Appendix H 

Reasonable Progress Evaluation 

and Long Term Strategy 

 
TABLE OF CONTENTS 

LIST OF ATTACHMENTS ........................................................................................................... 4

PURPOSE....................................................................................................................................... 5

1.0 BASE G CAA CONTROLS..................................................................................................... 6

1.1 Point Source Controls........................................................................................................... 9 

1.1.1 Electric Generating Units (EGU).............................................................................................9 

1.1.2 Non-EGUs..............................................................................................................................17 

1.2 Area Source Controls.......................................................................................................... 18 

1.3 Mobile Sources................................................................................................................... 19 

1.4 Non-Road............................................................................................................................ 20 

1.5 Conclusion .......................................................................................................................... 20 

2.0 UNIFORM RATE OF PROGRESS ....................................................................................... 23

Figure 2-1. CMAQ 2018 Base G2 results compared to Uniform Rate of Progress at the Sipsey 

Wilderness. ......................................................................................................................... 23 

3.0 GEORGIA INSTITUTE OF TECHNOLOGY (GA Tech) SENSITIVITIES........................ 24

3.1 Evaluation for the Sipsey Wilderness Area, AL................................................................. 24 

3.2 Summary............................................................................................................................. 27 

4.0 REASONABLE PROGRESS EVALUATION...................................................................... 27

4.1 Area of Influence (AoI) Analyses....................................................................................... 27 

4.2 Source Type Analyses ........................................................................................................ 29 

4.3 Back Trajectory Analyses................................................................................................... 29 

4.4 Area of Influence (AoI) Data and Displays........................................................................ 32 

4.5 Importance of Pollutants Other Than Sulfate ..................................................................... 38 

4.6 Summary of Emission Inventories Used in Reasonable Further Progress (RFP) Analysis 39 

5.0 REASONABLE PROGRESS ASSESSMENT ...................................................................... 41

6.0 FOUR FACTOR ANALYSIS .................................................................................................. 1

6.1 The Four Statutory Factors................................................................................................... 1 

6.1-1 Cost of Compliance .................................................................................................................1 

6.1-2 Time Necessary for Compliance .............................................................................................1 

6.1-3 Energy and Non-Air Quality Environmental Impacts of Compliance ....................................1 

6.1-4 Remaining Useful Life of the Source......................................................................................2 

6.2 Evaluating Four Statutory Factors for Specific SO2 Emissions Sources in Each Area of 

Influence (AoI) ..................................................................................................................... 2 

6.2-1 Cost of Compliance .................................................................................................................2 

6.2-2 Time Necessary for Compliance .............................................................................................3 

6.2-3 Energy and Non-Air Environmental Impacts..........................................................................3 

6.2-4 Remaining Useful Life ............................................................................................................4 

6.3 Process of Applying Statutory Factors ................................................................................. 4 

7.0 Best Available Retrofit Technology (BART)........................................................................... 6

 
7.1 Background........................................................................................................................... 6 

7.2 Approach to Implementation of BART Requirements......................................................... 7 

7.3 Identification of BART-Eligible Sources............................................................................. 8 

7.4 Contribution Threshold....................................................................................................... 10 

7.5 Exemption of Point Source Volatile Organic Compounds (VOCs) for BART Purposes .. 11 

7.5.1 Method ...................................................................................................................................11 

7.5.2 Conclusions............................................................................................................................13 

7.6 Treatment of Ammonia (NH3) Emissions for BART Purposes.......................................... 13 

7.6.1 Method ...................................................................................................................................14 

7.6.2 Conclusions............................................................................................................................15 

8.0 Explanation of BART Exemption Modeling .......................................................................... 15

8.1 Background......................................................................................................................... 15 

8.2 Alabama BART Sources Exemption Modeling.................................................................. 17 

8.3 Use of New IMPROVE Equation....................................................................................... 21 

8.4 Source Limits to Exempt from BART................................................................................ 22 

8.5 Conclusions......................................................................................................................... 22 

9.0 BART Determinations............................................................................................................ 23

9.1 BART Subject Sources....................................................................................................... 23 

9.1.1 BART-Eligible Units and Existing Control...........................................................................23 

9.2 Baseline Contribution ......................................................................................................... 25 

9.3 BART Determination Analysis........................................................................................... 25 

9.3.1 Control Scenarios Considered................................................................................................26 

9.3.2 Costs of Compliance........................................................................................................ 29 

9.3.3 Energy and Non-air Quality Impacts.....................................................................................32 

9.3.4 Existing Control.....................................................................................................................32 

9.3.5 Remaining Useful Life...........................................................................................................32 

9.3.6 Degree of Visibility Improvement.........................................................................................32 

9.4 Final BART Determination ................................................................................................ 34 

9.5 BART Subject Sources in Other States Within 300 km of Alabama Class I Areas........... 35 

9.6 Conclusions......................................................................................................................... 35 

10.0 FINAL LONG TERM STRATEGY (LTS) AND REASONABLE PROGRESS GOALS 

(RPGs)........................................................................................................................................... 36

10.1 Long-Term Strategy (LTS)............................................................................................... 36 

10.2 What Additional Emissions Controls Were Considered as Part of the Long-Term Strategy 

for Visibility Improvement by 2018? ................................................................................. 37 

10.3 Reasonable Progress Goals (RPGs).................................................................................. 38 

REFERENCES: ............................................................................................................................ 40

 
LIST OF ATTACHMENTS 

Attachment H.1 – Alabama’s AoI Analysis 

Attachment H.2 – BART Facility Letters 

Attachment H.3 - Alabama BART Eligible Sources 

Attachment H.4 - BART Analysis Sensitivity Modeling 

Attachment H.5 - BART Modeling Protocols 

Attachment H.6 - BART Demonstrations 

Attachment H.7 - Proposed BART Exemptions 

Attachment H.8 - Alabama Modeling Summary Report 

Attachment H.9 - BART Determination Submittals 

 
PURPOSE 

The purpose of this appendix is to outline the State’s strategy for complying with the 

requirement to set and meet Reasonable Progress Goals (RPGs) as part of our Regional Haze SIP 

under 40 CFR 51.308(d)(1), and the requirements for establishing best available retrofit (BART) 

controls under 40 CFR 51.308(e). 

In the 1977 amendments to the Clean Air Act (CAA), Congress set a national goal for visibility 

as “the prevention of any future, and the remedying of any existing, impairment of visibility in 

mandatory Federal Class I areas which impairment results from manmade pollution”. The 

Regional Haze Rule (RHR) at 51.308(d) requires states to demonstrate reasonable progress 

toward meeting the goal of a return to natural visibility conditions by 2064. As a guide for 

reasonable progress, the RHR directs states to graphically show what would be a “uniform rate 

of progress” toward natural conditions for each Class I area. This is known as the “glidepath”. 

The RHR then requires states to establish RPGs for visibility improvement at each affected Class 

I area covering each approximately 10 year period until 2064. Therefore, our first set of RPGs 

will comprise our long term strategy (LTS) covering the period from the present until 2018. This 

appendix provides an overview of this first LTS. In addition, a specific component of each 

state’s first LTS is dictated by the specific BART requirements in 40 CFR 51.308(e). This 

appendix will also include a discussion of our strategy for developing those BART requirements. 

Alabama’s LTS contains the following components: 

I. Inventory of all controls required or expected under all federal and state regulations by 

2009 and 2018. These controls are referred to as “on the books” or “on the way” 

(OTB/OTW). 

II. Modeled expected visibility improvement from OTB/OTW (Base G) controls and 

comparison of Base G results for 2018 to the uniform rate of progress, or “glidepath” for 

the Sipsey Wilderness area. 

III. Discussion of emissions sensitivity model runs to help determine which pollutants and 

source categories are contributing the most to visibility impairment at Class I areas (runs 

conducted by Georgia Institute of Technology). 

IV. Examination of SO2 Area of Influence (AoIs) projections for the Sipsey Wilderness area, 

and also for any surrounding states’ Class I areas whose AoI includes any Alabama 

sources, to determine which specific sources are most likely to be impairing visibility. 

V. Application of the four “statutory factors,” listed in 40 CFR 51.308(d)(1)(i)(A) to those 

sources identified in the previous step. 

VI. Using the results of the four factor analyses, identification of control determinations for 

specific sources. 

VII. Identification of BART-eligible sources. 

VIII. BART exemption modeling for BART-eligible sources. 

IX. BART determinations for sources subject to BART. 

X. Modeling demonstration of visibility improvement after inclusion of BART and 

reasonable progress control determinations. 

