, Quarries, and Gravel Pits 

Transitional Areas 

Mixed Barren Land 

80 Tundra 81 

82 

83 

84 

85 

Shrub and Brush Tundra 

Herbaceous Tundra 

Bare Ground 

Wet Tundra 

Mixed Tundra 

90 Perennial Snow or Ice 91 

92 

Perennial Snowfields 

Glaciers 
 4-6 Geophys

Table 4-2. Default CALMET Land Use Categories and Associated Geophysical Parameters Based on the U.S. Geologi

Classification System (14-Category System) 

Land Use Type Description Surface 

Roughness (m)

Albedo Bowen Ratio Soil Heat 

Flux Parameter

Anthropo

Heat Flux (

10 Urban or Built-up Land 1.0 0.18 1.5 .25 0.0 20 Agricultural Land - 

Unirrigated 

0.25 0.15 1.0 .15 0.0 

-20* Agricultural Land - Irrigated 0.25 0.15 0.5 .15 0.0 

30 Rangeland 0.05 0.25 1.0 .15 0.0 40 Forest Land 1.0 0.10 1.0 .15 0.0 50 Water 0.001 0.10 0.0 1.0 0.0 54 Small Water Body 0.001 0.10 0.0 1.0 0.0 55 Large Water Body 0.001 0.10 0.0 1.0 0.0 60 Wetland 1.0 0.10 0.5 .25 0.0 61 Forested Wetland 1.0 0.1 0.5 0.25 0.0 62 Nonforested Wetland 0.2 0.1 0.1 0.25 0.0 70 Barren Land 0.05 0.30 1.0 .15 0.0 80 Tundra .20 0.30 0.5 .15 0.0 90 Perennial Snow or Ice .05 0.70 0.5 .15 0.0 

* Negative values indicate "irrigated" land use 
 4-7 Geophysical and Meteorological Data 

Table 4-3. Meteorological Data Sources and Parameters Available 

Type of Dataset Frequency Source Parameters 

Surface obs. Hourly NWS/NCDC Wind speed, wind 

direction, temperature, 

ceiling height, cloud 

cover, relative humidity, 

surface pressure, 

precipitation type 

Upper Air Twice-daily NWS/NCDC Soundings of wind speed, 

wind direction, 

temperature, and pressure 

Precipitation Hourly NWS/NCDC Hourly precipitation 

amounts 

Modeled Profiles 

MM5 for 2001, 2002 

RUC data for 2003 

Hourly 

Hourly 

VISTAS 

NCEP 

Hourly, gridded fields of 

winds, temperature, 

pressure, and humidity and 

liquid water content on 12 

km grid for 2001 and 

2002. 

Same as MM5 above, but 

on 20 km grid for 2003. 
 4-8 Geophysical and Meteorological Data 

Table 4-4. NWS Hourly Surface Stations 

WMO INIT Station Name State Year Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

UTM X1

(km) 

UTM Y1

(km) 

724230 KSDF Louisville 

Standiford 

KY 01,02,03 38.18 85.73 146.6 611.232 4226.549 

724233 KFFT Capitol City Ap KY 01,02,03 38.18 84.90 245.0 683.933 4227.871 

724235 KLOU Louisville Bowman 

Fld 

KY 01,02,03 38.23 85.67 164.6 616.407 4232.171 

724237 KOWB Owensboro/Davies KY 01,02,03 37.73 87.17 124.0 485.020 4175.872 

724238 KEHR Henderson City KY 01,02,03 37.82 87.68 117.0 440.152 4186.062 

724240 KFTK Fort Knox Godman 

Ap 

KY 01,02,03 37.90 85.97 239.0 590.555 4195.220 

724320 KEVV Evansville Regional 

Ap 

KY 01,02,03 38.05 87.53 116.1 453.499 4211.495 

724365 KHNB Huntingburg KY 01,03 38.25 86.95 161.0 504.375 4233.555 

725342 KLWW Lawrenceville IL 01,02,03 38.77 87.60 131.0 447.877 4291.425 

744656 KFWC Fairfield IL 03 38.42 88.42 133.0 376.296 4253.035 

744659 KOLY Olney-Noble IL 03 38.72 88.18 147.0 397.154 4286.037 

746710 KHOP Fort Campbell Ap KY 01,02,03 36.67 87.48 173.1 455.320 4058.382 

746716 KBWG Bowling Green 

Warren 

KY 01,02,03 36.98 86.43 160.9 550.730 4092.806 

_______ 

1 Datum is NAD83, UTM Zone 16. 

Table 4-5. Upper Air Stations 

# Station Name WBAN# Latitude Longitude UTM X1

 UTM Y1 Elevation 

 (deg) (deg) (km) (km) (m) 

1 Lincoln-Logan 

County, Ap, IL 04833 36.25 86.57 301.538 4447.009 180.0 

2 Nashville, TN 13897 40.15 89.33 538.632 4011.764 178.0 

_______ 

1 Datum is NAD83, UTM Zone 16. 
 4-9 Geophysical and Meteorological Data 

Table 4-6. Hourly NWS Precipitation Stations 

Station Name Station ID Year of Longitude Latitude UTM X1 UTM Y1

 Data (deg) (deg) (km) (km)

 

Newburgh Lock & Dam, IN 126151 03 37.93 87.37 467.484 4198.113 

JT Myers Locks & Dam, IN 128967 02,03 37.8 87.99 412.844 4184.087 

Cannelton, IN 121256 01 37.9 86.63 532.529 4194.785 

Calhoun Lock, KY 151227 01,02,03 37.53 87.27 476.144 4153.704 

Custer 4 SE, KY 151980 01,02,03 37.72 86.22 568.742 4175.036 

Dundee 2 NE, KY 152358 02,03 37.58 86.78 519.425 4159.240 

Fordsville, KY 152979 01,02,03 37.63 86.72 524.703 4165.911 

Herndon 5 S, KY 153798 01,02,03 36.67 87.58 449.959 4058.412 

Hodgenville Lincoln, KY KY 153929 01,03 37.53 85.73 611.329 4154.416 

Lebanon 5 S, KY 154650 01,02 37.52 85.3 650.229 4153.918 

Madisonville, KY 155067 01,03 37.35 87.52 453.945 4133.827 

Munfordville 5 NW, KY 155684 01,02 37.33 85.95 593.021 4131.998 

Princeton 1 SE, KY 156580 01,03 37.12 87.87 422.712 4108.539 

Scottsville 3 SSW, KY 157215 01,02 36.73 86.22 569.656 4064.095 

Willisburg, KY 158719 01,02,03 37.8 85.12 665.514 4185.290 

Woodbury, KY 158824 01,02,03 37.18 86.63 532.843 4114.905 

Carthage, TN 401480 03 36.25 85.95 594.336 4012.189 

Celina, TN 401561 01,02,03 36.54 85.46 637.849 4044.948 

Lebanon, TN 405108 03 36.23 86.32 561.109 4009.674 

Springfield Exp Stn, TN 408562 01,02,03 36.47 86.85 513.439 4036.091 

_______ 

1 Datum is NAD83, UTM Zone 16. 
 4-10 Geophysical and Meteorological Data 

Figure 4-3. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the refined 

2001 modeling. Mammoth Cave National Park and the facility are also shown. 
 4-11 Geophysical and Meteorological Data 

Figure 4-4. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the refined 

2002 modeling. Mammoth Cave National Park and the facility are also shown. 
 4-12 Geophysical and Meteorological Data 

Figure 4-5. Plot of all the surface, upper air, RUC data and precipitation stations to be used in the 

refined 2003 modeling. Mammoth Cave National Park and the facility are also shown. 
 4-13 Geophysical and Meteorological Data 

4.4 Air Quality Monitoring Data 

CALPUFF uses hourly ozone concentration measurements in the chemical transformation rates (SO2 to 

SO4, NOx to HNO3/NO3). The ambient ozone measurements are used in determining SO2 loss rates due 

to chemical transformation to sulfate and in determining NOx loss rates to nitrate. Ambient ozone 

monitoring data for 2001, 2002 and 2003 will be extracted from the U.S. EPA AIRS and CASTNet 

networks and will be used to develop hourly ozone monitoring data files for the each year of the 

modeling analysis. A total of ~35 monitoring stations, listed in Table 4-7, are available for use in the 

modeling (see Figure 4-6, Figure 4-7 and Figure 4-8 which show the locations of each of the available 

stations for each year to be modeled.) This is a refinement to the LADCO procedure in that spatially 

varying hourly ozone data are used in the modeling instead of the monthly ozone values constant in 

space recommended in Table 2 of LADCO protocol. 

A constant ammonia concentration of 0.5 parts per billion (ppb) will be used in the modeling. If a more 

refined treatment of ammonia is justified, the use of time-varying ammonia concentrations may be 

requested. 
 4-14 Geophysical and Meteorological Data 

Table 4-7. Ozone Stations 

Network Year ID 

Latitude 

(deg) 

Longitude 

(deg) 

UTM X1

(km) 

UTM Y1

(km) 

AIRS 01,02,03 170650001 37.99822 -88.49311 368.898 4206.676 

AIRS 01,02,03 180190003 38.37695 -85.69028 614.405 4248.458 

AIRS 01,02,03 180431004 38.30806 -85.83417 601.933 4240.645 

AIRS 01,02,03 180510011 38.42525 -87.46589 459.333 4253.108 

AIRS 01,02,03 181290003 38.00528 -87.71833 436.935 4206.651 

AIRS 01,02,03 181630013 38.11389 -87.53694 452.93 4218.594 

AIRS 01,02,03 181730002 37.93750 -87.31416 472.393 4198.934 

AIRS 01,02,03 181730008 38.05195 -87.27834 475.58 4211.622 

AIRS 01,02,03 181730009 38.19444 -87.34139 470.105 4227.451 

AIRS 01,02,03 210470006 36.91167 -87.32361 471.173 4085.131 

AIRS 01,02,03 210590005 37.78083 -87.07555 493.347 4181.508 

AIRS 01,02,03 210610501 37.13139 -86.14806 575.675 4109.796 

AIRS 01,02,03 210830003 36.89917 -88.49361 366.921 4084.737 

AIRS 01,02,03 210910012 37.93889 -86.89694 509.056 4199.047 

AIRS 01,02,03 210930006 37.70639 -85.85167 601.226 4173.867 

AIRS 01,02,03 211010014 37.87139 -87.46333 459.249 4191.653 

AIRS 01,02,03 211110027 38.13722 -85.57833 624.593 4222.001 

AIRS 01,02,03 211110051 38.06083 -85.89611 596.843 4213.146 

AIRS 01,02,03 211111021 38.26361 -85.71167 612.712 4235.855 

AIRS 01,02,03 211390003 37.15556 -88.39306 376.297 4113.046 

AIRS 01,02,03 211490001 37.60639 -87.25389 477.590 4162.182 

AIRS 02 211771004 37.22729 -87.15833 485.954 4120.099 

AIRS 01,02,03 211850004 38.39861 -85.44334 635.936 4251.196 

AIRS 01,02,03 212130004 36.70861 -86.56639 538.729 4062.645 

AIRS 01,02,03 212210013 36.90139 -88.01361 409.693 4084.422 

AIRS 01,02,03 212270008 37.03667 -86.25056 566.653 4099.211 

AIRS 01,02,03 471410004 36.20500 -85.39945 643.89 4007.884 

AIRS 01,02,03 471650007 36.29778 -86.65278 531.178 4017.043 

AIRS 01,02,03 471650101 36.45389 -86.56416 539.056 4034.391 

CASTNet 01,02,03 CDZ171 36.7841 -87.8499 424.165 4071.259 

CASTNet 01,02,03 VIN140 38.7408 -87.4853 457.824 4288.125 

CASTNet 02,03 MAC426 37.2806 -86.2639 565.254 4126.255 

CASTNet 01,02,03 MCK131 37.7046 -85.0485 672.0299 4174.833 

CASTNet 01.02,03 MCK231 37.7046 -85.0485 672.0299 4174.833 

 

_______ 

1 Datum is NAD83, UTM Zone 16. 
 4-15 Geophysical and Meteorological Data 

Figure 4-6. Plot of all the ozone stations, both CASTNet and AIRS proposed for the refined 2001 

modeling. Mammoth Cave National Park and the facility are also shown. 
 4-16 Geophysical and Meteorological Data 

Figure 4-7. Plot of all the ozone stations, both CASTNet and AIRS proposed for the refined 2002 

modeling. Mammoth Cave National Park and the facility are also shown. 
 4-17 Geophysical and Meteorological Data 

Figure 4-8. Plot of all the ozone stations, both CASTNet and AIRS proposed for the refined 2003 

modeling. Mammoth Cave National Park and the facility are also shown. 
5-1 Air Quality Modeling Methodology 

5.0 AIR QUALITY MODELING METHODOLOGY 

5.1 Model Selection 

The terrain of the region, the large source-receptor distances, and the importance of chemical 

transformation, wet deposition, and dry deposition are important factors in the modeling that are treated 

in the recommended modeling approach using the CALPUFF model (Scire et al., 2000a,b) for the 

BART analysis for Mammoth Cave National Park. CALPUFF and its meteorological model CALMET, 

are designed to handle the complexities posed by complex terrain, the long source receptor distances, 

chemical transformation and deposition, and other issues related to Class I impacts. The U.S. 

Environmental Protection Agency (EPA) has recommended CALPUFF as the preferred model for 

BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline Model 

for Class I impact assessments and other long range transport applications and on a case-by-case basis 

for near-field applications involving complex flows (U.S. EPA, 2003a). CALPUFF is also 

recommended by both the Federal Land Managers Air Quality Workgroup (FLAG, 2000) and the 

Interagency Workgroup on Air Quality Modeling (U.S. EPA, 1998). CALPUFF is also recommended 

by the draft revised FLAG procedures (FLAG (2008). The modeling simulations will be using the EPA 

regulatory version of the CALPUFF modeling system (Version 5.8 series). 

CALMET is a diagnostic meteorological model that produces three-dimensional wind and temperature 

fields and two-dimensional fields of mixing heights and other meteorological fields. It contains slope 

flow effects, terrain channeling, and kinematic effects of terrain. CALPUFF is a non-steady-state 

Gaussian puff model. It includes algorithms for building downwash effects as well as chemical 

transformation, wet deposition, and dry deposition. One capability of CALPUFF not found in many 

specialized models such as CTDMPLUS is the ability to treat the combined effects of multiple 

processes (e.g., building downwash effects in complex terrain; dry deposition and overwater dispersion, 

etc.). A complete summary of the capabilities and features of CALMET and CALPUFF is provided in 

Sections 4.1.1 and 4.1.2. 

5.1.1 Major Features of CALMET 

The CALMET meteorological model consists of a diagnostic wind field module and 

micrometeorological modules for overwater and overland boundary layers. When using large domains, 

the user has the option to adjust input winds to a Lambert Conformal Projection coordinate system to 

account for Earth's curvature. The diagnostic wind field module uses a two-step approach to the 

computation of the wind fields (Douglas and Kessler, 1988). In the first step, an initial-guess wind field 

is adjusted for kinematic effects of terrain, slope flows, and terrain blocking effects to produce a Step 1 

wind field. The second step consists of an objective analysis procedure to introduce observational data 

into the Step 1 wind field to produce a final wind field. 

The major features and options of the meteorological model are summarized in Table 5-1. The 

techniques used in the CALMET model are briefly described below. 
5-2 Air Quality Modeling Methodology 

Step 1 Wind Field 

Kinematic Effects of Terrain: The approach of Liu and Yocke (1980) is used to evaluate kinematic 

terrain effects. The domain-scale winds are used to compute a terrain-forced vertical velocity, subject to 

an exponential, stability-dependent decay function. The kinematic effects of terrain on the horizontal 

wind components are evaluated by applying a divergence-minimization scheme to the initial guess wind 

field. The divergence minimization scheme is applied iteratively until the three-dimensional divergence 

is less than a threshold value. 

Slope Flows: The slope flow algorithm in CALMET has recently been upgraded (Scire and Robe, 

1997). It is based on the shooting flow algorithm of Mahrt (1982). This scheme includes both advectivegravity and equilibrium flow regimes. At night, the slope flow model parameterizes the flow down the 

sides of the valley walls into the floor of the valley, and during the day, upslope flows are 

parameterized. The magnitude of the slope flow depends on the local surface sensible heat flux and 

local terrain gradients. The slope flow wind components are added to the wind field adjusted for 

kinematic effects. 

Blocking Effects: The thermodynamic blocking effects of terrain on the wind flow are parameterized in 

terms of the local Froude number (Allwine and Whiteman, 1985). If the Froude number at a particular 

grid point is less than a critical value and the wind has an uphill component, the wind direction is 

adjusted to be tangent to the terrain. 

Step 2 Wind Field 

The wind field resulting from the adjustments described above of the initial-guess wind is the Step 1 

wind field. The second step of the procedure involves the introduction of observational data into the 

Step 1 wind field through an objective analysis procedure. An inverse-distance squared interpolation 

scheme is used which weighs observational data heavily in the vicinity of the observational station, 

while the Step 1 wind field dominates the interpolated wind field in regions with no observational data. 

The resulting wind field is subject to smoothing, an optional adjustment of vertical velocities based on 

the O'Brien (1970) method, and divergence minimization to produce a final Step 2 wind field. 
5-3 Air Quality Modeling Methodology 

Table 5-1. Major Features of the CALMET Meteorological Model 

Boundary Layer Modules of CALMET 

 - Overland Boundary Layer - Energy Balance Method 

 - Overwater Boundary Layer - Profile Method 

 - Produces Gridded Fields of: 

 - Surface Friction Velocity 

 - Convective Velocity Scale 

 - Monin-Obukhov Length 

 - Mixing Height 

 - PGT Stability Class 

 - Air Temperature (3-D) 

 - Precipitation Rate 

• Diagnostic Wind Field Module of CALMET

 - Slope Flows 

 - Kinematic Terrain Effects 

 - Terrain Blocking Effects 

 - Divergence Minimization 

 - Produces Gridded Fields of U, V, W Wind Components 

 - Inputs Include Domain-Scale Winds, Observations, and 

 (optionally) Coarse-Grid Prognostic Model Winds 

 - Lambert Conformal Projection Capability 
5-4 Air Quality Modeling Methodology 

CALMET Boundary Layer Models 

The CALMET model contains two boundary layer models for application to overland and overwater 

grid cells. 

