# Appendix 5d- BART determination Re port for Alcoa, Inc. - Warrick

Operations

# This page intentionally left blank.

# 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 C ontrol ............

................................ ......................... 4-1

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

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

5.0 BASELINE CONDITIONS AND VISIBI LITY 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 SO 2 

# 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 Potlin es ...................

................................ ......................... 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 fr om 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 NO

x 

# 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 BA RT Control Options for Potlines ........... 6-14

6.1.2.1 Feasible BART Control Options for Potline SO 2 

# .......................................... 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 NO

x 

# .......................................... 6-15

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

6.1.3.1 Control Effectiveness for Potline SO 2 

# ........................................................... 6-15

6.1.3.1.1 SO 2 

# 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 SO 2 

# 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 SO 2 

# 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 SO 2 

# 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 NO

x 

# ............................... 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 SO 2 

# ........................... 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 NO

x 

# ........................... 6-38

6.2.3 Control Effectiveness for Feasible BA RT Control Options for Industrial Boilers6-39

6.2.3.1 Control Effectiveness for Industrial Boiler SO 2 

# ............................................ 6-39

6.2.3.1.1 SO 2 

# Wet Scrubbing ...................................................................................... 6-39

6.2.3.2 Control Effectiveness for Industrial Boiler NO

x 

# ............................................ 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 SO 2 

# Wet Scrubber Control Options .................................. 6-44

6.2.4.2 Cost Analysis for NO

x 

# Control Options ......................................................... 6-44

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

6.2.4.4 Non-air Quality Environmental Impact s 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 Altern ative 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 F acilities ......................... 6-11

Table 6-2 SO 2 

# Post-Control Emission Rates ............................................................................ 6-17

Table 6-3 Summary of the Impacts Analysis for SO 2 

# Control Scenarios ................................. 6-20

Table 6-4 RBLC Database SO 2 

# Search Results for Industrial Boilers ..................................... 6-28

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

Table 6-6 SO 2 

# 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 SO 2 

# & 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 Improvem ent ...........................

................................ ......................... 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 Altern ative 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

NO

x 

# Nitrogen Oxides

PM Particulate Matter

PM 2.5 

# Particulate Matter less than 2.5 micrometers in diameter

PM 10 

# 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

SO 2 

# 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 Re trofit Technology (BART). Alcoa, Inc. – Warrick

Operations (Alcoa) is a “BART-eligible” sour ce. 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 indivi dual 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 em ission units. The BART determination and

proposed alternative to BART were rendered base d 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 determ ined 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 98 th 

# 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 98 th 

# 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 SO 2 

# emissions, 12% is attributable to NOx emissions and the remaining

3 1 percent is associated with particulate matter (PM). Results from the BART analysis for the

coal fired boilers are as follows:

 BART for SO 2 

# emissions control was determined to be wet SO 2 

# 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 98 th 

# 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. Nine ty-four percent of the potline primary control

device projected impact (0.11 dv) was from SO 2 

# 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 SO 2



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

manufacture anodes (i.e., coke). BART for ot her 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

SO 2 

# controls and raised concerns about the long-t erm viability of lower sulfur anode grade coke

as a pollution prevention m easure for minimizing potline SO 2 

# 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 strate gy 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 SO 2 

# 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 request s IDEM to determine that the alternative

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

technology requirements of Sectio n 169A(b)(2)(A), of the 1990 Clean Air Act for this facility.1-4July 2008Table 1 – 1 Summary of Baseline, BART, and Alternative to BART Visibility Impact at MCNP.BART OptionBaseline Visibility Impact (98Percentile Delta Deciview (dv)Post-BART Visibility Impact (98Percentile Delta Deciview (dv)AverageVisibilityImprovement(dv)200120022003Average200120022003AverageBART EligibleSources Onlya1.852 1.906 1.788 1.849 0.444 0.299 0.4020.3821.467Alternative toBART(BART Eligible PlusUnit 1 Controlled)b2.311 2.774 2.549 2.545 0.686 0.463 0.5950.5811.964aBased on wet SO2 scrubbing on Units 2, and 3 with 3% sulfur coke for potlinesbBased 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) ope rates 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 pl ants, and secondary metal produc tion 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 Holde r 1976

# December 2008 

# 3-2 The fossil-fuel fired steam electric plants of mo re than 250 MMBtu per hour heat input emission

unit group has the potential to emit ≥ 250 tons/year of sulfur dioxide (SO 2 

# )

, 

# 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 alumin um by the electrolytic reduction of alumina

in center-worked prebake cells. Direct electri cal 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 catho de 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 SO 2, 

# NO X 

# , 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 el ectrolytic 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 cont rol 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 SO 2 

# are adsorbed onto the alumina

surface. Fabric filtration devices are positione d 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 syst em (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 1W H 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 ho lders. 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 5E H 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 ea ch 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 NO

x 

# burner and overfire air in 2002 and Boiler 2 was equipped with a low NO

x 

# burner and over-fire air in 2004.

Boiler 4 was equipped with a low- NO

x 

# 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 visi bility attributable to Warrick’s BART-eligible

emission units and to quantify their individual relati ve 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 impact s. 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 CALPU FF 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 observ ations and upper air soundings within and

surrounding the CALMET modeling domain. In itial BART modeling projected the highest

visibility impact to be in Mammoth Cave Nati onal 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 imp acts at MCNP, since the change in visibility in

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

that visibility impacts within MCNP exceeded th e 0.5 dv contribution to visibility impairment

threshold suggested by USEPA; therefore, a refined modeling analysis was performed.5-2December 2008Table 5-1. Baseline Conditions Modeling Input DataIndexEmission UnitID #Stack NameReleaseHeight(m)MonitorWidth(m)ExitVeloc.(m/s)Delta T(K)BeginningUTM E/N(km)EndingUTM E/N(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2(g/s)NOx(g/s)L01103M.1Potline #2, Room 10314.02 1.52 2.9324.95471.119,4196.702471.198,4196.984 0.535 0.753 0.373 0.356 0.266 0.003L02104M.1Potline #2, Room 10414.02 1.52 2.9324.95471.087,4196.711471.166,4196.993 0.535 0.753 0.373 0.356 0.266 0.003L03105M.1Potline #3, Room 10514.02 1.52 2.9324.95471.024,4196.728471.103,4197.010 0.569 0.802 0.397 0.379 0.269 0.003L04106M.1Potline #3, Room 10614.02 1.52 2.9324.95470.992,4196.737471.070,4197.019 0.569 0.802 0.397 0.379 0.269 0.003L05107M.1Potline #4, Room 10714.02 1.52 2.9324.95470.961,4196.745471.038,4197.027 0.567 0.799 0.395 0.377 0.269 0.003L06108M.1Potline #4, Room 10814.02 1.52 2.9324.95470.929,4196.754471.007,4197.036 0.567 0.799 0.395 0.377 0.269 0.003L07109M.1Potline #5 , Room 10914.02 1.52 2.3123.18470.900,4196.770471.976,4197.052 0.470 0.663 0.328 0.313 0.259 0.003L08110M.1Potline #5, Room 11014.02 1.52 2.3123.18470.868,4196.778471.943,4197.061 0.470 0.663 0.328 0.313 0.259 0.003L09111M.1Potline #6 , Room 11114.02 1.52 2.3123.18470.803,4196.796471.881,4197.078 0.532 0.749 0.371 0.354 0.264 0.003L10112M.1Potline #6, Room 11214.02 1.52 2.3123.18470.771,4196.804471.848,4197.086 0.532 0.749 0.371 0.354 0.264 0.003IndexEmission UnitID #Stack NameStackHeight(m)Stackdiameter(m)ExitVeloc.(m/s)ExitTemperature(K)UTM Easting(km)UTMNorthing(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2(g/s)NOx(g/s)P01GTCPotlines #3 & #4 GTC PollutionControls 60.66 6.10 16.46 350 470.668 4196.863 0.986 0.116 1.757 4.409 46.8680.581P02160C1.1-160C1.36Potline #2 A-39814.94 3.70 21.12366471.118 4196.9530.393 0.0460.7001.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 4196.888 0.563 0.066 1.002 2.514 21.86 0.301P23134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 0.001 0.001 0.023 0.253P29134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 0.001 0.001 0.012 1.317P31134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 0.001 0.001 0.0016 0.297P33134.4 Melter6M1 38.401.223.80 583 470.9334197.1450.0620.0290.001 0.0050.00020.038P34134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245 0.007 0.003 0.000 0.000 0.006 1.140P41134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 0.000 0.000 0.0025 0.660WPP01 WPP01Warrick Power Plant Stack 1 Unit 2Only 115.82 5.91 12.88 423 470.810 4196.399 * 8.6 1.949 2.852 372.9 71.01WPP02 WPP02Warrick Power Plant Stack 2 Units 2and 3115.82 5.91 12.59428470.731 4196.443*22.017.62911.236 1245.7 203.98WPP03 WPP03Warrick Power Plant Stack 3 Unit 4 115.82 4.45 34.91 425 470.668 4196.433 * 49.525 8.13 11.895 0.0 0.0* 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 i ssues 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 si tuations 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 analyses 2 

# (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 visi bility 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 pr edicted visibility impacts from Alcoa emission

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

Table 5-2 presents the modeled 98 th 

# 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 MC NP was associated with emissions from stack 2 (50% of unit 2 and

unit 3 with the maximum 98 th 

# 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 SO 2 

# and 24.6% was

due to NOx emissions. 0.6 percen t 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 98 th 

# percentile visibility impact at MCNP associated

with emissions from stack 1 (50% of coal fired boi ler 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 SO 2 

# 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 Percenta g e of S p ecies Contribution

SO 4



# % NO 3



# % 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 98 th 

# 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 fr om the potlines or 0.12 dv was attribut able 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 esti mated impact or 0.112 dv was from emissions

of SO 2, 

# 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 98 th 

# 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 USEP A in Appendix Y to Part 51- Regional Haze

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

Final Rule. Reduction in emissions from thes e 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 potl ine primary control devices (A398s and GTC)

showed modeled 98 th 

# percentile visibility impacts of 1.8 dv and 0.12 dv, respectively. Given

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

4 and the reduction of SO 2 

# emissions emanating from the potlin e primary control devices (A398s

and GTC). Modeling data indicates that SO 2 

# 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 fo r the feasible options (Step 3), an evaluation of

the cost and secondary impacts for feasible altern atives (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, SO 2 

# , and

carbon monoxide. PM includes particulate fluoride, carbon dust, and alumina. SO 2 

# comes from

the sulfur in the components used to make the anodes. NO

x 

# 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 SO 2 

# Emission Controls for Potlines

Sulfur in the anodes is oxidized, releasing SO 2 

# from the potlines as the anodes are

consumed. Options for controlling SO 2 

# include both add-on controls and pollution prevention.

Absorption and adsorption have been used for the control of SO 2 

# emissions from numerous

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

SO 2 

# 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 SO 2 

# levels, in the range of 100 parts per million by volume (ppmv), and the

expected range of gas conditions, including temperature, oxygen content, humidity, SO 2 

# /O 2 

# ratio,

and gas impurities.

Eight different SO 2 

# 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 SO 2 

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

two use dry scrubbing technology. The eight po tentially 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 SO 2 

# 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 (500,0 00 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 scr ubbers 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 so rbent material is lime or limestone. Lime is

generally easier to manage on-site but is signifi cantly 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 ut ility 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 inst alled 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 simplifie d 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 SO 2 

# to form CaSO 3 

# . A portion of the slurry from the

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

dewatering to about 50% solids. In the utility industry, the CaSO 3 

# 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 pl ant 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 commonl y 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. SO 2 

# 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 feas ible retrofit control op tion for the potroom

reactor even though it is not ideally suited for wet scrubbing due to low SO 2 

# 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 simila r to LSFO except that the raw material is

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

system typically uses forced oxi dation, although natural oxidati on 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 m ode) 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, wh ich 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 utiliz ed 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 SO 2 

# . 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 calci um 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 solubili ty 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 SO 2 

# concentrations (<100 ppm).

6.1.1.1.2.2 Semi-dry Scrubbing (Spray Dryer)



# Semi-dry scrubbing is more commonly refe rred 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 solu bility 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 SO 2 

# as the liquid evaporates. This system is

categorized as a semi-dry system because the end product of the SO 2 

# 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 CaSO 3 

# , CaSO 4 

# , and unreacted lime.

This air pollution control system uses water for evaporative cooling and for the SO 2 

# 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 SO 2 

# removal

efficiencies in the range of 80–90%. Unlike a we t 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 SO 2 

# 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 SO 2 

# 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 SO 2 

# 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 e ligible 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 anticipat ed. Confidential research information belonging

to the market analysts assisting with the prepar ation 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 conti nue increasing in sulf ur 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 com ponent 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 incr eased 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 cu rrent specification re quirements 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 tigh tness 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 an alysis 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 SO 2 

# 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 b een 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 SO 2 

# 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) SO 2 

# 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 SO 2 

# FUEL SPEC:

LOW S COKE

AND PITCH (calc.

3% sulfur) 388 lb/hour

OR-0002 ALUMAX

PACIFIC CORP. 12/18/2001 ANODE

COKE SO 2 

# 3% S in coke

WA-0003 ALCOA 12/18/2001 POTLINES

1,2,3 SO 2 

# 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 SO 2 

# 321 lb/hour

MO-0036 NORANDA

ALUMINUM,

INC. 5/9/2006 POTLINE 1

AND 3 PM 10 

# 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 SO 2 

# 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 SO 2

# 6-12 July 2010 

# emissions. The facility’s current Title V permit fo r “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 contro ls are discussed in the following sections.



# 6.1.1.2.1 Fabric Filters

Fabric filters generally provide high collect ion efficiencies for both coarse and fine

(submicron) particles. They are relatively insens itive 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 generall y 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 NO

x 

# Emission Controls for Potlines

Potentially applicable NO

x 

# 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 NO

x 

# in the gas to

produce nitrogen and water. SNCR typically provides 30–50% NO

x 

# 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 NO

x 

# . The required temperature window is 1,600–2,100°F. Typical uncontrolled NO

x



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

at lower levels of uncontrolled NO

x 

# (EPA 2003e).

The temperature of the potroom emission exhaust (<300°F) and NO

x 

# 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 NO

x 

# 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 NO

x 

# reduction

efficiencies in the range of 70–90% and can be used with NO

x 

# concentrations as low as 20 ppm.

However, higher NO

x 

# levels result in increased performance (EPA 2003d).

The temperature of the potroom emission exhaust (<300°F) and NO

x 

# 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 BA RT Control Options for Potlines

6.1.2.1 Feasible BART Control Options for Potline SO 2



# One technically feasible option, adding a we t scrubber to the potline reactor exhausts,

was identified for controlling SO 2 

# 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 ar e 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 NO

x



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

technically feasible pre-combustion NO

x 

# controls. Likewise, there are no technically feasible

add-on control options because of the temperature of the potroom exhaust (<300°F) and low NO

x



# 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 SO 2



# 6.1.3.1.1 SO 2 

# Wet Scrubbing

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

reduce SO 2 

# from the potline reactors. Typical remova l 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. Th is 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% SO 2 

# removal was technically feasible. Accordingly, an

SO 2 

# 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 droplet s evaporates. The PM

concentration in the outlet of the wet scrubber was predicted to be 20 mg/Nm 3 

# 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 SO 2 

# 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 iden tified as feasible is the utilization of 3%

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

reductions/increases achievable by these scenarios were compared to baseline.6-17July 2010Table 6-2. SO2Post-Control Emission RatesaControlScenarioSO2ControlTechnologySO2NOXPM2.5PM10OrganicsEmissions(tons/yr)%Reduction(Increase)bEmissions(tons/yr)%Reduction(Increase)bEmissions(tons/yr)%Reduction(Increase)cEmissions(tons/year)%Reduction(Increase)eEmissions(tons/year)%Reduction(Increase)g13.0%SulfurCoke withPotlinesWetScrubber407 95.0 50.5 0 710dc. 536fe. 254hGCurrentPotentialEmissions2.0%SulfurCokePotlines4,052 50.5777d398f292haEmission 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 inorganicemissions 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 PM2.5to what the fabricfilter portion of the dry scrubber would remove.dIncludes 122 tons of inorganic condensables and 258 tons/yr. solid PM2.5from 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 PM10from 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 capturedemissions.hIncludes 138 tons/yr. of organic condensables from the roof vents.

# 6-18 July 2010 

# 6.1.4 Evaluation of Costs and Other Impacts fo r Potline Feasible BART Control Options

6.1.4.1 Cost Analysis for SO 2 

# 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 a nd 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 r eagent considering that these reagents are much

more expensive. The high solubility of sodi um 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 wa ste 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 devi ces, and (3) the system installation would also

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

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

would also affect the control system installation.

One of the vendors recognized the complexi ty 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 co st of installing and operating a LSFO wet scrubber on the

potlines to remove 95% of the SO 2 

# . 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 SO 2 

# removed,

assuming use of coke with 3.0% sulfur.