XI. Determination of RPGs based on the visibility improvement expected by 2018. 

 
1.0 BASE G CAA CONTROLS 

2009 and 2018 emissions projections include the following existing state and federal regulations: 

• Clean Air Interstate Rule (CAIR). Utility projections are based on the Integrated 

Planning Model (IPM). CAIR will permanently cap emissions of sulfur dioxide (SO2) 

and nitrogen oxides (NOx) in the eastern United States. CAIR achieves large reductions 

of SO2 and/or NOx emissions across 28 eastern states and the District of Columbia. When 

fully implemented, CAIR will reduce SO2 emissions in these states by over 70% and NOx

emissions by over 60% from 2003 levels. 

• NOx SIP Call. Phase I of the NOx SIP call applies to certain Electric Generating Units 

(EGUs) and large non-EGUs, including large industrial boilers and turbines, and cement 

kilns. States in the VISTAS region affected by the NOx SIP call have developed rules for 

the control of NOx emissions that have been approved by EPA. The available State rules 

and guidance documents were reviewed to determine the affected sources and ozone 

season allowances. Information in the EPA’s CAMD NOx Allowance Tracking System – 

Allowances Held Report was also obtained and reviewed. Since these controls are to be 

in effect by the year 2007, we capped the emissions for NOx SIP call affected sources at 

2007 levels and carried forward the capped levels for the 2009/2018 future year 

inventories. This rule resulted in a 68% reduction in NOx emissions from the State’s large 

stationary combustion sources. Phase II of the NOx SIP Call applies to reciprocating 

internal combustion engines with an average daily NOx emission rate of greater than one 

ton (during the baseline period of ozone season 1995). These units were required to 

reduce NOx emissions by not less then 82% of the Projected 2007 Ozone Season Base 

NOx Emissions by the control period of May 1 through September 30, 2007 and must 

maintain that reduction during future control periods 

• NC Clean Smokestacks Act. Under the act, enacted in 2002, coal-fired power plants in 

North Carolina must achieve a 77% cut in nitrogen oxide (NOx) emissions by 2009 and a 

73% cut in sulfur dioxide (SO2) emissions by 2013. 

• Consent Agreements (TECO, VEPCO, Gulf Power Crist 7, Santee Cooper, EKPC and 

APCO Plant Miller). 

• Under a settlement agreement, by 2008, Tampa Electric will install permanent 

emissions-control equipment to meet stringent pollution limits; implement a series 

of interim pollution-reduction measures to reduce emissions while the permanent 

controls are designed and installed; and retire pollution emission allowances that 

Tampa Electric or others could use, or sell to others, to emit additional NOx, SO2, 

and PM. 

• Virginia Electric and Power Co. (VEPCO) agreed to spend $1.2 billion by 2013 to 

eliminate 237,000 tons of SO2 and NOx emissions each year from eight coal-fired 

electricity generating plants in Virginia and West Virginia. 

• A 2002 agreement calls for Gulf Power to upgrade its operation to cut NOx

emission rates by 61% at its Crist generating plant by 2007, with major reductions 

 
• A 2004 consent agreement calls for Santee Cooper to install and commence 

operation of continuous emissions control equipment for PM/SO2/NOx emissions; 

comply with system-wide annual PM/SO2/NOx emissions limits; agree not to buy, 

sell or trade PM/SO2/NOx allowances allocated to Santee Cooper System as a 

result of said agreement; and to comply with emission unit limits of said 

agreement. 

• A July 2, 2007 consent agreement between the U.S. EPA and East Kentucky 

Power Cooperative (EKPC) requires the utility to reduce its emissions by 62,000 

tpy (including 54,000 tons of SO2 and 8,000 tons of NOx) by installing/operating 

selective catalytic reduction (SCR) technology; low-NOx burners, and PM and 

Mercury Continuous Emissions Monitoring at the utility’s Spurlock, Dale and 

Cooper Plants. According to the EPA, the plant’s total emissions will drop from 

between 50 – 75% from 2005 levels. As with all federal Consent Decrees, EKPC 

is precluded from using reductions required under other programs, such as the 

Clean Air Interstate Rule (CAIR). EKPC is expected to spend over $600 million 

on pollution controls. 

• Alabama Power Company – Plant Miller (Jefferson County) On April 25, 2006, 

the U.S. EPA and the Department of Justice announced a settlement with 

Alabama Power Company (APC) to reduce emissions of sulfur dioxide (SO2) and 

nitrogen oxides (NOx) from Boiler Units 3 and 4 at its Plant Miller in Quinton, 

Alabama. The plant is required to reduce SO2 by installing flue gas 

desulfurization (FGD) and is required to reduce NOx by installing selective 

catalytic reduction (SCR) equipment. The Consent Decree requires APC to 

commence continuous year-round operation of SCR equipment for control of NOx

emissions by May 1, 2008. APC is also required to begin year-round operation of 

the FGD equipment for control of SO2 emissions by December 31, 2011. The 

installation and operation of these controls are expected to result in the reduction 

of 4,953 tons per year of NOx and 22,788 tons per year of SO2. APC is also 

required to install and operate by December 31, 2008, a mercury continuous 

emission monitoring system. APC is precluded from using the emissions 

reductions required under other programs, such as the Clean Air Interstate Rule 

(CAIR). In addition, the Consent Decree requires APC to purchase and 

permanently retire $4.9 million worth of 2007 SO2 emissions allowances. 

• 1-hr Ozone SIPs (Atlanta / Birmingham / Northern Kentucky). The purpose of a State 

Implementation Plan (SIP) is demonstrate attainment or maintenance of the 1-hour Ozone 

National Ambient Air Quality Standard (NAAQS). States must determine which Clean 

Air Act requirements are applicable to their area and submit plans to EPA for public 

comment and approval. 

• Heavy Duty Diesel (2007) Engine Standard. A PM emissions standard for new heavyduty engines of 0.01 grams per brake-horsepower-hour (g/bhp-hr), to take full effect for 

diesels in the 2007 model year. Also includes standards for NOx and non-methane 

hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/ bhp-hr, respectively. These NOx and 

 
NMHC standards will be phased in together between 2007 and 2010, for diesel engines.

Sulfur in diesel fuel must be lowered to enable modern pollution-control technology to be 

effective on these trucks and buses. EPA will require a 97% reduction in the sulfur 

content of highway diesel fuel from its current level of 500 parts per million (low sulfur 

diesel, or LSD) to 15 parts per million (ultra-low sulfur diesel, or ULSD). 

• Tier 2 Tailpipe. Tier 2 is a fleet averaging program, modeled after the California LEV II 

standards. Manufacturers can produce vehicles with emissions ranging from relatively 

dirty to zero, but the mix of vehicles a manufacturer sells each year must have average 

NOx emissions below a specified value.

• Large Spark Ignition and Recreational Vehicle Rule. Sets emission standards for these 

categories of nonroad engines and vehicles. 

• Nonroad Diesel Rule. Implements a low sulfur fuel requirement that affects both future 

CMV and locomotive emissions.

• Industrial Boiler/Process Heater/RICE MACTs. The EPA issued final rules to 

substantially reduce emissions of toxic air pollutants from industrial, commercial and 

institutional boilers, process heaters and from stationary reciprocating internal 

combustion engines (RICE). These rules reduce emissions of a number of toxic air 

pollutants, including hydrogen chloride, manganese, lead, arsenic and mercury by 2009. 

This rule also reduces emissions of SO2 and PM in conjunction with the toxic air 

pollutant reductions. The applied Maximum Achievable Control Technology (MACT) 

control efficiencies were 4% for SO2 and 40% for PM10 and PM2.5. EPA’s industrial 

boiler MACT rules were vacated on June 8, 2007; however Alabama adopted the rules by 

reference. As such, the rules are still enforceable at the State level.

• Combustion Turbine MACT. The projection inventories do not include the NOx cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating 

Internal Combustion Engines, which EPA estimates to be small compared to the overall 

inventory.

• VOC 2-, 4-, 7-, and 10-year MACT Standards. The point source MACTs and associated 

emission reductions were designed from Federal Register (FR) notices and discussions 

with EPA’s Emission Standards Division (ESD) staff. We did not apply reductions for 

MACT standards with an initial compliance date of 2001 or earlier, assuming that the 

effects of these controls are already accounted for in the 2002 inventories supplied by the 

States. 

The following are source category specific controls used to project future year emissions 

inventories: 

 
1.1 Point Source Controls 

Different approaches were used for the Electric Generating Unit (EGU) and the non-EGU sectors 

of the point source inventory: 

• For the EGUs, the State relied primarily on the IPM to project future generation as well 

as to calculate the impact of future emission control programs, to include CAIR and 

CAMR. The IPM results were adjusted based on State and local (S/L) agency knowledge 

of planned emission controls at specific EGUs. 

• For non-EGUs, we used recently updated growth and control data consistent with the data 

used in EPA’s CAIR analyses, and supplemented these data with available S/L agency 

input and updated fuel use forecast data for the U.S. Department of Energy. 