Overland Boundary Layer Model: Over land surfaces, the energy balance method of Holtslag and van 

Ulden (1983) is used to compute hourly gridded fields of the sensible heat flux, surface friction velocity, 

Monin-Obukhov length, and convective velocity scale. Mixing heights are determined from the 

computed hourly surface heat fluxes and observed temperature soundings using a modified Carson 

(1973) method based on Maul (1980). Gridded fields of Pasquill-Gifford-Turner (PGT) stability class 

and optional hourly precipitation rates are also determined by the model. 

Overwater Boundary Layer Model: The aerodynamic and thermal properties of water surfaces suggest 

that a different method is best suited for calculating the boundary layer parameters in the marine 

environment. A profile technique, using air-sea temperature differences, is used in CALMET to 

compute the micrometeorological parameters in the marine boundary layer. 

An upwind-looking spatial averaging scheme is optionally applied to the mixing heights and 

3 dimensional temperature fields in order to account for important advective effects. 

5.1.2 Major Features of CALPUFF 

By its puff-based formulation and through the use of three-dimensional meteorological data developed 

by the CALMET meteorological model, CALPUFF can simulate the effects of time- and space-varying 

meteorological conditions on pollutant transport from sources in complex terrain. The major features 

and options of the CALPUFF model are summarized in Table 5-2. Some of the technical algorithms are 

briefly described below. 

Complex Terrain: The effects of complex terrain on puff transport are derived from the CALMET 

winds. In addition, puff-terrain interactions at gridded and discrete receptor locations are simulated 

using one of two algorithms that modify the puff-height (either that of ISCST3 or a general "plume path 

coefficient" adjustment), or an algorithm that simulates enhanced vertical dispersion derived from the 

weakly-stratified flow and dispersion module of the Complex Terrain Dispersion Model (CTDMPLUS) 

(Perry et al., 1989). The puff-height adjustment algorithms rely on the receptor elevation (relative to the 

elevation at the source) and the height of the puff above the surface. The enhanced dispersion 

adjustment relies on the slope of the gridded terrain in the direction of transport during the time step. 

Subgrid Scale Complex Terrain (CTSG): An optional module in CALPUFF, CTSG treats terrain 

features that are not resolved by the gridded terrain field, and is based on the Complex Terrain 

Dispersion Model (CTDMPLUS) (Perry et al., 1989). Plume impingement on subgrid-scale hills is 

evaluated at the CTSG subgroup of receptors using a dividing streamline height (Hd) to determine 

which pollutant material is deflected around the sides of a hill (below Hd) and which material is 

advected over the hill (above Hd). The local flow (near the feature) used to define Hd is taken from the 
5-5 Air Quality Modeling Methodology 

gridded CALMET fields. As in CTDMPLUS, each feature is modeled in isolation with its own set of 

receptors. 

Puff Sampling Functions: A set of accurate and computationally efficient puff sampling routines are 

included in CALPUFF which solve many of the computational difficulties encountered when applying a 

puff model to near-field releases. For near-field applications during rapidly-varying meteorological 

conditions, an elongated puff (slug) sampling function may be used. An integrated puff approach may 

be used during less demanding conditions. Both techniques reproduce continuous plume results under 

the appropriate steady state conditions. 

Building Downwash: The Huber-Snyder and Schulman-Scire downwash models are both incorporated 

into CALPUFF as is the PRIME building downwash model. An option is provided to use either model 

for all stacks, or make the choice on a stack-by-stack and wind sector-by-wind sector basis. Both 

algorithms have been implemented in such a way as to allow the use of wind direction specific building 

dimensions. 

Dispersion Coefficients: Several options are provided in CALPUFF for the computation of dispersion 

coefficients, including the use of turbulence measurements (σv and σw), the use of similarity theory to 

estimate σv and σw from modeled surface heat and momentum fluxes, or the use of Pasquill-Gifford 

(PG) or McElroy-Pooler (MP) dispersion coefficients, or dispersion equations based on the Complex 

Terrain Dispersion Model (CTDM). Options are provided to apply an averaging time correction or 

surface roughness length adjustments to the PG coefficients. 

Overwater and Coastal Interaction Effects: Because the CALMET meteorological model contains 

both overwater and overland boundary layer algorithms, the effects of water bodies on plume transport, 

dispersion, and deposition can be simulated with CALPUFF. The puff formulation of CALPUFF is 

designed to handle spatial changes in meteorological and dispersion conditions, including the abrupt 

changes that occur at the coastline of a major body of water. 

Dry Deposition: A full resistance model is provided in CALPUFF for the computation of dry 

deposition rates of gases and particulate matter as a function of geophysical parameters, meteorological 

conditions, and pollutant species. Options are provided to allow user-specified, diurnally varying 

deposition velocities to be used for one or more pollutants instead of the resistance model (e.g., for 

sensitivity testing) or to by-pass the dry deposition model completely. For particles, source-specific 

mass distributions may be provided for use in the resistance model. 

Wind Shear Effects: CALPUFF contains an optional puff splitting algorithm that allows vertical wind 

shear effects across individual puffs to be simulated. Differential rates of dispersion and transport 

among the "new" puffs generated from the original, well-mixed puff can substantially increase the 

effective rate of horizontal spread of the material. 
5-6 Air Quality Modeling Methodology 

Wet Deposition: An empirical scavenging coefficient approach is used in CALPUFF to compute the 

depletion and wet deposition fluxes due to precipitation scavenging. The scavenging coefficients are 

specified as a function of the pollutant and precipitation type (i.e., frozen vs. liquid precipitation). 

Chemical Transformation: CALPUFF includes options for parameterizing chemical transformation 

effects using the five species scheme (SO2, SO=

4, NOx, HNO3, and NO−3) employed in the MESOPUFF II 

model or a set of user-specified, diurnally-varying transformation rates. 
5-7 Air Quality Modeling Methodology 

Table 5-2. Major Features of the CALPUFF Model 

 • Source types

 - Point sources (constant or variable emissions) 

 - Line sources (constant or variable emissions) 

 - Volume sources (constant or variable emissions) 

 - Area sources (constant or variable emissions) 

 • Non-steady-state emissions and meteorological conditions

 - Gridded 3-D fields of meteorological variables (winds, temperature) 

 - Spatially-variable fields of mixing height, friction velocity, convective velocity scale, 

 Monin-Obukhov length, precipitation rate 

 - Vertically and horizontally-varying turbulence and dispersion rates 

 - Time-dependent source and emissions data for point, area, and volume sources 

 - Temporal or wind-dependent scaling factors for emission rates, for all source types 

 • Interface to the Emissions Production Model (EPM)

 - Time-varying heat flux and emissions from controlled burns and wildfires 

 • Efficient sampling functions

 - Integrated puff formulation 

 - Elongated puff (slug) formulation 

 • Dispersion coefficient (σy, σz) options

 - Direct measurements of σv and σw

 - Estimated values of σv and σw based on similarity theory 

 - Pasquill-Gifford (PG) dispersion coefficients (rural areas) 

 - McElroy-Pooler (MP) dispersion coefficients (urban areas) 

 - CTDM dispersion coefficients (neutral/stable) 

 • Vertical wind shear

 - Puff splitting 

 - Differential advection and dispersion 

 • Plume rise

 - Buoyant and momentum rise 

 - Stack tip effects 

 - Building downwash effects 

 - Partial penetration 

 - Vertical wind shear 

 • Building downwash

 - Huber-Snyder method 

 - Schulman-Scire method 

 - PRIME method 

 • Complex terrain

 - Steering effects in CALMET wind field 

 - Optional puff height adjustment: ISC3 or "plume path coefficient" 

 - Optional enhanced vertical dispersion (neutral/weakly stable flow in CTDMPLUS) 
5-8 Air Quality Modeling Methodology 

Table 5-2. Major Features of the CALPUFF Model (Cont’d) 

 • Subgrid scale complex terrain (CTSG option)

 - Dividing streamline, Hd, as in CTDMPLUS: 

 - Above Hd, material flows over the hill and experiences altered diffusion rates 

 - Below Hd, material deflects around the hill, splits, and wraps around the hill 

 • Dry Deposition 

 - Gases and particulate matter 

 - Three options: 

 - Full treatment of space and time variations of deposition with a resistance model 

 - User-specified diurnal cycles for each pollutant 

 - No dry deposition 

 • Overwater and coastal interaction effects

 - Overwater boundary layer parameters 

 - Abrupt change in meteorological conditions, plume dispersion at coastal boundary 

 - Plume fumigation 

 • Chemical transformation options

 - Pseudo-first-order chemical mechanism for SO2, SO=

4, NOx, HNO3, and NO−3 

(MESOPUFF II method) 

- Pseudo-first-order chemical mechanism for SO2, SO=

4, NO, NO2 HNO3, and NO−3 (RIVAD/ARM3 

method) 

 - User-specified diurnal cycles of transformation rates 

 - No chemical conversion 

 • Wet Removal

 - Scavenging coefficient approach 

 - Removal rate a function of precipitation intensity and precipitation type 

 • Graphical User Interface

 - Point-and-click model setup and data input 

 - Enhanced error checking of model inputs 

 - On-line Help files 

 • Interface Utilities

 - Scan ISCST3 and AUSPLUME meteorological data files for problems 

 - Translate ISCST3 and AUSPLUME input files to CALPUFF input format
5-9 Air Quality Modeling Methodology 

5.2 Modeling Domain Configuration 

CALMET and CALPUFF use terrain-following coordinates. In order to cover a large enough area, a 

modeling domain of 225 x 195 grid cells, uniform in the horizontal with a spatial resolution of 1 km is 

proposed. In the vertical, a stretched grid is proposed with finer resolution in the lower layers and 

somewhat coarser resolution aloft thus allowing adequate representation of the mixed layer. The ten 

vertical levels were centered at: 10, 30, 60, 120, 240, 480, 820, 1250, 1850 and 2600 meters. 

5.3 Meteorological Modeling Options 

Initial Guess Field 

MM5 data and RUC data will be used to define the initial guess field for the CALMET simulations. For 

2001 and 2002 hourly MM5 data with a grid spacing of 12 km and 34 vertical levels will be used as the 

initial guess wind field. RUC data with a grid spacing of 20 km and 50 vertical levels will be used as the 

initial guess wind field for 2003. 

This data set provides better resolution prognostic data from the 36 km MM5 data set for 2002-2004 in 

LADCO (2006). The higher resolution of the prognostic meteorological data set was the driving force 

for choosing the years 2001-2003 over the 2002-2004 period from LADCO. 

Step 1 Field: Terrain Effects 

In developing the Step 1 wind field, CALMET adjusts the initial guess field to reflect kinematic effects 

of the terrain, slope flows and blocking effects. Slope flows are a function of the local slope and altitude 

of the nearest crest. The crest is defined as the highest peak within a radius TERRAD around each grid 

point. A value of TERRAD of 10 km was determined based on an analysis of the scale of the terrain and 

will be used in the CALMET simulations. The Step 1 field produces a flow field consistent with the 

fine-scale CALMET terrain resolution (1 km). 

Step 2 Field: Objective Analysis 

In Step 2, observations are incorporated into the Step 1 wind field to produce a final wind field. Each 

observation site influences the final wind field within a radius of influence (parameters RMAX1 at the 

surface and RMAX2 aloft). Observations and Step 1 field are weighted by means of parameters R1 at 

the surface and R2 aloft: at a distance R1 from an observation site, the Step 1 wind field and the surface 

observations are weighted equally. RMAX1 and RMAX2 will be set to large values (40 km), while 

moderate values of R1 and R2 (10 km) will be used in order to allow diagnostically-generated terrain 

effects to be retained in the final wind fields. 

5.4 CALPUFF Computational Domain and Receptors 

CALPUFF will be run for three years, 2001, 2002 and 2003. A gridded field of discrete receptors will 

be located within the boundaries of the Mammoth Cave National Park. 
5-10 Air Quality Modeling Methodology 

The CALPUFF computational domain is the same as the CALMET computational domain. The 

modeling domain include a buffer zone of at least 50 km from the source and beyond the borders of the 

Class I area. This minimizes the edge effects and allow pollutants involved in flow reversals to be 

brought back into the Class I areas. CALPUFF will be run for three years, 2001, 2002 and 2003. 

The receptor locations along with receptor elevations were available from the National Park Service 

(NPS). This gridded field of discrete receptors will be used and is located within the boundaries of the 

Mammoth Cave National Park. 

5.5 Dispersion Modeling Options 

The CALPUFF simulations will be conducted using the following model options: 

 - Gaussian near-field distribution 

 - Transitional plume rise 

 - Stack tip downwash 

 - Pasquill-Gifford (PG) dispersion coefficients (rural areas) and 

McElroy-Pooler coefficients (urban areas) 

 - Transition of σy to time-dependent (Heffter) growth rates 

 - Partial plume path adjustment for terrain 

 - Wet deposition, dry deposition, and chemical transformation will be considered. 

Two important computational parameters in CALPUFF are XMXLEN (maximum length of an emitted 

puff, in grid units) and XSAMLEN (maximum travel distance of a puff, in grid units, during one time 

step). Both of these variables will be set to 1.0 in the CALPUFF simulations in order to allow the strong 

wind channeling effects to be accounted for in the puff trajectory calculations. The first parameter 

ensures that the length of an emitted puff does not become so large so that it cannot respond to changes 

in the wind field on the scale of the meteorological grid. The model automatically increases the 

frequency of puff releases to ensure the length of a single puff is not larger than the grid size. The 

second parameter decreases the internal time step to ensure the travel distance during one time step does 

not exceed the grid size. 

The partial plume path adjustment option will be used in CALPUFF for this analysis (MCTADJ=3). 

The CALMET wind field incorporates the effect of the terrain on the plume trajectories. The plume path 

coefficient is used to characterize the local effect on ground-level concentrations. The default plume 

path coefficients (PPC) used for this analysis are listed below: 

Stability Class A B C D E F 

PPC 0.5 0.5 0.5 0.5 0.35 0.35 

Deposition and chemical transformation effects will be modeled using the default dry deposition model, 

the scavenging coefficient wet removal module, and the default chemical transformation mechanism. 
5-11 Air Quality Modeling Methodology 

Eleven species will be modeled with CALPUFF for this analysis: SO2, SO4, NOx, HNO3, NO3, and six 

subcategories of PM10, (PM800, PM425, PM187, PM112, PM081, PM056). Of these eleven species, five are 

emitted by the project sources: SO2, SO4, NOx, PM10, and NH3. The chemical mechanism computes 

transformation rates of SO2 to SO4 and NOx to NO3/HNO3. Hourly measured ozone concentrations will 

be provided in an external OZONE.DAT file for use with the chemical transformation module. These 

ozone concentrations, along with radiation intensity, will be used as surrogates for the OH concentration 

during the day when the gas phase free radical chemistry was active. 

To allow for flexibility each source will be modeled individually and their source contributions will be 

summed at the end. 

5.6 Visibility Calculations 

Calculations of the impact of the simulated plume particulate matter component concentrations on light 

extinction is carried out in the CALPOST postprocessor. The annual average values will be used for the 

natural background values. The equation used is the usual IMPROVE/EPA equation which is applied to 

determine the change in light extinction due to changes in component concentrations. Using the 

notations of CALPOST, the formula is the following: 

Bext = 3f(RH)[(NH4)2SO4] + 3f(RH)[NH4NO3] + 

4[OC] + 1[Soil] + 0.6[Coarse Mass] +10[EC] + bray 

The concentrations, in square brackets, are in μg/m3

 and bext is in units of Mm-1. The Rayleigh scattering 

term (bray) has a default value of 10 Mm-1, as recommended in EPA Guidance for Estimating Natural 

Visibility Conditions Under the Regional Haze Program (U.S. EPA, 2003b). Note that organic carbon 

(OC) consists of condensable particulates which are assumed to be split evenly between the lowest two 

particle size categories. Soil is fine particulates which is defined as PM2.5. These species were created 

through scaling and summing of the CALPUFF output files using the POSTUTIL program. 

As a refinement to this analysis, a new IMPROVE algorithm may be used in the visibility analysis. The 

new IMPROVE algorithm includes revisions to the factor used to calculate organic mass from the 

measured organic carbon, the addition of a term for sea salt light scattering; revised dry extinction 

efficiencies for inorganic (e.g., sulfate and nitrate) and organic constituents that may vary depending on 

the measured concentrations; new relative humidity adjustment functions (f(RH)), to be technically 

consistent with the newly selected dry efficiency terms for the hygroscopic components. 

The haze index (HI) is calculated from the extinction coefficient via the following formula: 

HI = 10 ln(bext/10) 

where HI is in units of deciviews (dv) and bext is in Mm-1. The impact of a source is determined by 

comparing HI for estimated natural background conditions with the impact of the source and without the 

impact of the source. 
5-12 Air Quality Modeling Methodology 

CALPOST Method 6 will be used to compute the extinction change in deciviews consistent with the 

procedures outlined in the LADCO (2006) modeling protocol 

A monthly background concentration must be entered into the CALPOST input control file. The annual 

average natural visibility conditions for Mammoth Cave will be used. Annual background 

concentrations for the eastern United States are give in the Guidance for Estimating Natural Visibility 

Conditions in Table 2-1 (U.S. EPA, 2003b), and are also provided in Table 5-3 below. These 

background concentrations are entered in CALPOST. 

Table 5-4 provides the monthly f(RH) values based on the centroid of the Class I area as recommended 

by EPA for application of Method 6. The monthly f(RH) values for each month are extracted from 

Appendix A of Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule 

(2003). 

The 8th highest (98th percentile) predicted light extinction change value expressed in deciviews will then 

be compared to the threshold value of 0.5 deciviews. 