# 6-20 July 2010 

# Table 6-3. Summary of the Impacts Analysis for SO 2 

# 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 PM 2.5 

# 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 SO 2 

# 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 ma y be landfilled or commercially so ld. There is no way to know

at this time whether the gypsum would have co mmercial 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 wa ter 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 wa ter 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 wh en potline 1 and boiler unit # 1 were first

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

military, consumer, and other markets. Since its inception, Warrick Opera tions 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 SO 2 

# Emission Controls for Industrial Boilers

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

combustion process as SO 2



# .



# 6.2.1.1.1 Wet Scrubbing for Industrial Boilers

The primary development of SO 2 

# 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 scr ubbers 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 so rbent material is lime or limestone. Lime is

generally easier to manage on-site but is signifi cantly 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 ut ility 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 inst alled 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 SO 2 

# to form CaSO 3 

# . A portion of the slurry from the

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

dewatering to about 50% solids. In the utility industry, the CaSO 3 

# 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 pl ant 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 commonl y 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 th e scrubbing liquor to the spray nozzles. SO 2 

# 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 simila r to LSFO except that the raw material is

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

system typically uses forced oxi dation, although natural oxidati on 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 m ode) 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, wh ich 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 su ccessfully 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

SO 2 

# . 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 calci um 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 solubili ty 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 refe rred 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 solu bility 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 SO 2 

# as the liquid evaporates. This system is

# 6-26 July 2010 

# categorized as a semi-dry system because the end product of the SO 2 

# 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 CaSO 3 

# , CaSO 4 

# , and unreacted lime.

This air pollution control system uses water for evaporative cooling and for the SO 2 

# 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 SO 2 

# removal

efficiencies in the range of 80–90%. Unlike a we t 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 SO 2 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 sati sfactorily 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 no t 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 conten t 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 re ly 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 SO 2 

# Control Options from RBLC Database

A review or EPA’s RACT/B ACT/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 6-4.6-28July 2010Table 6-4. RBLC Database Search Results for SO2Control Industrial BoilersRBLCIDFacilityLastUpdateProcessControl OptionEmission LimitPercentEfficientND-0021GASCOYNE GENERATINGSTATION8/16/2005 BOILER, COAL-FIRED LIMESTONE INJECTION WITH A SPRAY DRYER.0.038 LB/MMBTU 98.9NV-0036 TS POWER PLANT8/31/2006 200 MW PC COAL BOILERLIME SPRAY SPRAY DRY SCRUBBER0.09 LB/MMBTUMO-0071KANSAS CITY POWER & LIGHTCOMPANY - IATAN STATION5/7/2007 PULVERIZED COAL BOILER - UNIT 2KCPL SHALL INSTALL SCR UNIT FOR THE UNIT 2 BOILER TO REDUCENOX EMISSIONS AND ALSO SHALL INSTALL WET SCRUBBER TOREDUCE SOX EMISSIONS. BOTH CONTROLS ARE NOT BACT FOR NOXAND SOX0.09 LB/MMBTUNE-0031 OPPD - NEBRASKA CITY STATION 8/30/2006 UNIT 2 BOILERDRYFLUE GAS DESULFURIZATION & FABRIC FILTER0.095 LB/MMBTU 90MO-0060CITY UTILITIES OF SPRINGFIELD -SOUTHWEST POWER STATION3/8/2007 PULVERIZED COAL FIREDBOILER DRY FLUE GAS DESULFURIZATION > 90% 0.095 LB/MMBTU 91.8UT-0053DESERET GENERATION ANDTRANSMISSION COMPANY12/18/2001 COAL FIRED BOILER WET SCRUBBER 0.0976LB/MMBTU12 MO.AVG.90UT-0065INTERMOUNTAIN POWERGENERATING STATION - UNIT #33/22/2006PULVERIZED COAL FIRED ELECTRICGENERATING UNITWET FLUE GAS DESULPHURIZATION, LOW SULFER COAL 0.1 LB/MMBTU 90WI-0228 WPS - WESTON PLANT8/31/2006SUPER CRITICAL PULVERIZED COALELECTRIC STEAM BOILER (S04, P04)DRY FGD, LIMIT ON EMISSIONS ENTERING CONTROL SYSTEM: 1.23LBS/MMBTU 30 DAY AVG.0.1 LB/MMBTU 92MO-0071KANSAS CITY POWER & LIGHTCOMPANY - IATAN STATION5/7/2007 PULVERIZED COAL BOILER - UNIT 10.1 LB/MMBTUWY-0057 WYGEN 29/23/2003 BOILER, 500 MW PCSEMI-DRY LIME SPRAY DRYER ABSORBER0.1 LB/MMBTUKS-0026 HOLCOMB UNIT #21/16/2004 BOILER, PULVERIZED COALDRY FLUE GAS DESULFURIZATION0.12 LB/MMBTU 94NE-0018 WHELAN ENERGY CENTER 8/10/2004 BOILER, UNIT 2 UTILITYSPRAY DRYERABSORBER (SDA)0.12 LB/MMBTUSC-0104SANTEE COOPER CROSSGENERATING STATION8/31/2006 BOILER, NO. 3 AND NO. 4 FLUE GAS DESULFURIZATION (WET SCRUBBING)0.13 LB/MMBTU 95MT-0027 HARDIN GENERATOR PROJECT 7/1/2004 BOILER, PULVERIZED COAL-FIRED WET VENTURI SCRUBBER 0.14 LB/MMBTUPA-0183 AES BEAVER VALLEY, LLC 9/4/2003 COAL FIRED BOILERHYDRATED ASH RE-INJECTION SYSTEM0.14 LB/MMBTUAR-0074 PLUM POINT ENERGY3/2/2004 BOILER , UNIT 1 -SN-01DRY FLUE GAS DESULFURIZATION0.16 LB/MMBTUAR-0079 PLUM POINT ENERGY5/2/2006 BOILER - SN-01DRY FLUE GAS DESULFURIZATION0.16 LB/MMBTUVA-0296 VIRGINIA TECH2/7/2006 OPERATION OFBOILER 11DRY SCRUBBER FLUE GAS DESULFURIZATION SYSTEM AND CEMS0.161 LB/MMBTU 92KY-0084THOROUGHBRED GENERATINGSTATION8/30/2006 BOILER, COAL, (2)WET FLUE GAS DESULFURIZATION (FGD), WESP, AND PROPER BOILERDESIGN0.167 LB/MMBTUWY-0039TWO ELK GENERATIONPARTNERS, LIMITEDPARTNERSHIP3/11/2004BOILER, STEAM ELECTRIC POWERGENERATINGLIME SPRAY DRY SCRUBBER 0.2LB/MMBTU(2HRFIXED)91PA-0162 EDISON MISSION ENERGY 6/12/2006BOILER, COAL, PULVERIZED BITUMINOUS,UNIT 3WET LIMESTONE SCRUBBER 0.4 LB/MMBTU 92VA-0268 THERMAL VENTURES9/5/2003 BOILER, STEAMGOOD COMBUSTION PRACTICES, CLEAN BURNING FUEL, ANDCONTINUOUS EMISSION MONITORING DEVICE.0.47 LB/MMBTUOH-0314 SMART PAPERS HOLDINGS, LLC 4/29/2008 PULVERIZED DRY BOTTOM BOILER1.7 LB/MMBTULA-0122 MANSFIELD MILL3/17/2005 POWER BOILER #1 & #2, COMBINED FUEL LIMIT SULFUR CONTENT OF FUELNOTES:The RBLC search was performed for industrial coal-fired boilerswith capacities greater than 250 MMBtu/hr. Facilities that operate circulating fluidized bed boilers were not included inthe search. Facilities with draft permits and facilitiesstill 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, seve n 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 SO 2 

# 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 SO 2



# .

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 collect ion efficiencies for both coarse and fine

(submicron) particles. They are relatively insens itive 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, wh ich 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 performa nce 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 generall y 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 NO

x



# Combustion controls and post-combustion controls are the two potential ways to reduce

NO

x 

# emissions from industrial coal-fired boilers. Combustion control methods seek to suppress

the formation of NO

x 

# during the combustion process by controlling the flame temperature and

the fuel/oxygen ratio. Combustion control methods typically include low NO

x 

# burners (LNBs),

overfire air (OFA), combustion optimization, and natural gas reburn. Post-combustion controls

capture a portion of the NO

x 

# after formation. Post-combustion controls typically include

selective non-catalytic reduction (SCR) and selective catalytic reduction systems (SCR).

Technologies such as Mobotec and NO X 

# Star are also examples of emerging post-combustion

control technologies. Post-combustion NO

x 

# control technologies use either ammonia or urea as a

reagent. The SCR technology also requires multiple layers of reduction catalyst. Seven different

NO

x 

# 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 NO X 

# Star

For this BART analysis, emphasis was placed on evaluating technically proven and

commercially available NO

x 

# control technologies. The Mo botec ROFA/ROTAMIX, the Mitsui

Babcock NO X 

# Star, 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 difficu lt to use as a retrofit technology in existing

coal-fired boilers. Combustion optimization is al so limited in effectiveness in a retrofit case

depending on how well the existing boilers are operated and maintained. The commercially

proven NO

x 

# 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 NO

x 

# 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 NO

x 

# formation, (2) a reduced flame temperature

that limits thermal NO

x 

# formation, and/or (3) a reduced residence time at peak temperature which also

limits thermal NO

x 

# 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 NO

x 

# 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 NO

x 

# 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 NO

x 

# in the gas to

produce nitrogen and water. SNCR typically provides 30–50% NO

x 

# 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 NO

x 

# . 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 O 

# F. 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 NO

x 

# levels where this

technology has been applied vary from 200 to 400 ppm. SNCR is less effective at lower levels of

uncontrolled NO

x 

# (EPA 2003e).

SNCR systems are capable of achieving a NO

x 

# emission reduction as high as 50 to 60

percent in optimum conditions (adequate reaction time, temperature, and reagent/flue gas

mixing; high baseline NO

x 

# conditions; and multiple levels of injectors) with ammonia slips of 10

to 50 ppmvd. Lower ammonia slip va lues can be achieved with lower NO

x 

# reduction

capabilities. Typically, optimum conditions ar e difficult to achieve, resulting in emission

reduction levels of 20 to 40 per cent. Potential performance is ve ry site-specific and varies with

fuel type, steam generator size, allowable ammo nia slip, furnace CO concentrations, and steam

generator heat transfer character istics. Due to the low inlet NO

x 

# 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 NO

x 

# reduction efficiency will be 20 percent or

less.

SNCR systems reduce NO

x 

# emissions using the same reduction mechanism as SCR

systems. Most of the undesirable chemical r eactions 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 NO

x 

# emissions while, at worst, the oxidation of ammonia can

# 6-33 July 2010 

# actually generate NO

x 

# . Accordingly, NO

x 

# 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 NO

x 

# removal capability, but

the capital cost increases significantly and ther e 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 NO

x 

# 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 NO

x 

# 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 selecti ng 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, cons cientious 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 NO

x



# 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 NO

x 

# 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 NO

x 

# reduction

efficiencies in the range of 70–90% and can be used with NO

x 

# concentrations as low as 20 ppm.

However, higher NO

x 

# 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 SO 2 

# to SO 3 

# could require moderate air heater modifications since

the acid dew point temperature of the flue gas is directly related to SO 3 

# concentrations. As the

SO 3 

# 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 th at 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 NO

x 

# concentration, flue gas flow

rate, and outlet NO

x 

# 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/B ACT/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 6-5.6-37July 2010Table 6-5. RBLC Database Search Results for NOXControl Industrial BoilersRBLC IDFacilityLast UpdateProcessControl OptionEmission LimitPercent EfficientNV-0036 TS POWER PLANT8/31/2006 200 MW PC COAL BOILERSCR & LOW NOX BURNERS0.07 LB/MMBTUUT-0065INTERMOUNTAIN POWER GENERATINGSTATION - UNIT #33/22/2006PULVERIZED COAL FIRED ELECTRICGENERATING UNITLOW NOX BURNERS, OVER FIRE AIR, SCR0.07 LB/MMBTU80WI-0228 WPS - WESTON PLANT8/31/2006SUPER CRITICAL PULVERIZED COALELECTRIC STEAM BOILER (S04, P04)LOW NOX BURNERS, GOOD COMBUSTION PRACTICES SELECTIVECATALYTIC REDUCTION (SCR)0.07 LB/MMBTUNE-0031 OPPD - NEBRASKA CITY STATION8/30/2006 UNIT 2 BOILERSELECTIVE CATALYTIC REDUCTION (SCR)0.07 LB/MMBTU90WY-0057 WYGEN 29/23/2003 BOILER, 500 MW PCLOW NOX BURNERS/SCR0.07 LB/MMBTUOK-0118 HUGO GENERATING STA9/27/2007COAL-FIRED STEAM EGU BOILER(HU-UNIT 2)LOW NOX BURNERS (LNB) W/ OVERFIRE AIR (OFA) AND SELECTIVECATALYTIC REDUCTION (SCR)0.07 LB/MMBTUSC-0104SANTEE COOPER CROSS GENERATINGSTATION8/31/2006 BOILER, NO. 3 AND NO. 4LOW NOX BURNERS AND SCR0.08 LB/MMBTUMO-0060CITY UTILITIES OF SPRINGFIELD -SOUTHWEST POWER STATION3/8/2007 PULVERIZED COAL FIRED BOILERIT WAS DETERMINED THAT THE BACT FOR NOX FROM THEPULVERIZED COAL FIRED BOILER IS GOOD COMBUSTION PRACTICESALONG WITH SCR HAVING A NOX EMISSION LIMIT OF 0.08 LB/MMBTUON A 30-DAY ROOLING AVERAGE.0.08 LB/MMBTU 82.6KY-0084 THOROUGHBRED GENERATING STATION8/30/2006 BOILER, COAL, (2)PROPER BOILER DESIGN, LOW NOX BURNERS, AND SCR0.08 LB/MMBTUMO-0071KANSAS CITY POWER & LIGHT COMPANY -IATAN STATION5/7/2007 PULVERIZED COAL BOILER - UNIT 2KCPL SHALL INSTALL SCR UNIT FOR THE UNIT 2 BOILER TO REDUCENOX EMISSIONS AND ALSO SHALL INSTALL WET SCRUBBER TOREDUCE SOX EMISSIONS. BOTH CONTROLS ARE NOT BACT FOR NOXAND SOX0.08 LB/MMBTUNE-0018 WHELAN ENERGY CENTER8/10/2004 BOILER, UNIT 2 UTILITYSELECTIVE CATALYTIC REDUCTION0.08 LB/MMBTUMT-0027 HARDIN GENERATOR PROJECT7/1/2004 BOILER, PULVERIZED COAL-FIRED SELECTIVE CATALYTIC REDUCTION0.09 LB/MMBTUAR-0074 PLUM POINT ENERGY3/2/2004 BOILER , UNIT 1 - SN-01LOW NOX BURNERS0.09 LB/MMBTUAR-0079 PLUM POINT ENERGY5/2/2006 BOILER - SN-01LOW NOX BURNERS0.09 LB/MMBTUMO-0071KANSAS CITY POWER & LIGHT COMPANY -IATAN STATION5/7/2007 PULVERIZED COAL BOILER - UNIT 10.1 LB/MMBTUKS-0026 HOLCOMB UNIT #21/16/2004 BOILER, PULVERIZED COALSCR, LOW NOX BURNERS, SEPARATED OVERFIRE AIR (SOFA)0.12 LB/MMBTU70PA-0162 EDISON MISSION ENERGY6/12/2006BOILER, COAL, PULVERIZEDBITUMINOUS, UNITS 1, 2 &3SCR. SEE COMMENT ABOUT NOX EMISSION LIMITS IN FACILITY NOTES.REGULATORY BASIS IS STATE IMPLEMENTATION PLAN.0.15 LB/MMBTU 70WY-0039TWO ELK GENERATION PARTNERS, LIMITEDPARTNERSHIP3/11/2004BOILER, STEAM ELECTRIC POWERGENERATINGLOW NOX BURNERS WITH OVER FIRE AIR AND SELECTIVE CATALYTICREDUCTION0.15LB/MMBTU (30DROLL)75VA-0296 VIRGINIA TECH2/7/2006 OPERATION OF BOILER 11EMISSIONS CONTROLLED BY A MASS-FEED STOKER CONFIGURATIONWITH LOW EXCESS AIR/STAGED COMBUSTION0.25 LB/MMBTUTX-0489SOUTHWESTERN PUBLIC SERVICE COMPANY-HARRINGTON STATION3/20/2007 UNIT 3 BOILERLOW NOX BURNERS, SEPARATED OVERFIRE AIR WINDBOX, WITHADDITIONAL YAW CONTROL OF THE BURNERS FOR ADDITIONAL NOXCONTROL0.3 LB/MMBTU 57VA-0268 THERMAL VENTURES9/5/2003 BOILER, STEAMGOOD COMBUSTION PRACTICES, CLEAN BURNING FUEL, ANDCONTINUOUS EMISSION MONITORING DEVICE.0.4 LB/MMBTUPA-0176 ORION POWER MIDWEST LP8/15/2006 BOILERS, COAL (3)OVERFIRE AIR, LOW NOX BURNERS0.5 LB/MMBTUUT-0053DESERET GENERATION AND TRANSMISSIONCOMPANY12/18/2001 COAL FIRED BOILERBOILER DESIGN0.55LB/MMBTU 3O-DAY AVG99.599NOTESThe 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. Facilities with draft permits and facilities still under construction were also excluded from thesearch 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 SO 2



# One technically feasible option was identif ied 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 emis sions 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 NO

x



# Combustion control options that were determin ed 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 SO 2



# 6.2.3.1.1 SO 2 

# Wet Scrubbing

Wet scrubbers were identified as a technically feasible add-on pollution control options to

reduce SO 2 

# from boiler units 2 and 3. Typical removal efficiencies are 80–95%.

Table 6-6 summarizes the SO 2 

# 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 SO 2 

# emissions

from each of units 2 and 3. The emissions reducti ons achievable by wet scrubbing at these units

were compared to baseline. Pursuant to 326 IAC 7-4-10 (Warrick County Sulfur Dioxide

Emission Limitations), SO 2 

# emission limits were established for units 2 and 3 that resulted in an

allowable SO 2 

# 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 SO 2 

# 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 th eir required participation in the Indiana Clean Air

Interstate Rule. PM emissions from utility boi ler 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 NO

x



# 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 c ontrol options for units 2 and 3.

Table 6-7 summarizes the NOx emission leve ls under the control scenarios considered for