 

For both sectors, we generated 2009 and 2018 inventories for a combined on-the-books (OTB) 

and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounts for post2002 emission reductions from promulgated and proposed federal, state, local, and site-specific 

control programs as of July 1, 2004. 

1.1.1 Electric Generating Units (EGU) 

S/L agencies specified a number of changes to the IPM results to better reflect current 

information on when and where future controls would occur. These changes to the IPM results 

primarily involved S/L agency addition or subtraction of future emission controls based on the 

best available data from state rules, enforcement agreements, compliance plans, permits, and 

discussions/commitments from individual companies. 

ADEM replaced the IPM emission projections for 2009 with projections from the utilities in the 

State who had applied for and received or were in the process of receiving permits. For the 2018 

basecase, ADEM elected to use the IPM results. 

 

Table 1-1 lists adjustments to IPM control determinations specified by S/L agencies for the Base 

G 2009/2018 EGU inventories. Table 1-2 lists other adjustments to IPM results specified by S/L 

agencies for Base G 2009/2018 inventories. 

 
Table 1-1. Adjustments to IPM Control Determinations Specified by S/L Agencies for the 

Base G 2009/2018 EGU Inventories. 

NOx Emission Controls SO2 Emission Controls 

State Plant Name and ID Unit 2009 2018 2009 2018 

IPM State IPM State IPM State IPM State 

AL James H. Miller 

ORISID=6002 

1 & 2 SCR 

during 

ozone 

season 

SCR 

probable 

year 

round 

due to 

CAIR 

SCR 

during 

ozone 

season 

SCR 

probable 

year 

round 

due to 

CAIR 

None None None None 

 3 & 4 SCR 

during 

ozone 

season 

SCR year 

round 

from 

Consent 

Decree 

SCR 

during 

ozone 

season 

SCR year 

round 

from 

Consent 

Decree 

None Scrubber None Scrubber 

 Barry 1, 2, 3 None SNCR SCR SNCR None None None None 

 ORISID=3 4 None SNCR SCR SNCR None None Scrubber None 

 5 None None SCR SCR None None Scrubber None 

 E C Gaston 1 - 4 SCR None SCR None None None Scrubber None 

 ORISID=26 5 SCR SCR SCR SCR Scrubber None Scrubber None 

 Gorgas 6 & 7 None None None None None None None None 

 ORISID=8 8 & 9 None None None None None Scrubber None Scrubber 

 10 SCR SCR SCR SCR None Scrubber Scrubber Scrubber 

 Charles R. Lowman 1 None None None None None Scrubber None Scrubber 

 ORISID=56 2 & 3 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

GA Bowen 1BLR SCR SCR SCR SCR None Scrubber Scrubber 

ORISID=703 2BLR SCR SCR SCR SCR None Scrubber Scrubber 

3BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber 

4BLR SCR SCR SCR SCR 

IPM had 

retrofit 

scrubbers 

but little 

emission 

reductions Scrubber Scrubber Scrubber 

 
Table 1-1 (continued) 

NOx Emission Controls SO2 Emission Controls 

State Plant Name and ID Unit 2009 2018 2009 2018 

IPM State IPM State IPM State IPM State 

GA Wansley 1 SCR SCR SCR SCR Scrubber Scrubber Scrubber 

ORISID=6052 2 SCR SCR SCR SCR 

IPM had 

retrofit 

scrubbers 

but little 

emission 

reductions 

None Scrubber Scrubber 

Kraft 1, 2 None None None None None None None None 

ORISID=733 3 None None SCR None None None None None 

McIntosh 

ORISID=6124 

1 None None SCR None None None None None 

Yates 1 None None None None Scrubber Scrubber Scrubber Scrubber 

ORISID=728 2, 3 None None None None None None None None 

4 – 7 None None SCR None None None Scrubber None 

Hammond 1 None None SCR SCR None Scrubber Scrubber Scrubber 

ORISID=708 2 None None SCR SCR None Scrubber Scrubber Scrubber 

3 None None SCR SCR None Scrubber Scrubber Scrubber 

4 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

KY Ghent 1 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

ORISID=1356 2 None None SCR SCR None Scrubber Scrubber Scrubber 

3, 4 None SCR SCR SCR None Scrubber Scrubber Scrubber 

Coleman C1 None None SCR SCR None Scrubber Scrubber Scrubber 

ORISID=1381 C2 None None SCR SCR None Scrubber Scrubber Scrubber 

C3 None None SCR SCR None Scrubber Scrubber Scrubber 

HMP&L Station 2 H1 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

H2 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

 
Table 1-1 (continued) 

NOx Emission Controls SO2 Emission Controls 

State Plant Name and ID Unit 2009 2018 2009 2018 

IPM State IPM State IPM State IPM State 

KY E W Brown 1 None None None None None Scrubber None Scrubber 

ORISID=1355 2 None None SCR SCR None Scrubber Scrubber Scrubber 

3 None None SCR SCR None Scrubber Scrubber Scrubber 

SC Jeffries 3 SCR None SCR None None None None None 

ORISID=3319 4 None None None None None None None None 

Wateree WAT1 SCR SCR SCR SCR None Scrubber None Scrubber 

ORISID=3297 WAT2 SCR SCR SCR SCR None Scrubber Scrubber Scrubber 

Canadys CAN1 None None None None None None None None 

ORISID=3280 CAN2 None None None None None None None None 

CAN3 None None None None None Scrubber None Scrubber 

Rainey CT1A None SCR None SCR None None None None 

ORISID=7834 CT1B None SCR None SCR None None None None 

TN Kingston 1 – 8 SCR SCR SCR SCR None None Scrubber Scrubber 

ORISID=3407 9 None SCR SCR SCR None None Scrubber Scrubber 

Johnsonville 1 – 10 SCR None SCR SCR None None None None 

ORISID=3406 

WV Willow Island 2 SCR None SCR SCR Scrubber None Scrubber Scrubber 

ORISID=3946 

Kammer 1 -3 SCR None SCR SCR Scrubber None Scrubber Scrubber 

ORISID=3947 

 
Table 1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 

2009/2018 EGU Inventories. 

State Plant Name and ID Unit Nature of Update/Correction 

FL Central Power and Lime 

ORISID= 10333 

GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. 

This is point 18 in Florida Crushed Stone (12-053-0530021). 

Removed IPM emissions for Central Power and Lime. 

Cedar Bay Generating 

ORISID=10672 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. Cedar 

Bay is connected to Stone Container (12-031-0310067). 

Replaced IPM emissions with 2002 emissions for Cedar Bay 

(12-031-0310337) times the growth factors for Stone 

Container. 

Indiantown Cogeneration 

ORISID=50976 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. 

Indiantown is connected to Louis Dreyfus Citrus (12-085-

0850002). Replaced IPM emissions with 2002 emissions for 

Indiantown (12-085-0850102) times the growth factors for 

Louis Drefus Citrus. 

GA Bowen 

ORISID=703 

1BLR 

2BLR 

3BLR 

4BLR 

IPM indicated retrofit scrubbers on all 4 units in 2009, but 

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect scrubbers on 1BLR and 

2BLR by 2009. 

Wansley 

ORISID=6052 

1, 2 IPM indicated retrofit scrubbers on both units in 2009, but 

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect one scrubber on Unit 1 

by 2009. 

Riverside 

ORISID=734 

4 All of plant Riverside was retired from service June 1, 2005; 

emissions set to zero in 2009 and 2018. 

McIntosh 

ORISID=727 

CT10A 

CT10B 

CT11A 

CT11B 

The McIntosh Combined Cycle facility became commercial 

June 1, 2005. Added 346 tons of NOx and 121 tons of SO2

per unit to the 2009 and 2018 inventories. 

Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power 

Development, Inc. GA specified that the emissions from this 

proposed plant be included in the 2018 projections. Boilers 1 

and 2 added 1,882 tons of NOx and 3,227 tons of SO2 per 

unit to the 2018 inventory. 

MS R D Morrow 

ORISID=6061 

1, 2 Revised the 2018 emissions to reflect controls not indicated 

by IPM. The SO2 emissions are much lower than IPM, but 

their expected NOx emissions are actually higher than IPM. 

The controls will be coming online 2009 or 2010, so the 

2009 inventory did not change. 

Jack Watson (2049) 

Victor J Daniel (6073) 

Chevron Oil (2047) 

All MS DEQ specified that the emission projections provided by 

the Southern Company for their units in Mississippi were to 

be used instead of the IPM results. 