Table 5-3. Background Natural Visibility Concentrations for the Eastern United States 

 East (μg/m3) 

Ammonium sulfate 0.23 

Ammonium nitrate 0.1 

Organic carbon 1.4 

Elemental carbon 0.02 

Soil 0.5 

Coarse Mass 3 

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (2003), Table 2-1

Table 5-4. Monthly f(RH) Values for Mammoth Cave Based on the Area Centroid 

Class I area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Mammoth Cave NP 3.4 3.1 2.9 2.6 3.2 3.5 3.7 3.9 3.9 3.4 3.2 3.5 

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (2003), Appendix A

5.7 Modeling Products 

The change in light extinction relative to the natural background due to sulfur dioxide, particulate matter 

and nitrogen oxides from the BART-eligible sources will be computed. BART methodology with 

CALPOST Method 6 and 98th percentile day results will be used to determine light extinction. The light 
5-13 Air Quality Modeling Methodology 

extinction impacts at Mammoth Cave will be presented for each modeled year in units of change in 

deciview, as well as for a full three-year period. 
 6-1 References 

6.0 REFERENCES 

Allwine, K.J. and C.D. Whiteman, 1985: MELSAR: A mesoscale air quality model for complex terrain: 

Volume 1--Overview, technical description and user's guide. Pacific Northwest Laboratory, 

Richland, Washington. 

Carson, D.J., 1973: The development of a dry, inversion-capped, convectively unstable boundary layer. 

Quart. J. Roy. Meteor. Soc., 99, 450-467. 

Douglas, S. and R. Kessler, 1988: User's guide to the diagnostic wind model. California Air Resources 

Board, Sacramento, CA. 

FLAG, 2000. Federal Land Manager' Air Quality Related Values Workgroup (FLAG). Phase I Report. 

U.S. Forest Service, National Park Service, U.S. Fish and Wildlife Service. 

FLAG, 2008. Federal Land Manager' Air Quality Related Values Workgroup (FLAG). Phase I Report 

(Revised). Draft report dated June 27, 2008. U.S. Forest Service, National Park Service, U.S. 

Fish and Wildlife Service. 

Holtslag, A.A.M. and A.P. van Ulden, 1983: A simple scheme for daytime estimates of the surface 

fluxes from routine weather data. J. Clim. and Appl. Meteor., 22, 517-529. 

Liu, M.K. and M. A. Yocke, 1980: Siting of wind turbine generators in complex terrain. J. Energy, 4, 

10:16. 

Lake Michigan Air Directors Consortium (LADCO), 2006: Single Source Modeling to Support 

Regional Haze BART Modeling Protocol. March 21, 2006. Available from 

http://www.in.gov/idem/files/BART_protocol.pdf 

Mahrt, L., 1982: Momentum Balance of Gravity Flows. Journal of Atmos. Sci., 39, 2701-2711. 

Maul, P.R., 1980: Atmospheric transport of sulfur compound pollutants. Central Electricity Generating 

Bureau MID/SSD/80/0026/R. Nottingham, England. 

O'Brien, J.J., 1970: A note on the vertical structure of the eddy exchange coefficient in the planetary 

boundary layer. J. Atmos. Sci., 27, 1213-1215. 

Perry, S.G., D.J. Burns, L.H. Adams, R.J. Paine, M.G. Dennis, M.T. Mills, D.G. Strimaitis, R.J. 

Yamartino, E.M. Insley, 1989: User's Guide to the Complex Terrain Dispersion Model Plus 

Algorithms for Unstable Situations (CTDMPLUS) Volume 1: Model Description and User 

Instructions. EPA/600/8-89/041, U.S. Environmental Protection Agency, Research Triangle 

Park, NC. 

Scire, J.S. and F.R. Robe, 1997: Fine-Scale Application of the CALMET Meteorological Model to a 

Complex Terrain Site. Paper 97-A1313. Air & Waste Management Association 90th Annual 

Meeting & Exhibition, Toronto, Ontario, Canada. 8-13 June 1997. 

Scire, J.S., D.G. Strimaitis, and R.J. Yamartino, 2000a: A User’s Guide for the CALPUFF Dispersion 

Model (Version 5). Earth Tech, Inc., Concord, MA 

Scire, J.S., F.R. Robe, M.E. Fernau, and R.J. Yamartino, 2000b: A User’s Guide for the CALMET 

Meteorological Model (Version 5). Earth Tech, Inc., Concord, MA. 
 6-2 References 

U.S. Environmental Protection Agency (EPA), 1998: Interagency Workgroup on Air Quality Modeling 

(IWAQM), Phase 2 Report: Summary Report and Recommendation for Modeling Long Range 

Transport and Impacts on Regional Visibility. EPA-454/R-98-019. 

U.S. Environmental Protection Agency (EPA), 2003a: Revision to the Guideline on Air Quality Models: 

Adoption of a Preferred Long Range Transport Model and Other Revisions; Final Rule. 40 CRF 

51. Federal Register, April 15, 2003, 68, 72, pp 18440-18482. 

U.S. Environmental Protection Agency (EPA), 2003b: Guidance for Estimating Natural Visibility 

Conditions Under the Regional Haze Program. EPA-454/B-03-005, September 2003. 

U.S. Environmental Protection Agency (EPA), 2005: Regional Haze Regulations and Guidelines for 

Best Available Retrofit Technology (BART) Determinations; Final Rule, 40 CFR 41. Federal 

Register, July 6, 2006, 70, 128, pp 39104-39172. 

VISTAS, 2005: Protocol for the Application of the CALPUFF Model for Analysis of Best Available 

Retrofit Technology (BART). Visibility Improvement State and Tribal Association of the 

Southeast (VISTAS). Revision 3.2, August 31, 2006. Available from: http://www.vistassesarm.org/documents. 
This page intentionally left blank. 
Appendix B to 

BART determination Report for Alcoa, Inc. - Warrick Operations 
This page intentionally left blank. 
Appendix B Revisions to Alcoa BART Modeling Report

These revisions to Appendix B were submitted in September 2010 in a format not compatible with th

tables in this attachment replace the tables by the same numbers included in the original report. 
Table 2-3. Point and Line Source Emissions, ‘BART Eligible Baseline’ Case

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - PM2.5

 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s)

S

(

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0

P01 GTC 

Potlines #3 & #4 GTC 

Pollution Controls 0.986 0.116 1.757 4.409 

44

P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 2P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 2P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 

2

2

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 0P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 0P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 0P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 0P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 

0

0

P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 

0

0

P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 

0

0

P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 0P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 0P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 0P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 0P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 0P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0

WPP01 WPP stack 1 WPP Stack 1 Unit 2 Only * 8.6 1.949 2.852 3WPP02 WPP stack 2 WPP Stack 2 Units 2 and 3 * 22.01 21.96 7.629 5.73 11.236 8.384 1WPP03 WPP stack 3 WPP Stack 3 Unit 4 * 49.525 49.523 8.13 11.895 0.0 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5

2-5 Source Description 
Table 2-4. Point and Line Source Emissions, ‘BART Eligible Baseline + Unit 1’ Case

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - PM2.5

 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s)

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

P01 GTC 

Potlines #3 & #4 GTC 

Pollution Controls 0.986 0.116 1.757 4.409 4

P02 

160C1.1-

160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 

P03 

161B5.1-

161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 

P04 

161B6.1-

161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 2

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 0P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 0P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 0P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 

WPP1a WPP Stack 1 WPP Stack 1 Unit 1 and 2 * 24.18 17.576 5.869 3.92 8.588 5.735

WPP2 WPP Stack 2 WPP Stack 2 Unit 2 and 3 22.01 21.96 7.679 5.73 11.236 8.384 WPP3 WPP Stack 3 WPP Stack 3 Unit 4 * 49.525 49.523 8.13 11.895 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5

2-6 Source Description 
Table 2-5. Point and Line Source Emissions, ‘Alternative to BART’ Case

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - 

PM2.5 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s) SO

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.4L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.4L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.4L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.4L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.4L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.4L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.4L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.4L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.4L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.4

P01 GTC 

Potlines #3 & #4 GTC 

Pollution Controls 1.185 0.986 1.667 0.116 1.757 4.409 75.

P02 

160C1.1-

160C1.36 Potline #2 A-398 0.535 0.393 0.753 0.046 0.700 1.758 37.

P03 

161B5.1-

161B5.36 Potline #5 A-398 0.541 0.555 0.760 0.065 0.989 2.482 36.

P04 

161B6.1-

161B6.36 Potline #6 A-398 0.532 0.563 0.748 0.066 1.002 2.514 36.

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 0.0P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 0P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 0.0P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 0P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 0.0P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 

WPP123 WPP Units 1-3 * 17.94 15.36 3.351 3.251 4.902 3.815 228

WPP4 WPP Unit 4 * 18.303 6.12 13.806 8.953 1.268 0.0

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5 2-7 
Table 2-6. Point and Line Source Emissions, ‘BART with Potlines Scrubbed’ Case

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - 

PM2.5 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s) SO

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.3L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.3L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.3L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.

W01 

Lines 3-6 Common 

Scrubber 1.591 4.335 10.879 8.

W02 Line 2 SO2 Scrubber 0.374 0.700 1.758 2.

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 0.0P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 0P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 0.0P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 0P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 0.0P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 

WPP123 

WPP Unit2&3 * 12.75 2.699 3.167 

WPP4 WPP Unit 4 * 2.745 1.268 13.806 0.

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5

2-7 Source Description 
Table 2-7. Point and Line Source Emissions, ‘BART Control Level’ Case

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - 

PM2.5 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s) SO

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.3L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.3L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.3L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.

P01 GTC 

Potlines #3 & #4 GTC 

Pollution Controls 1.185 0.986 1.667 0.116 1.757 4.409 65.

P02 

160C1.1-

160C1.36 Potline #2 A-398 0.535 0.393 0.753 0.046 0.700 1.758 32.

P03 

161B5.1-

161B5.36 Potline #5 A-398 0.541 0.555 0.760 0.065 0.989 2.482 31.

P04 

161B6.1-

161B6.36 Potline #6 A-398 0.532 0.563 0.748 0.066 1.002 2.514 31.

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 0.0P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 0P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 0.0P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 0P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 0.0P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 

WPP123 

WPP Unit2&3 WPP units 2&3 * 12.75 2.699 3.167 

WPP4 WPP Unit 4 * 2.745 1.268 13.806 0.

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5

2-9 S
Table 2-8. PM Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible Ba

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

L01 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L02 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L03 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L04 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L05 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L06 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L07 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L08 0.470 0.6630 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L09 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 L10 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 

P01 0.986 0.116 1.757 4.409 0.493 0.493 0.029 0.029 2.234 2.234 0.879 P02 0.393 0.046 0.700 1.758 0.197 0.197 0.012 0.012 0.891 0.891 0.350 P03 0.555 0.065 0.989 2.482 0.278 0.278 0.016 0.016 1.257 1.257 0.495 P04 0.563 0.066 1.002 2.514 0.282 0.282 0.017 0.017 1.274 1.274 0.501 P23 0.056 0.027 0.001 0.001 0.028 0.028 0.007 0.007 0.007 0.007 2.50E-0P24 0.017 0.026 0.002 0.002 0.009 0.009 0.007 0.007 0.007 0.007 7.50E-0P25 0.065 0.030 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-0P26 0.011 0.016 0.002 0.002 0.006 0.006 0.004 0.004 0.005 0.005 7.50E-0P28 0.061 0.028 0.001 0.001 0.031 0.031 0.007 0.007 0.007 0.007 2.50E-0P29 0.110 0.167 0.015 0.015 0.055 0.055 0.042 0.042 0.049 0.049 7.50E-0P30 0.095 0.044 0.001 0.001 0.048 0.048 0.011 0.011 0.012 0.012 5.00E-0P31 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P32 0.066 0.031 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-0P33 0.062 0.029 0.001 0.005 0.031 0.031 0.007 0.007 0.010 0.010 2.50E-0P34 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P35 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-0P36 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P37 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-0

________ 1 Emissions are fine filterable plus inorganic condensables 

_____________________________________________________________________________________________________

2-10 S
Table 2-8. PM Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible Ba

 Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

P39 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00 P41 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00 

WPP1 - 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 WPP2 

- 22.01

21.96

7.629

5.73

11.236

8.384

0.000 0.000 5.503

5.490

5.5035.490

11.1219.682

11.1215.490

3.814 2.865

 WPP3 - 49.525 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.329 18.328 18.329 18.328 4.065 

________ 1 Emissions are fine filterable plus inorganic condensables 

_____________________________________________________________________________________________________

2-10A 
Table 2-9. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible Baselin

 Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

WPP1 

- 

24.1824.176 5.869 8.588 8.587 0.000 0.000 6.045 6.044 6.045 6.044 10.339 10.338 10.339 10.338 2.935 

Table 2-10. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘Alternative to BART

 Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

WPP123 

- 17.94

15.36

3.3513.251

4.9023.815

0.000 0.000 4.485

3.840

4.4853.840

6.9365.748

6.9365.748

1.676 1.626

WPP4 - 18.303 6.12 13.806 8.953 1.268 0.000 0.000 4.576 4.576 9.053 5.210 9.053 5.210 3.060 6.903 

____________________________________________________________________________________

 2-11 Sourc
Table 2-11. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART with Potlines S

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

W01 

- 

1.591 4.335 10.879 0.000 0.000 0.398 0.398 5.837 5.837 2.168 

W02 - 0.374 0.700 1.758 0.000 0.000 0.094 0.094 0.973 0.973 0.350 

WPP23 - 12.75 2.699 3.167 0.000 0.000 3.188 3.188 4.771 4.771 1.350 

WPP4 - 2.745 1.268 13.806 0.000 0.000 0.686 0.686 7.589 7.589 0.634 

Table 2-12. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Control Level

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

WPP23 - 12.75 2.699 3.167 0.000 0.000 3.188 3.188 4.771 4.771 1.350 

WPP4 - 2.745 1.268 13.806 0.000 0.000 0.686 0.686 7.589 7.589 0.634 

____________________________________________________________________________________

 2-11A Sour
Table 6-1.Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART Eligible 

Baseline’ Case Emissions. ___________________________________________________________________________________ Maximum 98th Percentile Maximum 98th Percentile  Delta Delta Delta Delta 

Year Bext Bext Deciview Deciview 

 (%) (%) (dv) (dv) 

2001 46.13 91.62 22.36 44.46 3.275 6.504 1.852 3.6782002 56.17 116.68 23.38 48.57 3.722 7.732 1.906 3.9592003 37.03 72.21 21.40 41.73 2.787 5.435 1.788 3.487

2001 - 2003 56.17 116.68 22.38 44.69 3.722 7.732 1.849 3.694

Table 6-2.Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART Eligible Baseline+ Unit 1’ Case Emissions. ___________________________________________________________________________________ Maximum 98th Percentile Maximum 98th Percentile  Delta Delta Delta Delta 

Year Bext Bext Deciview Deciview 

 (%) (%) (dv) (dv) 

2001 60.69 114.74 28.81 54.46 4.042 7.642 2.311 4.3692002 85.38 144.44 35.39 59.88 4.570 7.732 2.774 4.6932003 55.30 90.32 31.61 51.63 3.329 5.435 2.549 4.163

2001 - 2003 85.38 144.44 31.94 55.65 4.570 7.732 2.545 4.424

6-2 Result
Table 6-3.Summary of Visibility Impacts at Mammoth Cave National Park due to ‘Alternative to 

BART’ Case Emissions. ___________________________________________________________________________________ Maximum 98th Percentile Maximum 98th Percentile  Delta Delta Delta Delta 

Year Bext Bext Deciview Deciview 

 (%) (%) (dv) (dv) 

2001 13.98 21.76 7.24 11.27 1.265 1.969 0.686 1.0682002 16.33 26.76 4.81 7.89 1.446 2.371 0.463 0.7592003 14.85 24.42 5.75 9.45 1.323 2.185 0.549 0.903

2001 - 2003 16.33 26.76 5.93 9.84 1.345 2.371 0.566 0.938

Table 6-4.Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART with Pot

Scrubbed’ Case Emissions. ___________________________________________________________________________________

 Maximum 98th Percentile Maximum 98th Percentile  Delta Delta Delta Delta 

Year Bext Bext Deciview Deciview 

 (%) (%) (dv) (dv) 

2001 6.38 11.42 3.86 6.91 0.604 1.081 0.374 0.6692002 8.41 16.75 2.23 4.43 0.778 1.549 0.218 0.4342003 7.83 15.19 2.75 5.34 0.729 1.414 0.268 0.520

2001 - 2003 8.41 16.75 2.95 5.41 0.704 1.549 0.289 0.527

6-3 Results 
Table 6-5.Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART Control 

Level’ Case Emissions. ___________________________________________________________________________________ Maximum 98th Percentile Maximum 98th Percentile  Delta Delta Delta Delta 

Year Bext Bext Deciview Deciview 

 (%) (%) (dv) (dv) 

2001 9.18 15.19 4.60 7.66 0.850 1.414 0.444 0.7392002 10.46 18.89 3.07 5.55 0.958 1.731 0.299 0.5402003 10.75 17.30 4.16 6.69 0.992 1.596 0.402 0.647

2001 - 2003 10.46 18.89 3.94 6.88 0.933 1.731 0.382 0.665

 6-3A Results 
Table 6-7. Source and Species Contributions to the 8th Highest Extinction Coefficient Changes for ‘

Baseline’ Case at Mammoth Cave National Park.