BART.6-41July 2010Table 6-6. SO2Post-Control Emission RatesControlScenarioSO2ControlTechnologySO2NOXPM2.5PM10OrganicsEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/year)%Reduction(Increase)aEmissions(tons/year)%Reduction(Increase)a1WetScrubber oneach ofunits 2 and34,49792.0b9,5510 564 63.7 0 0 84 75.0CurrentPotentialEmissions56,215 9,551 1,552 0 334aCompared 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 4ControlScenarioSO2ControlTechnologySO2NOXPM2.5PM10OrganicsEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/year)%Reduction(Increase)aEmissions(tons/year)%Reduction(Increase)a1WetScrubberNAbNAbNAb0 406 81.0 0 0 213 24.6CurrentPotentialEmissionsNAbNAb2,133 0 282aCompared with current potential emissions.bBART is not applicable for utility boilers, with respect to SO2 andNOx, due to their required participation in the Indiana Cle an Air Interstate rule( which is presumed to require a BART equivalent degree of control).6-42July 2010This page left blank intentionally.6-43July 2010Table 6-7. NOx Post-Control Emission Rates for Boilers 2 and 3ControlScenarioNOxControlTechnologyNOxSO2PM2.5PM10OrganicsEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/yr)%Reduction(Increase)aEmissions(tons/year)%Reduction(Increase)aEmissions(tons/year)%Reduction(Increase)a3Low NOxBurners /wOverfireAir andSCR onUnits 2 & 32,10378.056,2150 564 63.7 0 84 75.02Low NOxBurners /wOverfireAir andSNCR onUnits 2 & 33,463 63.756,2150 564 63.7 0 84 75.01Low NOxBurners w/OverfireAir onUnits 2 & 34,70050.856,215 0 564 63.70 84 75.0CurrentPotentialEmissionsUnits 2and 3Low NOxBurners w/OverfireAir and NoControls onUnits 2 & 39,55156,2151,552 0 334aCompared with current potential emissions.6-44July 20106.2.4Evaluation of Cost and Other Impacts for Feasible BART Control Options6.2.4.1Cost Analysis for SO2Wet Scrubber Control OptionsConventional wet scrubbers, which were determined to be oneof the most effective technically feasible control options,are currently being installed to control SO2emissions on units 2, 3, and 4. Scrubberswere connected to boilers 2 and 3 in Mayand July, 2008 respectively.The purpose of a control technology cost analysis in a BART determination is to evaluate which, if any, control option isfeasible from a cost stand point. Since Alcoa has chosen to install the most effective technically feasible control option forSO2removal on boilers 2 and 3, a cost analysis for controlling SO2from the boilers was not deemed necessary for this BARTdetermination.6.2.4.2Cost Analysis for NOxControl OptionsThe costs for Alcoa’s BART determination were based onan engineering evaluation of NOx controls for Units 2 and 3by Black & Veatch. The cost estimates are included in Appendix C.The approximate capital cost of adding low-NOx burners toUnits 2 and 3 would be approximately $8,100,000. Thenominal cost effectiveness would be approximately $160 per tonof NOx removed. The actual cost effectiveness would behigher because this assumes operating at 8,760 hours/year. Low NOx burners are a cost effective option for Units 2 and 3.6-45July 2010The cost of adding SNCR to Units 2 and 3 would primarily be the operating cost of injecting ammonia or urea. Theapproximate capital cost would be approximately $3,000,000 withan operating cost of $4,200,000 per year. The nominal costeffectiveness would be approximately $3,392 per ton of NOx removed. The actual cost effectiveness would be higher becausethis assumes operating at 8,760 hours/year. Adding SNCR is not areliable option considering the technical difficulties discussedpreviously. Even if SNCR were a good technical option, it is not cost effective considering that 87% of the visibility impactsareassociated 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 and3 would be approximately $70,100,000 with an operatingcost of $13,400,000 per year. The nominal cost effectiveness would be approximately $5,148 per ton of NOx removed. As withthe other options, the actual cost effectiveness would be muchhigher because this assumes operating at 8,760 hours/year. SCR isa technically feasible option but is not cost effective considering that 87% of the visibility impacts are associated SO2 emissionsrather than NOx. SCR is not a cost effective BART option for these units.Table 6-8 summarizes the cost of installing and operatinglow NOx burners and over-fire air systems on units 2 and 3and the incremental cost of adding SNCR (though its technical feasibility is questionable) on units 2 and 3 as well as theincremental cost of adding SCR on units 2 and 3.6-46July 2010Table 6-8. Summary of the Impacts Analysis for NOx Control ScenariosControlScenarioControl TechnologyEvaluatedEmissionRate(tons/year)EmissionsReductions(tons/year)aInstalledCapitalCost($000)TotalAnnualizedControlCosts($000)IncrementalCostEffectiveness($ per ton ofpollutantremoved)EnergyImpact(000 kWhour/year)Non-AirQualityEnvironmentalImpacts3Low NOx Burners/w Overfire Airand SCR on Unit 4and Low NOxBurners w/Overfire Air andSCR on Units 2 &34,0492,597 $70,144 $13,371 $5,148 20,533Catalystdisposal, aciddew pointcorrosion,safety handlingof ammonia2Low NOx Burners/w Overfire Airand SCR on Unit 4and Low NOxBurners w/Overfire Air andSNCR on Units 2& 35,4091,237 $2,970 $4,196 $3,392 876Boiler tubefowling due toformation ofammoniumsulfates1Low NOx Burners/w Overfire Airand SCR on Unit 4and Low NOxBurners w/Overfire Air onUnits 2 & 36,646 4,851$8,100 $765 $158 0CurrentPotentialEmissions11,506aCompared with baseline emissions.6-47July 20106.2.4.3Energy Impact AnalysisA wet scrubber removes SO2by forcing the exhaust gas through a spray tower or absorber where it contacts waterdroplets 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 isassociated with operation of fans to move the exhaust airthrough the scrubbers, for the slurry pumps, instrumentation, and miscellaneousitems (e.g., lighting).The energy impacts of operating an SNCR system are primarily due to pumping and atomizing the reagent. Theestimated energy use would be 876,000 kWhr per year.The energy impacts of operating an SCR system includeammonia vaporization and the additional pressure drop ofmoving the gas stream through the catalyst. The estimated energy use would be 20,500,000 kWhr per year.6.2.4.4Non-air Quality Environmental Impacts for Feasible Industrial Boiler BART Control OptionsWet scrubbers using limestone oxidizes the spent slurry to gypsum. This waste from the wet scrubbers would belandfilled each year.Several hundred million gallons of water will be required annually to operate the wet scrubbers. This willsignificantly impact the community infrastructure in that this will increase daily water demand. There will be relatively noimpact due to water discharge.Several million kWh will be needed to operate the scrubbers annually. This would impact powerdemand on the current generating capacity and thereforealso 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 formammonium bisulfate and ammonium sulfate. These compounds are often “sticky” and difficult to remove which leads to foulingof boiler tubes. Ultimately new soot blowers may be needed or additional maintenancetime is required to remove these deposits.6-48July 2010SCR systems typically use ammonia. An issue with SCR systems is that the safety considerations of storing andhandling ammonia (which is a toxic chemical) must be addressed. The SCR catalyst is gradually poisoned by flue gasconstituents and must be replaced. Another issue that must be addressed is the disposal of the spent catalyst that contains activemetals (e.g., vanadium and titanium). A portion of the SO2 can be oxidized to SO3 by the catalyst. This results in another issuethat must be addressed where the additional SO3 causes a higher acid dew point downstream of the catalyst that can causeincreased corrosion.1.0Formatted:Bullets and Numbering

# 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 SO 2 

# rather than NOx. It was also determ ined that the addition of SNCR or SCR

to low NOx burners and over-fire air would no t 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 SO 2 

# control

scenarios and boiler NOx control scenarios. The baseline modeling results indicate that the

average 98 th 

# 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 98 th



# 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 98 th 

# percentile visibility

impact from Alcoa’s BART-eligible sources at MCNP was 0.289 dv.7-3December 2008Table 7-1. SO2& NOx Controls – Visibility Modeling Results at MCNPControl ScenarioNo.Control Technology200120022003AverageModeled 98thPercentile Value(dv)Modeled 98thPercentile Value(dv)Modeled 98thPercentile Value(dv)Modeled 98thPercentileValue (dv)Baseline1.8521.9061.7881.849Scenario 13% sulfur coke inthe anodes andexisting controls onthe potlines, ESPand wet scrubbercontrols, low NOxburners and overfireair on each of boilerunits 2 and 3, andESP and wetscrubber controlonboiler unit 40.4440.2990.4020.382Scenario 23% sulfur in coke inthe anodes and wetscrubber control onthe potlines, ESPand wet scrubbercontrols, low NOxburners and overfireair on each of boilerunits 2 and 3, andESP and wetscrubber control onboiler unit 40.374 0.2180.268 0.289

# 8-1 December 2008 

# 8.0 DETERMINATION OF BART

8.1 Aluminum Potlines

For potline SO 2 

# 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 SO 2 

# emission

was rejected as BART due to excessive costs: total cost effectiveness of $15,000 per ton of SO 2



# removed and capital and total annualized costs of >$300,000,000 and $55,000,000 per year,

respectively.

For PM emissions, BART was de termined to be the current le vel 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 NO

x 

# from potlines; thus, BART for

NO

x 

# was determined to be no controls.

8.2 Coal Fired Boilers

For SO 2 

# 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 98 th



# 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 visibi lity improvement associat ed 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 98 th 

# percentile value of 1.849 dv to an

average 98 th 

# percentile value of 0.382 dv, or an improvement in visibility of 3.060 dv.December 20088-3December 20088-3Table 8-1. BART Conditions Modeling Input DataIndexEmission UnitID #Stack NameReleaseHeight(m)MonitorWidth(m)ExitVeloc.(m/s)Delta T(K)BeginningUTM E/N(km)EndingUTM E/N(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2 (g/s)NOx(g/s)L01103M.1Potline #2, Room 10314.02 1.522.9324.95471.119,4196.702471.198,4196.984 0.535 0.753 0.373 0.3560.363 0.003L02104M.1Potline #2, Room 10414.02 1.522.9324.95471.087,4196.711471.166,4196.993 0.535 0.753 0.373 0.356 0.363 0.003L03105M.1Potline #3, Room 10514.02 1.522.9324.95471.024,4196.728471.103,4197.010 0.569 0.8020.3970.379 0.3680.003L04106M.1Potline #3, Room 10614.02 1.522.9324.95470.992,4196.737471.070,4197.019 0.569 0.8020.3970.3790.3680.003L05107M.1Potline #4, Room 10714.02 1.522.9324.95470.961,4196.745471.038,4197.027 0.567 0.799 0.395 0.3770.3680.003L06108M.1Potline #4, Room 10814.02 1.522.9324.95470.929,4196.754471.007,4197.036 0.567 0.799 0.395 0.3770.3680.003L07109M.1Potline #5 , Room 10914.02 1.522.3123.18470.900,4196.770471.976,4197.052 0.470 0.6630.3280.313 0.3560.003L08110M.1Potline #5, Room 11014.02 1.522.3123.18470.868,4196.778471.943,4197.061 0.470 0.6630.3280.313 0.3560.003L09111M.1Potline #6 , Room 11114.02 1.522.3123.18470.803,4196.796471.881,4197.078 0.532 0.749 0.371 0.354 0.363 0.003L10112M.1Potline #6, Room 11214.02 1.522.3123.18470.771,4196.804471.848,4197.086 0.532 0.749 0.371 0.354 0.363 0.003IndexEmission UnitID #Stack NameStackHeight(m)Stackdiameter(m)ExitVeloc.(m/s)ExitTemperature(K)UTM Easting(km)UTMNorthing(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2 (g/s)NOx(g/s)P01GTCPotlines #3 & #4 GTC PollutionControls 60.66 6.10 16.46 350 470.668 4196.863 1.1851.6671.757 4.40965.826 0.581P02160C1.1-160C1.36Potline #2 A-39814.94 3.70 21.12366471.1184196.953 0.535 0.7530.7001.75832.744 0.289P03161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.541 0.760 0.989 2.482 31.612 0.291P04161B6.1-161B6.36 Potline #6 A-398 14.94 3.69 21.12 366 470.746 4196.888 0.532 0.748 1.002 2.514 31.381 0.301P23134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 0.001 0.001 0.0023 0.253P29134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 0.001 0.001 0.012 1.317P31134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 0.001 0.001 0.0016 0.297P33134.4 Melter6M1 38.401.223.80 583 470.9334197.1450.0620.029 0.001 0.0050.00020.038P34134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter30.78 1.04 5.20 583470.9264197.245 0.007 0.0030.0000.000 0.006 1.140P41134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 0.000 0.000 0.0025 0.660WPP02WPP Units 2 & 3 Units 2 and 3 115.82 5.91 12.59 428 470.727 4196.445 * 12.75 2.699 3.167 129.49 135.329WPP03WPP Unit 4Unit 4115.82 4.45 34.91425470.7204196.340*2.7451.26813.8060.00 0.00* 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

Only a 

# 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 SO 2 

# controls. To

address these concerns, Alcoa is proposing an alternative to BA RT that will result in greater

visibility improvement compared to BART, whil e 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 SO 2 

# 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, Alco a is proposing to install a SO 2 

# 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 SO 2 

# scrubber at 91%

efficiency, LNBs with staged OFA

Boilers 2 and 3 Wet SO 2 

# scrubber at 92% efficiency

LNBs with staged OFA ESP, Wet SO 2 

# scrubber at 90%

efficiency, LNBs with staged OFA

Boiler 4 Wet SO 2 

# scrubber and cold side ESP

providing 0.015 lb./mm Btu PM

control Wet SO 2 

# 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.December 20089-3Table 9-2. Baseline Including Boiler Unit 1 Conditions Modeling Input DataIndexEmissionUnit ID #Stack NameReleaseHeight(m)MonitorWidth(m)ExitVeloc.(m/s)Delta T(K)BeginningUTM E/N(km)EndingUTM E/N(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2 (g/s)NOx(g/s)L01103M.1Potline #2, Room 10314.02 1.522.9324.95471.119,4196.702471.198,4196.984 0.535 0.753 0.373 0.356 0.266 0.003L02104M.1Potline #2, Room 10414.02 1.522.9324.95471.087,4196.711471.166,4196.993 0.535 0.753 0.373 0.356 0.266 0.003L03105M.1Potline #3, Room 10514.02 1.522.9324.95471.024,4196.728471.103,4197.010 0.569 0.8020.3970.379 0.269 0.003L04106M.1Potline #3, Room 10614.02 1.522.9324.95470.992,4196.737471.070,4197.019 0.569 0.8020.3970.379 0.269 0.003L05107M.1Potline #4, Room 10714.02 1.522.9324.95470.961,4196.745471.038,4197.027 0.567 0.799 0.395 0.377 0.269 0.003L06108M.1Potline #4, Room 10814.02 1.522.9324.95470.929,4196.754471.007,4197.036 0.567 0.799 0.395 0.377 0.269 0.003L07109M.1Potline #5 , Room 10914.02 1.522.3123.18470.900,4196.770471.976,4197.052 0.470 0.6630.3280.313 0.259 0.003L08110M.1Potline #5, Room 11014.02 1.522.3123.18470.868,4196.778471.943,4197.061 0.470 0.6630.3280.313 0.259 0.003L09111M.1Potline #6 , Room 11114.02 1.522.3123.18470.803,4196.796471.881,4197.078 0.532 0.749 0.371 0.354 0.264 0.003L10112M.1Potline #6, Room 11214.02 1.522.3123.18470.771,4196.804471.848,4197.086 0.532 0.749 0.371 .0354 0.264 0.003IndexEmissionUnit ID #Stack NameStackHeight(m)Stackdiameter(m)ExitVeloc.(m/s)ExitTemperature(K)UTM Easting(km)UTMNorthing(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2 (g/s)NOx(g/s)P01GTC Potlines #3 & #4 GTC Pollution Controls 60.66 6.10 16.46350470.6684196.863 0.986 0.1161.7574.40946.868 0.581P02160C1.1-160C1.36Potline #2 A-39814.94 3.70 21.12366471.1184196.953 0.393 0.0460.7001.75823.312 0.289P03161B5.1-161B5.36Potline #5 A-39814.94 3.72 21.12366470.7684196.888 0.555 0.0650.9892.48222.008 0.291P04161B6.1-161B6.36Potline #6 A-39814.94 3.69 21.12366470.7464196.888 0.5630.066 1.002 2.514 21.8460.301P23134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 0.001 0.001 0.0023 0.253P29134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 0.001 0.001 0.012 1.317P31134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 0.001 0.001 0.0016 0.297P33134.4 Melter6M1 38.401.223.80 583 470.9334197.1450.0620.0290.001 0.0050.00020.038P34134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter30.78 1.04 5.20 583470.9264197.245 0.007 0.0030.0000.000 0.006 1.140P41134.75 Offlines #2 West Melter30.78 1.52 0.83 555470.8864197.261 0.007 0.0030.0000.000 0.0025 0.660WPP01 WPP01Warrick Power Plant Stack 1 Unit 1 & 2 115.82 5.91 12.88 423 470.810 4196.399 * 24.18 5.8698.588 1118.71213.02WPP02 WPP02Warrick Power Plant Stack 2 Unit 2 and 3 115.82 5.91 12.59 428 470.731 4196.443 * 22.01 7.679 11.236 1245.7 203.98WPP03 WPP03Warrick Power Plant Stack 3 Unit 4 115.82 4.45 34.91 425 470.668 4196.433 * 49.525 8.13 11.895 0.00 0.00* All Solid PM is 10 microns or less. There is no data available for solid PM2.5December 20089-4Table 9-3. Alternative to BART Conditions Modeling Input DataIndexEmission UnitID #Stack NameReleaseHeight(m)MonitorWidth(m)ExitVeloc.(m/s)Delta T(K)BeginningUTM E/N(km)EndingUTM E/N(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2 (g/s)NOx(g/s)L01103M.1Potline #2, Room 10314.02 1.522.9324.95471.119,4196.702471.198,4196.984 0.535 0.7530.3730.356 0.4190.003L02104M.1Potline #2, Room 10414.02 1.522.9324.95471.087,4196.711471.166,4196.993 0.535 0.753 0.373 0.356 0.419 0.003L03105M.1Potline #3, Room 10514.02 1.522.9324.95471.024,4196.728471.103,4197.010 0.569 0.802 0.397 0.379 0.424 0.003L04106M.1Potline #3, Room 10614.02 1.522.9324.95470.992,4196.737471.070,4197.019 0.569 0.8020.3970.379 0.4240.003L05107M.1Potline #4, Room 10714.02 1.522.9324.95470.961,4196.745471.038,4197.027 0.567 0.7990.3950.377 0.4240.003L06108M.1Potline #4, Room 10814.02 1.522.9324.95470.929,4196.754471.007,4197.036 0.567 0.799 0.395 0.377 0.424 0.003L07109M.1Potline #5 , Room 10914.02 1.522.3123.18470.900,4196.770471.976,4197.052 0.470 0.663 0.328 0.313 0.412 0.003L08110M.1Potline #5, Room 11014.02 1.522.3123.18470.868,4196.778471.943,4197.061 0.470 0.6630.3280.313 0.4120.003L09111M.1Potline #6 , Room 11114.02 1.522.3123.18470.803,4196.796471.881,4197.078 0.532 0.7490.3710.354 0.4190.003L10112M.1Potline #6, Room 11214.02 1.522.3123.18470.771,4196.804471.848,4197.086 0.532 0.749 0.371 0.354 0.419 0.003Emission UnitID #Stack NameStackHeight(m)Stackdiameter(m)ExitVeloc.(m/s)ExitTemperature(K)UTM Easting(km)UTMNorthing(km)FilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)Org.Condensable(g/s)InorganicCondensable(g/s)SO2 (g/s)NOx(g/s)P01GTCPotlines #3 & #4 GTC PollutionControls60.66 6.10 16.46350470.6684196.863 1.185 1.6671.7574.40975.616 0.581P02160C1.1-160C1.36Potline #2 A-39814.94 3.70 21.12366471.1184196.953 0.535 0.7530.7001.75837.619 0.289P03161B5.1-161B5.36 Potline #5 A-398 14.94 3.72 21.12 366 470.768 4196.888 0.541 0.760 0.989 2.482 36.575 0.291P04161B6.1-161B6.36 Potline #6A-398 14.94 3.69 21.12 366470.7464196.888 0.532 0.748 1.0022.514 36.3060.301P23134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133 0.061 0.028 0.001 0.001 0.0023 0.253P29134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135 0.095 0.044 0.001 0.001 0.012P31134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141 0.066 0.031 0.001 0.001 0.0016 0.297P33134.4 Melter6M1 38.401.223.80 583 470.9334197.1450.0620.029 0.001 0.0050.00020.038P34134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245 0.007 0.003 0.000 0.000 0.006 1.140P41134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261 0.007 0.003 0.000 0.000 0.0025 0.660WPP Units1-2 &3Units 1 - 3 115.82 5.79 12.33 329 470.727 4196.445 * 17.94 3.351 4.902 228.98 204.169WPP Unit 4Unit 4115.82 4.45 34.91329470.7204196.340* 18.3036.128.9530.00 0.00* All Solid PM is 10 microns or less. There is no data available for solid PM2.5December 20089-59.2Visibility Impact of Proposed Alternative to BART versus BARTTable 9-4 presents the results of modeling that was performed in association withAlcoa Inc. – Warrick Operations and APGI – Warrick Power Plant’s proposed Alternative to BART. In order to compare thevisibility improvement associated with BART versus Alcoa’s proposed Alternative to BART, unit 1 was added as an emissionssource to the BART-eligible sources. Even though unit 1 is not BART eligible, its baseline period uncontrolled emissionsimpacted visibility at MCNP. Installation of a wet scrubber for SO2 control, and LNB’s for NOx control on unit 1 will providean improvement in visibility impact. These controls are not required by the Regional Haze Program, and serve as the basis forthe 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 thismodeling, it was determined that the proposed Alternative toBART would improve visibility at MCNP more than BART. The average visibility improvement due to Alcoa’s Alternative toBART 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% sulfurcoke, will result in a “better than BART” visibility improvement. On average, the BART Alternative results in an additional0.50 dv improvement over a BART-eligible source only scenario. Because the “Alternative to BART” provides Alcoa withmore business certainty, and provides greater visibility improvement at MCNP, Alcoa requests IDEM to determine that thealternative emission reduction strategy described herein fulfills the best available retrofit technology requirements of Section169A(b)(2)(A), of the 1990 Clean Air Act for this facility.December 20089-6Table 9 -4. Summary of Baseline, BART, and Alternative to BART Visibility Impact at MCNP.BART OptionBaseline Visibility Impact (98Percentile Delta Deciview (dv)Post-BART Visibility Impact (98Percentile Delta Deciview (dv)AverageVisibilityImprovement(dv)2001 2002 2003 Average 2001 2002 2003 AverageBART EligibleSources Onlya1.852 1.906 1.788 1.849 0.444 0.299 0.402 0.382 1.467Alternative to BART(BART Eligible PlusUnit 1 Controlled)a2.3112.7742.5492.5450.686 0.463 0.595 0.581 1.964aBased on ESP and wet SO2 scrubbing on Units 2 - 3 and 4 with 3% sulfur coke for potlinesbBased 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% sulfurcoke 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 F act 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 Al coa, Inc. - Warrick Operations