 
Table 1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

NC G G Allen (2718) 

Belews Creek (8042)1 

Buck (2720) 

Cliffside (2721) 

Dan River (2723) 

Marshall (2727) 

Riverbend (2732) 

All Replaced all IPM 2009 results with emission projections 

from Duke Power’s NC Clean Air Compliance Plan for 

2006. Used IPM results for 2018 

Asheville (2706) 

Cape Fear (2708) 

Lee (2709) 

Mayo (6250) 

Roxboro (2712) 

Sutton (2713) 

Weatherspoon (2716) 

All Replaced all IPM 2009 results with emission projections 

from Progress Energy’s NC Clean Smokestacks Act 

Calendar Year 2005 Progress Report. Used IPM results for 

2018 

Dwayne Collier Battle 

Cogeneration Facility 

ORISID=10384 

GEN1 

GEN2 

Dwayne Collier Battle is a duplicate entry. This is Cogentrix 

of Rocky Mount (37-065-3706500146, stacks G-26 and G27). Duplicate entries were removed both the 2009 and 2018 

inventories. 

Kannapolis Energy 

Partners 

ORISID=10626 

GEN2 

GEN3 

Kannapolis Energy emissions are being used as credits for 

another facility. IPM emissions from this facility (37-025-

ORIS10626) were removed from the EGU inventory for 

2009 and 2018. Emissions from Kannapolis Energy (37-025-

3702500113) were carried forward in the 2009/2018. 

SC Cross 

ORISID=130 

1, 2 Unit 1: upgrade scrubber from 82 percent to 95 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

Unit 2: upgrade scrubber from 70 percent to 87 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

Winyah 

ORISID=6249 

1 – 4 Unit 1: Install scrubber that meets 95 percent removal 

efficiency by Dec. 31, 2008; Upgrade ESP from 0.38 to 0.03 

lb/mmBTU by Dec. 31, 2008 

Unit 2: Replace scrubber with one that meets 95 percent 

removal efficiency from 45 percent by Dec. 31, 2008; 

Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 

2008 

Unit 3: Upgrade scrubber from 70 percent to 90 percent 

removal efficiency by Dec. 31, 2012; Upgrade ESP from 

0.10 to 0.03 lb/mmBTU by Dec. 31, 2012 

Unit 4: Upgrade scrubber from 70 percent to 90 percent 

removal efficiency by Dec. 31, 2007; Upgrade ESP from 

0.10 to 0.03 lb/mmBTU by Dec. 31, 2007 

Recalculated SO2 and PM emissions based on upgrade in 

control efficiencies. 

 
Table 1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

SC Dolphus Grainger 

ORISID=3317 

1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

Unit 2: Install low NOx burners that meet 0.46 lb/mmBTU 

from 0.9 by May 1, 2004. Recalculated NOx emissions using 

0.46/lbs/mmBtu and IPM heat input 

Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

SC Jeffries 

ORISID=3319 

3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 

94.44 percent based on change in allowable emission rate 

Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 

31, 2012. Reduced PM10 and PM25 emissions in 2018 by 

94.44 percent based on change in allowable emission rate 

W S Lee 

ORISID=3264 

1, 2 IPM does not indicate that these units are installing SOFA 

NOx control technology by April 30, 2006 to meet 0.27 

lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NOx

emissions using IPM heat input and 0.27 lbs/mmBtu 

Generic Unit 

ORISID=900545 

All All predictions for generic units appear reasonable with the 

exception of Plant ID ORIS900545 Point ID GSC45 which 

was modeled in Georgetown County. It will be very difficult 

to add new generation this close to the Cape Romain Class I 

area. Santee Cooper has no plans for future generation in 

Georgetown County, but does have plans for new future 

generation in Florence County. This unit was moved to 

coordinates specified in Florence County. 

VA AEP Clinch River 

ORISID=3775 

1, 2, 3 Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

AEP Glen Lyn 

ORISID=3776 

51, 52, 

6 

Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

Dominion Clover 

ORISID=7213 

1, 2 Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

Dominion Bremo 

ORISID=3796 

3, 4 Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

Dominion Chesterfield 

ORISID=3797 

3, 4, 

5, 6 

Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

Dominion Yorktown 

ORISID=3809 

1, 2, 3 Units 1, 2: Replaced all 2009/2018 IPM results using 

VADEQ’s growth and control estimates. 

Unit 3: IPM predicts zero heat input for this 880 MW #6 oil 

fired unit. IPM does not predict a retirement, just that the 

heat input is zero. Dominion plans to continue to operate 

Unit 3. Replaced all 2009/2018 IPM results using VADEQ’s 

growth and control estimates. 

 
Table 1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

VA Dominion Chesapeake 

ORISID=3803 

1 – 4 Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

Dominion Possum Point 

ORISID=3804 

3 & 4 

5 

6 

Unit 3&4: IPM had 137 tons of NOx for these units in 2009 

and 111 tons in 2018. VA DEQ specified that the permitted 

emission rates should be used, which equates to 3,066 tons 

in 2009 and 2018. 

Unit 5: IPM had zero heat input for this unit. Replaced all 

2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s 

growth and control estimates. 

Potomac River 

ORISID=3788 

1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at 

this time to retire any units. Replaced all 2009/2018 IPM 

results using VADEQ’s growth and control estimates. 

Units 3, 4, 5: Replaced all 2009/2018 IPM results using 

VADEQ’s growth and control estimates. 

WV Albright 

ORISID=3942 

1, 2 IPM predicted early retirement for these units. AEP 

indicated there are no for early retirement. For 2009, used 

2002 emissions as these units are not likely to retire by 2009. 

For 2018, used IPM prediction of retirement. 

Rivesville 

ORISID=3945 

7, 8 IPM predicted early retirement for these units. AEP 

indicated there are no for early retirement. For 2009, used 

2002 emissions as these units are not likely to retire by 2009. 

For 2018, used IPM prediction of retirement. 

Willow Island 

ORISID=3946 

1, 2 Unit 1: IPM predicted early retirement for these units. AEP 

indicated there are no for early retirement. For 2009, used 

2002 emissions as these units are not likely to retire by 2009. 

For 2018, used IPM prediction of retirement. 

Unit 2: IPM predicted SCR and scrubber for 2009. These 

controls will not be in place by 2009. 

North Branch Power 

Station 

ORISID=7537 

1A, 1B SO2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. 

Used SO2 Permit Rate of 0.678 lb/MMBtu and IPM 

predicted total fuel used to calculate SO2 emissions in 2009 

and 2018 

Mt. Storm 

ORISID=3954 

1, 2, 3 SO2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. 

Used SO2 Permit Rate of 0.15 lb/MMBtu and IPM predicted 

total fuel used to calculate SO2 emissions in 2009 and 2018 

 
1.1.2 Non-EGUs 

The general approach for assembling future year data was to use recently updated growth and 

control data consistent with the data used in EPA’s CAIR analyses, supplement these data with 

available stakeholder input, and provide the results for stakeholder review to ensure credibility.

MACTEC (MACTEC, 2006) used the same control programs for both the 2009 and 2018 nonEGU point inventory. Two control scenarios were developed: on-the-books (OTB) controls and 

on-the-way (OTW) controls. The OTB control scenario accounts for post-2002 emission 

reductions from recently promulgated federal, state, local, and site-specific control programs. 

The OTW control scenario accounts for proposed (but not final) control programs that are 

reasonably anticipated to result in post-2002 emission reductions. 

Maximum achievable control technology (MACT) requirements were also applied, as 

documented in the report entitled Control Packet Development and Data Sources, dated July 14, 

2004. The point source MACTs and associated emission reductions were designed from Federal 

Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD) staff. 

Reductions for MACT standards with an initial compliance date of 2001 or earlier were not 

applied, assuming that the effects of these controls are already accounted for in the 2002 

inventories supplied by the States. Emission reductions were applied only for MACT standards 

with an initial compliance date of 2002 or greater. 

The final Phase II NOx SIP call rule was finalized on April 21, 2004. States had until April 21, 

2005, to submit SIPs meeting the Phase II NOx budget requirements. The Phase II rule applies to 

large IC engines, which are primarily used in pipeline transmission service at compressor 

stations. Affected units were identified using the same methodology as was used by EPA in the 

proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per 

day during 2002). The final rule reflects a control level of 82% for natural gas-fired IC engines 

and 90 percent for diesel or dual fuel categories. Several S/L agencies provided more specific 

information on the anticipated controls at the compressor stations. This information was used 

instead of the default approach used by EPA in the proposed Phase II rule. 

A summary of non-EGU point source control programs included in 2009/2018 

projection inventories include: 

• Atlanta / Northern Kentucky / Birmingham 1-hr Ozone SIPs 

• Industrial Boiler/Process Heater/RICE MACT. The applied MACT control efficiencies 

were 4% for SO2 and 40% for PM10 and PM2.5 to account for the co-benefit from 

installation of acid gas scrubbers and other control equipment to reduce HAPs.