Source Bext Contrib. to Modeled Species Contribution to Modeled Extinction Coefficient in 1/Mm Percentage of Species ContribGroup Change Total Bext Ext. SO4 NO3 Organics E.Carbon PM_Coarse PM_Fine SO4 NO3 Organics  (%) Change (%) 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm % % % 

2001: 8th highest impact is 1.852 3.678 Deciview 

All 22.36 

44.46

100.00 4.757 

9.456

4.508 9.118

0.100 0.196

0.064 0.060

0.000 0.000 

0.003

0.081 0.079

94.77 96.43

2.10 2.07

1.35 0.63

Lines 0.12 0.53 

0.26

0.025 0.007 0.000 0.009 0.000 0.002 0.007 28.00 0.00 36.00 

GTC 0.60 2.67 

1.34

0.127 0.120 0.000 0.004 0.000 0.000 0.003 94.49 0.00 3.15 

A-398s 0.86 3.85 

1.94

0.183 0.172 0.000 0.007 0.000 0.000 0.004 93.99 0.00 3.83 

Melter / Holder 

0.01 0.06 

0.03

0.003 0.000 0.002 0.000 0.000 0.000 0.001 0.00 66.67 0.00 

wpp01 4.73 21.17 

10.65

1.007 0.970 0.025 0.005 0.000 0.000 0.007 96.33 2.48 0.50 

wpp02 15.77 

15.74

70.51 35.40

3.354 3.347

3.239 0.075 0.014 0.000 0.000 0.019 96.77 2.24 0.42 

wpp03 0.27 

22.39

1.21 50.35

0.058 4.761

0.000 4.610

0.000 0.093

0.020 0.000 0.000 0.038 0.00 

96.83

0.00 1.95

34.48 0.42

2002: 8th highest impact is 1.906 3.959 Deciview 

All 23.38 

48.57

100.00 5.042 

10.473

3.655 7.877

1.214 2.425

0.069 0.000 0.001 0.103 

0.101

72.49 75.21

24.08 23.15

1.37 0.66

Lines 0.04 0.20 

0.10

0.010 0.002 0.000 0.004 0.000 0.001 0.003 20.00 0.00 40.00 

GTC 0.33 1.39 

0.67

0.070 0.063 0.001 0.004 0.000 0.000 0.002 90.00 1.43 5.71 

A-398s 0.36 1.57 

0.75

0.079 0.069 0.002 0.005 0.000 0.000 0.003 87.34 2.53 6.33 

Melter / Holder 

0.01 0.04 

0.02

0.002 0.000 0.002 0.000 0.000 0.000 0.000 0.00 100.00 0.00 

wpp01 5.33 22.77 

10.96

1.148 0.818 0.313 0.007 0.000 0.000 0.010 71.25 27.26 0.61 

wpp02 16.92 

16.90

72.37 34.80

3.649 3.645

2.703 0.896 0.020 0.000 0.000 0.026 74.16 24.58 0.55 

wpp03 0.39 

25.60

1.66 52.71

0.084 5.520

0.000 4.223

0.000 1.210

0.027 0.030

0.000 0.000 0.057 0.00 

76.50

0.00 21.92

32.14 0.54

_____________________________________________________________________________________________________

6 – 5 
Table 6-7. Source and Species Contributions to the 8th Highest Extinction Coefficient Changes for ‘

Baseline’ Case at Mammoth Cave National Park, continued.

Source Bext Contrib. to Modeled Species Contribution to Modeled Extinction Coefficient in 1/Mm Percentage of Species ContribGroup Change Total Bext Ext. SO4 NO3 Organics E.Carbon PM_Coarse PM_Fine SO4 NO3 Organics  (%) Change (%) 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm % % % 

2003: 8th highest impact is 1.788 3.487 Deciview 

All 21.40 

41.73

100.00 4.656 

9.081

4.097 8.161

0.411 0.777

0.065 0.061

0.000 0.001 

0.002

0.082 0.080

87.99 89.87

8.83 8.56

1.40 0.67

Lines 0.08 0.37 

0.19

0.017 0.004 0.000 0.007 0.000 0.001 

0.002

0.005 23.53 0.00 41.18 

GTC 0.55 2.58 

1.32

0.120 0.111 0.001 0.005 0.000 0.000 

0.001

0.003 92.50 0.83 4.17 

A-398s 0.82 3.80 

1.95

0.177 0.164 0.001 0.007 0.000 0.000 0.005 92.66 0.56 3.95 

Melter / Holder 

0.04 0.00 

0.09

0.000 0.008

0.000 0.007 0.000 0.000 0.000 0.001 0.00 87.50 0.00 

wpp01 4.55 21.28 

10.91

0.991 0.881 0.098 0.005 0.000 0.000 0.007 88.90 9.89 0.50 

wpp02 15.08 

15.05

70.51 36.08

3.283 3.276

2.937 0.304 0.02 

0.015

0.000 0.000 0.022 

0.020

89.46 89.65

9.26 9.28

0.61 0.46

wpp03 0.28 

20.63

1.46 49.45

0.06 4.491

0.00 4.064

0.00 0.367

0.021 0.000 0.000 0.039 0.00 

90.49

0.00 8.17

35.00 0.47

________________________________________________________________________________________________ 6-5A 
Revisions to Appendix A, Alcoa BART Modeling Protocol
Table 2-3. Point and Line Source Emissions

Source 

ID 

Emission Unit ID #

Stack Name Filterable 

PM10 - PM2.5

 (g/s)

Filterable PM2.5 (g/s)

Organic Condensable PM2.5 (g/s)

Inorganic Condensable PM2.5 (g/s)

S

(

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0

P01 GTC 

Potlines #3 & #4 GTC 

Pollution Controls 0.986 0.116 1.757 4.409 

44

P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 2P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 2P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 

2

2

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 0P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 0P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 0P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 0P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 

0

0

P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 

0

0

P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 

0

0

P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 0P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 0P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 0P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 0P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 0P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0

WPP01 WPP stack 1 WPP Stack 1 Unit 2 Only * 8.6 1.949 2.852 3WPP02 WPP stack 2 WPP Stack 2 Units 2 and 3 * 22.01 21.96 7.629 5.73 11.236 8.384 1WPP03 WPP stack 3 WPP Stack 3 Unit 4 * 49.525 49.523 8.13 11.895 0.0 

* All Solid PM is 10 microns or less. There is no data available for solid PM2.5

2-5 Sour
Table 2-4. PM Speciation of Particulate Matter Emitted from Lines and Stacks

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

L01 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L02 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L03 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L04 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L05 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L06 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L07 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L08 0.470 0.6630 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L09 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 L10 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 

P01 0.986 0.116 1.757 4.409 0.493 0.493 0.029 0.029 2.234 2.234 0.879 P02 0.393 0.046 0.700 1.758 0.197 0.197 0.012 0.012 0.891 0.891 0.350 P03 0.555 0.065 0.989 2.482 0.278 0.278 0.016 0.016 1.257 1.257 0.495 P04 0.563 0.066 1.002 2.514 0.282 0.282 0.017 0.017 1.274 1.274 0.501 P23 0.056 0.027 0.001 0.001 0.028 0.028 0.007 0.007 0.007 0.007 2.50E-0P24 0.017 0.026 0.002 0.002 0.009 0.009 0.007 0.007 0.007 0.007 7.50E-0P25 0.065 0.030 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-0P26 0.011 0.016 0.002 0.002 0.006 0.006 0.004 0.004 0.005 0.005 7.50E-0P28 0.061 0.028 0.001 0.001 0.031 0.031 0.007 0.007 0.007 0.007 2.50E-0P29 0.110 0.167 0.015 0.015 0.055 0.055 0.042 0.042 0.049 0.049 7.50E-0P30 0.095 0.044 0.001 0.001 0.048 0.048 0.011 0.011 0.012 0.012 5.00E-0P31 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P32 0.066 0.031 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-0P33 0.062 0.029 0.001 0.005 0.031 0.031 0.007 0.007 0.010 0.010 2.50E-0P34 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P35 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-0P36 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-0P37 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-0

________ 1 Emissions are fine filterable plus inorganic condensables 

_____________________________________________________________________________________________________

2-6 So
Table 2-4. PM Speciation of Particulate Matter Emitted from Lines and Stacks, Continued

Coarse PM Fine PM Organ

Source Index 

PM10 - 

PM2.5 

(g/s)

SolidPM2.5 

(g/s)

Org. Cond (g/s)

InOrg Cond (g/s)

6-10 um (g/s)

2.5- 6.0 um (g/s)

1.25- 2.5 um (g/s)

1.00- 1.25 um (g/s) 

0.625- 1.00 um1

(g/s) 

0.500- 0.625 um1

(g/s) 

0.625- 1.00 um (g/s) 

P39 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00 P41 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00 

WPP1 - 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 WPP2 

- 22.01

21.96

7.629

5.73

11.236

8.384

0.000 0.000 5.503

5.490

5.5035.490

11.1219.682

11.1215.490

3.814 2.865

WPP3 - 49.525 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.329 18.328 18.329 18.328 4.065 

________ 1 Emissions are fine filterable plus inorganic condensables 

_____________________________________________________________________________________________________

2-6A 
This page intentionally left blank. 
BART Assessment of the Alcoa Warrick 

Operations and Warrick Power Plant, 

Warrick County, Indiana 

Prepared For: 

Alcoa Warrick Operations 

Warrick County, Indiana 

Submitted By: 

TRC Environmental Corporation 

650 Suffolk Street, Wannalancit Mills 

Lowell, Massachusetts 01854 

(978) 970-5600 

December 2008 
i

TABLE OF CONTENTS 

Page

1.0 INTRODUCTION ......................................................................................................................1-1

2.0 SOURCE DESCRIPTION .........................................................................................................2-1

3.0 SCREENING MODELING .......................................................................................................3-1

4.0 GEOPHYSICAL AND METEOROLOGICAL DATA FOR REFINED MODELING ......4-5

4.1 Terrain ......................................................................................................................................4-5

4.2 Land Use...................................................................................................................................4-5

4.3 Meteorological Data Base ........................................................................................................4-8

4.4 Air Quality Monitoring Data ....................................................................................................4-8

5.0 AIR QUALITY MODELING METHODOLOGY..................................................................5-1

5.1 Model Selection........................................................................................................................5-1

5.2 Modeling Domain Configuration .............................................................................................5-1

5.3 Meteorological Modeling Options............................................................................................5-2

5.4 CALPUFF Computational Domain and Receptors ..................................................................5-2

5.5 Dispersion Modeling Options...................................................................................................5-3

5.6 Visibility Calculations ..............................................................................................................5-4

6.0 RESULTS ....................................................................................................................................6-1

7.0 REFERENCES............................................................................................................................7-1
ii

LIST OF FIGURES 

Page

Figure 2-1. An aerial photo of the facility with the potrooms and other major buildings outlined. 2-2

Figure 3-1. Terrain elevations for the VISTAS CALMET 12-km regional domain. CALPUFF 

computational subdomain, the Class I areas and the locations of Warrick facilities are 

also shown. 3-3

Figure 4-1. Terrain contours (m MSL) at 1 km resolution for the 225 x 195 CALMET and 

CALPUFF computational domains. The Class I area, Mammoth Cave NP and the 

Alcoa Warrick facility are shown. 4-6

Figure 4-2. Dominant land use categories at 1 km resolution on the 225 km x 195 km CALMET 

and CALPUFF model domains. Mammoth Cave National Park and the facility are 

also shown. 4-7

Figure 4-3. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the 

refined 2001 modeling. Mammoth Cave National Park and the facility are also 

shown. 4-12

Figure 4-4. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the 

refined 2002 modeling. Mammoth Cave National Park and the facility are also 

shown. 4-13

Figure 4-5. Plot of all the surface, upper air, RUC data and precipitation stations to be used in the 

refined 2003 modeling. Mammoth Cave National Park and the facility are also 

shown. 4-14

Figure 4-6. Plot of all the ozone stations, both CASTNet and AIRS, used in the refined 2001 

modeling. Mammoth Cave National Park and the facility are also shown. 4-16

Figure 4-7. Plot of all the ozone stations, both CASTNet and AIRS, used in the refined 2002 

modeling. Mammoth Cave National Park and the facility are also shown. 4-17

Figure 4-8. Plot of all the ozone stations, both CASTNet and AIRS, used in the refined 2003 

modeling. Mammoth Cave National Park and the facility are also shown. 4-18
iii

LIST OF TABLES 

Page

Table 2-1. Line Source Parameters used in CALPUFF 2-3

Table 2-2. Point Source Parameters used in CALPUFF 2-4

Table 2-3. Point and Line Source Emissions, ‘BART Eligible Baseline’ Case 2-5

Table 2-4. Point and Line Source Emissions, ‘BART Eligible Baseline + Unit 1’ Case. 2-6

Table 2-5. Point and Line Source Emissions, ‘Alternative to BART’ Case. 2-7

Table 2-6. Point and Line Source Emissions, ‘BART with Potlines Scrubbed’ Case. 2-8

Table 2-7. Point and Line Source Emissions, ‘BART Control Level’ Case. 2-9

Table 2-8. PM Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible 

Baseline’ Case 2-10

Table 2-9. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible 

Baseline + Unit 1’ Case. 2-11

Table 2-10. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘Alternative to 

BART’ Case. 2-11

Table 2-11. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART with 

Potlines Scrubbed’ Case. 2-11

Table 2-12. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Control 

Level’ Case. 2-11

Table 3-1. Class I Areas within 500 km of Alcoa Warrick 3-2

Table 3-2. Monthly f(RH) Values Based on Area Centroids for Application with Visibility 

Method 6 3-2

Table 3-3. Average Natural Levels of Aerosol Components 3-2

Table 3-4. Results of the Screening Simulations 3-4

Table 4-1. Meteorological Data Sources and Parameters Available 4-9

Table 4-2. NWS Hourly Surface Stations 4-10

Table 4-3. Upper Air Stations 4-10

Table 4-4. Hourly NWS Precipitation Stations 4-11

Table 4-5. Ozone Stations 4-15
iv

LIST OF TABLES (continued) 

Page

Table 5-1. Background Natural Visibility Concentrations for the Eastern United States 5-5

Table 5-2. Monthly f(RH) Values for Mammoth Cave Based on the Area Centroid 5-5

Table 6-1. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART 

Eligible Baseline’ Case Emissions. 6-2

Table 6-2. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART 

Eligible Baseline + Unit 1’ Case Emissions. 6-2

Table 6-3. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘Alternative 

to BART’ Case Emissions. 6-2

Table 6-4. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART with 

Potlines Scrubbed’ Case Emissions. 6-3

Table 6-5. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART 

Control Level’ Case Emissions. 6-3

Table 6-6. Grouping of the Sources for the Contribution Values. 6-4

Table 6-7. Source and Species Contributions to the 8th Highest Extinction Coefficient Changes 

for ‘BART Eligible Baseline’ Case at Mammoth Cave National Park. 6-5
1-1 Introduction

1.0 INTRODUCTION 

TRC Environmental Corporation conducted a Best Available Retrofit Technology (BART) 

analysis for the Alcoa Warrick aluminum plant and Warrick Power Plant. This facility is situated 

in Warrick County, Indiana on the northern shores of the Ohio River along the Indiana/Kentucky 

border. It is approximately 23 km southeast of Evansville. The Alcoa Warrick Operations facility 

is a primary aluminum smelter. 

On July 6, 2005 the US Environment Protection Agency produced the Federal Register 

document, 40 CFR Part 51 in order to introduce new National Regional Haze Regulations for 

Best Available Retrofit Technology. The regional haze rule requires States to submit 

implementation plans (SIPs) to address regional haze visibility impairment in 156 Federallyprotected parks and wilderness areas, commonly referred to as “Class 1 Areas”. The final rule 

included a requirement for BART for certain large stationary sources that were put in place 

between 1962 and 1977. The regional haze rule uses the term “BART-eligible source” to describe 

those sources which have the potential to emit 250 tons or more of a visibility-impairing air 

pollutant, were put in place between August 7, 1962 and August 7, 1977 and whose operations 

fall within one or more of 26 specifically listed source categories, which includes primary 

aluminum ore reduction plants. 

BART review is required when the source ‘emits any air pollutant which may reasonably be 

anticipated to cause or contribute to any impairment of visibility in any Class 1 area. In 

identifying a level of control of BART, States are required by section 169A(g) of the CAA to 

consider; (a) the costs of compliance, (b) the energy and non-air quality environmental impacts of 

compliance, (c) any existing pollution control technology in use at the source, (d) the remaining 

useful life of the source and (e) the degree of visibility improvement which may reasonably be 

anticipated from the use of BART. 

The purpose of the modeling was to assess the ambient air quality impacts of sulfur dioxide 

(SO2), particulate matter (PM) and nitrogen oxides (NOx) emissions at Mammoth Cave National 

Park which is located in a south east direction approximately 120 km away. The impacts of the 

facility on visibility was evaluated. 

The topography of the domain area consists of gentle rolling terrain where elevation of the land 

ranges from ~120m in the Ohio River Valley in the north and west of the model domain to 

~240m in the east. There is the potential for some terrain effects, both on the meteorological 

fields and in terms of plume-terrain interaction effects. The CALMET and CALPUFF nonsteady-state models (Scire et al., 2000a,b) were used for the modeling analysis. The U.S. 

Environmental Protection Agency (EPA) has recommended CALPUFF as the preferred model for 

BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline 
1-2 Introduction

Model for Class I impact assessments and other long range transport applications and on a caseby-case basis for near-field applications involving complex flows (U.S. EPA, 2003a). CALPUFF 

is also recommended by both the Federal Land Managers Air Quality Workgroup (FLAG, 2000) 

and the Interagency Workgroup on Air Quality Modeling (U.S. EPA, 1998). CALPUFF is also 

recommended in the new draft proposed updated to FLAG (FLAG, 2008).

CALMET is a diagnostic meteorological model that produces three-dimensional wind fields 

based on parameterized treatments of terrain effects such as slope flows, terrain blocking effects, 

and kinematic effects. Meteorological observations were used to determine the wind field in areas 

where the observations were representative. Hourly meteorological data produced by the 

Mesoscale Model, Version 5 (MM5) on a 12 km grid were used by CALMET for 2001 and 2002 

to help define the initial estimate of the wind fields. For 2003, RUC data, (Rapid Update Cycle) 

has been transformed into 3D.DAT format for its inclusion into CALMET. RUC is a high 

frequency weather forecast and data assimilation system which is supported and developed by 

NCEP. The RUC model provides high frequency mesoscale analyses and short range numerical 

forecasts. In this analysis the 50 original vertical levels were extracted and transformed into an 

MM5 data input file. The horizontal resolution of the data is 20 km Fine scale terrain effects 

(1 km resolution) were determined by the diagnostic wind module in CALMET. It had been 

expected that spatial variability would occur in the wind fields over short distances due to the 

terrain channeling. 