# This page intentionally left blank.Revisions to Appendix A, Alcoa BART Modeling ProtocolThese revisions to Appendix A were submitted in September 2010 in a format notcompatible with the Appendix. Thetables in this attachment replace the tables bythe same numbers includedin the original report.Table 2-3. Point and Line Source EmissionsSourceIDEmissionUnit ID #Stack NameFilterablePM10- PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.266 0.003L02104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.266 0.003L03105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.269 0.003L04106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.269 0.003L05107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.269 0.003L06108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.269 0.003L07109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.259 0.003L08110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.259 0.003L09111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.264 0.003L10112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.264 0.003P01GTCPotlines #3 & #4 GTCPollution Controls 0.986 0.116 1.757 4.40946.86846.8170.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.51421.8621.8360.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.0010.0230.00040.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 

# 0.0120.00041.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 

# 0.00160.00040.297P33134.4 Melter 6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0.006 1.140P41134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0.0025 0.660WPP01WPP stack 1 WPP Stack 1 Unit 2 Only * 8.6 1.949 2.852 372.9 71.01WPP02WPP stack 2 WPP Stack 2 Units 2 and 3 *22.0121.967.6295.7311.2368.3841245.7 203.98WPP03WPP stack 3 WPP Stack 3 Unit 4 *49.52549.5238.13 11.8950.01755.70.0250.96*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-5Source DescriptionTable 2-4. PM Speciation of Particulate Matter Emitted from Lines and StacksCoarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)L010.535 0.7530.373 0.3560.268 0.268 0.188 0.188 0.366 0.366 0.187 0.187L020.535 0.7530.373 0.3560.268 0.268 0.188 0.188 0.366 0.366 0.187 0.187L030.569 0.8020.397 0.3790.285 0.285 0.201 0.201 0.390 0.390 0.199 0.199L040.569 0.8020.397 0.3790.285 0.285 0.201 0.201 0.390 0.390 0.199 0.199L050.567 0.7990.395 0.3770.284 0.284 0.200 0.200 0.388 0.388 0.198 0.198L060.567 0.7990.395 0.3770.284 0.284 0.200 0.200 0.388 0.388 0.198 0.198L070.470 0.6630.328 0.3130.235 0.235 0.166 0.166 0.322 0.322 0.164 0.164L080.470 0.66300.328 0.3130.235 0.235 0.166 0.166 0.322 0.322 0.164 0.164L090.532 0.7490.371 0.3540.266 0.266 0.187 0.187 0.364 0.364 0.186 0.186L100.5320.7490.371 0.3540.266 0.266 0.187 0.187 0.364 0.364 0.186 0.186P010.986 0.1161.757 4.4090.493 0.493 0.029 0.029 2.234 2.234 0.879 0.879P020.393 0.0460.700 1.7580.197 0.197 0.012 0.012 0.891 0.891 0.350 0.350P030.555 0.0650.989 2.4820.278 0.278 0.016 0.016 1.257 1.257 0.495 0.495P040.563 0.0661.002 2.5140.282 0.282 0.017 0.017 1.274 1.274 0.501 0.501P230.056 0.0270.001 0.0010.028 0.028 0.007 0.007 0.007 0.007 2.50E-04 2.50E-04P240.017 0.0260.002 0.0020.009 0.009 0.007 0.007 0.007 0.007 7.50E-04 7.50E-04P250.065 0.0300.001 0.0010.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 2.50E-04P260.011 0.0160.002 0.0020.006 0.006 0.004 0.004 0.005 0.005 7.50E-04 7.50E-04P280.061 0.0280.001 0.0010.031 0.031 0.007 0.007 0.007 0.007 2.50E-04 2.50E-04P290.110 0.1670.015 0.0150.055 0.055 0.042 0.042 0.049 0.049 7.50E-03 7.50E-03P300.095 0.0440.001 0.0010.048 0.048 0.011 0.011 0.012 0.012 5.00E-04 5.00E-04P310.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P320.066 0.0310.001 0.0010.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 2.50E-04P330.062 0.0290.001 0.0050.031 0.031 0.007 0.007 0.010 0.010 2.50E-04 2.50E-04P340.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P350.062 0.0290.001 0.0010.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 2.50E-04P360.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P370.062 0.0290.001 0.0010.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 2.50E-04________1Emissions are fine filterable plus inorganic condensables___________________________________________________________________________________________________________________________2-6Source DescriptionTable 2-4. PM Speciation of Particulate Matter Emitted from Linesand Stacks, ContinuedCoarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)P390.007 0.0030.000 0.0000.004 0.004 0.001 0.001 0.001 0.001 0.00 0.00P410.007 0.0030.000 0.0000.004 0.004 0.001 0.001 0.001 0.001 0.00 0.00WPP1-8.61.949 2.8520.000 0.000 2.150 2.150 3.576 3.576 0.975 0.975WPP2-22.0121.967.6295.7311.2368.3840.000 0.0005.5035.4905.5035.49011.1219.68211.1215.4903.8142.8653.8142.865WPP3-49.52549.5238.13 11.8950.000 0.000 12.381 12.38118.32918.32818.32918.3284.065 4.065________1Emissions are fine filterable plus inorganic condensables___________________________________________________________________________________________________________________________2-6ASource Description

# 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.................................................................................................5-1 0

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 CA LMET 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 sta tions, 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 sta tions, 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 sta tions, 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 a nd 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 introdu ce new National Regional Haze Regulations for

Best Available Retrofit Technology. The re gional haze rule requires States to submit

implementation plans (SIPs) to address regiona l 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 “BAR T-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 ‘em its any air pollutant which may reasonably be

anticipated to cause or contribute to any impa irment 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 ener gy and non-air quality environmental impacts of

compliance, (c) any existing pollution control techno logy 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 ambi ent air quality impacts of sulfur dioxide (SO 2 

# ),

particulate matter (PM) and nitrogen oxides (NO

x 

# ) emissions at Mammoth Cave National Park

which is located in a south east direction approxi mately 120 km away. The impacts of the facility

on visibility will be evaluated.

The topography of the domain area consists of ge ntle 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 in teraction effects. The CALMET and CALPUFF nonsteady-state models (Scire et al., 2000a,b) ar e used for the modeling analysis. The U.S.

Environmental Protection Agency (EPA) has reco mmended CALPUFF as th e preferred model for

BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline

# 1-2 Introduction 

# Modelfor Class I impact assessments and other long range transport applications and on a caseby-case basis for near-field applications invol ving 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 fi elds. For 2003, RUC data, (Rapid Update Cycle)

has been transformed into 3D.DAT format fo r 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 th e data is 20 km Fine scale terrain effects (1

km resolution) were determined by the di agnostic 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 mode l. It accounts for spatial changes in the

CALMET-produced meteorological fields, variability in surface conditions (elevation, surface

roughness, vegetation type, etc.), chemical transf ormation, wet removal due to rain and snow, dry

deposition, and terrain influen ces 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 ex tinction, as well as wet and dry acid deposition

fluxes. The refined meteorological and dispersi on modeling simulations will be conducted for a

three-year period (2001, 2002 and 2003). Visibility impacts from SO 2 

# , PM, and NO

x 

# , and their

secondary products resulting from emissions from th e 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 refine d modeling domain with 1 km grid instead of 36

km grid spacing, modeling of 2001-2003 using the di fferent 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 Operati ons 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 fac ilities 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 f acility 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 stac ks 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 e ffective 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 4198.0UTM 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.1 104. 1 141A NE 141A NW 141A SE 141A SW 144A

160C1.37

112A.1

161B5.37 16B6.16

166 160C1.1-160C1

GTC 161B5.1-161B5 161B6.1-161B6 110.2 134.62 134.64 134.65 134. 66 134.67

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, Hemis p here = 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.2-3Source DescriptionTable 2-1. Line Source Parameters used in CALPUFFSourceIDEmissionUnit ID #Stack NameReleaseHeight(m)MonitorWidth (m)Exit Velocity(m/s)Delta Temp(oK)BeginUTME/N (km)EndingUTME/N (km)L01103M.1Potline #2, Room 10314.02 1.52 2.93 24.95 471.119, 4196.702 471.198, 4196.984L02104M.1Potline #2, Room 10414.02 1.52 2.93 24.95 471.087, 4196.711 471.166, 4196.993L03105M.1Potline #3, Room 10514.02 1.52 2.93 24.95 471.024, 4196.728 471.103, 4197.010L04106M.1Potline #3, Room 10614.02 1.52 2.93 24.95 470.992, 4196.737 471.070, 4197.019L05107M.1Potline #4, Room 10714.02 1.52 2.93 24.95 470.961, 4196.745 471.038, 4197.027L06108M.1Potline #4, Room 10814.02 1.52 2.93 24.95 470.929, 4196.754 471.007, 4197.036L07109M.1Potline #5 , Room 10914.02 1.52 2.31 23.18 470.900, 4196.770 471.976, 4197.052L08110M.1Potline #5, Room 11014.02 1.52 2.31 23.18 470.868, 4196.778 471.943, 4197.061L09111M.1Potline #6 , Room 11114.02 1.52 2.31 23.18 470.803, 4196.796 471.881, 4197.078L10112M.1Potline #6, Room 11214.02 1.52 2.31 23.18 470.771, 4196.804 471.848, 4197.086Notes: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 =20.57mL07-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 =26.67mThe release height (m), monitor width (m), exit velocity (m/s) and exit temperature (oK) were all taken from the 2002 Alcoa Warrick CO studyAll the coordinates were digitized to match aerial photos in NAD83 datumL01-L06: Average Line Source Buoyancy Parameter (F') CalculationL07-L10: Average Line Source Buoyancy Parameter (F') CalculationF' = [gLWmw(Ts-Ta)]/Ts= 1002.186 m4/s3where F' = [gLWmw(Ts-Ta)]/Ts= 736.541 m4/s3, where,g = acceleration of gravity = 9.81 m/s2g = acceleration of gravity = 9.81 m/s2L = line source length = 292.6 m L = line source length = 292.24Wm = line source width = 1.52 m Wm = line source width = 1.52 mw = line source exit velocity = 2.93 m/s w = line source exit velocity = 2.31 m/sTs = line source exit temperature = 318.3 K Ts = line source exit temperature = 316.8 KTa = ambient air temperature = 293.3 KTa = ambient air temperature = 293.6 KTs - Ta =ΔT = 24.95 K Ts-Ta =ΔT = 23.18 K2-4Source DescriptionTable 2-2. Point Source Parameters used in CALPUFFIndexEmissionUnit ID #Stack NameStackHeight(m)StackDiameter(m)Exit Velocity(m/s)ExitTemp(oK)UTMEasting(km)UTMNorthing(km)P01GTC Potlines #3 & #4 GTC Pollution Controls 60.66 6.10 16.46 350 470.668 4196.863P02160C1.1-160C1.36 Potline#2A-398 14.94 3.70 21.12 366 471.118 4196.953P03161B5.1-161B5.36 Potline#5A-398 14.94 3.72 21.12 366 470.768 4196.888P04161B6.1-161B6.36 Potline#6A-398 14.94 3.69 21.12 366 470.746 4196.888P23134.62 Melter1M1 38.401.592.16472470.7354197.193P24134.64 Holder1EH 38.401.222.00445470.7184197.198P25134.65 Melter1M2 38.401.592.16472470.7104197.201P26134.66 Holder1WH 38.401.222.00445470.7084197.203P28134.33 Melter5M1 38.401.223.80583470.9834197.133P29134.35 Holder5EH 38.401.372.34466470.9684197.128P30134.36 Melter5M2 38.401.223.80583470.9634197.135P31134.38 Holder5WH 38.401.372.34466470.9414197.138P32134.39 Melter5M3 38.401.223.80583470.9434197.141P33134.4 Melter 6M1 38.40 1.22 3.80 583 470.933 4197.145P34134.41 Holder6EH 38.401.372.34466470.9234197.141P35134.42 Melter6M2 38.401.223.80583470.9234197.148P36134.43 Holder6WH 38.401.372.34466470.9134197.143P37134.44 Melter6M3 38.401.223.80583470.9134197.148P39134.71Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245P41134.75Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261WPP1WPP stack 1WPP Stack 1, Unit 2 only 115.82 5.91 12.88 423 470.810 4196.399WPP2WPP stack 2 WPP Stack 2, Units 2 and 3 115.82 5.91 12.59 428 470.731 4196.443WPP3WPP stack 3WPP Stack 3, Unit 4115.82 4.45 34.91 425 470.668 4196.4332-5Source DescriptionTable 2-3. Point and Line Source EmissionsSourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1Potline #2, Room 1030.535 0.753 0.373 0.356 0.266 0.003L02104M.1Potline #2, Room 1040.535 0.753 0.373 0.356 0.266 0.003L03105M.1Potline #3, Room 1050.569 0.802 0.397 0.379 0.269 0.003L04106M.1Potline #3, Room 1060.569 0.802 0.397 0.379 0.269 0.003L05107M.1Potline #4, Room 1070.567 0.799 0.395 0.377 0.269 0.003L06108M.1Potline #4, Room 1080.567 0.799 0.395 0.377 0.269 0.003L07109M.1Potline #5 , Room 1090.470 0.663 0.328 0.313 0.259 0.003L08110M.1Potline #5, Room 1100.470 0.663 0.328 0.313 0.259 0.003L09111M.1Potline #6 , Room 1110.532 0.749 0.371 0.354 0.264 0.003L10112M.1Potline #6, Room 1120.532 0.749 0.371 0.354 0.264 0.003P01GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 46.817 0.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 21.836 0.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 9.00E-04 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 1.40E-03 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 2.00E-03 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 3.00E-03 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.001 4.00E-04 0.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 1.26E-03 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 4.00E-04 1.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 1.26E-03 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 4.00E-04 0.297P33134.4 Melter6M10.062 0.029 0.001 0.005 2.00E-04 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 1.00E-04 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 2.00E-04 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 1.00E-04 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 2.00E-04 0.038P39134.71 Offlines #2 East Melter0.007 0.003 0.000 0.000 6.00E-03 1.140P41134.75 Offlines #2 West Melter0.007 0.003 0.000 0.000 2.50E-03 0.660WPP1WPP stack 1 WPP Stack 1, Unit 2 only * 8.6 1.949 2.852 372.9 71.01WPP2WPP stack 2 WPP Stack 2, Units 2 and 3 * 21.96 5.73 8.384 1245.7 203.98WPP3WPP stack 3 WPP Stack 3, Unit 4 * 49.523 8.13 11.895 1755.7 250.962-6Source DescriptionTable 2-4. PM Speciation of Particulate Matter Emitted from Lines and StacksCoarse PM FinePM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(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)0.500-0.625μm(g/s)L010.535 0.753 0.373 0.356 0.268 0.2680.188 0.188 0.366 0.366 0.187 0.187L020.535 0.753 0.373 0.356 0.268 0.2680.188 0.188 0.366 0.366 0.187 0.187L030.569 0.802 0.397 0.379 0.285 0.2850.201 0.201 0.390 0.390 0.199 0.199L040.569 0.802 0.397 0.379 0.285 0.2850.201 0.201 0.390 0.390 0.199 0.199L050.567 0.799 0.395 0.377 0.284 0.2840.200 0.200 0.388 0.388 0.198 0.198L060.567 0.799 0.395 0.377 0.284 0.2840.200 0.200 0.388 0.388 0.198 0.198L070.470 0.663 0.328 0.313 0.235 0.2350.166 0.166 0.322 0.322 0.164 0.164L080.470 0.663 0.328 0.313 0.235 0.2350.166 0.166 0.322 0.322 0.164 0.164L090.532 0.749 0.371 0.354 0.266 0.2660.187 0.187 0.364 0.364 0.186 0.186L100.532 0.749 0.371 0.354 0.266 0.2660.187 0.187 0.364 0.364 0.186 0.186P010.986 0.116 1.757 4.409 0.493 0.4930.029 0.029 2.234 2.234 0.879 0.879P020.393 0.046 0.700 1.758 0.197 0.1970.012 0.012 0.891 0.891 0.350 0.350P030.555 0.065 0.989 2.482 0.278 0.2780.016 0.016 1.257 1.257 0.495 0.495P040.563 0.066 1.002 2.514 0.282 0.2820.017 0.017 1.274 1.274 0.501 0.501P230.056 0.027 0.001 0.001 0.028 0.028 0.0070.007 0.007 0.007 2.50E-04 2.50E-04P240.017 0.026 0.002 0.002 0.009 0.009 0.0070.007 0.007 0.007 7.50E-04 7.50E-04P250.065 0.030 0.001 0.001 0.033 0.033 0.0080.008 0.008 0.008 2.50E-04 2.50E-04P260.011 0.016 0.002 0.002 0.006 0.006 0.0040.004 0.005 0.005 7.50E-04 7.50E-04P280.061 0.028 0.001 0.001 0.031 0.031 0.0070.007 0.007 0.007 2.50E-04 2.50E-04P290.110 0.167 0.015 0.015 0.055 0.055 0.0420.042 0.049 0.049 7.50E-03 7.50E-03P300.095 0.044 0.001 0.001 0.048 0.048 0.0110.011 0.012 0.012 5.00E-04 5.00E-04P310.119 0.180 0.017 0.017 0.060 0.060 0.0450.045 0.053 0.053 8.25E-03 8.25E-03P320.066 0.031 0.001 0.001 0.033 0.033 0.0080.008 0.008 0.008 2.50E-04 2.50E-04P330.062 0.029 0.001 0.005 0.031 0.031 0.0070.007 0.010 0.010 2.50E-04 2.50E-04P340.119 0.180 0.017 0.017 0.060 0.060 0.0450.045 0.053 0.053 8.25E-03 8.25E-03P350.062 0.029 0.001 0.001 0.031 0.031 0.0070.007 0.008 0.008 2.50E-04 2.50E-04P360.119 0.180 0.017 0.017 0.060 0.060 0.0450.045 0.053 0.053 8.25E-03 8.25E-03P370.062 0.029 0.001 0.001 0.031 0.031 0.0070.007 0.008 0.008 2.50E-04 2.50E-04P390.007 0.003 0.000 0.000 0.004 0.004 0.0010.001 0.001 0.001 0.00E+00 0.00E+00P410.007 0.003 0.000 0.000 0.004 0.004 0.0010.001 0.001 0.001 0.00E+00 0.00E+00wpp1- 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 0.975wpp2- 21.96 5.73 8.384 0.000 0.000 5.490 5.490 9.682 9.682 2.865 2.865wpp3- 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.328 18.328 4.065 4.065_______1Emissions are fine filterable plus inorganic condensables.