• NOx RACT in 8-hr NAA SIPs. 

• NOx SIP Call Phase I- except where States have adopted II already. Phase I of the NOx

SIP call applies to certain large non-EGUs, including large industrial boilers and turbines, 

and cement kilns. States in the VISTAS region affected by the NOx SIP call have 

 
developed rules for the control of NOx emissions that have been approved by EPA. State 

rules and guidance documents were reviewed to determine the affected sources and ozone 

season allowances. 

• Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV). This initiative 

addresses the most significant Clean Air Act compliance concerns affecting the 

petroleum refinery industry. Since December 2000, 17 global refinery settlements have 

been reached with refiners representing nearly 77% of domestic refining capacity. Three 

refineries in the VISTAS region are affected by two October 2003 Clean Air Act 

settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the 

Chevron refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3) 

the Ergon refinery in Newell, WV. 

• Reasonable Further Progress 3 percent plans where in place for 1 hour Ozone plans 

(Metropolitan Washington, DC, and Atlanta, GA). 

• VOC 2-, 4-, 7-, and 10-year MACT Standards. The point source MACTs and associated 

emission reductions were designed from Federal Register (FR) notices and discussions 

with EPA’s Emission Standards Division (ESD) staff. Reductions for MACT standards 

with an initial compliance date of 2001 or earlier, were not applied, assuming that the 

effects of these controls are already accounted for in the 2002 inventories supplied by the 

States. 

• Combustion Turbine MACT. The projection inventories do not include the NOx cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating 

Internal Combustion Engines, which EPA estimates to be small compared to the overall 

inventory. 

• NOx SIP Call (Phase II – remaining States & IC engines). 

For more information on the development of point source inventories, see Appendix D. 

1.2 Area Source Controls 

Controls (including control efficiency, rule effectiveness and rule penetration) provided by the 

States or originally developed for use in estimating projected emissions for U.S. EPA’s Heavy 

Duty Diesel (HDD) rulemaking emission projections and used in the Clean Air Interstate Rule 

(CAIR) projections were used to calculate controlled emissions. 

The controls obtained by MACTEC (MACTEC, 2006) for the HDD rulemaking were controls 

for the years 2007, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, 

control values for intermediate years were prepared using a straight-line interpolation of control 

level between 2007 and 2020. 

 
State submitted controls had precedence over the U.S. EPA developed controls. Control 

measures submitted by the Alabama Department of Environmental Management (ADEM) 

include Stage I controls for gasoline dispensing facilities, and open burning controls. 

As part of the air toxics program, Stage I controls for gasoline dispensing facilities was adopted 

by the State, effective October 1990. Stage I is the vapor recovery technology on the 

underground storage tanks and reduces the emissions during the tank filling operations at service 

stations. 

The Petroleum Section of the ADEM Air Division is tasked with inspecting Stage I controls. If a 

facility is not found to be properly maintaining the control equipment, then the ADEM sends a 

notice of violation informing the facility that the controls are required and gives the facility time 

to correct the violation before fines are accessed. From this information the rule effectiveness 

and rule penetration can be estimated. The rule effectiveness is the percentage of facilities 

complying with the rule, where as the rule penetration is the percentage of facilities requiring 

Stage I controls. Control efficiency is the expected percent reduction from this control 

technology. 

Open burning is treated as a means of waste disposal in rural areas. Materials burned generally 

include household trash, agricultural refuse, landscaping refuse, or scrap wood. It should be noted 

that burning of household garbage is forbidden by ADEM regulations. The open burning emissions 

inventory includes SCC 2610030000, residential open burning of household waste and SCC 

2610000100, open burning of yard trimmings. During the months of May through September, 

there is an open burning ban in twelve Alabama counties (Morgan, Madison, Lawrence, 

Jefferson, Shelby, Montgomery, Mobile, Russell, DeKalb, Etowah, Talladega and Baldwin). The 

ban includes the burning of untreated wood, tree trimmings and brush or plant growth generated 

by clearing or maintenance of land and from construction and demolition operations. Provided 

there are no local or state ordinances which would restrict the activity, burning the materials 

listed above may take place during the other seven months of the year in the counties affected by 

the open burning ban and year-round in other counties. Open burning of other types of materials, 

such as garbage, shingles, rubber products, paper, treated wood, plastic, salvage materials, 

insulation etc. is prohibited at all times across the state. 

For more information on the development of area source inventories, see Appendix D. 

1.3 Mobile Sources 

Local controls included vehicle emissions inspection (i.e., I/M) programs, Stage II vapor 

recovery programs, anti-tampering programs, etc. By nature, the assumptions used for the 2002 

initial base year inventory vary across the VISTAS region, but the presumption is that these data 

accurately reflected each State’s situation as it existed in 2002. If a State had no plans to change 

program requirements between 2002 and 2018, we proposed to maintain the 2002 program 

descriptions without change. However, if a State planned changes, we requested information on 

those plans. In the final implementation of the inventory, Stage II controls were exercised in the 

 
area source component of the inventory, since the units used to develop Stage II refueling 

estimates are different between MOBILE6 and the NONROAD models. 

For more information on the development of mobile source inventories, see Appendix D. 

1.4 Non-Road 

Using the 2002 base year emissions inventory for aircraft, locomotives, and commercial marine 

vessels (CMV) prepared as described earlier in this document, corresponding emission 

projections for 2009 and 2018 were developed. Detailed inventory data (both before and after 

controls) for these same emission sources for 1996, 2010, 2015, and 2020 were obtained from 

the EPA's Clean Air Interstate Rule (CAIR) Technical Support Document. Using these data, 

combined growth and control factors for the period 2002-2009 and 2002-2018 were estimated 

using straight-line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 

2018). This is done at the State-county-SCC-pollutant level of detail. According to EPA 

documentation, the CAIR baseline emissions include the impacts of the Tier 4 (T4) non-road 

diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV 

and locomotive emissions. 

For more information on the development of non-road source inventories, see Appendix D. 

1.5 Conclusion 

In conclusion of this discussion on source sector controls, Figures 1.1-1.4 depict pollutant totals 

for NH3, PM2.5, NOx, and SO2 for the various sectors by state for 2002, 2009, and 2018 Base G2 

modeling. 

 
0

20

40

60

80

100

120

140

160

180

200

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NH3 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW

Figure 1-1. Annual NH3 emissions – Base G2. 

0

20

40

60

80

100

120

140

160

180

200

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual PM-2.5 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 

2018 OTW

Figure 1-2. Annual PM2.5 emissions – Base G2. 

 
0

100

200

300

400

500

600

700

800

900

1,000

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU 2002 Typical

2009 OTW

2018 OTW

Figure 1-3. Annual NOx emissions – Base G2. 

0

100

200

300

400

500

600

700

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW

Figure 1-4. Annual SO2 emissions – Base G2. 

 
2.0 UNIFORM RATE OF PROGRESS 

The linear rate of improvement sufficient to attain natural conditions by 2064 is referred to as the 

“uniform rate of progress” or “glide path”. The baseline represents the starting point from which 

reasonable progress will be measured. There are two baseline values for each Class I area. 

Using 2000 - 2004 Interagency Monitoring of Protected Visual Environments (IMPROVE) 

monitoring data, the deciview (dv) values for the 20% best days in each year are averaged 

together, producing a single average dv value for the best days. Similarly, the dv values for the 

20% worst days in each year are averaged together, producing a single average dv value for the 

worst days. Extinction from individual PM components is calculated from the IMPROVE 

equation (EPA, 2003; Hand and Malm, 2006). EPA defined target natural conditions in 2064 for 

each Class I area (EPA, 2003). For each VISTAS Class I area, a baseline visibility using 2000-

2004 IMPROVE data and uniform rate of progress was established, using EPA default 

assumptions for calculating visibility and natural background. Most recently, the scientific 

community has reviewed the assumptions used to calculate current and natural background 

visibility and has agreed to revised methods (Hand and Malm, 2006, Pitchford, 2006). VISTAS 

intends to present both the original and revised methods to calculate visibility and visibility 

improvement. Figure 2.1 illustrates the average 20% worst visibility days in the 2000-2004 

baseline period for the Sipsey Wilderness area, the target natural condition in 2064 for the 20% 

worst days, and the incremental dv changes assuming a uniform rate of progress between current 

and natural conditions in 2064, using the original method for calculating visibility. 

Progress Assessment Base G2 inventory, new 

IMPROVE Algorithm

Sipsey - Worst 20% Days

29.03

27.52

24.80

21.78

18.76

15.74

12.72

10.90

26.43

23.53

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction

Figure 2-1. CMAQ 2018 Base G2 results compared to Uniform Rate of Progress at the 

Sipsey Wilderness. 