CALPUFF is a non-steady-state puff dispersion model. It accounts for spatial changes in the 

CALMET-produced meteorological fields, variability in surface conditions (elevation, surface 

roughness, vegetation type, etc.), chemical transformation, wet removal due to rain and snow, dry 

deposition, and terrain influences on plume interaction with the surface. CALPUFF contains a 

module to compute visibility effects, based on a humidity-dependent relationship between 

particulate matter concentrations and light extinction, as well as wet and dry acid deposition 

fluxes. The refined meteorological and dispersion modeling simulations were conducted for a 

three-year period (2001, 2002 and 2003). Visibility impacts from SO2, PM, and NOx, and their 

secondary products resulting from emissions from the Alcoa sources were predicted by the model 

at receptors in the Class I area. 

The Lake Michigan Air Directors Consortium (LADCO) 2006 Document was used as a starting 

point for establishing the modeling procedures for the Warrick BART analysis. A few exceptions 

to the procedures from (LADCO, 2006) were made such as the use of the EPA-approved version 

of the model (Version 5.8), a more refined modeling domain with 1 km grid instead of 36 km grid 

spacing, modeling of 2001-2003 using the different meteorological data set from what is specified 

in (LADCO, 2006) in order to allow the use of higher resolution meteorological data. 
1-3 Introduction

In Section 2, a general description of the study area and the source configuration is provided. The 

results of a screening analysis that allowed the identification of the primary Class I area 

controlling the BART analysis are presented in Section 3. Descriptions of the site characteristics 

and the data bases (meteorological, geophysical, and aerometric) used in the analysis are provided 

in Section 4. Section 5 includes an overview of the CALMET and CALPUFF models, and the 

importance of evaluating non-steady-state effects. Results of the refined modeling BART analysis 

are provided in Section 6. 
 2-1 Source Description

2.0 SOURCE DESCRIPTION 

The Alcoa Warrick Operations facility is a primary aluminum smelter located in Warrick County, 

Indiana on the northern shore of the Ohio River along the Indiana/Kentucky border. It is 

approximately 23 km southeast of Evansville, IN. 

The potential BART-eligible facilities consists of five potlines (10 potrooms), and 16 melting 

and/or holding furnaces. Figure 2-1 shows an aerial photo of the facility with the potrooms and 

other major buildings outlined. In the existing facility configuration, there are 16 furnace stacks, 

and 108 stacks associated with the A-398 reactors for Lines 2, 5, and 6. Each A-398 has 36 

stacks. The common pollution control system for Potlines 3 and 4 emissions exit through a 199 ft 

stack. 

Three stacks for the Warrick Power Plant were modeled using the parameters listed in Table 2-2. 

For modeling purposes, banks of closely-spaced stacks of identical stack characteristics were 

treated as a single effective stack. The effective stack uses the same exit velocity and exit 

temperature as the individual stacks, but the effective diameter was computed so that the 

volumetric flow of the effective stack is equal to the sum of the flows of the individual stacks in 

the bank. Therefore each bank of stacks is replaced by a single point source. 

Table 2-1 lists the line source parameters while Table 2-2 shows the source parameters for the 

point sources. Tables 2-3 through 2-7 summarizes the line and point source emissions for the 

following six cases, respectively: (1) ‘BART Eligible Baseline’, (2) ‘BART Eligible Baseline + 

Unit 1’, (3) ‘Alternative to BART’, (4) ‘BART with Potlines Scrubbed’, and (5) ‘BART Control 

Level’ case. 

Table 2-8 summarizes the particulate speciation for the ‘BART Eligible Baseline’ case. In the 

following four tables (Tables 2-9 through 2-12), for each of the four additional scenarios, 

speciation for only those stacks for which PM emission rates are different from the ‘BART 

Eligible Baseline’ case is presented. 
 2-2 Source Description

470.2 470.4 470.6 470.8 471.0 471.2 471.4 471.6 471.8 472.0

UTM Easting (km)

4195.6

4195.8

4196.0

4196.2

4196.4

4196.6

4196.8

4197.0

4197.2

4197.4

4197.6

4197.8

4198.0

UTM Northing (km)

 103M.1 104M.1 

 105M. 1 

 106M.1 107M.1 

 108M.1 

 109M.1 110M.1 111M.1 

 112M.1 

 60.3 60.8 

 61A.1 

 Tank 62 BC-24 

 61B.1 

 141A NW 141A SW 104. 1 141A NE 141A SE 

 144A 

 160C1.37 

 112A.1 

 16B6.16 161B5.37 

 166 

160C1.1-160C1

 GTC 

161B6.1-161B6 161B5.1-161B5

 110.2 

 134.62 134.64 134.67 134. 66 134.65 

 134.33 134.35 134.36 134.38 134.39 134.4 134. 41 134. 42 134.43 134.44 

 134.45 

 134.71 134. 73 

 134.75 134.76 134.68 134. 77 134. 69 134.7 

 379.1 

(UTM Zone = 16, Hemisphere = N, Datum = NAD83: GRS80/NAR-C)

ALCOA Warrick: Plant Layout

Figure 2-1. An aerial photo of the facility with the potrooms and other major buildings outlined. 
 2-3 

Table 2-1. Line Source Parameters used in CALPUFF 

Source 

ID 

Emission 

Unit ID # Stack Name 

Release 

Height 

(m) 

Monitor 

Width (m) 

Exit Velocity

(m/s) 

Delta Temp

(oK) 

Begin 

UTM 

E/N (km) 

E

U

E/

L01 103M.1 Potline #2, Room 103 14.02 1.52 2.93 24.95 471.119, 4196.702 471.19L02 104M.1 Potline #2, Room 104 14.02 1.52 2.93 24.95 471.087, 4196.711 471.16L03 105M.1 Potline #3, Room 105 14.02 1.52 2.93 24.95 471.024, 4196.728 471.10L04 106M.1 Potline #3, Room 106 14.02 1.52 2.93 24.95 470.992, 4196.737 471.07L05 107M.1 Potline #4, Room 107 14.02 1.52 2.93 24.95 470.961, 4196.745 471.03L06 108M.1 Potline #4, Room 108 14.02 1.52 2.93 24.95 470.929, 4196.754 471.00L07 109M.1 Potline #5 , Room 109 14.02 1.52 2.31 23.18 470.900, 4196.770 471.97L08 110M.1 Potline #5, Room 110 14.02 1.52 2.31 23.18 470.868, 4196.778 471.94L09 111M.1 Potline #6 , Room 111 14.02 1.52 2.31 23.18 470.803, 4196.796 471.88L10 112M.1 Potline #6, Room 112 14.02 1.52 2.31 23.18 470.771, 4196.804 471.84

Notes: L01-L02, L03-L04, L05-l06: F’ = 1002.186; Ave. line source width = 1.52m; Ave. building dimension = 292.6m; H = 13.61m, W = 16.0m; Ave. building separation L07-L08, L09-L10: F’ = 736.541; Ave. line source width = 1.52m; Ave. building dimension = 292.24m; H = 13.15m, W = 17.0m; Ave. building separation The release height (m), monitor width (m), exit velocity (m/s) and exit temperature (oK) were all taken from the 2002 Alcoa Warrick CO st

All the coordinates were digitized to match aerial photos in NAD83 datum 

L01-L06: Average Line Source Buoyancy Parameter (F') Calculation L07-L10: Average Line Source Buoyancy Param

F' = [gLW

mw(Ts-Ta)]/Ts = 1002.186 m4/s3 where F' = [gLW

mw(Ts-Ta)]/Ts = 736.541 m4/s3, where

g = acceleration of gravity = 9.81 m/s2 g = acceleration of gravity = 9.81 m/s2

L = line source length = 292.6 m L = line source length = 292.24 Wm = line source width = 1.52 m Wm = line source width = 1.52 m w = line source exit velocity = 2.93 m/s w = line source exit velocity = 2.31 m/s Ts = line source exit temperature = 318.3 K Ts = line source exit temperature = 316.8 K 

Ta = ambient air temperature = 293.3 K Ta = ambient air temperature = 293.6 K Ts - Ta = 

ΔT = 24.95 K Ts-Ta = 

ΔT = 23.18 K 
 2-4 

Table 2-2. Point Source Parameters used in CALPUFF 

Index Emission 

Unit ID # 

Stack Name Stack 

Height 

(m) 

Stack 

 Diameter 

(m) 

Exit 

Velocity 

(m/s) 

Exit 

Temp 

(oK) 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 60.66 6.10 16.46 350 P02 160C1.1-160C1.36 Potline #2 A-398 14.94 3.70 21.12 366 

P02a C1.GTC Potline #2 GTC 60.66 3.05 31.46 366 

P03 161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 P04 161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 

W01 Lines 3-6 ,Common Scrubber 60.66 7.92 16.46 314 W02 Line 2 SO2 Scrubber 60.66 3.05 26.82 317 

P23 134.62 Melter 1M1 38.40 1.59 2.16 472 P24 134.64 Holder 1EH 38.40 1.22 2.00 445 P25 134.65 Melter 1M2 38.40 1.59 2.16 472 P26 134.66 Holder 1WH 38.40 1.22 2.00 445 P28 134.33 Melter 5M1 38.40 1.22 3.80 583 P29 134.35 Holder 5EH 38.40 1.37 2.34 466 P30 134.36 Melter 5M2 38.40 1.22 3.80 583 P31 134.38 Holder 5WH 38.40 1.37 2.34 466 P32 134.39 Melter 5M3 38.40 1.22 3.80 583 P33 134.4 Melter 6M1 38.40 1.22 3.80 583 P34 134.41 Holder 6EH 38.40 1.37 2.34 466 P35 134.42 Melter 6M2 38.40 1.22 3.80 583 P36 134.43 Holder 6WH 38.40 1.37 2.34 466 P37 134.44 Melter 6M3 38.40 1.22 3.80 583 P39 134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 P41 134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 

WPP123 WPP units 1-3 115.82 12.33 5.79 329 

WPP4 WPP Unit 4 115.82 6.10 15.80 329 WPP1 WPP stack 1 WPP Stack 1, Unit 2 only 115.82 5.91 12.88 423 WPP2 WPP stack 2 WPP Stack 2, Units 2 and 3 115.82 5.91 12.59 428 WPP3 WPP stack 3 WPP Stack 3, Unit 4 115.82 4.45 34.91 425 
 2-5 

Table 2-3. Point and Line Source Emissions, ‘BART Eligible Baseline’ Case 

Source 

ID 

Emission 

Unit ID # Stack Name 

Filterable 

PM10-PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

Organic 

Condensable 

PM2.5

(g/s) 

Inorganic 

Condensable 

PM2.5

(g/s) 

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 9P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 1P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 2P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 3P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 4P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 1P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 4P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 1P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 4P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 2P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 1P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 2P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 1P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 2P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 6P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 2

WPP1 WPP stack 1 WPP Stack 1, Unit 2 only * 8.6 1.949 2.852 WPP2 WPP stack 2 WPP Stack 2, Units 2 and 3 * 21.96 5.73 8.384 WPP3 WPP stack 3 WPP Stack 3, Unit 4 * 49.523 8.13 11.895 
 2-6 

Table 2-4. Point and Line Source Emissions, ‘BART Eligible Baseline + Unit 1’ Case. 

Source 

ID 

Emission 

Unit ID # Stack Name 

Filterable 

PM10-PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

Organic 

Condensable 

PM2.5

(g/s) 

Inorganic 

Condensable 

PM2.5

(g/s) 

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 9P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 1P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 2P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 3P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 4P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 1P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 4P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 1P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 4P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 2P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 1P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 2P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 1P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 2P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 6P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 2

WPP1a WPP stack 1 WPP Stack 1, Unit 2 only * 15.576 3.92 5.735 

WPP2 WPP stack 2 WPP Stack 2, Units 2 and 3 * 21.96 5.73 8.384 WPP3 WPP stack 3 WPP Stack 3, Unit 4 * 49.523 8.13 11.895 
 2-7 

Table 2-5. Point and Line Source Emissions, ‘Alternative to BART’ Case. 

Source 

ID 

Emission 

Unit ID # Stack Name 

Filterable 

PM10-PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

Organic 

Condensable 

PM2.5

(g/s) 

Inorganic 

Condensable 

PM2.5

(g/s) 

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 P02 C1.GTC Potline #2 GTC 0.393 0.046 0.700 1.758 P03 161B5.1- Potline #5 A-398 0.555 0.065 0.989 2.482 P04 161B6.1- Potline #6 A-398 0.563 0.066 1.002 2.514 P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 9P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 1P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 2P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 3P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 4P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 1P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 4P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 1P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 4P33 134.4 Melter 6M1 0.062 0.029 0.005 0.001 2P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 1P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 2P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 1P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 2P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 6P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 2

WPP123 WPP units 1-3 * 15.36 3.251 3.815 

WPP4 WPP Unit 4 * 18.303 13.806 1.268 
 2-8 

Table 2-6. Point and Line Source Emissions, ‘BART with Potlines Scrubbed’ Case. 

Source 

ID 

Emission 

Unit ID # Stack Name 

Filterable 

PM10-PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

Organic 

Condensable 

PM2.5

(g/s) 

Inorganic 

Condensable 

PM2.5

(g/s) 

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

W01 Lines 3-6 ,Common Scrubber 1.591 4.335 10.879 W02 Line 2 SO2 Scrubber 0.374 0.700 1.758 

P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 9P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 1P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 2P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 3P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 4P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 1P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 4P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 1P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 4P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 2P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 1P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 2P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 1P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 2P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 6P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 2

WPP123 WPP unit 2&3 WPP unit 2&3 * 12.750 2.699 3.167 1

WPP4 WPP unit 4 WPP unit 4 * 2.745 1.268 13.806 
 2-9 

Table 2-7. Point and Line Source Emissions, ‘BART Control Level’ Case. 

Source 

ID 

Emission 

Unit ID # Stack Name 

Filterable 

PM10-PM2.5

(g/s) 

Filterable 

PM2.5

(g/s) 

Organic 

Condensable 

PM2.5

(g/s) 

Inorganic 

Condensable 

PM2.5

(g/s) 

L01 103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 L02 104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 L03 105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 L04 106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 L05 107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 L06 108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 L07 109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 L08 110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 L09 111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 L10 112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 

P01 GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 P02 160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 P03 161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 P04 161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 P23 134.62 Melter 1M1 0.056 0.027 0.001 0.001 9P24 134.64 Holder 1EH 0.017 0.026 0.002 0.002 1P25 134.65 Melter 1M2 0.065 0.030 0.001 0.001 2P26 134.66 Holder 1WH 0.011 0.016 0.002 0.002 3P28 134.33 Melter 5M1 0.061 0.028 0.001 0.001 4P29 134.35 Holder 5EH 0.110 0.167 0.015 0.015 1P30 134.36 Melter 5M2 0.095 0.044 0.001 0.001 4P31 134.38 Holder 5WH 0.119 0.180 0.017 0.017 1P32 134.39 Melter 5M3 0.066 0.031 0.001 0.001 4P33 134.4 Melter 6M1 0.062 0.029 0.001 0.005 2P34 134.41 Holder 6EH 0.119 0.180 0.017 0.017 1P35 134.42 Melter 6M2 0.062 0.029 0.001 0.001 2P36 134.43 Holder 6WH 0.119 0.180 0.017 0.017 1P37 134.44 Melter 6M3 0.062 0.029 0.001 0.001 2P39 134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 6P41 134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 2

WPP123 WPP units 2&3 WPP units 2&3 * 12.75 2.699 3.167 

WPP4 WPP unit 4 WPP unit 4 * 2.745 1.268 13.806 
 2-10 

Table 2-8. PM Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible Baseline’ Case 

 Coarse PM Fine PM Organic Cond

Source 

Index 

PM10-

PM2.5 

(g/s) 

Solid 

PM2.5 

(g/s) 

Org. 

Cond 

(g/s) 

InOrg. 

Cond 

(g/s) 

6-10μm 

(g/s) 

2.5-

6.00μm 

(g/s) 

1.25-

2.5μm 

(g/s) 

1.00-

1.25μm 

(g/s) 

0.625-

1.00μm1 

(g/s) 

0.500-

0.625μm1 

(g/s) 

0.625-

1.00μm 

(g/s) 

0

L01 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L02 0.535 0.753 0.373 0.356 0.268 0.268 0.188 0.188 0.366 0.366 0.187 L03 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L04 0.569 0.802 0.397 0.379 0.285 0.285 0.201 0.201 0.390 0.390 0.199 L05 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L06 0.567 0.799 0.395 0.377 0.284 0.284 0.200 0.200 0.388 0.388 0.198 L07 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L08 0.470 0.663 0.328 0.313 0.235 0.235 0.166 0.166 0.322 0.322 0.164 L09 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 L10 0.532 0.749 0.371 0.354 0.266 0.266 0.187 0.187 0.364 0.364 0.186 

P01 0.986 0.116 1.757 4.409 0.493 0.493 0.029 0.029 2.234 2.234 0.879 P02 0.393 0.046 0.700 1.758 0.197 0.197 0.012 0.012 0.891 0.891 0.350 P03 0.555 0.065 0.989 2.482 0.278 0.278 0.016 0.016 1.257 1.257 0.495 P04 0.563 0.066 1.002 2.514 0.282 0.282 0.017 0.017 1.274 1.274 0.501 P23 0.056 0.027 0.001 0.001 0.028 0.028 0.007 0.007 0.007 0.007 2.50E-04 P24 0.017 0.026 0.002 0.002 0.009 0.009 0.007 0.007 0.007 0.007 7.50E-04 P25 0.065 0.030 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 P26 0.011 0.016 0.002 0.002 0.006 0.006 0.004 0.004 0.005 0.005 7.50E-04 P28 0.061 0.028 0.001 0.001 0.031 0.031 0.007 0.007 0.007 0.007 2.50E-04 P29 0.110 0.167 0.015 0.015 0.055 0.055 0.042 0.042 0.049 0.049 7.50E-03 P30 0.095 0.044 0.001 0.001 0.048 0.048 0.011 0.011 0.012 0.012 5.00E-04 P31 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 P32 0.066 0.031 0.001 0.001 0.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 P33 0.062 0.029 0.001 0.005 0.031 0.031 0.007 0.007 0.010 0.010 2.50E-04 P34 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 P35 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 P36 0.119 0.180 0.017 0.017 0.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 P37 0.062 0.029 0.001 0.001 0.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 P39 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00E+00 0P41 0.007 0.003 0.000 0.000 0.004 0.004 0.001 0.001 0.001 0.001 0.00E+00 0

wpp1 - 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 wpp2 - 21.96 5.73 8.384 0.000 0.000 5.490 5.490 9.682 9.682 2.865 wpp3 - 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.328 18.328 4.065 

_______ 1 Emissions are fine filterable plus inorganic condensables.
 2-11 

Table 2-9. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible Baseline + Unit 1’ Cas

 Coarse PM Fine PM Organic Cond

Source 

Index 

PM10-

PM2.5 

(g/s) 

Solid 

PM2.5 

(g/s) 

Org. 