# 3-1 Screening Modeling 

# 3.0 SCREENING MODELING

As a first step into the BART analysis for Al coa 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 simu lations and BART analysis, VISTAS 12-km regional

CALMET domain was used (VISTAS, 2005) with CALPUFF computational s ubdomain 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 Ca ve, which is by a large margin the closest Class I

area to the facility (Table 2-4). Mammoth Cave is ap proximately 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 m odeled year separately (2001 to 2003) and for all 3

years together. The 98 th 

# percentile value for a single year is the 8 th 

# highest values, while for three-year

period is the 22 nd 

# highest.

Since Mammoth Cave is the Class I area with the high est impacts and controls for Warrick facility will

be based on the influence at Mammo th 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 Ce ntroids 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/m 3 

# )

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 Natura l 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 400LCC North (km)



# LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84 

# Elevation

(meters)

GA AL 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 m odeling domain are derived from 3 arc-second digital

elevation models (DEMs) produced by the United St ates 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 usin g 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 Worl d 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 (F igure 4-1) which includes Mammoth Cave National

Park, located directly southeast of the source. Th e 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 a nd land use in the area. Figure 4-1 shows contours of

the terrain averaged to 1 km. Th e 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 an d valleys associated with the Class I area and the

surrounding area are captured by the 225 x 195 grid cells, a workable numb er of cells. The CALPUFF

computational domain will be the same as the CA LMET 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 f acility will be used to produce a gridded field of

dominant Land Use categories. The land use data pr oposed 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 4250UTM 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 4250UTM Y Coordinate (km) - NAR-C



# Alcoa Warrick Aluminum Plant

Mammoth Cave National Park

U rb

a n l a n d

A g r i c u l t u r a l l a n d

R

a n g e l a n d

F

o r e s t l a n d

W

a t e r

W e t l a n d

B a r r e n l a n d

T

u n d

r a

S n o w

a n d

I c e



# 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 sma ll 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-dimensi onal 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 u sed, 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 Nashv ille, TN and Lincoln-Logan County, IL

(Table 4-5). Both these sites are located well off the model domain.

Approximately 16 precipitation stations are availabl e for use in the modeling (Table 4-6). These data

will be obtained from NCDC in TD3240 format. Fi gure 4-3, Figure 4-4 and Figure 4-5 show the

locations and spatial covera ge 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

Glaciers4-6Geophysical and Meteorological DataTable 4-2. Default CALMET Land Use Categories and Associated Geophysical Parameters Based on the U.S. Geological Survey Land UseClassification System (14-Category System)Land Use TypeDescriptionSurfaceRoughness (m)AlbedoBowen RatioSoil HeatFlux ParameterAnthropogenicHeat Flux (W/m2)Leaf AreaIndex10 Urban or Built-up Land 1.0 0.18 1.5 .25 0.0 0.220Agricultural Land -Unirrigated0.25 0.15 1.0 .15 0.0 3.0-20*Agricultural Land - Irrigated 0.250.150.5.150.03.030 Rangeland0.05 0.251.0 .15 0.0 0.540 Forest Land1.0 0.10 1.0 .15 0.0 7.050 Water0.001 0.10 0.0 1.0 0.0 0.054 Small Water Body0.001 0.10 0.0 1.0 0.0 0.055 Large Water Body0.001 0.10 0.0 1.0 0.0 0.060 Wetland1.0 0.10 0.5 .25 0.0 2.061 Forested Wetland 1.0 0.1 0.5 0.25 0.0 2.062 Nonforested Wetland 0.2 0.1 0.1 0.25 0.0 1.070 Barren Land0.05 0.30 1.0 .15 0.0 0.0580 Tundra.20 0.30 0.5 .15 0.0 0.090 Perennial Snow or Ice.05 0.70 0.5 .15 0.0 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 X 1



# (km) UTM Y 1



# (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 X 1 

# UTM Y 1 

# 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

Stat i o n Na m e Stat i o n ID Y ea r o f L o n g i tude L at i tude U TM X 1 

# U TM Y 1



# Data ( de g) ( de g) ( 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 Pa rk 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 Pa rk 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 Nationa l Park and the facility are also shown.

# 4-13 Geophysical and Meteorological Data 

# 4.4 Air Quality Monitoring Data

CALPUFF uses hourly ozone concentration measuremen ts in the chemical transformation rates (SO 2 

# to

SO 4 

# , NO

x 

# to HNO 3 

# /NO 3 

# ). The ambient ozone measuremen ts are used in determining SO 2 

# loss rates due

to chemical transformation to sulfate and in determining NO

x 

# loss rates to nitrate. Ambient ozone

monitoring data for 2001, 2002 and 2003 will be ex tracted 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 wh ich show the locations of each of the available

stations for each year to be modeled.) This is a refinement to the LADCO pr ocedure 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 b illion (ppb) will be used in the modeling. If a more

refined treatment of ammonia is justified, the us e 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 X 1



# (km) UTM Y 1



# (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-rece ptor distances, and the importance of chemical

transformation, wet deposition, and dry deposition are im portant 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 r ecommended CALPUFF as the preferred model for

BART analyses (U.S. EPA, 2005). The CALPUFF modeli ng system is the regulatory Guideline Model

for Class I impact assessments and other long rang e transport applications and on a case-by-case basis

for near-field applications involving comple x 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 fo r 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 over land 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 fl ows, 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 meteorol ogical 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 com pute 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 applie d 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, th e 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 comp onents are added to the wind field adjusted for

kinematic effects.

Blocking Effects : The thermodynamic blocking effects of terra in 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 wi nd 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 descri bed above of the initial-guess wind is the Step 1

wind field. The second step of the procedure involv es the introduction of observational data into the

Step 1 wind field through an objective analysis pro cedure. 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-S cale 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 ar e 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 calcula ting 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 inte ractions 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 simu lates 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 algorith ms 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 usi ng a dividing streamline height (Hd) to determine

which pollutant material is deflected around the si des of a hill (below Hd) and which material is

advected over the hill (above Hd). The local flow (nea r the feature) used to de fine Hd is taken from the

# 5-5 Air Quality Modeling Methodology 

# gridded CALMET fields. As in CTDMPLUS, each featur e 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 comput ational difficulties encountered when applying a

puff model to near-field releases. For near-field a pplications during rapidl y-varying meteorological

conditions, an elongated puff (slug) sampling function may be used. An integrated puff approach may

be used during less demanding conditions. Both t echniques reproduce conti nuous 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 ( σ

v 

# and σ

w 

# ), the use of similarity theory to

estimate σ

v 

# and σ

w 

# 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 coas tline 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 pa rameters, meteorological

conditions, and pollutant species. Options are provid ed to allow user-specified, diurnally varying

deposition velocities to be used for one or more po llutants 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 simulate d. Differential rates of dispersion and transport

among the "new" puffs generated from the original , well-mixed puff can subs tantially increase the

effective rate of horizontal spread of the material.

# 5-6 Air Quality Modeling Methodology 

# Wet Deposition: An empirical scavenging coefficient appr oach 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 (SO 2 

# , SO = 4 

# , NO

x 

# , HNO 3 

# , and NO − 3 

# ) employed in the MESOPUFF II

model or a set of user-specified, di urnally-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-var ying turbulence and dispersion rates

- Time-dependent source and emissions data for point, area, and volume sources

- Temporal or wind-dependent scaling fa ctors for emission rates, for all source types

• Interface to the Emissions Production Model (EPM)

- Time-varying heat flux and emi ssions from controlled burns and wildfires

• Efficient sampling functions

- Integrated puff formulation

- Elongated puff (slug) formulation

• Dispersion coefficient ( σ y 

# , σ

z 

# ) options

- Direct measurements of σ

v 

# and σ

w 

# - Estimated values of σ

v 

# and σ

w 

# based on similarity theory

- Pasquill-Gifford (PG) dispersion coefficients (rural areas)

- McElroy-Pooler (MP) disper sion 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, H d 

# , as in CTDMPLUS:

- Above H d 

# , material flows over the hill and experiences altered diffusion rates

- Below H d 

# , 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 vari ations of deposition with a resistance model

- User-specified diur nal 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 ch emical mechanism for SO 2 

# , SO = 4 

# , NO

x 

# , HNO 3 

# , and NO − 3 

# (MESOPUFF II method)

- Pseudo-first-order chemical mechanism for SO 2 

# , SO = 4 

# , NO, NO 2 

# HNO 3 

# , 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 coordinat es. 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 propo sed with finer resolution in the lower layers and

somewhat coarser resolution aloft thus allowing ade quate 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 reso lution prognostic data from the 36 km MM5 data set for 2002-2004 in

LADCO (2006). The higher resolution of the prognos tic 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 adjust s 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 hi ghest peak within a radius TERRAD around each grid

point. A value of TERRAD of 10 km was determined b ased 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 St ep 1 wind field to produce a final wind field. Each

observation site influences the final wind field with in a radius of influence (parameters RMAX1 at the

surface and RMAX2 aloft). Observations and Step 1 fi eld 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 RM AX2 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 minimi zes the edge effects and allow pollutant s 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 elevati ons 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 conducte d 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 σ y 

# 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 CALP UFF 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 th e puff trajectory calculations. The first parameter

ensures that the length of an emitted puff does not beco me so large so that it cannot respond to changes

in the wind field on the scale of the meteorologi cal 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 characteriz e 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 defau lt 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: SO 2 

# , SO 4 

# , NO

x 

# , HNO 3 

# , NO 3, 

# and six

subcategories of PM 10 

# , (PM 800 

# , PM 425 

# , PM 187 

# , PM 112 

# , PM 081 

# , PM 056 

# ). Of these eleven species, five are

emitted by the project sources: SO 2 

# , SO 4 

# , NO

x 

# , PM 10 

# , and NH 3 

# . The chemical mechanism computes

transformation rates of SO 2 

# to SO 4 

# and NO

x 

# to NO 3 

# /HNO 3 

# . Hourly measured ozone concentrations will

be provided in an external OZONE.DAT file for u se with the chemical transformation module. These

ozone concentrations, along with radi ation 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 i ndividually 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 th e 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:

B

ext 

# = 3f(RH)[(NH 4 

# ) 2 

# SO 4 

# ] + 3f(RH)[NH 4 

# NO 3 

# ] +

4[OC] + 1[Soil] + 0.6[Coarse Mass] +10[EC] + b

ray



# The concentrations, in square brackets, are in μ g/m 3 

# and b

ext 

# is in units of Mm -1 

# . The Rayleigh scattering

term (b

ray 

# ) has a default value of 10 Mm -1 

# , as recommended in EPA Guid ance for Estimating Natural

Visibility Conditions Under the Re gional Haze Program (U.S. EPA, 2003b). Note that organic carbon

(OC) consists of condensable particulates which ar e assumed to be split evenly between the lowest two

particle size categories. Soil is fine particulates which is defined as PM 2.5 

# . 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 al gorithm may be used in the visibility analysis. The

new IMPROVE algorithm includes revisions to the f actor 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 effi ciency terms for the hygroscopic components.

The haze index (HI) is calculated from the extinction coefficient via the following formula:

HI = 10 ln(b

ext 

# /10)

where HI is in units of deciviews (dv) and b

ext 

# is in Mm -1 

# . The impact of a source is determined by

comparing HI for estimated natural background conditi ons 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 Ma mmoth 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 8 th 

# highest (98 th 

# 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 Con centrations for the Eastern United States

East (μg/m 3 

# )

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 Conditi ons 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 sour ces will be computed. BART methodology with

CALPOST Method 6 and 98 th 

# 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 presente d 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, invers ion-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 Re lated Values Workgroup (FLAG). Phase I Report.

U.S. Forest Service, National Park Serv ice, U.S. Fish and Wildlife Service.

FLAG, 2008. Federal Land Manage r' 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 Gr avity 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 coe fficient 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 (CTDMPLU S) 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 App lication of the CALMET Meteorological Model to a

Complex Terrain Site. Paper 97-A1313. Air & Waste Management Asso ciation 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 Estimati ng Natural Visibility

Conditions Under the Regional Haze Program . EPA-454/B-03-005, September 2003.

U.S. Environmental Protection Agency (EPA), 200 5: 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 Al coa, Inc. - Warrick Operations

# This page intentionally left blank.Appendix B Revisions to Alcoa BART Modeling ReportThese revisions to Appendix B were submitted in September 2010 in a format notcompatible with the Appendix. Thetables in this attachment replace the tables bythe same numbers includedin the original report.Table 2-3. Point and Line Source Emissions, ‘BART Eligible Baseline’ CaseSourceIDEmissionUnit ID #Stack NameFilterablePM10- PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.266 0.003L02104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.266 0.003L03105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.269 0.003L04106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.269 0.003L05107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.269 0.003L06108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.269 0.003L07109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.259 0.003L08110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.259 0.003L09111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.264 0.003L10112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.264 0.003P01GTCPotlines #3 & #4 GTCPollution Controls 0.986 0.116 1.757 4.40946.86846.8170.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.51421.8621.8360.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.0010.0230.00040.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 

# 0.0120.00041.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 

# 0.00160.00040.297P33134.4 Melter 6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0.006 1.140P41134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0.0025 0.660WPP01WPP stack 1 WPP Stack 1 Unit 2 Only * 8.6 1.949 2.852 372.9 71.01WPP02WPP stack 2 WPP Stack 2 Units 2 and 3 *22.0121.967.6295.7311.2368.3841245.7 203.98WPP03WPP stack 3 WPP Stack 3 Unit 4 *49.52549.5238.13 11.8950.01755.70.0250.96*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-5Source DescriptionTable 2-4. Point and Line Source Emissions, ‘BART Eligible Baseline + Unit 1’ CaseSourceIDEmissionUnit ID #Stack NameFilterablePM10- PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2 (g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.266 0.003L02104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.266 0.003L03105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.269 0.003L04106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.269 0.003L05107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.269 0.003L06108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.269 0.003L07109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.259 0.003L08110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.259 0.003L09111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.264 0.003L10112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.264 0.003P01GTCPotlines #3 & #4 GTCPollution Controls 0.986 0.116 1.757 4.40946.86846.8170.581P02160C1.1-160C1.36Potline #2 A-3980.3930.0460.7001.75823.3120.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.51421.8621.8360.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.0010.0230.00040.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 

# 0.0120.00041.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 

# 0.00160.00040.297P33134.4 Melter 6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0.006 1.140P41134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0.0025 0.660WPP1aWPP Stack 1 WPP Stack 1 Unit 1 and 2 *24.1817.5765.8693.92 

# 8.5885.7351118.71808.81142.01213.02WPP2WPP Stack 2 WPP Stack 2 Unit 2 and 322.0121.967.6795.7311.2368.3841245.7 203.98WPP3WPP Stack 3 WPP Stack 3 Unit 4 *49.52549.5238.13 11.8950.001755.70.00250.96*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-6Source DescriptionTable 2-5. Point and Line Source Emissions, ‘Alternative to BART’ CaseSourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2 (g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.3560.4190.4070.003L02104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.3560.4190.4070.003L03105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.3790.4240.4120.003L04106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.3790.4240.4120.003L05107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.3770.4240.4120.003L06108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.3770.4240.4120.003L07109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.3130.4120.4000.003L08110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.3130.4120.4000.003L09111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.3540.4190.4070.003L10112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.3540.4190.4070.003P01GTCPotlines #3 & #4 GTCPollution Controls1.1850.9861.6670.1161.7574.40975.61673.4420.581P02160C1.1-160C1.36 Potline #2 A-3980.5350.3930.7530.0460.700 1.75837.61935.4390.289P03161B5.1-161B5.36 Potline #5 A-3980.5410.5550.7600.0650.989 2.48236.57535.4970.291P04161B6.1-161B6.36 Potline #6 A-3980.5320.5630.7480.0661.002 2.51436.30635.2200.301P23134.62 Melter1M1 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder1EH 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter5M1 0.061 0.028 0.001 0.0010.00230.00040.253P29134.35 Holder5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter5M2 0.095 0.044 0.001 0.0010.0120.0004P31134.38 Holder5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter5M3 0.066 0.031 0.001 0.0010.00160.00040.297P33134.4 Melter6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.0030.0000.0000.0061.140P41134.75 Offlines #2 West Melter 0.007 0.0030.0000.0000.00250.660WPP123WPP Units1-3*17.9415.363.3513.2514.9023.815228.98229.28204.169WPP4WPPUnit 4 * 18.3036.1213.8068.9531.2680.00122.8970.0055.956*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-7Source DescriptionTable 2-6. Point and Line Source Emissions, ‘BART with Potlines Scrubbed’ CaseSourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2 (g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.7530.3730.3560.3630.3530.003L02104M.1 Potline #2, Room 104 0.535 0.7530.3730.3560.3630.3530.003L03105M.1 Potline #3, Room 105 0.569 0.8020.3970.3790.3680.3570.003L04106M.1 Potline #3, Room 106 0.569 0.8020.3970.3790.3680.3570.003L05107M.1 Potline #4, Room 107 0.567 0.7990.3950.3770.3680.3570.003L06108M.1 Potline #4, Room 108 0.567 0.7990.3950.3770.3680.3570.003L07109M.1 Potline #5 , Room 109 0.470 0.6630.3280.3130.3560.3460.003L08110M.1 Potline #5, Room 110 0.470 0.6630.3280.3130.3560.3460.003L09111M.1 Potline #6 , Room 111 0.532 0.7490.3710.3540.3630.3510.003L10112M.1 Potline #6, Room 112 0.532 0.7490.3710.3540.3630.3510.003W01Lines 3-6 CommonScrubber 1.591 4.335 10.8798.8766.2470.581W02Line 2 SO2 Scrubber0.3740.7001.7582.1661.5420.289P23134.62 Melter1M1 0.056 0.027 0.001 0.001 0.00090.1610.291P24134.64 Holder1EH 0.017 0.026 0.002 0.002 0.00140.1490.301P25134.65 Melter1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter5M1 0.061 0.028 0.001 0.0010.00230.00040.253P29134.35 Holder5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter5M2 0.095 0.044 0.001 0.0010.0120.00041.317P31134.38 Holder5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter5M3 0.066 0.031 0.001 0.0010.00160.00040.297P33134.4 Melter6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.0030.0000.0000.0061.140P41134.75 Offlines #2 West Melter 0.007 0.0030.0000.0000.00250.660WPP123WPP Unit2&3* 12.75 2.699 3.167 129.49 135.329WPP4WPPUnit 4 * 2.745 1.268 13.8060.0087.7840.0055.956*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-7Source DescriptionTable 2-7. Point and Line Source Emissions, ‘BART Control Level’ CaseSourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2 (g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.7530.3730.3560.3630.3530.003L02104M.1 Potline #2, Room 104 0.535 0.7530.3730.3560.3630.3530.003L03105M.1 Potline #3, Room 105 0.569 0.8020.3970.3790.3680.3570.003L04106M.1 Potline #3, Room 106 0.569 0.8020.3970.3790.3680.3570.003L05107M.1 Potline #4, Room 107 0.567 0.7990.3950.3770.3680.3570.003L06108M.1 Potline #4, Room 108 0.567 0.7990.3950.3770.3680.3570.003L07109M.1 Potline #5 , Room 109 0.470 0.6630.3280.3130.3560.3460.003L08110M.1 Potline #5, Room 110 0.470 0.6630.3280.3130.3560.3460.003L09111M.1 Potline #6 , Room 111 0.532 0.7490.3710.3540.3630.3510.003L10112M.1 Potline #6, Room 112 0.532 0.7490.3710.3540.3630.3510.003P01GTCPotlines #3 & #4 GTCPollution Controls1.1850.9861.6670.1161.757 4.40965.82646.8170.581P02160C1.1-160C1.36 Potline #2 A-3980.5350.393 