 
3.0 GEORGIA INSTITUTE OF TECHNOLOGY (GA Tech) 

SENSITIVITIES 

GA Tech performed emission sensitivities to examine the impact of emission reductions on 

regional haze, annual PM2.5, and 8-hour ozone concentrations using CMAQv4.4_SOAmods on 

the VISTAS 12 km modeling domain, using the 2009 OTW (On the Way) Base D emissions. 

Once the key pollutants contributing to visibility impairment at each Class I area were identified, 

the sources or source categories responsible for emitting these pollutants or pollutant precursors 

were determined. Emissions sensitivity analyses were conducted using CMAQ with 2009 Base 

D inventory and considering 30% reductions from major pollutants and source categories. The 

sensitivity runs were initially designed to consider pollutant contributions in 2009 to PM2.5 in 

urban areas; results were also considered for Class I areas even though the full benefit of controls 

anticipated by 2018 are not included in these sensitivity analyses. Results are qualitatively 

similar to previous sensitivity results using an earlier (Base A) 2018 inventory. While the 2009 

sensitivity analyses cannot be used to judge absolute contributions from each state or source 

sector, the results do indicate relative level of response among pollutants, sectors, and geographic 

areas. 

3.1 Evaluation for the Sipsey Wilderness Area, AL 

Figure 3-1 shows the results of emissions sensitivity run for Sipsey for summer (since summer is 

when 20% worst days occur). CMAQ was run using 30% reductions from the 2009 Base D 

inventory assumptions for implementing existing state and federal regulations (Section 1.0) for 

major source categories of SO2, NOx, VOC, and PM. The results identify geographic origins for 

visibility impairing pollutants, and serve as a good starting point when considering potential air 

quality benefits from additional controls for specific source sectors in VISTAS states or 

neighboring Regional Planning Organizations (RPOs). The greatest benefits at Sipsey in 2009 

are projected to come from further reducing SO2 from electric generating utilities (EGUs). 

Additional, smaller benefits are projected from additional SO2 emission reductions from nonutility, industrial point sources. Reductions of nitrogen oxide emissions from point sources 

(EGU and non-EGU) or ground level sources (on road vehicles, off road engines, and area 

sources) and reductions of primary carbon from point or ground level sources are projected to be 

significantly less beneficial than reductions in SO2 emissions. Reductions in anthropogenic 

VOC emissions show no response in visibility, while a 30% reduction in biogenic VOC 

emissions result in a measurable improvement. However, controlling the VOCs from biogenics 

is not possible or appropriate. For this sensitivity run, further reducing SO2 emissions from 

electricity generating utilities in Alabama, Georgia and Tennessee would have the greatest 

benefit for SIPS1; reductions from electric generating utilities in other VISTAS states would 

have additional but smaller benefits at SIPS1. 

 
Sipsey, AL (Summer)

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

Δ

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 3-1. Sources of various visibility-reducing pollutants – SIPS1 summer using 2009 

Base D emissions. 

Similar sensitivity analyses were performed for wintertime using the 2009 Base D inventory 

(Figure 3-2). These results suggest that in wintertime, reductions in ammonia emissions could be 

more beneficial for reducing ammonium nitrate contributions to visibility impairment than 

further reducing nitrogen oxide emissions from either ground or point sources. Reducing 

ammonia emissions could also be more effective in improving visibility in wintertime than 

further reductions in SO2 emissions. The largest sources of ammonia emissions in this region are 

agricultural. 

 
Sipsey, AL (Winter)

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

Δ

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 3-2. Sources of various visibility-reducing pollutants – SIPS1 winter using 2009 

Base D emissions. 

Several states contribute to modeled reductions in SO4 at SIPS1 on the 20% worst days modeled 

in the June episode in response to further reductions in 2009 SO2 emissions from EGUs (Figure 

3-3). For this sensitivity run, beyond controlling Alabama EGUs, further reducing SO2 

emissions from electricity generating utilities in Tennessee, Georgia, and West Virginia would 

have the greatest benefit for SIPS1; reductions from electric generating utilities in other VISTAS 

States would have much smaller benefits at SIPS1. Slightly greater than one fourth of the benefit 

at SIPS1 from further SO2 emission reductions would come from outside VISTAS states. 

 
AL

FL

GA

KY

M

NC

SC

TN

VA

WV

VISTAS

CENRAP

MANE-VU

MRPO

Boundary

Utility Contributions, by State and Region, to SO4 at Sipsey, AL

Using 2009 Emissions and CMAQ model run for June 2002

Boundary Conditions 

MRPO 

MANECE

V

TN S

N

GA

F

13%

13% 

1

2

WV 10% 

2

13%

4

1

10%

3

3 M

K

23%

2

AL

Figure 3-3. Utility Contributions, by State and Region to SO4 at SIPS1 for 20% worst days 

using 2009 Base D emissions. 

3.2 Summary 

Emissions sensitivity analyses show the relative benefits of reducing different pollutants from 

different source categories and geographic areas. These 2009 sensitivity analyses indicate that 

further reductions in SO2 emissions from EGUs would be most beneficial for visibility at 

VISTAS Class I areas, followed by SO2 reductions from industrial point sources. Controlling 

NOx or primary carbon emissions from either point or ground level sources would have little 

benefit to visibility. Controlling anthropogenic sources of VOC would not be effective in 

improving visibility in winter. In wintertime, controlling ammonia emissions would be more 

effective in reducing ammonium nitrate than controlling nitrogen oxide emissions. 

4.0 REASONABLE PROGRESS EVALUATION 

4.1 Area of Influence (AoI) Analyses

The objective of the VISTAS AoI analyses is to identify the geographic source regions that are 

contributing to visibility impairment at the Class I areas on the 20% worst visibility days. This 

 
information will be used by the State as part of the evaluation and demonstration of reasonable 

progress toward visibility improvement in Class I areas. 

VISTAS’ contribution assessment based on IMPROVE monitoring data (Brewer and Adlhoch, 

2005) demonstrated that ammonium sulfate is the major contributor to PM2.5 mass and visibility 

impairment at Class I areas in the VISTAS and neighboring states. As illustrated in Figure 4-1, 

on the 20% worst visibility days in 2000-2004, ammonium sulfate accounted for greater than 

70% of the calculated light extinction at Class I areas in the Southern Appalachians and greater 

than 60% of the calculated light extinction for coastal sites in the VISTAS states (excepting 

Everglades). In contrast, ammonium nitrate contributed less than 5% of the calculated light 

extinction at VISTAS Class I areas on the 20% worst visibility days. (Nitrate has a somewhat 

larger contribution on 20% worst days at Class I areas in neighboring states to the VISTAS 

region.) Particulate organic matter (organic carbon) accounted for 10-20% of light extinction on 

20% worst visibility days (except Everglades where organic carbon accounted for 40%). 

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

CADI1

BRIG1

BRET1

MING1

HEGL1UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm -1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

CADI1

BRIG1

BRET1

MING1

HEGL1UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm -1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 4-1. Average Extinction for 20% Worst Visibility Days in 2000-2004 using New 

IMPROVE Equation (data from VIEWS). 

VISTAS emissions sensitivity analyses using the CMAQ regional air quality model project that 

reductions in SO2 emissions from EGU and non-EGU industrial point sources will result in the 

greatest improvements in visibility at VISTAS Class I areas. EGU and non-EGU industrial point 

sources comprise 95+% of the SO2 emissions inventory in the VISTAS states. The emissions 

sensitivity analyses also indicate that improvements in visibility from reductions in NOx or 

primary carbon emissions from ground level sources or point sources would be small. Based on 

these analyses, VISTAS states chose to focus their reasonable progress evaluation for the first 

 
Regional Haze SIP on potential controls of SO2 emissions from EGU and non-EGU point 

sources. To select the specific point sources that would be considered for each Class I area, 

states first identified the geographic areas that most likely influence visibility in each Class I area 

and then identified the major SO2 point sources in that geographic area. 

4.2 Source Type Analyses 

The following analyses are illustrative of an initial approach from September 2005 to evaluate 

potential control strategies. These analyses rely on the 200 km area surrounding the Class I area 

and use the Base F4 model run. 

VISTAS emissions inventory for the simplest AoI, the 200 km concentric circle, indicated for 

SIPS1 in 2018 that fuel combustion from electric utilities and industrial processes produces the 

majority of the remaining SO2 emissions (Table 4-1), with 85% of 2018 SO2 total coming from 

fuel combustion. 

Table 4-1. Source types 2018 Base G2 modeling SIPS1 – Percentage. 