Cond 

(g/s) 

InOrg. 

Cond 

(g/s) 

6-10μm 

(g/s) 

2.5-

6.00μm 

(g/s) 

1.25-

2.5μm 

(g/s) 

1.00-

1.25μm 

(g/s) 

0.625-

1.00μm1 

(g/s) 

0.500-

0.625μm1 

(g/s) 

0.625-

1.00μm 

(g/s) 

0

wpp1 24.176 5.869 8.587 0.000 0.000 6.044 6.044 10.338 10.338 2.935 

Table 2-10. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘Alternative to BART’ Case. 

 Coarse PM Fine PM Organic Cond

Source 

Index 

PM10-

PM2.5 

(g/s) 

Solid 

PM2.5 

(g/s) 

Org. 

Cond 

(g/s) 

InOrg. 

Cond 

(g/s) 

6-10μm 

(g/s) 

2.5-

6.00μm 

(g/s) 

1.25-

2.5μm 

(g/s) 

1.00-

1.25μm 

(g/s) 

0.625-

1.00μm1 

(g/s) 

0.500-

0.625μm1 

(g/s) 

0.625-

1.00μm 

(g/s) 

0

wpp123 15.36 3.251 3.815 0.000 0.000 3.840 3.840 5.748 5.748 1.626 

wpp4 18.303 13.806 1.268 0.000 0.000 4.576 4.576 5.210 5.210 6.903 

Table 2-11. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART with Potlines Scrubbed’ Case. 

 Coarse PM Fine PM Organic Cond

Source 

Index 

PM10-

PM2.5 

(g/s) 

Solid 

PM2.5 

(g/s) 

Org. 

Cond 

(g/s) 

InOrg. 

Cond 

(g/s) 

6-10μm 

(g/s) 

2.5-

6.00μm 

(g/s) 

1.25-

2.5μm 

(g/s) 

1.00-

1.25μm 

(g/s) 

0.625-

1.00μm1 

(g/s) 

0.500-

0.625μm1 

(g/s) 

0.625-

1.00μm 

(g/s) 

0

W01 1.591 4.335 10.879 0.000 0.000 0.398 0.398 5.837 5.837 2.168 W02 0.374 0.700 1.758 0.000 0.000 0.094 0.094 0.973 0.973 0.350 

wpp23 12.750 2.699 3.167 0.000 0.000 3.188 3.188 4.771 4.771 1.350 

wpp4 2.745 1.268 13.806 0.000 0.000 0.686 0.686 7.589 7.589 0.634 

Table 2-12. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Control Level’ Case. 

 Coarse PM Fine PM Organic Cond

Source 

Index 

PM10-

PM2.5 

(g/s) 

Solid 

PM2.5 

(g/s) 

Org. 

Cond 

(g/s) 

InOrg. 

Cond 

(g/s) 

6-10μm 

(g/s) 

2.5-

6.00μm 

(g/s) 

1.25-

2.5μm 

(g/s) 

1.00-

1.25μm 

(g/s) 

0.625-

1.00μm1 

(g/s) 

0.500-

0.625μm1 

(g/s) 

0.625-

1.00μm 

(g/s) 

0

wpp23 12.75 2.699 3.167 0.000 0.000 3.188 3.188 4.771 4.771 1.350 

wpp4 2.745 1.268 13.806 0.000 0.000 0.686 0.686 7.589 7.589 0.634 
 3-1 Screening Modeling

3.0 SCREENING MODELING 

As a first step into the BART analysis for Alcoa Warrick and Warrick Power Plant, screening 

simulations were made to analyze the influence of the facilities at Class I Areas located up to 500 km 

from the site (Table 3-1). For the screening simulations and BART analysis, VISTAS 12-km regional 

CALMET domain was used (VISTAS, 2005) with CALPUFF computational subdomain to cover the 

facility, all seven Class I areas and sufficient buffer zone of 100 km around the facility and Class I areas 

(Figure 3-1). This is a sufficient buffer zone at the boundaries which allows for the effects of flow 

curvature and possible small-scale recirculation to be evaluated. 

Method 6 visibility was used with monthly average relative humidity factors as listed in Table 3-2 and 

estimated natural concentrations for East United States as listed in Table 3-3. 

As indicated in the LADCO (2006) protocol, emission controls for the Warrick facility are normally 

based on impacts at the Class I area with the highest predicted visibility impairment. The results of the 

screening simulations showed that this will always be Mammoth Cave, which is by a large margin the 

closest Class I area to the facility (Table 2-4). Mammoth Cave is approximately 120 km from the 

facility while the next nearest Class I area (Mingo) is more than twice as far away. The other Class I 

areas on the list are all close to or beyond 400 km away from the facility. 

Results in Table 3-4 are presented for each of the modeled year separately (2001 to 2003) and for all 3 

years together. The 98th percentile value for a single year is the 8th highest values, while for three-year 

period is the 22nd highest. 

Since Mammoth Cave is the Class I area with the highest impacts, the modeling presented in this report 

is conducted with the domain that is appropriate for refined modeling of the visibility impacts from the 

Warrick sources on Mammoth Cave. The description of this domain, its characteristics and 

methodology used in the refined modeling is described in the next section. 

An additional modeling domain will be constructed for the supplemental refined modeling of the 

visibility impacts in the Mingo Class I area. Although Mingo is nearly 270 km away from the source, 

while Mammoth cave is only 120 km away, visibility impacts at Mingo will be evaluated at the request 

of IDEM. These results will be reported separately within 60 days, as agreed to by IDEM. 
 3-2 Screening Modeling

Table 3-1. Class I Areas within 500 km of Alcoa Warrick 

Class I Area Distance from 

Warrick (km) 

Mammoth Cave 120 

Mingo 268 

Sipsey 391 

Great Smoky Mountains 394 

Joyce Kilmer 401 

Cohutta 404 

Shining Rock 481 

Table 3-2. Monthly f(RH) Values Based on Area Centroids for Application with Visibility Method 6 

Class I area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Mammoth Cave 3.4 3.1 2.9 2.6 3.2 3.5 3.7 3.9 3.9 3.4 3.2 3.5 

Mingo 3.3 3.0 2.8 2.6 3.0 3.2 3.3 3.5 3.5 3.1 3.1 3.3 

Sipsey 3.4 3.1 2.9 2.8 3.3 3.7 3.9 3.9 3.9 3.6 3.3 3.4 

Great Smoky 3.3 3.0 2.9 2.7 3.2 3.9 3.8 4.0 4.2 3.8 3.3 3.4 

Joyce Kilmer 3.3 3.1 2.9 2.7 3.3 3.8 4.0 4.2 4.2 3.8 3.3 3.5 

Cohutta 3.3 3.1 3.0 2.8 3.4 3.8 4.0 4.2 4.2 3.8 3.4 3.5 

Shining Rock 3.3 3.0 2.9 2.7 3.4 3.9 4.1 4.5 4.4 3.8 3.3 3.4 

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (U.S EPA, 2003), Appendix A

Table 3-3. Average Natural Levels of Aerosol Components 

 East (μg/m3) 

Ammonium sulfate 0.23 

Ammonium nitrate 0.1 

Organic carbon 1.4 

Elemental carbon 0.02 

Soil 0.5 

Coarse Mass 3 

Source: Guidance for Estimating Natural Visibility Conditions 

Under the Regional Haze Rule (U.S EPA, 2003), Table 2-1
 3-3 Screening Modeling

Figure 3-1. Terrain elevations for the VISTAS CALMET 12-km regional domain. CALPUFF 

computational subdomain, the Class I areas and the locations of Warrick facilities are also 

shown. 

200 400 600 800 1000 1200 1400 1600 1800 2000

LCC East (km)

-1600

-1400

-1200

-1000

-800

-600

-400

-200

0

200

400

LCC North (km)

LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84

Elevation

(meters)

AL GA

TN

SC

NC

VA

FL

KY

MS

WV

Sipsey

Cohutta

Mammoth Cave

Mingo

Great Smoky Mountains

Joyce Kilmer-Slickrock

Shining Rock

-25

0.1

50

100

150

200

300

400

500

600

700

800

900

1000

1100

1200

1300

1400

Warrick

CALPUFF 

computational domain
 3-4 Screening Modeling

Table 3-4. Results of the Screening Simulations 

Class I Area 

(distance from 

Warrick (km)) Year 

Maximum 

Delta 

Bext 

98th 

Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th 

Percentile 

Delta 

Deciview 

 (%) 

(#days>5%, 

#days>10%) 

(%) (dv) 

(#days>0.5dv, 

#days>1dv) 

(dv) 

 

Mammoth Cave (120) 2001 94.68 (105,74) 60.12 6.662 (105,73) 4.708 

Mingo (268) 2001 71.84 (44,33) 39.44 5.414 (44,32) 3.325 

Sipsey (391) 2001 67.69 (53,25) 25.52 5.169 (52,24) 2.273 

Great Smoky (394) 2001 51.04 (40,20) 15.00 4.124 (37,18) 1.397 

Joyce Kilmer (401) 2001 43.27 (35,12) 11.66 3.596 (32,11) 1.103 

Cohutta (404) 2001 25.44 (37,11) 12.92 2.267 (35,10) 1.255 

Shining Rock (481) 2001 32.84 (21,10) 12.70 2.839 (20,10) 1.195 

 

Mammoth Cave (120) 2002 133.75 (89,62) 68.73 8.491 (87,59) 5.232 

Mingo (268) 2002 92.30 (67,47) 53.87 6.463 (66,47) 4.286 

Sipsey (391) 2002 67.10 (56,33) 31.72 5.134 (55,32) 2.755 

Great Smoky (394) 2002 32.51 (47,19) 16.46 2.815 (46,18) 1.524 

Joyce Kilmer (401) 2002 29.75 (38,18) 16.85 2.604 (37,17) 1.557 

Cohutta (404) 2002 82.52 (40,22) 20.89 6.017 (39,20) 1.903 

Shining Rock (481) 2002 13.97 (21,1) 7.49 1.307 (21,1) 0.725 

 

Mammoth Cave (120) 2003 150.13 (134,107) 85.01 9.168 (132,105) 6.153 

Mingo (268) 2003 142.82 (44,33) 30.98 8.872 (44,33) 2.699 

Sipsey (391) 2003 50.01 (61,38) 28.70 4.056 (61,38) 2.523 

Great Smoky (394) 2003 32.95 (59,29) 24.26 2.848 (58,28) 2.172 

Joyce Kilmer (401) 2003 37.78 (49,19) 22.79 3.205 (49,18) 2.053 

Cohutta (404) 2003 38.66 (57,24) 23.38 3.269 (56,22) 2.101 

Shining Rock (481) 2003 20.87 (30,13) 14.28 1.895 (30,12) 1.335 

 

Mammoth Cave (120) 2001-2003 150.13 (328,243) 72.38 9.168 (324,237 5.445 

Mingo (268) 2001-2003 142.82 (155,113) 43.39 8.872 (154,112) 3.604 

Sipsey (391) 2001-2003 67.69 (170,96) 29.31 5.169 (168,94) 2.570 

Great Smoky (394) 2001-2003 51.04 (146,68) 19.53 4.124 (141,64) 1.784 

Joyce Kilmer (401) 2001-2003 43.27 (122,49) 16.85 3.596 (118,46) 1.557 

Cohutta (404) 2001-2003 82.52 (134,57) 18.07 6.017 (130,52) 1.661 

Shining Rock (481) 2001-2003 32.84 (72,24) 11.70 2.839 (71,23) 1.107 
 4-5 Geophysical and Meteorological Data 

4.0 GEOPHYSICAL AND METEOROLOGICAL DATA FOR REFINED MODELING 

4.1 Terrain 

Gridded terrain elevations for the modeling domain are derived from 3 arc-second digital elevation 

models (DEMs) produced by the United States Geological Survey (USGS). Data are provided in files 

covering 1 degree by 1 degree blocks of latitude and longitude. The 1-degree DEMs are produced by the 

Defense Mapping Agency using cartographic and photographic sources. USGS 1:250,000 scale 

topographic maps are the primary source of 1-degree DEMs. 

One degree DEM data consists of an array of 1201 by 1201 elevations referenced on the geographic 

(latitude/longitude) coordinate system of the World Geodetic System 1972 Datum. Elevations are in 

meters relative to mean sea level, and the spacing of the elevations along each profile is 3 arc-seconds, 

which corresponds to a spacing of approximately 90 meters. 

The CALMET computational domain is located over Warrick County, Indiana. The modeling domain 

covers an area of 225 km by 195 km (Figure 4-1) which includes Mammoth Cave National Park, located 

directly southeast of the source. The domain includes an adequate buffer of more than 50 km in each 

direction both from the Class I area and the facility . The terrain is gently rolling, with terrain height 

increasing to the east of the model domain. A horizontal resolution of 1 km represents the variations of 

the terrain elevations and land use in the area. Figure 4-1 shows contours of the terrain averaged to 1 

km. The USGS elevation records located within each grid cell in the computational domain were 

averaged to produce a mean elevation at each grid point. Adequate representation of the important 

terrain features and valleys associated with the Class I area and the surrounding area are captured by the 

225 x 195 grid cells, a workable number of cells. The CALPUFF computational domain is the same as 

the CALMET domain. The domain extends beyond the Class I area in order to provide an adequate 

buffer zone at the boundaries, and to allow the effects of flow curvature and possible small-scale 

recirculation to be evaluated. 

4.2 Land Use 

The USGS Land Use data in the vicinity of the facility were used to produce a gridded field of dominant 

Land Use categories. The land use data used in the analysis are the Composite Theme Grid land use data 

(CTG) from the USGS, at a resolution of 200 m. 

Land use data were processed to produce a 1 km resolution gridded field of fractional Land Use 

categories. The 37 USGS Land Use categories were then mapped into 14 CALMET LU categories. 

Surface properties such as albedo, Bowen ratio, roughness length, and leaf area index were computed 

proportionally to the fractional LU. The USGS Land Use categories are described in Table 4-1 of the 

Alcoa Warrick Modeling Protocol (2008). Table 4-2 in the same Protocol displays the 14 CALMET 

land use categories and their associated geophysical parameters. Figure 4-2 show the dominant land use 

categories used in the modeling. 
 4-6 Geophysical and Meteorological Data 

Figure 4-1. Terrain contours (m MSL) at 1 km resolution for the 225 x 195 CALMET and CALPUFF 

computational domains. The Class I area, Mammoth Cave NP and the Alcoa Warrick 

facility are shown. 

400 450 500 550 600 650

UTM X Coordinate (km) - NAR-C

4050

4100

4150

4200

4250

UTM Y Coordinate (

km) - NAR-C

Alcoa Warrick Aluminum Plant

Mammoth Cave National Park

IN

TN

KY

IL

100

125

150

175

200

225

250

275

300

325

terrain

elevations

(m)
 4-7 Geophysical and Meteorological Data 

Figure 4-2. Dominant land use categories at 1 km resolution on the 225 km x 195 km CALMET and 

CALPUFF model domains. Mammoth Cave National Park and the facility are also shown. 

400 450 500 550 600 650

UTM X Coordinate (km) - NAR-C

4050

4100

4150

4200

4250

UTM Y Coordinate (

km) - NAR-C

Alcoa Warrick Aluminum Plant

Mammoth Cave National Park

Urban land

Agricultural land

Range land

Forest land

Water

Wet land

Barren land

Tundra

Snow and Ice

10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 95 100

IN

TN

KY

IL
 4-8 Geophysical and Meteorological Data 

4.3 Meteorological Data Base 

The wind fields in the modeling domain are expected to be variable. Depending on the location, some of 

the observational data is only representative of a small area around itself. The local terrain is expected to 

influence the local flow, much of the structure in the wind fields were determined by CALMET using its 

diagnostic wind field module, rather than being driven by observations. 

The CALMET model requires meteorological information from the surface and upper air as well as 

geophysical information about the Land Use and terrain heights. Specifically, CALMET requires 

surface observations of wind speed, wind direction, temperature, cloud cover, ceiling height, surface 

pressure, relative humidity, and precipitation type (e.g., snow, rain, etc.). These variables are routinely 

measured at the National Weather Service (NWS) surface stations. The upper air data include twicedaily observations of vertical profiles of wind speed, wind direction, temperature, and pressure. In 

addition, hourly precipitation measurements were included in the modeling and are required for wet 

deposition calculations in CALPUFF. Three-dimensional gridded data from the prognostic numerical 

model MM5 were also included as well as RUC data for the 2003 modeling. Table 4-1 lists the types of 

observational and modeled data available that were used in the modeling. There are ten surface 

meteorological stations that were used, all located within or near the modeling domain (Table 4-2): 

Louisville Standiford, KY; Capitol City, KY; Louisville Bowman, KY; Owensboro, KY; Henderson 

City, KY; Fort Knox, KY; Evansville, KY; Huntingsburg, KY; Lawrenceville, KY; Fort Campbell, KY, 

and, Bowling Green, KY. The surface data were extracted from the Integrated Surface Hourly Weather 

Observations (ISHWO) CD-roms (Volume 19 for 2001, Volume 23 for 2002) and 2003 ISHWO DVD. 