# 0.7530.0460.700 1.75832.74423.3120.289P03161B5.1-161B5.36 Potline #5 A-3980.5410.5550.7600.0650.989 2.48231.61222.0080.291P04161B6.1-161B6.36 Potline #6 A-3980.5320.5630.7480.0661.002 2.51431.38121.8360.301P23134.62 Melter1M1 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder1EH 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter5M1 0.061 0.028 0.001 0.0010.00230.00040.253P29134.35 Holder5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter5M2 0.095 0.044 0.001 0.0010.0120.00041.317P31134.38 Holder5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter5M3 0.066 0.031 0.001 0.0010.00160.00040.297P33134.4 Melter6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.0030.0000.0000.0061.140P41134.75 Offlines #2 West Melter 0.007 0.0030.0000.0000.00250.660WPP123WPP Unit2&3WPP units 2&3*12.752.6993.167129.49135.329WPP4WPPUnit 4 * 2.745 1.268 13.8060.0087.7840.0055.956*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-9Source DescriptionTable 2-8. PM Speciation of Particulate Matter Emittedfrom Lines and Stacks, ‘BART Eligible Baseline’ CaseCoarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)L010.535 0.7530.373 0.3560.268 0.268 0.188 0.188 0.366 0.366 0.187 0.187L020.535 0.7530.373 0.3560.268 0.268 0.188 0.188 0.366 0.366 0.187 0.187L030.569 0.8020.397 0.3790.285 0.285 0.201 0.201 0.390 0.390 0.199 0.199L040.569 0.8020.397 0.3790.285 0.285 0.201 0.201 0.390 0.390 0.199 0.199L050.567 0.7990.395 0.3770.284 0.284 0.200 0.200 0.388 0.388 0.198 0.198L060.567 0.7990.395 0.3770.284 0.284 0.200 0.200 0.388 0.388 0.198 0.198L070.470 0.6630.328 0.3130.235 0.235 0.166 0.166 0.322 0.322 0.164 0.164L080.470 0.66300.328 0.3130.235 0.235 0.166 0.166 0.322 0.322 0.164 0.164L090.532 0.7490.371 0.3540.266 0.266 0.187 0.187 0.364 0.364 0.186 0.186L100.5320.7490.371 0.3540.266 0.266 0.187 0.187 0.364 0.364 0.186 0.186P010.986 0.1161.757 4.4090.493 0.493 0.029 0.029 2.234 2.234 0.879 0.879P020.393 0.0460.700 1.7580.197 0.197 0.012 0.012 0.891 0.891 0.350 0.350P030.555 0.0650.989 2.4820.278 0.278 0.016 0.016 1.257 1.257 0.495 0.495P040.563 0.0661.002 2.5140.282 0.282 0.017 0.017 1.274 1.274 0.501 0.501P230.056 0.0270.001 0.0010.028 0.028 0.007 0.007 0.007 0.007 2.50E-04 2.50E-04P240.017 0.0260.002 0.0020.009 0.009 0.007 0.007 0.007 0.007 7.50E-04 7.50E-04P250.065 0.0300.001 0.0010.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 2.50E-04P260.011 0.0160.002 0.0020.006 0.006 0.004 0.004 0.005 0.005 7.50E-04 7.50E-04P280.061 0.0280.001 0.0010.031 0.031 0.007 0.007 0.007 0.007 2.50E-04 2.50E-04P290.110 0.1670.015 0.0150.055 0.055 0.042 0.042 0.049 0.049 7.50E-03 7.50E-03P300.095 0.0440.001 0.0010.048 0.048 0.011 0.011 0.012 0.012 5.00E-04 5.00E-04P310.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P320.066 0.0310.001 0.0010.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 2.50E-04P330.062 0.0290.001 0.0050.031 0.031 0.007 0.007 0.010 0.010 2.50E-04 2.50E-04P340.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P350.062 0.0290.001 0.0010.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 2.50E-04P360.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P370.062 0.0290.001 0.0010.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 2.50E-04________1Emissions are fine filterable plus inorganic condensables___________________________________________________________________________________________________________________________2-10Source DescriptionTable 2-8. PM Speciation of ParticulateMatter Emitted from Lines and Stacks,‘BART Eligible Baseline’ Case, cont.Coarse PM Fine PM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)P390.007 0.0030.000 0.0000.004 0.004 0.001 0.001 0.001 0.001 0.00 0.00P410.007 0.0030.000 0.0000.004 0.004 0.001 0.001 0.001 0.001 0.00 0.00WPP1-8.61.949 2.8520.000 0.000 2.150 2.150 3.576 3.576 0.975 0.975WPP2-22.0121.967.6295.7311.2368.3840.000 0.0005.5035.4905.5035.49011.1219.68211.1215.4903.8142.8653.8142.865WPP3-49.52549.5238.13 11.8950.000 0.000 12.381 12.38118.32918.32818.32918.3284.065 4.065________1Emissions are fine filterable plus inorganic condensables___________________________________________________________________________________________________________________________2-10ASource DescriptionTable 2-9. Speciation of Particulate Matter Emitted from Lines andStacks, ‘BART Eligible Baseline + Unit 1’ Case.Coarse PM Fine PM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)WPP1-24.1824.1765.8698.5888.5870.000 0.0006.0456.0446.0456.04410.33910.33810.33910.3382.935 2.935Table 2-10. Speciation of ParticulateMatter Emitted from Lines and Stacks, ‘Alternative to BART’ Case.Coarse PM Fine PM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)WPP123-17.9415.363.3513.2514.9023.8150.000 0.0004.4853.8404.4853.8406.9365.7486.9365.7481.6761.6261.6761.626WPP4-18.3036.1213.8068.9531.2680.000 0.000 4.576 4.5769.0535.2109.0535.2103.0606.9033.0606.903________________________________________________________________________________________________2-11Source DescriptionTable 2-11. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART with Potlines Scrubbed’ Case.Coarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)W01-1.591 4.335 10.8790.0000.0000.3980.3985.8375.8372.1682.168W02-0.374 0.700 1.7580.0000.0000.0940.0940.9730.9730.3500.350WPP23-12.75 2.699 3.1670.0000.0003.1883.1884.7714.7711.3501.350WPP4-2.745 1.268 13.8060.0000.0000.6860.6867.5897.5890.6340.634Table 2-12. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Control Level’ Case.Coarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)WPP23-12.75 2.699 3.1670.0000.0003.1883.1884.7714.7711.3501.350WPP4-2.745 1.268 13.8060.0000.0000.6860.6867.5897.5890.6340.634________________________________________________________________________________________________2-11ASource DescriptionTable 6-1.Summary of VisibilityImpacts at Mammoth Cave NationalPark due to ‘BART EligibleBaseline’ Case Emissions.___________________________________________________________________________________Maximum 98thPercentile Maximum 98thPercentileDelta DeltaDelta DeltaYear Bext Bext Deciview Deciview(%) (%) (dv) (dv)200146.1391.6222.3644.463.2756.5041.8523.678200256.17116.6823.3848.573.7227.7321.9063.959200337.0372.2121.4041.732.7875.4351.7883.4872001 - 200356.17116.6822.3844.693.7227.7321.8493.694Table 6-2.Summary of VisibilityImpacts at Mammoth Cave NationalPark due to ‘BART EligibleBaseline+ Unit 1’ Case Emissions.___________________________________________________________________________________Maximum 98thPercentile Maximum 98thPercentileDelta DeltaDelta DeltaYear Bext Bext Deciview Deciview(%) (%) (dv) (dv)200160.69114.7428.8154.464.0427.6422.3114.369200285.38144.4435.3959.884.5707.7322.7744.693200355.3090.3231.6151.633.3295.4352.5494.1632001 - 200385.38144.4431.9455.654.5707.7322.5454.4246-2ResultsTable 6-3.Summary of Visibility Impacts at Mammoth Cave NationalPark due to ‘Alternative toBART’ Case Emissions.___________________________________________________________________________________Maximum 98thPercentile Maximum 98thPercentileDelta DeltaDelta DeltaYear Bext Bext Deciview Deciview(%) (%) (dv) (dv)200113.9821.767.2411.271.2651.9690.6861.068200216.3326.764.817.891.4462.3710.4630.759200314.8524.425.759.451.3232.1850.5490.9032001 - 200316.3326.765.939.841.3452.3710.5660.938Table 6-4.Summary of Visibility Impacts at Mammoth Cave National Park due to ‘BART with PotlinesScrubbed’ Case Emissions.___________________________________________________________________________________Maximum 98thPercentile Maximum 98thPercentileDelta DeltaDelta DeltaYear Bext Bext Deciview Deciview(%) (%) (dv) (dv)20016.3811.423.866.910.6041.0810.3740.66920028.4116.752.234.430.7781.5490.2180.43420037.8315.192.755.340.7291.4140.2680.5202001 - 20038.4116.752.955.410.7041.5490.2890.5276-3ResultsTable 6-5.Summary of VisibilityImpacts at Mammoth Cave NationalPark due to ‘BART ControlLevel’ Case Emissions.___________________________________________________________________________________Maximum 98thPercentile Maximum 98thPercentileDelta DeltaDelta DeltaYear Bext Bext Deciview Deciview(%) (%) (dv) (dv)20019.1815.194.607.660.8501.4140.4440.739200210.4618.893.075.550.9581.7310.2990.540200310.7517.304.166.690.9921.5960.4020.6472001 - 200310.4618.893.946.880.9331.7310.3820.6656-3AResultsTable 6-7. Source and Species Contributions to the 8thHighest Extinction Coefficient Changes for ‘BART EligibleBaseline’ Case at Mammoth Cave National Park.Source Bext Contrib. to ModeledSpecies Contribution to Modeled Extinction Coefficient in 1/Mm Percentage of Species Contribution to Modeled Extinction CoefficientGroup Change Total BextExt. SO4 NO3 Organics E.Carbon PM_Coarse PM_FineSO4 NO3 Organics E.Carbon PM_Coarse PM_Fine(%) Change (%)1/Mm 1/Mm1/Mm 1/Mm 1/Mm 1/Mm 1/Mm% % % %%%2001: 8thhighest impact is 1.8523.678DeciviewAll 

# 22.3644.46100.00 

# 4.7579.456 

# 4.5089.118 

# 0.1000.196 

# 0.0640.0600.000 

# 0.0000.003 

# 0.0810.079 

# 94.7796.43 

# 2.102.07 

# 1.350.630.00 

# 0.000.03 

# 1.780.84Lines 0.12 

# 0.530.260.025 0.007 0.000 0.009 0.000 0.002 0.00728.00 0.00 36.00 0.00 8.00 28.00GTC 0.60 

# 2.671.340.127 0.120 0.000 0.004 0.000 0.0000.003 94.49 0.00 3.15 0.00 0.00 2.36A-398s 0.86 

# 3.851.940.183 0.172 0.000 0.007 0.000 0.0000.004 93.99 0.00 3.83 0.00 0.00 2.19Melter /Holder0.01 

# 0.060.030.003 0.000 0.002 0.000 0.000 0.0000.001 0.00 66.67 0.00 0.00 0.00 33.33wpp01 4.73 

# 21.1710.651.007 0.970 0.025 0.005 0.000 0.0000.007 96.33 2.48 0.50 0.00 0.00 0.70wpp02 

# 15.7715.74 

# 70.5135.40 

# 3.3543.3473.239 0.075 0.014 0.000 0.0000.019 96.77 2.24 0.42 0.00 0.00 0.57wpp03 

# 0.2722.39 

# 1.2150.35 

# 0.0584.761 

# 0.0004.610 

# 0.0000.0930.020 0.000 0.0000.038 

# 0.0096.83 

# 0.001.95 

# 34.480.420.00 0.00 

# 65.520.802002: 8thhighest impact is 1.9063.959DeciviewAll 

# 23.3848.57100.00 

# 5.04210.473 

# 3.6557.877 

# 1.2142.4250.069 0.0000.001 

# 0.1030.101 

# 72.4975.21 

# 24.0823.15 

# 1.370.660.00 

# 0.020.01 

# 2.040.96Lines 0.04 

# 0.200.100.010 0.002 0.000 0.004 0.0000.001 0.003 20.00 0.0040.00 0.00 10.00 30.00GTC 0.33 

# 1.390.670.070 0.063 0.001 0.004 0.0000.0000.002 90.00 1.43 5.71 0.00 0.00 2.86A-398s 0.36 

# 1.570.750.079 0.069 0.002 0.005 0.0000.0000.003 87.34 2.53 6.33 0.00 0.00 3.80Melter /Holder0.01 

# 0.040.020.002 0.000 0.002 0.000 0.0000.0000.000 0.00 100.00 0.00 0.00 0.00 0.00wpp01 5.33 

# 22.7710.961.148 0.8180.313 0.007 0.0000.0000.010 71.25 27.26 0.61 0.00 0.00 0.87wpp02 

# 16.9216.90 

# 72.3734.80 

# 3.6493.6452.703 0.896 0.020 0.0000.0000.026 74.16 24.58 0.55 0.00 0.00 0.71wpp03 

# 0.3925.60 

# 1.6652.71 

# 0.0845.520 

# 0.0004.223 

# 0.0001.210 

# 0.0270.0300.000 0.000 0.057 

# 0.0076.50 

# 0.0021.92 

# 32.140.540.00 0.00 

# 67.861.03_____________________________________________________________________________________________________________________6 – 5ResultsTable 6-7. Source and Species Contributions to the 8thHighest Extinction Coefficient Changes for ‘BART EligibleBaseline’ Case at Mammoth Cave National Park, continued.Source Bext Contrib. to ModeledSpecies Contribution to Modeled Extinction Coefficient in 1/Mm Percentage of Species Contribution to Modeled Extinction CoefficientGroup Change Total BextExt. SO4 NO3 Organics E.Carbon PM_Coarse PM_FineSO4 NO3 Organics E.Carbon PM_Coarse PM_Fine(%) Change (%)1/Mm 1/Mm1/Mm 1/Mm 1/Mm 1/Mm 1/Mm% % % %%%2003: 8thhighest impact is1.7883.487DeciviewAll 

# 21.4041.73100.00 

# 4.6569.081 

# 4.0978.161 

# 0.4110.777 

# 0.0650.0610.000 

# 0.0010.002 

# 0.0820.080 

# 87.9989.87 

# 8.838.56 

# 1.400.670.00 0.02 

# 1.760.88Lines 0.08 

# 0.370.190.017 0.004 0.000 0.007 0.000 

# 0.0010.0020.005 23.53 0.00 41.18 0.005.88 29.41GTC 0.55 

# 2.581.320.120 0.111 0.001 0.005 0.000 

# 0.0000.0010.003 92.50 0.83 4.17 0.000.002.50A-398s 0.82 

# 3.801.950.177 0.164 0.001 0.007 0.0000.0000.005 92.66 0.56 3.95 0.000.002.82Melter /Holder0.04 

# 0.000.09 

# 0.0000.0080.000 0.007 0.000 0.0000.0000.001 0.00 87.50 0.00 0.000.0012.50wpp01 4.55 

# 21.2810.910.991 0.881 0.098 0.005 0.0000.0000.007 88.90 9.89 0.50 0.000.000.71wpp02 

# 15.0815.05 

# 70.5136.08 

# 3.2833.2762.937 0.304 

# 0.020.0150.000 0.000 

# 0.0220.020 

# 89.4689.65 

# 9.269.28 

# 0.610.460.00 0.00 

# 0.670.61wpp03 

# 0.2820.63 

# 1.4649.45 

# 0.064.491 

# 0.004.064 

# 0.000.3670.021 0.0000.000 0.039 

# 0.0090.49 

# 0.008.17 

# 35.000.470.00 0.00 

# 65.000.87___________________________________________________________________________________________________________________6-5AResultsRevisions to Appendix A, Alcoa BART Modeling ProtocolTable 2-3. Point and Line Source EmissionsSourceIDEmissionUnit ID #Stack NameFilterablePM10- PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.266 0.003L02104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.266 0.003L03105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.269 0.003L04106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.269 0.003L05107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.269 0.003L06108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.269 0.003L07109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.259 0.003L08110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.259 0.003L09111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.264 0.003L10112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.264 0.003P01GTCPotlines #3 & #4 GTCPollution Controls 0.986 0.116 1.757 4.40946.86846.8170.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.51421.8621.8360.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 0.0009 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 0.0014 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 0.002 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 0.003 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.0010.0230.00040.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 0.00126 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 

# 0.0120.00041.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 0.00126 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 

# 0.00160.00040.297P33134.4 Melter 6M1 0.062 0.029 0.001 0.005 0.0002 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 0.0001 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 0.0002 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 0.0001 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 0.0002 0.038P39134.71 Offlines #2 East Melter 0.007 0.003 0.000 0.000 0.006 1.140P41134.75 Offlines #2 West Melter 0.007 0.003 0.000 0.000 0.0025 0.660WPP01WPP stack 1 WPP Stack 1 Unit 2 Only * 8.6 1.949 2.852 372.9 71.01WPP02WPP stack 2 WPP Stack 2 Units 2 and 3 *22.0121.967.6295.7311.2368.3841245.7 203.98WPP03WPP stack 3 WPP Stack 3 Unit 4 *49.52549.5238.13 11.8950.01755.70.0250.96*All Solid PM is 10 microns or less. There is no data available for solid PM2.52-5Source DescriptionTable 2-4. PM Speciation of Particulate Matter Emitted from Lines and StacksCoarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)L010.535 0.7530.373 0.3560.268 0.268 0.188 0.188 0.366 0.366 0.187 0.187L020.535 0.7530.373 0.3560.268 0.268 0.188 0.188 0.366 0.366 0.187 0.187L030.569 0.8020.397 0.3790.285 0.285 0.201 0.201 0.390 0.390 0.199 0.199L040.569 0.8020.397 0.3790.285 0.285 0.201 0.201 0.390 0.390 0.199 0.199L050.567 0.7990.395 0.3770.284 0.284 0.200 0.200 0.388 0.388 0.198 0.198L060.567 0.7990.395 0.3770.284 0.284 0.200 0.200 0.388 0.388 0.198 0.198L070.470 0.6630.328 0.3130.235 0.235 0.166 0.166 0.322 0.322 0.164 0.164L080.470 0.66300.328 0.3130.235 0.235 0.166 0.166 0.322 0.322 0.164 0.164L090.532 0.7490.371 0.3540.266 0.266 0.187 0.187 0.364 0.364 0.186 0.186L100.5320.7490.371 0.3540.266 0.266 0.187 0.187 0.364 0.364 0.186 0.186P010.986 0.1161.757 4.4090.493 0.493 0.029 0.029 2.234 2.234 0.879 0.879P020.393 0.0460.700 1.7580.197 0.197 0.012 0.012 0.891 0.891 0.350 0.350P030.555 0.0650.989 2.4820.278 0.278 0.016 0.016 1.257 1.257 0.495 0.495P040.563 0.0661.002 2.5140.282 0.282 0.017 0.017 1.274 1.274 0.501 0.501P230.056 0.0270.001 0.0010.028 0.028 0.007 0.007 0.007 0.007 2.50E-04 2.50E-04P240.017 0.0260.002 0.0020.009 0.009 0.007 0.007 0.007 0.007 7.50E-04 7.50E-04P250.065 0.0300.001 0.0010.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 2.50E-04P260.011 0.0160.002 0.0020.006 0.006 0.004 0.004 0.005 0.005 7.50E-04 7.50E-04P280.061 0.0280.001 0.0010.031 0.031 0.007 0.007 0.007 0.007 2.50E-04 2.50E-04P290.110 0.1670.015 0.0150.055 0.055 0.042 0.042 0.049 0.049 7.50E-03 7.50E-03P300.095 0.0440.001 0.0010.048 0.048 0.011 0.011 0.012 0.012 5.00E-04 5.00E-04P310.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P320.066 0.0310.001 0.0010.033 0.033 0.008 0.008 0.008 0.008 2.50E-04 2.50E-04P330.062 0.0290.001 0.0050.031 0.031 0.007 0.007 0.010 0.010 2.50E-04 2.50E-04P340.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P350.062 0.0290.001 0.0010.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 2.50E-04P360.119 0.1800.017 0.0170.060 0.060 0.045 0.045 0.053 0.053 8.25E-03 8.25E-03P370.062 0.0290.001 0.0010.031 0.031 0.007 0.007 0.008 0.008 2.50E-04 2.50E-04________1Emissions are fine filterable plus inorganic condensables___________________________________________________________________________________________________________________________2-6Source DescriptionTable 2-4. PM Speciation of Particulate Matter Emitted from Linesand Stacks, ContinuedCoarse PMFine PMOrganic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(g/s)Org.Cond(g/s)InOrgCond(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)0.500-0.625 um(g/s)P390.007 0.0030.000 0.0000.004 0.004 0.001 0.001 0.001 0.001 0.00 0.00P410.007 0.0030.000 0.0000.004 0.004 0.001 0.001 0.001 0.001 0.00 0.00WPP1-8.61.949 2.8520.000 0.000 2.150 2.150 3.576 3.576 0.975 0.975WPP2-22.0121.967.6295.7311.2368.3840.000 0.0005.5035.4905.5035.49011.1219.68211.1215.4903.8142.8653.8142.865WPP3-49.52549.5238.13 11.8950.000 0.000 12.381 12.38118.32918.32818.32918.3284.065 4.065________1Emissions are fine filterable plus inorganic condensables___________________________________________________________________________________________________________________________2-6ASource Description

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# 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 CA LMET 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 Emitte d 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 a nd 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 8 th 

# 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 introdu ce new National Regional Haze Regulations for

Best Available Retrofit Technology. The re gional haze rule requires States to submit

implementation plans (SIPs) to address regiona l 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 “BAR T-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 ‘em its any air pollutant which may reasonably be

anticipated to cause or contribute to any impa irment 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 ener gy and non-air quality environmental impacts of

compliance, (c) any existing pollution control techno logy 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 am bient air quality impacts of sulfur dioxide

(SO 2 

# ), particulate matter (PM) and nitrogen oxides (NO

x 

# ) 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 ge ntle 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 in teraction effects. The CALMET and CALPUFF nonsteady-state models (Scire et al., 2000a,b) we re used for the modeling analysis. The U.S.