T

F

F

F

C

M

P

O

S

S

W

H

O

M

ier VOC NOX CO SO2 PM-10 PM-2.5 NH3

uel Comb. Elec. Util. 1% 24% 1% 58% 8% 16% 1%

uel Comb. Industrial 1% 18% 2% 21% 3% 5% 0%

uel Comb. Other 5% 6% 2% 6% 3% 7% 0%

hemical & Allied Product Mfg 1% 1% 1% 2% 1% 1% 0%

etals Processing 1% 1% 3% 5% 3% 6% 0%

etroleum & Related Industries 0% 0% 0% 1% 0% 0% 0%

ther Industrial Processes 8% 6% 1% 5% 9% 10% 1%

olvent Utilization 43% 0% 0% 0% 0% 1% 0%

torage & Transport 6% 0% 0% 0% 1% 1% 0%

aste Disposal & Recycling 3% 1% 4% 0% 6% 14% 0%

ighway Vehicles 17% 22% 44% 0% 1% 2% 9%

ff-highway 11% 19% 32% 1% 2% 4% 0%

iscellaneous 3% 1% 9% 0% 64% 33% 87%

VISTAS Total 100% 100% 100% 100% 100% 100% 100%

4.3 Back Trajectory Analyses 

ADEM defined AoIs to identify source regions for which additional controls might be 

considered and that are likely to have the greatest impact on each Class I area. Initial focus on 

AoIs is on SO2 emissions because SO4 contributes greater than 60% of the calculated light 

extinction on the haziest days. In fact, in the previous section, Figure 4-1 shows that for the 

mountain areas (SIPS1), SO4 contributes roughly 80% to the calculated light extinction on the 

haziest days. To better understand the sources that should be considered in a four factor analysis 

for reasonable progress, VISTAS contracted ENVIRON to partner with VISTAS’s Data Analysis 

 
contractor, Air Resource Specialists (ARS), to provide SO2 AoIs for each VISTAS and six 

neighboring Class I areas. ARS generated meteorological back trajectories for IMPROVE sites 

in VISTAS and neighboring states. Back trajectory analyses use interpolated measured or 

modeled meteorological fields to estimate the most likely central path of air masses that arrive at 

a receptor at a given time. The method essentially follows a parcel of air backward in hourly 

steps for a specified length of time. Back trajectories account for the impact of wind direction 

and wind speed on delivery of emissions to the receptor, but do not account for chemical 

transformation and dispersion of emissions. 

Trajectories were generated using the Hybrid-Single Particle Lagrangian Integrated Trajectory 

(HYSPLIT) model developed by the National Oceanic and Atmospheric Administration’s 

(NOAA) Air Resources Laboratory (ARL). HYSPLIT uses archived 3-dimensional 

meteorological fields generated from observations and short-term forecasts. HYSPLIT can be 

run to generate forward or backward trajectories using several available meteorological data 

archives. 

The data archives used in this analysis were the National Weather Service's National Centers for 

Environmental Prediction Eta Data Assimilation System (EDAS). The EDAS fields are archived 

by the ARL across the continental U.S., including a buffer zone, at a horizontal resolution of 80 

km before 2004, and at a horizontal resolution of 40 km starting in 2004. Detailed information 

regarding the trajectory model and these data sets can be found on NOAA’s Web site 

(http://www.arl.noaa.gov/ready/hysplit4.html). 

The major model parameters selected for this analysis include those listed in Table 4-2. 

Table 4-2. Back Trajectory Model Parameters Selected for VISTAS AoI Analysis 

Model Parameter Value 

Trajectory duration 72 hours backward in time 

Top of model domain 14,000 meters 

Vertical motion option Used model data 

Meteorological Field EDAS 

End Times 0600, 1200, 1800 and 2400 EST 

End Heights 100 and 500 m 

The choice of these parameters affects the trajectories generated and the final attribution 

analyses. In particular, trajectories tend to become increasingly uncertain the further back in 

time they are used. Vertical motion in the model is sometimes best represented by following 

actual vertical motion measurements (represented by model data), surfaces of constant entropy, 

or surfaces of constant pressure, depending on the meteorological conditions at a given location 

and time. The impact of receptor height (or end height) on an individual trajectory is also 

important. Low-ending trajectories represent air parcels nearer to ground level and high-ending 

trajectories may represent more accurate boundary layer flow above the local terrain. 

For the years 2000–2004, back trajectories were computed for the following IMPROVE 

sampling sites in and around the VISTAS region: 

 
1. Breton, LA (BRET1) 

2. Brigantine NWR, NJ (BRIG1) 

3. Cadiz, KY (CADI1) 

4. Caney Creek, AR (CACR1) 

5. Cape Romain NWR, SC (ROMA1) 

6. Chassahowitzka NWR, FL (CHAS1) 

7. Cohutta, GA (COHU1) 

8. Dolly Sods Wilderness, WV (DOSO1) 

9. Everglades NP, FL (EVER1) 

10. Great Smoky Mountains NP, TN (GRSM1) 

11. Hercules-Glades, MO (HEGL1) 

12. James River Face Wilderness, VA (JARI1) 

13. Linville Gorge, NC (LIGO1) 

14. Mammoth Cave NP, KY (MACA1) 

15. Mingo, MO (MING1) 

16. Okefenokee NWR, GA (OKEF1) 

17. Shenandoah NP, VA (SHEN1) 

18. Shining Rock Wilderness, NC (SHRO1) 

19. Sipsey Wilderness, AL (SIPS1) 

20. St. Marks, FL (SAMA1) 

21. Swanquarter, NC (SWAN1) 

22. Upper Buffalo Wilderness, AR (UPBU1) 

Figure 4-2 shows the 72-hour back trajectory analysis performed for the Sipsey Wilderness Area. 

Figure 4-2. Example 72-hour back trajectories for 20% worst visibility days in 2002 for the 

Sipsey Wilderness Area. 

 
Based on the five years of individual back trajectories, ARS generated extinction-weighted 

residence time data for each IMPROVE site. Each hourly trajectory point was tagged with its 

associated sample (or end) date. Back trajectories with end dates corresponding to the 20% 

worst visibility days were weighted with calculated extinction values and summed into 1-degree 

horizontal grid cells of latitude and longitude. 

Extinction data is based on the IMPROVE Regional Haze Rule (RHR) dataset, as available from 

the VIEWS website (http://vista.cira.colostate.edu/views/Web/IMPROVE/SummaryData.aspx) 

from November 2005 and is calculated based on the original IMPROVE algorithm. For sites 

with less than three complete years of data, ARS developed and applied a data substitution 

protocol to fill missing data. Organic carbon and elemental carbon values were filled based on 

correlations to hydrogen and sulfate values for the same site. Other components were filled 

based on data from nearby sites. 

Trajectory data were weighted by total extinction, and by extinction components including 

ammonium sulfate (AmmSO4), ammonium nitrate (AmmNO3), particulate organic material 

(POM), Light Absorbing Carbon (LAC), Soil, and Coarse Mass (CM). Weighing trajectories for 

the 20% worst days by sulfate extinction gave greater importance to days influenced by SO2

emissions and lesser importance to days influenced by organic carbon (POM) emissions. This 

allowed a geographic AoI to be identified based on sulfate contributions and not skewed by 

contributions from fire. 

These data files were provided to ENVIRON. ENVIRON was charged with developing 

residence time plots to define the geographic area with highest probability of influencing the 

Class I areas on the 20% worst days dominated by sulfate. Residence time over an area is 

indicative of general flow patterns, but since it does not account for emissions and removal 

processes, it does not necessarily imply specific areas contributed significantly to haze 

compounds at a specific site. 

4.4 Area of Influence (AoI) Data and Displays 

The primary objective of the AoI displays and data sets are to assist the State in focusing its 

reasonable progress analysis on those geographic regions and source categories which most 

impact a particular Class I Area. The sources of data used in these analyses include backtrajectory residence time data, provided by ARS as described above, and the VISTAS 2002 and 

2018 36-km gridded emissions data (Base G, Aug 2006 inventory version). 

Extinction weighted back trajectory residence time plots were provided by ARS for all Class I 

areas in the VISTAS region as well as for the surrounding neighboring states. These trajectories 

were processed on an un-projected (i.e., geodetic lat/long 1 degree by 1 degree) grid and 

transferred to ENVIRON for further GIS processing and analysis. Back trajectories were run for 

100-meter and 500-meter start heights. Because the back-trajectories were to be combined with 

gridded emissions data, the first step in the analysis and GIS processing involved re-projecting 

these data to the Inter-RPO Unified Lambert Conformal Projection domain. Once the data were 

re-projected, the data were mapped to the 36-km grid cells in the RPO projection using an areaweighted mapping routine. The re-projected extinction weighted back-trajectory residence times 

 
were then plotted on the VISTAS 12-km modeling domain. As sulfate is the primary visibility 

impairing component of the total extinction in the Southeast, the SO4 weighted residence time 

trajectories were chosen as the basic data set for display. For clarity, these data are scaled by the 

maximum value of the total extinction-weighted residence time within the modeling domain. 