Upper air data were extracted from the FSL/NCDC Radiosonde Database at http://raob.fsl.noaa.gov/. 

The available upper air sites are Nashville, TN and Lincoln-Logan County, IL (Table 4-3). Both these 

sites are located well off the model domain. Precipitation stations used in modeling are listed in Table 4-

4. These data were obtained from NCDC in TD3240 format. Figure 4-3, Figure 4-4 and Figure 4-5 show 

the locations and spatial coverage of all of these stations for 2001, 2002 and 2003. 

4.4 Air Quality Monitoring Data 

CALPUFF uses hourly ozone concentration measurements in the chemical transformation rates (SO2 to 

SO4, NOx to HNO3/NO3). The ambient ozone measurements are used in determining SO2 loss rates due 

to chemical transformation to sulfate and in determining NOx loss rates to nitrate. Ambient ozone 

monitoring data for 2001, 2002 and 2003 were extracted from the U.S. EPA AIRS and CASTNet 

networks and were used to develop hourly ozone monitoring data files for the each year of the modeling 

analysis. A total of ~35 monitoring stations, listed in Table 4-5, were available for use in the modeling 

(see Figure 4-6, Figure 4-7 and Figure 4-8 which show the locations of each of the available stations for 

each year to be modeled.) This is a refinement to the LADCO procedure in that spatially varying hourly 

ozone data were used in the modeling instead of the monthly ozone values constant in space 

recommended in Table 2 of LADCO protocol. 

A constant ammonia concentration of 0.5 parts per billion (ppb) was used in the modeling. 
 4-9 Geophysical and Meteorological Data 

Table 4-1. Meteorological Data Sources and Parameters Available 

Type of Dataset Frequency Source Parameters 

Surface obs. Hourly NWS/NCDC Wind speed, wind 

direction, temperature, 

ceiling height, cloud 

cover, relative humidity, 

surface pressure, 

precipitation type 

Upper Air Twice-daily NWS/NCDC Soundings of wind speed, 

wind direction, 

temperature, and pressure 

Precipitation Hourly NWS/NCDC Hourly precipitation 

amounts 

Modeled Profiles 

MM5 for 2001, 2002 

RUC data for 2003 

Hourly 

Hourly 

VISTAS 

NCEP 

Hourly, gridded fields of 

winds, temperature, 

pressure, and humidity and 

liquid water content on 12 

km grid for 2001 and 

2002. 

Same as MM5 above, but 

on 20 km grid for 2003. 
 4-10 Geophysical and Meteorological Data 

Table 4-2. NWS Hourly Surface Stations 

WMO INIT Station Name State Year Latitude 

(deg) 

Longitude 

(deg) 

Elevation 

(m) 

UTM X1

(km) 

UTM Y1

(km) 

724230 KSDF Louisville 

Standiford 

KY 01,02,03 38.18 85.73 146.6 611.232 4226.549 

724233 KFFT Capitol City Ap KY 01,02,03 38.18 84.90 245.0 683.933 4227.871 

724235 KLOU Louisville Bowman 

Fld 

KY 01,02,03 38.23 85.67 164.6 616.407 4232.171 

724237 KOWB Owensboro/Davies KY 01,02,03 37.73 87.17 124.0 485.020 4175.872 

724238 KEHR Henderson City KY 01,02,03 37.82 87.68 117.0 440.152 4186.062 

724240 KFTK Fort Knox Godman 

Ap 

KY 01,02,03 37.90 85.97 239.0 590.555 4195.220 

724320 KEVV Evansville Regional 

Ap 

KY 01,02,03 38.05 87.53 116.1 453.499 4211.495 

724365 KHNB Huntingburg KY 01,03 38.25 86.95 161.0 504.375 4233.555 

725342 KLWW Lawrenceville IL 01,02,03 38.77 87.60 131.0 447.877 4291.425 

744656 KFWC Fairfield IL 03 38.42 88.42 133.0 376.296 4253.035 

744659 KOLY Olney-Noble IL 03 38.72 88.18 147.0 397.154 4286.037 

746710 KHOP Fort Campbell Ap KY 01,02,03 36.67 87.48 173.1 455.320 4058.382 

746716 KBWG Bowling Green 

Warren 

KY 01,02,03 36.98 86.43 160.9 550.730 4092.806 

_______ 

1 Datum is NAD83, UTM Zone 16. 

Table 4-3. Upper Air Stations 

# Station Name WBAN# Latitude Longitude UTM X1

 UTM Y1 Elevation 

 (deg) (deg) (km) (km) (m) 

1 Lincoln-Logan 

County, Ap, IL 04833 36.25 86.57 301.538 4447.009 180.0 

2 Nashville, TN 13897 40.15 89.33 538.632 4011.764 178.0 

_______ 

1 Datum is NAD83, UTM Zone 16. 
 4-11 Geophysical and Meteorological Data 

Table 4-4. Hourly NWS Precipitation Stations 

Station Name Station ID Year of Longitude Latitude UTM X1 UTM Y1

 Data (deg) (deg) (km) (km)

 

Newburgh Lock & Dam, IN 126151 03 37.93 87.37 467.484 4198.113 

JT Myers Locks & Dam, IN 128967 02,03 37.8 87.99 412.844 4184.087 

Cannelton, IN 121256 01 37.9 86.63 532.529 4194.785 

Calhoun Lock, KY 151227 01,02,03 37.53 87.27 476.144 4153.704 

Custer 4 SE, KY 151980 01,02,03 37.72 86.22 568.742 4175.036 

Dundee 2 NE, KY 152358 02,03 37.58 86.78 519.425 4159.240 

Fordsville, KY 152979 01,02,03 37.63 86.72 524.703 4165.911 

Herndon 5 S, KY 153798 01,02,03 36.67 87.58 449.959 4058.412 

Hodgenville Lincoln, KY KY 153929 01,03 37.53 85.73 611.329 4154.416 

Lebanon 5 S, KY 154650 01,02 37.52 85.3 650.229 4153.918 

Madisonville, KY 155067 01,03 37.35 87.52 453.945 4133.827 

Munfordville 5 NW, KY 155684 01,02 37.33 85.95 593.021 4131.998 

Princeton 1 SE, KY 156580 01,03 37.12 87.87 422.712 4108.539 

Scottsville 3 SSW, KY 157215 01,02 36.73 86.22 569.656 4064.095 

Willisburg, KY 158719 01,02,03 37.8 85.12 665.514 4185.290 

Woodbury, KY 158824 01,02,03 37.18 86.63 532.843 4114.905 

Carthage, TN 401480 03 36.25 85.95 594.336 4012.189 

Celina, TN 401561 01,02,03 36.54 85.46 637.849 4044.948 

Lebanon, TN 405108 03 36.23 86.32 561.109 4009.674 

Springfield Exp Stn, TN 408562 01,02,03 36.47 86.85 513.439 4036.091 

_______ 

1 Datum is NAD83, UTM Zone 16. 
 4-12 Geophysical and Meteorological Data 

Figure 4-3. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the refined 

2001 modeling. Mammoth Cave National Park and the facility are also shown. 
 4-13 Geophysical and Meteorological Data 

Figure 4-4. Plot of all the surface, upper air, MM5 and precipitation stations to be used in the refined 

2002 modeling. Mammoth Cave National Park and the facility are also shown. 
 4-14 Geophysical and Meteorological Data 

Figure 4-5. Plot of all the surface, upper air, RUC data and precipitation stations to be used in the 

refined 2003 modeling. Mammoth Cave National Park and the facility are also shown. 
 4-15 Geophysical and Meteorological Data 

Table 4-5. Ozone Stations 

Network Year ID 

Latitude 

(deg) 

Longitude 

(deg) 

UTM X1

(km) 

UTM Y1

(km) 

AIRS 01,02,03 170650001 37.99822 -88.49311 368.898 4206.676 

AIRS 01,02,03 180190003 38.37695 -85.69028 614.405 4248.458 

AIRS 01,02,03 180431004 38.30806 -85.83417 601.933 4240.645 

AIRS 01,02,03 180510011 38.42525 -87.46589 459.333 4253.108 

AIRS 01,02,03 181290003 38.00528 -87.71833 436.935 4206.651 

AIRS 01,02,03 181630013 38.11389 -87.53694 452.93 4218.594 

AIRS 01,02,03 181730002 37.93750 -87.31416 472.393 4198.934 

AIRS 01,02,03 181730008 38.05195 -87.27834 475.58 4211.622 

AIRS 01,02,03 181730009 38.19444 -87.34139 470.105 4227.451 

AIRS 01,02,03 210470006 36.91167 -87.32361 471.173 4085.131 

AIRS 01,02,03 210590005 37.78083 -87.07555 493.347 4181.508 

AIRS 01,02,03 210610501 37.13139 -86.14806 575.675 4109.796 

AIRS 01,02,03 210830003 36.89917 -88.49361 366.921 4084.737 

AIRS 01,02,03 210910012 37.93889 -86.89694 509.056 4199.047 

AIRS 01,02,03 210930006 37.70639 -85.85167 601.226 4173.867 

AIRS 01,02,03 211010014 37.87139 -87.46333 459.249 4191.653 

AIRS 01,02,03 211110027 38.13722 -85.57833 624.593 4222.001 

AIRS 01,02,03 211110051 38.06083 -85.89611 596.843 4213.146 

AIRS 01,02,03 211111021 38.26361 -85.71167 612.712 4235.855 

AIRS 01,02,03 211390003 37.15556 -88.39306 376.297 4113.046 

AIRS 01,02,03 211490001 37.60639 -87.25389 477.590 4162.182 

AIRS 02 211771004 37.22729 -87.15833 485.954 4120.099 

AIRS 01,02,03 211850004 38.39861 -85.44334 635.936 4251.196 

AIRS 01,02,03 212130004 36.70861 -86.56639 538.729 4062.645 

AIRS 01,02,03 212210013 36.90139 -88.01361 409.693 4084.422 

AIRS 01,02,03 212270008 37.03667 -86.25056 566.653 4099.211 

AIRS 01,02,03 471410004 36.20500 -85.39945 643.89 4007.884 

AIRS 01,02,03 471650007 36.29778 -86.65278 531.178 4017.043 

AIRS 01,02,03 471650101 36.45389 -86.56416 539.056 4034.391 

CASTNet 01,02,03 CDZ171 36.7841 -87.8499 424.165 4071.259 

CASTNet 01,02,03 VIN140 38.7408 -87.4853 457.824 4288.125 

CASTNet 02,03 MAC426 37.2806 -86.2639 565.254 4126.255 

CASTNet 01,02,03 MCK131 37.7046 -85.0485 672.0299 4174.833 

CASTNet 01.02,03 MCK231 37.7046 -85.0485 672.0299 4174.833 

 

_______ 

1 Datum is NAD83, UTM Zone 16. 
 4-16 Geophysical and Meteorological Data 

Figure 4-6. Plot of all the ozone stations, both CASTNet and AIRS, used in the refined 2001 modeling. 

Mammoth Cave National Park and the facility are also shown. 
 4-17 Geophysical and Meteorological Data 

Figure 4-7. Plot of all the ozone stations, both CASTNet and AIRS, used in the refined 2002 modeling. 

Mammoth Cave National Park and the facility are also shown. 
 4-18 Geophysical and Meteorological Data 

Figure 4-8. Plot of all the ozone stations, both CASTNet and AIRS, used in the refined 2003 modeling. 

Mammoth Cave National Park and the facility are also shown. 
5-1 Air Quality Modeling Methodology 

5.0 AIR QUALITY MODELING METHODOLOGY 

5.1 Model Selection 

The terrain of the region, the large source-receptor distances, and the importance of chemical 

transformation, wet deposition, and dry deposition are important factors in the modeling. All these 

factors are treated in the chosen modeling approach using the CALPUFF model (Scire et al., 2000a,b) 

for the BART analysis for Mammoth Cave National Park. CALPUFF and its meteorological model 

CALMET, are designed to handle the complexities posed by complex terrain, the long source receptor 

distances, chemical transformation and deposition, and other issues related to Class I impacts. The U.S. 

Environmental Protection Agency (EPA) has recommended CALPUFF as the preferred model for 

BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline Model 

for Class I impact assessments and other long range transport applications and on a case-by-case basis 

for near-field applications involving complex flows (U.S. EPA, 2003a). CALPUFF is also 

recommended by both the Federal Land Managers Air Quality Workgroup (FLAG, 2000) and the 

Interagency Workgroup on Air Quality Modeling (U.S. EPA, 1998). CALPUFF is also recommended 

by the draft revised FLAG procedures (FLAG (2008). The modeling simulations used the EPA 

regulatory version of the CALPUFF modeling system (Version 5.8 series). 

CALMET is a diagnostic meteorological model that produces three-dimensional wind and temperature 

fields and two-dimensional fields of mixing heights and other meteorological fields. It contains slope 

flow effects, terrain channeling, and kinematic effects of terrain. CALPUFF is a non-steady-state 

Gaussian puff model. It includes algorithms for building downwash effects as well as chemical 

transformation, wet deposition, and dry deposition. One capability of CALPUFF not found in many 

specialized models such as CTDMPLUS is the ability to treat the combined effects of multiple 

processes (e.g., building downwash effects in complex terrain; dry deposition and overwater dispersion, 

etc.). A complete summary of the capabilities and features of CALMET and CALPUFF is provided in 

Sections 5.1.1 and 5.1.2 of the Alcoa Warrick Modeling Protocol (2008). 

5.2 Modeling Domain Configuration 

CALMET and CALPUFF use terrain-following coordinates. In order to cover a large enough area, a 

modeling domain of 225 x 195 grid cells, uniform in the horizontal with a spatial resolution of 1 km was 

used. In the vertical, a stretched grid was used with finer resolution in the lower layers and somewhat 

coarser resolution aloft thus allowing adequate representation of the mixed layer. The ten vertical levels 

were centered at: 10, 30, 60, 120, 240, 480, 820, 1250, 1850 and 2600 meters. 
5-2 Air Quality Modeling Methodology 

5.3 Meteorological Modeling Options 

Initial Guess Field 

MM5 data and RUC data were used to define the initial guess field for the CALMET simulations. For 

2001 and 2002 hourly MM5 data with a grid spacing of 12 km and 34 vertical levels were used as the 

initial guess wind field. RUC data with a grid spacing of 20 km and 50 vertical levels were used as the 

initial guess wind field for 2003. 

This data set provides better resolution prognostic data from the 36 km MM5 data set for 2002-2004 in 

LADCO (2006). The higher resolution of the prognostic meteorological data set was the driving force 

for choosing the years 2001-2003 over the 2002-2004 period from LADCO. 

Step 1 Field: Terrain Effects 

In developing the Step 1 wind field, CALMET adjusts the initial guess field to reflect kinematic effects 

of the terrain, slope flows and blocking effects. Slope flows are a function of the local slope and altitude 

of the nearest crest. The crest is defined as the highest peak within a radius TERRAD around each grid 

point. A value of TERRAD of 10 km was determined based on an analysis of the scale of the terrain and 

that value was used in the CALMET simulations. The Step 1 field produces a flow field consistent with 

the fine-scale CALMET terrain resolution (1 km). 

Step 2 Field: Objective Analysis 

In Step 2, observations are incorporated into the Step 1 wind field to produce a final wind field. Each 

observation site influences the final wind field within a radius of influence (parameters RMAX1 at the 

surface and RMAX2 aloft). Observations and Step 1 field are weighted by means of parameters R1 at 

the surface and R2 aloft: at a distance R1 from an observation site, the Step 1 wind field and the surface 

observations are weighted equally. RMAX1 and RMAX2 were set to large values (40 km), while 

moderate values of R1 and R2 (10 km) were used in order to allow diagnostically-generated terrain 

effects to be retained in the final wind fields. 

5.4 CALPUFF Computational Domain and Receptors 

CALPUFF was run for three years, 2001, 2002 and 2003. The CALPUFF computational domain is the 

same as the CALMET computational domain. The modeling domain includes a buffer zone of at least 

50 km from the source and beyond the borders of the Class I area. This minimizes the edge effects and 

allows pollutants involved in flow reversals to be brought back into the Class I areas. 

The receptor locations along with receptor elevations were available from the National Park Service 

(NPS). This gridded field of discrete receptors was used and is located within the boundaries of the 

Mammoth Cave National Park. 
5-3 Air Quality Modeling Methodology 

5.5 Dispersion Modeling Options 

The CALPUFF simulations were conducted using the following model options: 

 - Gaussian near-field distribution 

 - Transitional plume rise 

 - Stack tip downwash 

 - Pasquill-Gifford (PG) dispersion coefficients (rural areas) and 

McElroy-Pooler coefficients (urban areas) 

 - Transition of σy to time-dependent (Heffter) growth rates 

 - Partial plume path adjustment for terrain 

 - Wet deposition, dry deposition, and chemical transformation were considered. 

Two important computational parameters in CALPUFF are XMXLEN (maximum length of an emitted 

puff, in grid units) and XSAMLEN (maximum travel distance of a puff, in grid units, during one time 

step). Both of these variables were set to 1.0 in the CALPUFF simulations in order to allow the strong 

wind channeling effects to be accounted for in the puff trajectory calculations. The first parameter 

ensures that the length of an emitted puff does not become so large so that it cannot respond to changes 

in the wind field on the scale of the meteorological grid. The model automatically increases the 

frequency of puff releases to ensure the length of a single puff is not larger than the grid size. The 

second parameter decreases the internal time step to ensure the travel distance during one time step does 

not exceed the grid size. 