Environmental Protection Agency (EPA) has reco mmended CALPUFF as th e preferred model for

BART analyses (U.S. EPA, 2005). The CALPUFF modeling system is the regulatory Guideline

# 1-2 Introduction 

# Modelfor Class I impact assessments and other long range transport applications and on a caseby-case basis for near-field applications invol ving 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 fi elds. For 2003, RUC data, (Rapid Update Cycle)

has been transformed into 3D.DAT format fo r 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 di agnostic 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 mode l. It accounts for spatial changes in the

CALMET-produced meteorological fields, variability in surface conditions (elevation, surface

roughness, vegetation type, etc.), chemical transf ormation, wet removal due to rain and snow, dry

deposition, and terrain influen ces 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 ex tinction, as well as wet and dry acid deposition

fluxes. The refined meteorological and disper sion modeling simulations were conducted for a

three-year period (2001, 2002 and 2003). Visibility impacts from SO 2 

# , PM, and NO

x 

# , 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 modeli ng 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 Sec tion 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 overvie w 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 Operati ons 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 fac ilities 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 f acility 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 mode led using the parameters listed in Table 2-2.

For modeling purposes, banks of closely-spaced st acks 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 e ffective 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 Elig ible 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 4198.0UTM 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.1 104. 1 141A NE 141A NW 141A SE 141A SW 144A

160C1.37

112A.1

161B5.37 16B6.16

166 160C1.1-160C1

GTC 161B5.1-161B5 161B6.1-161B6 110.2 134.62 134.64 134.65 134. 66 134.67

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, Hemis p here = 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.2-3Source DescriptionTable 2-1. Line Source Parameters used in CALPUFFSourceIDEmissionUnit ID #Stack NameReleaseHeight(m)MonitorWidth (m)Exit Velocity(m/s)Delta Temp(oK)BeginUTME/N (km)EndingUTME/N (km)L01103M.1Potline #2, Room 10314.02 1.52 2.93 24.95 471.119, 4196.702 471.198, 4196.984L02104M.1Potline #2, Room 10414.02 1.52 2.93 24.95 471.087, 4196.711 471.166, 4196.993L03105M.1Potline #3, Room 10514.02 1.52 2.93 24.95 471.024, 4196.728 471.103, 4197.010L04106M.1Potline #3, Room 10614.02 1.52 2.93 24.95 470.992, 4196.737 471.070, 4197.019L05107M.1Potline #4, Room 10714.02 1.52 2.93 24.95 470.961, 4196.745 471.038, 4197.027L06108M.1Potline #4, Room 10814.02 1.52 2.93 24.95 470.929, 4196.754 471.007, 4197.036L07109M.1Potline #5 , Room 10914.02 1.52 2.31 23.18 470.900, 4196.770 471.976, 4197.052L08110M.1Potline #5, Room 11014.02 1.52 2.31 23.18 470.868, 4196.778 471.943, 4197.061L09111M.1Potline #6 , Room 11114.02 1.52 2.31 23.18 470.803, 4196.796 471.881, 4197.078L10112M.1Potline #6, Room 11214.02 1.52 2.31 23.18 470.771, 4196.804 471.848, 4197.086Notes: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 =20.57mL07-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 =26.67mThe release height (m), monitor width (m), exit velocity (m/s) and exit temperature (oK) were all taken from the 2002 Alcoa Warrick CO studyAll the coordinates were digitized to match aerial photos in NAD83 datumL01-L06: Average Line Source Buoyancy Parameter (F') CalculationL07-L10: Average Line Source Buoyancy Parameter (F') CalculationF' = [gLWmw(Ts-Ta)]/Ts= 1002.186 m4/s3where F' = [gLWmw(Ts-Ta)]/Ts= 736.541 m4/s3, where,g = acceleration of gravity = 9.81 m/s2g = acceleration of gravity = 9.81 m/s2L = line source length = 292.6 m L = line source length = 292.24Wm = line source width = 1.52 m Wm = line source width = 1.52 mw = line source exit velocity = 2.93 m/s w = line source exit velocity = 2.31 m/sTs = line source exit temperature = 318.3 K Ts = line source exit temperature = 316.8 KTa = ambient air temperature = 293.3 KTa = ambient air temperature = 293.6 KTs - Ta =ΔT = 24.95 K Ts-Ta =ΔT = 23.18 K2-4Source DescriptionTable 2-2. Point Source Parameters used in CALPUFFIndexEmissionUnit ID #Stack NameStackHeight(m)StackDiameter(m)ExitVelocity(m/s)ExitTemp(oK)UTMEasting(km)UTMNorthing(km)P01GTC Potlines #3 & #4 GTC Pollution Controls 60.66 6.10 16.46 350 470.668 4196.863P02160C1.1-160C1.36 Potline#2A-398 14.94 3.70 21.12 366 471.118 4196.953P02aC1.GTC Potline#2GTC 60.66 3.05 31.46 366471.1184196.473P03161B5.1-161B5.36 Potline#5A-398 14.94 3.72 21.12 366 470.768 4196.888P04161B6.1-161B6.36 Potline#6A-398 14.94 3.69 21.12 366 470.746 4196.888W01Lines 3-6 ,Common Scrubber 60.66 7.92 16.46 314 470.668 4196.625W02Line 2 SO2 Scrubber 60.66 3.05 26.82 317 471.118 4196.473P23134.62 Melter 1M1 38.40 1.59 2.16 472 470.735 4197.193P24134.64 Holder 1EH 38.40 1.22 2.00 445 470.718 4197.198P25134.65 Melter 1M2 38.40 1.59 2.16 472 470.710 4197.201P26134.66 Holder 1WH 38.40 1.22 2.00 445 470.708 4197.203P28134.33 Melter 5M1 38.40 1.22 3.80 583 470.983 4197.133P29134.35 Holder 5EH 38.40 1.37 2.34 466 470.968 4197.128P30134.36 Melter 5M2 38.40 1.22 3.80 583 470.963 4197.135P31134.38 Holder 5WH 38.40 1.37 2.34 466 470.941 4197.138P32134.39 Melter 5M3 38.40 1.22 3.80 583 470.943 4197.141P33134.4 Melter6M1 38.401.223.80583470.9334197.145P34134.41 Holder 6EH 38.40 1.37 2.34 466 470.923 4197.141P35134.42 Melter 6M2 38.40 1.22 3.80 583 470.923 4197.148P36134.43 Holder 6WH 38.40 1.37 2.34 466 470.913 4197.143P37134.44 Melter 6M3 38.40 1.22 3.80 583 470.913 4197.148P39134.71 Offlines #2 East Melter 30.78 1.04 5.20 583 470.926 4197.245P41134.75 Offlines #2 West Melter 30.78 1.52 0.83 555 470.886 4197.261WPP123WPP units 1-3 115.82 12.33 5.79 329 470.727 4196.445WPP4WPP Unit 4 115.82 6.10 15.80 329 470.720 4196.340WPP1WPP stack 1WPP Stack 1, Unit 2 only115.82 5.91 12.88 423 470.810 4196.399WPP2WPP stack 2WPP Stack 2, Units 2 and 3 115.82 5.91 12.59 428 470.731 4196.443WPP3WPP stack 3WPP Stack 3, Unit 4115.82 4.45 34.91 425 470.668 4196.4332-5Source DescriptionTable 2-3. Point and Line Source Emissions, ‘BART Eligible Baseline’ CaseSourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1Potline #2, Room 1030.535 0.753 0.373 0.356 0.266 0.003L02104M.1Potline #2, Room 1040.535 0.753 0.373 0.356 0.266 0.003L03105M.1Potline #3, Room 1050.569 0.802 0.397 0.379 0.269 0.003L04106M.1Potline #3, Room 1060.569 0.802 0.397 0.379 0.269 0.003L05107M.1Potline #4, Room 1070.567 0.799 0.395 0.377 0.269 0.003L06108M.1Potline #4, Room 1080.567 0.799 0.395 0.377 0.269 0.003L07109M.1Potline #5 , Room 1090.470 0.663 0.328 0.313 0.259 0.003L08110M.1Potline #5, Room 1100.470 0.663 0.328 0.313 0.259 0.003L09111M.1Potline #6 , Room 1110.532 0.749 0.371 0.354 0.264 0.003L10112M.1Potline #6, Room 1120.532 0.749 0.371 0.354 0.264 0.003P01GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 46.817 0.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 21.836 0.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 9.00E-04 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 1.40E-03 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 2.00E-03 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 3.00E-03 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.001 4.00E-04 0.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 1.26E-03 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 4.00E-04 1.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 1.26E-03 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 4.00E-04 0.297P33134.4 Melter6M10.062 0.029 0.001 0.005 2.00E-04 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 1.00E-04 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 2.00E-04 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 1.00E-04 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 2.00E-04 0.038P39134.71 Offlines #2 East Melter0.007 0.003 0.000 0.000 6.00E-03 1.140P41134.75 Offlines #2 West Melter0.007 0.003 0.000 0.000 2.50E-03 0.660WPP1WPP stack 1 WPP Stack 1, Unit 2 only * 8.6 1.949 2.852 372.9 71.01WPP2WPP stack 2 WPP Stack 2, Units 2 and 3 * 21.96 5.73 8.384 1245.7 203.98WPP3WPP stack 3 WPP Stack 3, Unit 4 * 49.523 8.13 11.895 1755.7 250.962-6Source DescriptionTable 2-4. Point and Line Source Emissions, ‘BART Eligible Baseline + Unit 1’ Case.SourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1Potline #2, Room 1030.535 0.753 0.373 0.356 0.266 0.003L02104M.1Potline #2, Room 1040.535 0.753 0.373 0.356 0.266 0.003L03105M.1Potline #3, Room 1050.569 0.802 0.397 0.379 0.269 0.003L04106M.1Potline #3, Room 1060.569 0.802 0.397 0.379 0.269 0.003L05107M.1Potline #4, Room 1070.567 0.799 0.395 0.377 0.269 0.003L06108M.1Potline #4, Room 1080.567 0.799 0.395 0.377 0.269 0.003L07109M.1Potline #5 , Room 1090.470 0.663 0.328 0.313 0.259 0.003L08110M.1Potline #5, Room 1100.470 0.663 0.328 0.313 0.259 0.003L09111M.1Potline #6 , Room 1110.532 0.749 0.371 0.354 0.264 0.003L10112M.1Potline #6, Room 1120.532 0.749 0.371 0.354 0.264 0.003P01GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 46.817 0.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 23.312 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 22.008 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 21.836 0.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 9.00E-04 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 1.40E-03 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 2.00E-03 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 3.00E-03 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.001 4.00E-04 0.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 1.26E-03 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 4.00E-04 1.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 1.26E-03 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 4.00E-04 0.297P33134.4 Melter6M10.062 0.029 0.001 0.005 2.00E-04 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 1.00E-04 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 2.00E-04 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 1.00E-04 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 2.00E-04 0.038P39134.71 Offlines #2 East Melter0.007 0.003 0.000 0.000 6.00E-03 1.140P41134.75 Offlines #2 West Melter0.007 0.003 0.000 0.000 2.50E-03 0.660WPP1aWPP stack 1 WPP Stack 1, Unit 2 only * 15.576 3.92 5.735 808.81 142.01WPP2WPP stack 2 WPP Stack 2, Units 2 and 3 * 21.96 5.73 8.384 1245.7 203.98WPP3WPP stack 3 WPP Stack 3, Unit 4 * 49.523 8.13 11.895 1755.7 250.962-7Source DescriptionTable 2-5. Point and Line Source Emissions, ‘Alternative to BART’ Case.SourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1Potline #2, Room 1030.535 0.753 0.373 0.356 0.407 0.003L02104M.1Potline #2, Room 1040.535 0.753 0.373 0.356 0.407 0.003L03105M.1Potline #3, Room 1050.569 0.802 0.397 0.379 0.412 0.003L04106M.1Potline #3, Room 1060.569 0.802 0.397 0.379 0.412 0.003L05107M.1Potline #4, Room 1070.567 0.799 0.395 0.377 0.412 0.003L06108M.1Potline #4, Room 1080.567 0.799 0.395 0.377 0.412 0.003L07109M.1Potline #5 , Room 1090.470 0.663 0.328 0.313 0.400 0.003L08110M.1Potline #5, Room 1100.470 0.663 0.328 0.313 0.400 0.003L09111M.1Potline #6 , Room 1110.532 0.749 0.371 0.354 0.407 0.003L10112M.1Potline #6, Room 1120.532 0.749 0.371 0.354 0.407 0.003P01GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 73.442 0.581P02C1.GTC Potline #2GTC0.393 0.046 0.700 1.758 35.439 0.289P03161B5.1- Potline #5 A-398 0.555 0.065 0.989 2.482 35.497 0.291P04161B6.1- Potline #6 A-398 0.563 0.066 1.002 2.514 35.220 0.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 9.00E-04 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 1.40E-03 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 2.00E-03 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 3.00E-03 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.001 4.00E-04 0.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 1.26E-03 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 4.00E-04 1.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 1.26E-03 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 4.00E-04 0.297P33134.4 Melter6M10.062 0.029 0.005 0.001 2.00E-04 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 1.00E-04 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 2.00E-04 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 1.00E-04 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 2.00E-04 0.038P39134.71 Offlines #2 East Melter0.007 0.003 0.000 0.000 6.00E-03 1.140P41134.75 Offlines #2 West Melter0.007 0.003 0.000 0.000 2.50E-03 0.660WPP123WPP units 1-3 * 15.36 3.251 3.815 229.28 204.17WPP4WPP Unit 4 * 18.303 13.806 1.268 122.9 55.9562-8Source DescriptionTable 2-6. Point and Line Source Emissions, ‘BART with Potlines Scrubbed’ Case.SourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1 Potline #2, Room 103 0.535 0.753 0.373 0.356 0.353 0.003L02104M.1 Potline #2, Room 104 0.535 0.753 0.373 0.356 0.353 0.003L03105M.1 Potline #3, Room 105 0.569 0.802 0.397 0.379 0.357 0.003L04106M.1 Potline #3, Room 106 0.569 0.802 0.397 0.379 0.357 0.003L05107M.1 Potline #4, Room 107 0.567 0.799 0.395 0.377 0.357 0.003L06108M.1 Potline #4, Room 108 0.567 0.799 0.395 0.377 0.357 0.003L07109M.1 Potline #5 , Room 109 0.470 0.663 0.328 0.313 0.346 0.003L08110M.1 Potline #5, Room 110 0.470 0.663 0.328 0.313 0.346 0.003L09111M.1 Potline #6 , Room 111 0.532 0.749 0.371 0.354 0.351 0.003L10112M.1 Potline #6, Room 112 0.532 0.749 0.371 0.354 0.351 0.003W01Lines 3-6 ,Common Scrubber1.591 4.335 10.879 6.247 0.581W02Line 2 SO2 Scrubber0.374 0.700 1.758 1.542 0.289P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 9.00E-04 0.291P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 1.40E-03 0.301P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 2.00E-03 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 3.00E-03 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.001 4.00E-04 0.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 1.26E-03 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 4.00E-04 1.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 1.26E-03 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 4.00E-04 0.297P33134.4 Melter6M10.062 0.029 0.001 0.005 2.00E-04 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 1.00E-04 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 2.00E-04 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 1.00E-04 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 2.00E-04 0.038P39134.71 Offlines #2 East Melter0.007 0.003 0.000 0.000 6.00E-03 1.140P41134.75 Offlines #2 West Melter0.007 0.003 0.000 0.000 2.50E-03 0.660WPP123WPP unit 2&3WPP unit 2&3* 12.750 2.699 3.167 129.485 135.329WPP4WPP unit 4 WPP unit 4 * 2.745 1.268 13.806 87.784 55.9562-9Source DescriptionTable 2-7. Point and Line Source Emissions, ‘BART Control Level’ Case.SourceIDEmissionUnit ID #Stack NameFilterablePM10-PM2.5(g/s)FilterablePM2.5(g/s)OrganicCondensablePM2.5(g/s)InorganicCondensablePM2.5(g/s)SO2(g/s)NOx(g/s)L01103M.1Potline #2, Room 1030.535 0.753 0.373 0.356 0.353 0.003L02104M.1Potline #2, Room 1040.535 0.753 0.373 0.356 0.353 0.003L03105M.1Potline #3, Room 1050.569 0.802 0.397 0.379 0.357 0.003L04106M.1Potline #3, Room 1060.569 0.802 0.397 0.379 0.357 0.003L05107M.1Potline #4, Room 1070.567 0.799 0.395 0.377 0.357 0.003L06108M.1Potline #4, Room 1080.567 0.799 0.395 0.377 0.357 0.003L07109M.1Potline #5 , Room 1090.470 0.663 0.328 0.313 0.346 0.003L08110M.1Potline #5, Room 1100.470 0.663 0.328 0.313 0.346 0.003L09111M.1Potline #6 , Room 1110.532 0.749 0.371 0.354 0.351 0.003L10112M.1Potline #6, Room 1120.532 0.749 0.371 0.354 0.351 0.003P01GTC Potlines #3 & #4 GTC Pollution Controls 0.986 0.116 1.757 4.409 63.881 0.581P02160C1.1-160C1.36 Potline #2 A-398 0.393 0.046 0.700 1.758 30.834 0.289P03161B5.1-161B5.36 Potline #5 A-398 0.555 0.065 0.989 2.482 30.653 0.291P04161B6.1-161B6.36 Potline #6 A-398 0.563 0.066 1.002 2.514 30.414 0.301P23134.62 Melter 1M1 0.056 0.027 0.001 0.001 9.00E-04 0.161P24134.64 Holder 1EH 0.017 0.026 0.002 0.002 1.40E-03 0.149P25134.65 Melter 1M2 0.065 0.030 0.001 0.001 2.00E-03 0.402P26134.66 Holder 1WH 0.011 0.016 0.002 0.002 3.00E-03 0.149P28134.33 Melter 5M1 0.061 0.028 0.001 0.001 4.00E-04 0.253P29134.35 Holder 5EH 0.110 0.167 0.015 0.015 1.26E-03 0.318P30134.36 Melter 5M2 0.095 0.044 0.001 0.001 4.00E-04 1.317P31134.38 Holder 5WH 0.119 0.180 0.017 0.017 1.26E-03 0.318P32134.39 Melter 5M3 0.066 0.031 0.001 0.001 4.00E-04 0.297P33134.4 Melter6M10.062 0.029 0.001 0.005 2.00E-04 0.038P34134.41 Holder 6EH 0.119 0.180 0.017 0.017 1.00E-04 0.016P35134.42 Melter 6M2 0.062 0.029 0.001 0.001 2.00E-04 0.038P36134.43 Holder 6WH 0.119 0.180 0.017 0.017 1.00E-04 0.016P37134.44 Melter 6M3 0.062 0.029 0.001 0.001 2.00E-04 0.038P39134.71 Offlines #2 East Melter0.007 0.003 0.000 0.000 6.00E-03 1.140P41134.75 Offlines #2 West Melter0.007 0.003 0.000 0.000 2.50E-03 0.660WPP123WPP units 2&3WPP units 2&3* 12.75 2.699 3.167 129.49 135.33WPP4WPP unit 4 WPP unit 4 * 2.745 1.268 13.806 87.784 55.9562-10Source DescriptionTable 2-8. PM Speciation of Particulate Matter Emittedfrom Lines and Stacks, ‘BART Eligible Baseline’ CaseCoarse PM FinePM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(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)0.500-0.625μm(g/s)L010.535 0.753 0.373 0.356 0.268 0.2680.188 0.188 0.366 0.366 0.187 0.187L020.535 0.753 0.373 0.356 0.268 0.2680.188 0.188 0.366 0.366 0.187 0.187L030.569 0.802 0.397 0.379 0.285 0.2850.201 0.201 0.390 0.390 0.199 0.199L040.569 0.802 0.397 0.379 0.285 0.2850.201 0.201 0.390 0.390 0.199 0.199L050.567 0.799 0.395 0.377 0.284 0.2840.200 0.200 0.388 0.388 0.198 0.198L060.567 0.799 0.395 0.377 0.284 0.2840.200 0.200 0.388 0.388 0.198 0.198L070.470 0.663 0.328 0.313 0.235 0.2350.166 0.166 0.322 0.322 0.164 0.164L080.470 0.663 0.328 0.313 0.235 0.2350.166 0.166 0.322 0.322 0.164 0.164L090.532 0.749 0.371 0.354 0.266 0.2660.187 0.187 0.364 0.364 0.186 0.186L100.532 0.749 0.371 0.354 0.266 0.2660.187 0.187 0.364 0.364 0.186 0.186P010.986 0.116 1.757 4.409 0.493 0.4930.029 0.029 2.234 2.234 0.879 0.879P020.393 0.046 0.700 1.758 0.197 0.1970.012 0.012 0.891 0.891 0.350 0.350P030.555 0.065 0.989 2.482 0.278 0.2780.016 0.016 1.257 1.257 0.495 0.495P040.563 0.066 1.002 2.514 0.282 0.2820.017 0.017 1.274 1.274 0.501 0.501P230.056 0.027 0.001 0.001 0.028 0.028 0.0070.007 0.007 0.007 2.50E-04 2.50E-04P240.017 0.026 0.002 0.002 0.009 0.009 0.0070.007 0.007 0.007 7.50E-04 7.50E-04P250.065 0.030 0.001 0.001 0.033 0.033 0.0080.008 0.008 0.008 2.50E-04 2.50E-04P260.011 0.016 0.002 0.002 0.006 0.006 0.0040.004 0.005 0.005 7.50E-04 7.50E-04P280.061 0.028 0.001 0.001 0.031 0.031 0.0070.007 0.007 0.007 2.50E-04 2.50E-04P290.110 0.167 0.015 0.015 0.055 0.055 0.0420.042 0.049 0.049 7.50E-03 7.50E-03P300.095 0.044 0.001 0.001 0.048 0.048 0.0110.011 0.012 0.012 5.00E-04 5.00E-04P310.119 0.180 0.017 0.017 0.060 0.060 0.0450.045 0.053 0.053 8.25E-03 8.25E-03P320.066 0.031 0.001 0.001 0.033 0.033 0.0080.008 0.008 0.008 2.50E-04 2.50E-04P330.062 0.029 0.001 0.005 0.031 0.031 0.0070.007 0.010 0.010 2.50E-04 2.50E-04P340.119 0.180 0.017 0.017 0.060 0.060 0.0450.045 0.053 0.053 8.25E-03 8.25E-03P350.062 0.029 0.001 0.001 0.031 0.031 0.0070.007 0.008 0.008 2.50E-04 2.50E-04P360.119 0.180 0.017 0.017 0.060 0.060 0.0450.045 0.053 0.053 8.25E-03 8.25E-03P370.062 0.029 0.001 0.001 0.031 0.031 0.0070.007 0.008 0.008 2.50E-04 2.50E-04P390.007 0.003 0.000 0.000 0.004 0.004 0.0010.001 0.001 0.001 0.00E+00 0.00E+00P410.007 0.003 0.000 0.000 0.004 0.004 0.0010.001 0.001 0.001 0.00E+00 0.00E+00wpp1- 8.6 1.949 2.852 0.000 0.000 2.150 2.150 3.576 3.576 0.975 0.975wpp2- 21.96 5.73 8.384 0.000 0.000 5.490 5.490 9.682 9.682 2.865 2.865wpp3- 49.523 8.13 11.895 0.000 0.000 12.381 12.381 18.328 18.328 4.065 4.065_______1Emissions are fine filterable plus inorganic condensables.2-11Source DescriptionTable 2-9. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Eligible Baseline + Unit 1’ Case.Coarse PM FinePM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(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)0.500-0.625μm(g/s)wpp124.176 5.869 8.587 0.000 0.000 6.044 6.044 10.338 10.338 2.935 2.935Table 2-10. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘Alternative to BART’ Case.Coarse PM FinePM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(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)0.500-0.625μm(g/s)wpp12315.36 3.251 3.815 0.000 0.000 3.840 3.840 5.748 5.748 1.626 1.626wpp418.303 13.806 1.268 0.000 0.000 4.576 4.576 5.210 5.210 6.903 6.903Table 2-11. Speciation of Particulate Matter Emitted fromLines and Stacks, ‘BART with Potlines Scrubbed’ Case.Coarse PM FinePM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(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)0.500-0.625μm(g/s)W011.591 4.335 10.879 0.000 0.000 0.398 0.398 5.837 5.837 2.168 2.168W020.374 0.700 1.758 0.000 0.000 0.094 0.094 0.973 0.973 0.350 0.350wpp2312.750 2.699 3.167 0.000 0.000 3.188 3.188 4.771 4.771 1.350 1.350wpp42.745 1.268 13.806 0.000 0.000 0.686 0.686 7.589 7.589 0.634 0.634Table 2-12. Speciation of Particulate Matter Emitted from Lines and Stacks, ‘BART Control Level’ Case.Coarse PM FinePM Organic CondensableSourceIndexPM10-PM2.5(g/s)SolidPM2.5(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)0.500-0.625μm(g/s)wpp2312.75 2.699 3.167 0.000 0.000 3.188 3.188 4.771 4.771 1.350 1.350wpp42.745 1.268 13.806 0.000 0.000 0.686 0.686 7.589 7.589 0.634 0.634