The partial plume path adjustment option was used in CALPUFF for this analysis (MCTADJ=3). The 

CALMET wind field incorporates the effect of the terrain on the plume trajectories. The plume path 

coefficient is used to characterize the local effect on ground-level concentrations. The default plume 

path coefficients (PPC) used for this analysis are listed below: 

Stability Class A B C D E F 

PPC 0.5 0.5 0.5 0.5 0.35 0.35 

Deposition and chemical transformation effects were modeled using the default dry deposition model, 

the scavenging coefficient wet removal module, and the default chemical transformation mechanism. 

Eleven species were modeled with CALPUFF for this analysis: SO2, SO4, NOx, HNO3, NO3, and six 

subcategories of PM10, (PM800, PM425, PM187, PM112, PM081, PM056). Of these eleven species, five are 

emitted by the project sources: SO2, SO4, NOx, PM10, and NH3. The chemical mechanism computes 

transformation rates of SO2 to SO4 and NOx to NO3/HNO3. Hourly measured ozone concentrations were 

provided in an external OZONE.DAT file for use with the chemical transformation module. These 

ozone concentrations, along with radiation intensity, were used as surrogates for the OH concentration 

during the day when the gas phase free radical chemistry was active. 
5-4 Air Quality Modeling Methodology 

To allow for flexibility each source was modeled individually and their source contributions were 

summed at the end. 

5.6 Visibility Calculations 

Calculations of the impact of the simulated plume particulate matter component concentrations on light 

extinction is carried out in the CALPOST postprocessor. The annual average values were used for the 

natural background values. The equation used is the usual IMPROVE/EPA equation which is applied to 

determine the change in light extinction due to changes in component concentrations. Using the 

notations of CALPOST, the formula is the following: 

Bext = 3f(RH)[(NH4)2SO4] + 3f(RH)[NH4NO3] + 

4[OC] + 1[Soil] + 0.6[Coarse Mass] +10[EC] + bray 

The concentrations, in square brackets, are in μg/m3

 and bext is in units of Mm-1. The Rayleigh scattering 

term (bray) has a default value of 10 Mm-1, as recommended in EPA Guidance for Estimating Natural 

Visibility Conditions Under the Regional Haze Program (U.S. EPA, 2003b). Note that organic carbon 

(OC) consists of condensable particulates which are assumed to be split evenly between the lowest two 

particle size categories. Soil is fine particulates which is defined as PM2.5. These species were created 

through scaling and summing of the CALPUFF output files using the POSTUTIL program. 

The haze index (HI) is calculated from the extinction coefficient via the following formula: 

HI = 10 ln(bext/10) 

where HI is in units of deciviews (dv) and bext is in Mm-1. The impact of a source is determined by 

comparing HI for estimated natural background conditions with the impact of the source and without the 

impact of the source. 

CALPOST Method 6 was used to compute the extinction change in deciviews consistent with the 

procedures outlined in the LADCO (2006) modeling protocol. 

A monthly background concentrations were entered into the CALPOST input control file. The annual 

average natural visibility conditions for Mammoth Cave were used. Annual background concentrations 

for the eastern United States are give in the Guidance for Estimating Natural Visibility Conditions in 

Table 2-1 (U.S. EPA, 2003b), and are also provided in Table 5-1 below. These background 

concentrations were entered in CALPOST. 

Table 5-2 provides the monthly f(RH) values based on the centroid of the Class I area as recommended 

by EPA for application of Method 6. The monthly f(RH) values for each month are extracted from 

Appendix A of Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule 

(2003). 

The 8th highest (98th percentile) predicted light extinction change value expressed in deciviews were 

compared to the threshold value of 0.5 deciviews (Section 6). 
5-5 Air Quality Modeling Methodology 

Table 5-1. Background Natural Visibility Concentrations for the Eastern United States 

 East (μg/m3) 

Ammonium sulfate 0.23 

Ammonium nitrate 0.1 

Organic carbon 1.4 

Elemental carbon 0.02 

Soil 0.5 

Coarse Mass 3 

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (2003), Table 2-1

Table 5-2. Monthly f(RH) Values for Mammoth Cave Based on the Area Centroid 

Class I area Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 

Mammoth Cave NP 3.4 3.1 2.9 2.6 3.2 3.5 3.7 3.9 3.9 3.4 3.2 3.5 

Source: Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule (2003), Appendix A
6-1 Results 

6.0 RESULTS 

The change in light extinction relative to the natural background due to sulfur dioxide, particulate matter 

and nitrogen oxides from the BART-eligible sources was computed. BART methodology with 

CALPOST Method 6 and 98th percentile day results were used to determine light extinction. The light 

extinction impacts at Mammoth Cave are presented for each modeled year in units of change in 

deciview and as a percent change in the light extinction coefficient, for each year separately as well as 

for a full three-year period. The results of the visibility calculations are presented in Table 6-1 through 

Table 6-5 for the ‘BART Eligible Baseline’ case and five other scenarios. 

For the ‘BART Eligible Baseline’ case, contribution from the sources is determined. Table 6-6 shows 

how are sources being grouped for the contribution, while Table 6-7 shows the contribution of the 

sources for each of the three modeled years. 
6-2 Results 

Table 6-1. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART Eligible 

Baseline’ Case Emissions. 

Year 

Maximum 

Delta 

Bext 

98th Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th Percentile 

Delta 

Deciview 

 (%) (%) (dv) (dv) 

 

2001 91.62 44.46 6.504 3.678 

 

2002 116.68 48.57 7.732 3.959 

 

2003 72.21 41.73 5.435 3.487 

 

2001-2003 116.68 44.69 7.732 3.694 

Table 6-2. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART Eligible 

Baseline + Unit 1’ Case Emissions. 

Year 

Maximum 

Delta 

Bext 

98th Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th Percentile 

Delta 

Deciview 

 (%) (%) (dv) (dv) 

 

2001 114.74 54.80 7.642 4.369 

 

2002 144.44 59.88 8.938 4.693 

 

2003 90.32 51.63 6.435 4.163 

 

2001-2003 114.74 55.65 8.938 4.424 

Table 6-3. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘Alternative to 

BART’ Case Emissions. 

Year 

Maximum 

Delta 

Bext 

98th Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th Percentile 

Delta 

Deciview 

 (%) (%) (dv) (dv) 

 

2001 21.76 11.27 1.969 1.068 

 

2002 26.76 7.89 2.371 0.759 

 

2003 24.42 9.45 2.185 0.903 

 

2001-2003 26.76 9.84 2.371 0.938 
6-3 Results 

Table 6-4. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART with Potlines 

Scrubbed’ Case Emissions. 

Year 

Maximum 

Delta 

Bext 

98th Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th Percentile 

Delta 

Deciview 

 (%) (%) (dv) (dv) 

 

2001 11.42 6.91 1.081 0.669 

 

2002 16.75 4.43 1.549 0.434 

 

2003 15.19 5.34 1.414 0.520 

 

2001-2003 16.75 5.41 1.549 0.527 

Table 6-5. Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART Control 

Level’ Case Emissions. 

Year 

Maximum 

Delta 

Bext 

98th Percentile 

Delta 

Bext 

 Maximum 

Delta 

Deciview 

98th Percentile 

Delta 

Deciview 

 (%) (%) (dv) (dv) 

 

2001 15.19 7.66 1.414 0.739 

 

2002 18.89 5.55 1.731 0.540 

 

2003 17.30 6.69 1.596 0.647 

 

2001-2003 18.89 6.88 1.731 0.665 
6-4 Results 

Table 6-6. Grouping of the Sources for the Contribution Values. 

Index Emission 

Unit ID # 

Stack Name Group 

Name 

L01 103M.1 Potline #2, Room 103 

L02 104M.1 Potline #2, Room 104 

L03 105M.1 Potline #3, Room 105 

L04 106M.1 Potline #3, Room 106 

L05 107M.1 Potline #4, Room 107 

L06 108M.1 Potline #4, Room 108 

L07 109M.1 Potline #5 , Room 109 

L08 110M.1 Potline #5, Room 110 

L09 111M.1 Potline #6 , Room 111 

L10 112M.1 Potline #6, Room 112 

Lines 

P01 GTC Potlines #3 & 4 GTC Controls GTC 

P02 160C1.1-160C1.36 Potline #2 A-398 

P03 161B5.1-161B5.36 Potline #5 A-398 

P04 161B6.1-161B6.36 Potline #6 A-398 

A398 

P23 134.62 Melter 1M1 

P24 134.64 Holder 1EH 

P25 134.65 Melter 1M2 

P26 134.66 Holder 1WH 

P28 134.33 Melter 5M1 

P29 134.35 Holder 5EH 

P30 134.36 Melter 5M2 

P31 134.38 Holder 5WH 

P32 134.39 Melter 5M3 

P33 134.4 Melter 6M1 

P34 134.41 Holder 6FH 

P35 134.42 Melter 6M2 

P36 134.43 Holder 6WH 

P37 134.44 Melter 6M3 

P39 134.71 Offlines #2 East Melter 

P41 134.75 Offlines #2 West Melter 

Holder/Melter 

wpp01 wpp01 Warrick Power Plant Units 2 wpp01 

wpp02 wpp02 Warrick Power Plant Units 3 wpp02 

wpp03 wpp03 Warrick Power Plant Unit 4 wpp03 
6-5 

Table 6-7. Source and Species Contributions to the 8th Highest Extinction Coefficient Changes for ‘BART Eligible Bas

Cave National Park. 

Source Group Bext Contrib. to Modeled Species Contribution to Modeled Extinction Coefficient in 1/Mm Percentage of Species Contribu

 Change Total Bext Ext. SO4 NO3 Organics E. Carbon PM_Coarse PM_Fine SO4 NO3 Organics E (%) Change(%) 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm 1/Mm % % % 

2001: 8th highest impact is 3.678 Deciview 

All 44.46 100.00 9.456 9.118 0.196 0.060 0.000 0.003 0.079 96.43 2.07 0.63 

Lines 0.12 0.26 0.025 0.007 0.000 0.009 0.000 0.002 0.007 28.00 0.00 36.00 

GTC 0.60 1.34 0.127 0.120 0.000 0.004 0.000 0.000 0.003 94.49 0.00 3.15 

A398s 0.86 1.94 0.183 0.172 0.000 0.007 0.000 0.000 0.004 93.99 0.00 3.83 

Melter/Holder 0.01 0.03 0.003 0.000 0.002 0.000 0.000 0.000 0.001 0.00 66.67 0.00 

wpp01 4.73 10.65 1.007 0.970 0.025 0.005 0.000 0.000 0.007 96.33 2.48 0.50 wpp02 15.74 35.40 3.347 3.239 0.075 0.014 0.000 0.000 0.019 96.77 2.24 0.42 wpp03 22.39 50.35 4.761 4.610 0.093 0.020 0.000 0.000 0.038 96.83 1.95 0.42 

2002: 8th highest impact is 3.959 Deciview 

All 48.57 100.00 10.473 7.877 2.425 0.069 0.000 0.001 0.101 75.21 23.15 0.66 

Lines 0.04 0.10 0.010 0.002 0.000 0.004 0.000 0.001 0.003 20.00 0.00 40.00 

GTC 0.33 0.67 0.070 0.063 0.001 0.004 0.000 0.000 0.002 90.00 1.43 5.71 

A398s 0.36 0.75 0.079 0.069 0.002 0.005 0.000 0.000 0.003 87.34 2.53 6.33 

Melter/Holder 0.01 0.02 0.002 0.000 0.002 0.000 0.000 0.000 0.000 0.00 100.00 0.00 

wpp01 5.33 10.96 1.148 0.818 0.313 0.007 0.000 0.000 0.010 71.25 27.26 0.61 wpp02 16.90 34.80 3.645 2.703 0.896 0.020 0.000 0.000 0.026 74.16 24.58 0.55 wpp03 25.60 52.71 5.520 4.223 1.210 0.030 0.000 0.000 0.057 76.50 21.92 0.54 

2003: 8th highest impact is 3.487 Deciview 

All 41.73 100.00 9.081 8.161 0.777 0.061 0.000 0.002 0.080 89.87 8.56 0.67 

Lines 0.08 0.19 0.017 0.004 0.000 0.007 0.000 0.001 0.005 23.53 0.00 41.18 

GTC 0.55 1.32 0.120 0.111 0.001 0.005 0.000 0.000 0.003 92.50 0.83 4.17 

A398s 0.82 1.95 0.177 0.164 0.001 0.007 0.000 0.000 0.005 92.66 0.56 3.95 

Melter/Holder 0.04 0.09 0.008 0.000 0.007 0.000 0.000 0.000 0.001 0.00 87.50 0.00 

wpp01 4.55 10.91 0.991 0.881 0.098 0.005 0.000 0.000 0.007 88.90 9.89 0.50 wpp02 15.05 36.08 3.276 2.937 0.304 0.015 0.000 0.000 0.020 89.65 9.28 0.46 wpp03 20.63 49.45 4.491 4.064 0.367 0.021 0.000 0.000 0.039 90.49 8.17 0.47 
 7-1 References 

7.0 REFERENCES 

Alcoa Warrick Modeling Protocol, 2008: Modeling Protocol for a BART Assessment of the Alcoa 

Warrick Operations and Warrick Power Plant, Warrick County, Indiana, 

Allwine, K.J. and C.D. Whiteman, 1985: MELSAR: A mesoscale air quality model for complex terrain: 

Volume 1--Overview, technical description and user's guide. Pacific Northwest Laboratory, 

Richland, Washington. 

Carson, D.J., 1973: The development of a dry, inversion-capped, convectively unstable boundary layer. 

Quart. J. Roy. Meteor. Soc., 99, 450-467. 

Douglas, S. and R. Kessler, 1988: User's guide to the diagnostic wind model. California Air Resources 

Board, Sacramento, CA. 

FLAG, 2000. Federal Land Manager' Air Quality Related Values Workgroup (FLAG). Phase I Report. 

U.S. Forest Service, National Park Service, U.S. Fish and Wildlife Service. 

FLAG, 2008. Federal Land Manager' Air Quality Related Values Workgroup (FLAG). Phase I Report 

(Revised). Draft report dated June 27, 2008. U.S. Forest Service, National Park Service, U.S. 

Fish and Wildlife Service. 

Holtslag, A.A.M. and A.P. van Ulden, 1983: A simple scheme for daytime estimates of the surface 

fluxes from routine weather data. J. Clim. and Appl. Meteor., 22, 517-529. 

Liu, M.K. and M. A. Yocke, 1980: Siting of wind turbine generators in complex terrain. J. Energy, 4, 

10:16. 

Lake Michigan Air Directors Consortium (LADCO), 2006: Single Source Modeling to Support 

Regional Haze BART Modeling Protocol. March 21, 2006. Available from 

http://www.in.gov/idem/files/BART_protocol.pdf 

Mahrt, L., 1982: Momentum Balance of Gravity Flows. Journal of Atmos. Sci., 39, 2701-2711. 

Maul, P.R., 1980: Atmospheric transport of sulfur compound pollutants. Central Electricity Generating 

Bureau MID/SSD/80/0026/R. Nottingham, England. 

O'Brien, J.J., 1970: A note on the vertical structure of the eddy exchange coefficient in the planetary 

boundary layer. J. Atmos. Sci., 27, 1213-1215. 

Perry, S.G., D.J. Burns, L.H. Adams, R.J. Paine, M.G. Dennis, M.T. Mills, D.G. Strimaitis, R.J. 

Yamartino, E.M. Insley, 1989: User's Guide to the Complex Terrain Dispersion Model Plus 

Algorithms for Unstable Situations (CTDMPLUS) Volume 1: Model Description and User 

Instructions. EPA/600/8-89/041, U.S. Environmental Protection Agency, Research Triangle 

Park, NC. 

Scire, J.S. and F.R. Robe, 1997: Fine-Scale Application of the CALMET Meteorological Model to a 

Complex Terrain Site. Paper 97-A1313. Air & Waste Management Association 90th Annual 

Meeting & Exhibition, Toronto, Ontario, Canada. 8-13 June 1997. 

Scire, J.S., D.G. Strimaitis, and R.J. Yamartino, 2000a: A User’s Guide for the CALPUFF Dispersion 

Model (Version 5). Earth Tech, Inc., Concord, MA 
 7-2 References 

Scire, J.S., F.R. Robe, M.E. Fernau, and R.J. Yamartino, 2000b: A User’s Guide for the CALMET 

Meteorological Model (Version 5). Earth Tech, Inc., Concord, MA. 

U.S. Environmental Protection Agency (EPA), 1998: Interagency Workgroup on Air Quality Modeling 

(IWAQM), Phase 2 Report: Summary Report and Recommendation for Modeling Long Range 

Transport and Impacts on Regional Visibility. EPA-454/R-98-019. 

U.S. Environmental Protection Agency (EPA), 2003a: Revision to the Guideline on Air Quality Models: 

Adoption of a Preferred Long Range Transport Model and Other Revisions; Final Rule. 40 CRF 

51. Federal Register, April 15, 2003, 68, 72, pp 18440-18482. 

U.S. Environmental Protection Agency (EPA), 2003b: Guidance for Estimating Natural Visibility 

Conditions Under the Regional Haze Program. EPA-454/B-03-005, September 2003. 

U.S. Environmental Protection Agency (EPA), 2005: Regional Haze Regulations and Guidelines for 

Best Available Retrofit Technology (BART) Determinations; Final Rule, 40 CFR 41. Federal 

Register, July 6, 2006, 70, 128, pp 39104-39172. 

VISTAS, 2005: Protocol for the Application of the CALPUFF Model for Analysis of Best Available 

Retrofit Technology (BART). Visibility Improvement State and Tribal Association of the 

Southeast (VISTAS). Revision 3.2, August 31, 2006. Available from: http://www.vistassesarm.org/documents. 
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Appendix C to 

BART determination Report for Alcoa, Inc. - Warrick Operations 
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