# 3-1 Screening Modeling 

# 3.0 SCREENING MODELING

As a first step into the BART analysis for Al coa 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 simu lations and BART analysis, VISTAS 12-km regional

CALMET domain was used (VISTAS, 2005) with CALPUFF computational s ubdomain 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, emissi on controls for the Warrick facility are normally

based on impacts at the Class I area with the highest predicted visibility impair ment. 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 m odeled year separately (2001 to 2003) and for all 3

years together. The 98 th 

# percentile value for a single year is the 8 th 

# highest values, while for three-year

period is the 22 nd 

# highest.

Since Mammoth Cave is the Class I area with the hi ghest impacts, the modeling presented in this report

is conducted with the domain that is appropriate fo r 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 supplem ental 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 Ce ntroids 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/m 3 

# )

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 Natura l 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 400LCC North (km)



# LCC Origin: 40.0 N, 97.0 W

Standard Parallels: 33.0 N, 45.0 N

Datum: NWS-84 

# Elevation

(meters)

GA AL 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 a nd 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 Worl d 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 . Th e terrain is gently rolli ng, 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. Figur e 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 Cl ass I area in order to provide an adequate

buffer zone at the boundaries, and to allow the e ffects 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 an alysis 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 4250UTM 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 4250UTM Y Coordinate (km) - NAR-C



# Alcoa Warrick Aluminum Plant

Mammoth Cave National Park

U rb

a n l a n d

A g r i c u l t u r a l l a n d

R

a n g e l a n d

F

o r e s t l a n d

W

a t e r

W e t l a n d

B a r r e n l a n d

T

u n d

r a

S n o w

a n d

I c e



# 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 sma ll 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-dimensi onal 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 we re used in the modeling. There are ten surface

meteorological stations that were used, all locate d within or near the modeling domain (Table 4-2):

Louisville Standiford, KY; Capitol City, KY; L ouisville Bowman, KY; Owensboro, KY; Henderson

City, KY; Fort Knox, KY; Evansville, KY; Huntings burg, KY; Lawrenceville, KY; Fort Campbell, KY,

and, Bowling Green, KY. The surface data were ex tracted from the Integrated Surface Hourly Weather

Observations (ISHWO) CD-roms (Volume 19 for 2 001, 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. Precipitati on stations used in modeling are listed in Table 4-

4. These data were obtained from NCDC in TD3240 fo rmat. 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 measuremen ts in the chemical transformation rates (SO 2 

# to

SO 4 

# , NO

x 

# to HNO 3 

# /NO 3 

# ). The ambient ozone measuremen ts are used in determining SO 2 

# loss rates due

to chemical transformation to sulfate and in determining NO

x 

# 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 devel op 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 th e 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 part s 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 X 1



# (km) UTM Y 1



# (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 X 1 

# UTM Y 1 

# 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

Stat i o n Na m e Stat i o n ID Y ea r o f L o n g i tude L at i tude U TM X 1 

# U TM Y 1



# Data ( de g) ( de g) ( 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 Pa rk 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 Pa rk 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 Nationa l 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 X 1



# (km) UTM Y 1



# (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 CA STNet 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 CA STNet 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 CA STNet 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-rece ptor distances, and the importance of chemical

transformation, wet deposition, and dry deposition ar e important factors in the modeling. All these

factors are treated in the chosen modeling appro ach using the CALPUFF model (Scire et al., 2000a,b)

for the BART analysis for Mammoth Cave Nati onal Park. CALPUFF and it s 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 r ecommended CALPUFF as the preferred model for

BART analyses (U.S. EPA, 2005). The CALPUFF modeli ng system is the regulatory Guideline Model

for Class I impact assessments and other long rang e transport applications and on a case-by-case basis

for near-field applications involving comple x 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 fo r 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 Al coa Warrick Modeling Protocol (2008).

5.2 Modeling Domain Configuration

CALMET and CALPUFF use terrain-following coordinat es. 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 represen tation 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 th e 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 reso lution prognostic data from the 36 km MM5 data set for 2002-2004 in

LADCO (2006). The higher resolution of the prognos tic 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 adjust s 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 hi ghest peak within a radius TERRAD around each grid

point. A value of TERRAD of 10 km was determined b ased 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 St ep 1 wind field to produce a final wind field. Each

observation site influences the final wind field with in a radius of influence (parameters RMAX1 at the

surface and RMAX2 aloft). Observations and Step 1 fi eld 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 RM AX2 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 mode ling 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 elevati ons 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 conducte d 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 σ y 

# to time-dependent (Heffter) growth rates

- Partial plume path adjustment for terrain

- Wet deposition, dry deposition, and ch emical transformation were considered.

Two important computational parameters in CALP UFF 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 th e puff trajectory calculations. The first parameter

ensures that the length of an emitted puff does not beco me so large so that it cannot respond to changes

in the wind field on the scale of the meteorologi cal 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 characteriz e 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 defau lt dry deposition model,

the scavenging coefficient wet removal module, and the default chemical transformation mechanism.

Eleven species were modeled with CALPUFF for this analysis: SO 2 

# , SO 4 

# , NO

x 

# , HNO 3 

# , NO 3, 

# and six

subcategories of PM 10 

# , (PM 800 

# , PM 425 

# , PM 187 

# , PM 112 

# , PM 081 

# , PM 056 

# ). Of these eleven species, five are

emitted by the project sources: SO 2 

# , SO 4 

# , NO

x 

# , PM 10 

# , and NH 3 

# . The chemical mechanism computes

transformation rates of SO 2 

# to SO 4 

# and NO

x 

# to NO 3 

# /HNO 3 

# . Hourly measured ozone concentrations were

provided in an external OZONE.DAT file for use with the chemical transformation module. These

ozone concentrations, along with ra diation 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 i ndividually and their sour ce 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 equati on 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:

B

ext 

# = 3f(RH)[(NH 4 

# ) 2 

# SO 4 

# ] + 3f(RH)[NH 4 

# NO 3 

# ] +

4[OC] + 1[Soil] + 0.6[Coarse Mass] +10[EC] + b

ray



# The concentrations, in square brackets, are in μ g/m 3 

# and b

ext 

# is in units of Mm -1 

# . The Rayleigh scattering

term (b

ray 

# ) has a default value of 10 Mm -1 

# , as recommended in EPA Guid ance for Estimating Natural

Visibility Conditions Under the Re gional Haze Program (U.S. EPA, 2003b). Note that organic carbon

(OC) consists of condensable particulates which ar e assumed to be split evenly between the lowest two

particle size categories. Soil is fine particulates which is defined as PM 2.5 

# . 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(b

ext 

# /10)

where HI is in units of deciviews (dv) and b

ext 

# is in Mm -1 

# . The impact of a source is determined by

comparing HI for estimated natural background conditi ons with the impact of the source and without the

impact of the source

.



# CALPOST Method 6 was used to compute the extincti on 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 Ca ve were used. Annual b ackground concentrations

for the eastern United States are give in the Guidan ce 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 8 th 

# highest (98 th 

# percentile) predicted light extinction cha nge 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 Con centrations for the Eastern United States

East (μg/m 3 

# )

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 Conditi ons 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 s ources was computed. BART methodology with

CALPOST Method 6 and 98 th 

# 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 extinc tion coefficient, for each year separately as well as

for a full three-year period. The results of the visi bility calculations are presen ted in Table 6-1 through

Table 6-5 for the ‘BART Eligible Baseline’ case and five other scenarios.

For the ‘BART Eligible Baseline’ case, contributio n 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 Mammo th 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 Mammo th 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 Mammo th 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 Mammo th 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 So urces 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 wpp036-5ResultsTable 6-7. Source and Species Contributions to the 8thHighest Extinction Coefficient Changes for ‘BART Eligible Baseline’ Case at MammothCave National Park.Source Group BextContrib. to ModeledSpecies Contribution to ModeledExtinction Coefficient in 1/MmPercentage of Species Contributionto Modeled Extinction CoefficientChangeTotal Bext Ext.SO4NO3OrganicsE. CarbonPM_CoarsePM_FineSO4NO3OrganicsE. CarbonPM_CoarsePM_Fine(%)Change(%) 1/Mm1/Mm1/Mm1/Mm1/Mm1/Mm1/Mm%%%%%%2001: 8th highest impact is 3.678 DeciviewAll44.46100.00 9.456 9.118 0.1960.060 0.000 0.003 0.07996.432.070.630.000.030.84Lines0.120.26 0.025 0.007 0.0000.009 0.000 0.002 0.00728.000.0036.000.008.0028.00GTC0.601.34 0.127 0.120 0.0000.004 0.000 0.000 0.00394.490.003.150.000.002.36A398s0.861.94 0.183 0.172 0.0000.007 0.000 0.000 0.00493.990.003.830.000.002.19Melter/Holder0.010.03 0.003 0.000 0.0020.000 0.000 0.000 0.0010.0066.670.000.000.0033.33wpp014.7310.65 1.007 0.970 0.0250.005 0.000 0.000 0.00796.332.480.500.000.000.70wpp0215.7435.40 3.347 3.239 0.0750.014 0.000 0.000 0.01996.772.240.420.000.000.57wpp0322.3950.35 4.761 4.610 0.0930.020 0.000 0.000 0.03896.831.950.420.000.000.802002: 8th highest impact is 3.959 DeciviewAll48.57100.00 10.473 7.877 2.4250.069 0.000 0.001 0.10175.2123.150.660.000.010.96Lines0.040.10 0.010 0.002 0.0000.004 0.000 0.001 0.00320.000.0040.000.0010.0030.00GTC0.330.67 0.070 0.063 0.0010.004 0.000 0.000 0.00290.001.435.710.000.002.86A398s0.360.75 0.079 0.069 0.0020.005 0.000 0.000 0.00387.342.536.330.000.003.80Melter/Holder0.010.02 0.002 0.000 0.0020.000 0.000 0.000 0.0000.00100.000.000.000.000.00wpp015.3310.96 1.148 0.818 0.3130.007 0.000 0.000 0.01071.2527.260.610.000.000.87wpp0216.9034.80 3.645 2.703 0.8960.020 0.000 0.000 0.02674.1624.580.550.000.000.71wpp0325.6052.71 5.520 4.223 1.2100.030 0.000 0.000 0.05776.5021.920.540.000.001.032003: 8th highest impact is 3.487 DeciviewAll41.73100.00 9.081 8.161 0.7770.061 0.000 0.002 0.08089.878.560.670.000.020.88Lines0.080.19 0.017 0.004 0.0000.007 0.000 0.001 0.00523.530.0041.180.005.8829.41GTC0.551.32 0.120 0.111 0.0010.005 0.000 0.000 0.00392.500.834.170.000.002.50A398s0.821.95 0.177 0.164 0.0010.007 0.000 0.000 0.00592.660.563.950.000.002.82Melter/Holder0.040.09 0.008 0.000 0.0070.000 0.000 0.000 0.0010.0087.500.000.000.0012.50wpp014.5510.91 0.991 0.881 0.0980.005 0.000 0.000 0.00788.909.890.500.000.000.71wpp0215.0536.08 3.276 2.937 0.3040.015 0.000 0.000 0.02089.659.280.460.000.000.61wpp0320.6349.45 4.491 4.064 0.3670.021 0.000 0.000 0.03990.498.170.470.000.000.87

# 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, invers ion-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 Re lated Values Workgroup (FLAG). Phase I Report.

U.S. Forest Service, National Park Serv ice, U.S. Fish and Wildlife Service.

FLAG, 2008. Federal Land Manage r' 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 Gr avity 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 coe fficient 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 (CTDMPLU S) 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 App lication of the CALMET Meteorological Model to a

Complex Terrain Site. Paper 97-A1313. Air & Waste Management Asso ciation 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 Estimati ng Natural Visibility

Conditions Under the Regional Haze Program . EPA-454/B-03-005, September 2003.

U.S. Environmental Protection Agency (EPA), 200 5: 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 Al coa, Inc. - Warrick Operations

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