The 100-km and 200-km distances from the Class I area were labeled. 

Using the trajectories with the 100-m start height, the State has defined the SO2 AoI as the area 

with grid cells showing 10% (area shaded in yellow in following plots) or greater residence time 

(the frequency that winds pass over that area on the way to the Class I area on the 20% worst 

days dominated by sulfate) for the period 2000-2004. Residence time over an area is indicative 

of general flow patterns, but since it does not account for emissions and removal processes, it 

does not necessarily imply specific areas contributed significantly to haze compounds at a 

receptor site. Figure 4-3 shows the extinction weighted residence time plots for SIPS1 for 100-m 

and 500-m trajectory start heights. 

 
Figure 4-3. Sipsey Wilderness SO4 extinction-weighted residence time plots for the period 

2000-2004. 

 

As an aid to the analysis, all regions with scaled residence time values greater than 5% and 

greater than 10% were noted on the display. Finally, county boundaries were overlaid to identify 

those counties and 36-km modeling grid cells for which the extinction-weighted residence time 

back-trajectories exceeded 5% and 10%. These data were then exported as comma-delimited 

ASCII data files for further analyses. These residence time displays are used primarily to 

determine the regions (counties and/or grid cells) impacting each Class I area. The next step in 

the analysis is to determine the potential impact from emission sources within the regions 

identified from the extinction-weighted back-trajectory residence time displays and analyses. 

Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory 

analyses have indicated that SO4 is the largest contributor to haze on the 20% worst visibility 

days and that EGUs and industrial point sources are the largest contributors to SO4 levels at the 

Class I areas. These two source categories make up 95% of the VISTAS SO2 inventory. 

Therefore these two source categories were identified as the highest priority for evaluation of 

reasonable progress in 2018 at the Class I areas. 

 
The potential impacts of SO2 point source emissions for each Class I area are determined by 

combining gridded emissions data and weighted back-trajectory residence times for the 36-km 

grid cells. The analysis was carried out with both the 2002 and 2018 base year emission 

inventories. Figures 4-4 and 4-5 display the gridded point source SO2 emissions from the 

VISTAS modeling databases, for 2002 and 2018, respectively. These data were processed by 

summing all vertical layers for each grid column and then summing across all days to obtain 

annual emission totals for each grid cell. 

Figure 4-4. Annual point source SO2 emissions for the VISTAS region for in tons/year. 

(2002 Base G) 

 
Figure 4-5. Annual point source SO2 emissions for the VISTAS region for in tons/year. 

(2018 Base G) 

As a way of incorporating the effects of transport, deposition, and chemical transformation of 

point source emissions along the path of the trajectories, these data were weighted by 1/d, where 

d was calculated as the distance between grid cell centers, in kilometers. For the grid cell 

containing the Class I area monitor, a weighting of 1/9 was applied. The distance-weighted point 

source SO2 emissions are then combined with the gridded extinction-weighted back-trajectory 

residence times at a spatial resolution of 36-km. 

The final step in the development of the displays and datasets involved the combination of the 

residence times and gridded emission data. The distance weighted (1/d) gridded point source 

SO2 emissions are multiplied by the total extinction-weighted back-trajectory residence times 

(SO2 * Bext-weighted RT * (1/d)) on a grid cell by grid cell basis. These results are then 

normalized by the domain-wide total and displayed as a percentage. The analysis is carried out 

for both the 2002 and 2018 base year inventories. Figure 4-6 displays the result of this final 

analysis step for the Sipsey Wilderness area. Note that the outlined regions (in red and light 

orange) represent the extent of the >10% and >5% sulfate extinction-weighted residence times, 

determined from the first step in the analysis (see Figure 4-3). As with the residence time 

analysis, the results of the combined distance-weighted SO2 emissions and extinction-weighted 

residence times are overlayed with county boundaries and exported to comma-delimited ASCII 

data files for further analyses of emissions for specific sources. 

 
2002 vs 2018 SO2 Emissions weighted by Residence 

Time 

Sipsey, AL 

Max Value = 37%

2002 SO2 emissions 2018 SO2 emissions 

Green circles indicate 100-km and 200-km radii from Class I area. 

Red line perimeter indicate Area of Influence with Residence Time > 10%. 

Orange line perimeter indicate Area of Influence with Residence Time > 5%. 

Figure 4-6. Sipsey Wilderness 2002 SO2 Emissions * SO4 extinction-weighted residence 

time plots.

The following plot (Figures 4-7) shows the 2018 SO2 Emissions multiplied by the SO4

extinction-weighted residence time plots for the Sipsey Wilderness areas. These were produced 

the same way as the previous plots, only using 2018 emissions instead of 2002 emissions. 

To understand how emissions have changed by 2018, Figure 4-7 compares 2002 and 2018 SO2

multiplied by residence time. 

 
Figure 4-7. Sipsey Wilderness 2002 vs. 2018 SO2 emissions multiplied by residence time. 

2002 vs 2018 SO2 Emissions weighted by Residence 

Time 

Sipsey, AL (100m start height) 2002 SO2 emissions 2018 SO2 emissions 

Green circles indicate 100-km and 200-km radii from Class I area. 

Red line perimeter indicate Area of Influence with Residence Time > 10%. 

Orange line perimeter indicate Area of Influence with Residence Time > 5%. 

VISTAS states evaluated these plots of residence time weighted by sulfate extinction plots of 

gridded SO2 emissions and defined the SO2 AoIs as those areas with residence time greater than 

10%, based on trajectories with start height of 100m and 4 start times per day. 

Extinction-weighted residence plots for Class I areas indicate that the areas of probable influence 

for sulfate contribution to visibility impairment are similar to those for nitrate contribution even 

though the visibility impact of nitrate is an order of magnitude smaller than that of sulfate. From 

these plots we can initially conclude that it is appropriate to focus on sources that contribute to 

sulfate concentrations and that sources near a Class I area are more likely to contribute to 

visibility impairment than more distant sources. Gridded SO2 emissions for the sulfate 

extinction-weighted residence time plots indicate that large emissions sources at great distance 

from the Class I area can contribute to visibility impairment on some 20% worst days. However, 

it is expected that these same sources will be evaluated by Class I areas that are closer and thus 

are impacted greater.

4.5 Importance of Pollutants Other Than Sulfate 

For completion, the following is a brief discussion of the importance of other PM components 

and contributing source categories. If NOx controls are considered, slightly greater than 50% of 

 
NOx is from point sources (see Tables 4.1), approximately 25% is from highway vehicles, and 

roughly 20% is from nonroad engines. Elevated organic carbon (OC) and elemental carbon (EC) 

are indicators of fire. Some states may need to consider emissions from residential wood 

burning, forest fires (wild and prescribed), land clearing, and agricultural burning. 

Nitrate (NH4NO3) levels in winter can be significant and are dependent on availability of NH3; 

87% of NH3 is from area sources (e.g. agriculture). In Alabama, the major source of ammonia is 

agriculture and livestock. However, given that sulfate contributes greater than 70% at SIPS1 on 

the 20% worst visibility days, ADEM believes it is appropriate to focus on SO2 reductions in this 

first Regional Haze SIP. 

4.6 Summary of Emission Inventories Used in Reasonable Further Progress (RFP) Analysis 

A necessary component of the analysis is a thorough review of the emission inventories that are 

used in the modeling of the future year base case. These inventories can shed light on the 

residual emissions from sources or source categories defined to be within areas of transport or 

impact of a Class I area. The most current (Base G Fall 2006) VISTAS future year (2018) base 

case and 2002 base year emissions was used to conduct this analysis. For purposes of listing 

sources within the AoI, data were provided for all sources with emissions over distance (Q/d) 

greater than 5 and maximum residence time (RTmax) greater than 5. States independently 

defined the criteria for selecting which sources from this list would be considered for reasonable 

control measures. 

The NIF formatted and SMOKE-ready modeling files for both 2002 and 2018 base year and base 

cases were obtained from VISTAS emissions development and modeling contractors and 

converted to annual emissions and summed for the geography and domain of interest. 

Tables 4-3 and 4-4 present the State breakdown of these emissions for the entire VISTAS 

domain. Because the SMOKE-ready files were used in this analysis, the particulate matter 

transport factor (0.90 times inventory values) is included in the PM emission summaries. This 

factor is applied to account for the removal of a substantial portion of fugitive dust emissions 

near a source by surrounding vegetation and structures when such emissions are used in regional 

scale modeling analyses. 

 
Table 4-3. VISTAS 2002 Base Year Annual Emissions Summary. 

State VOC NOx CO SO2 PM-10 PM-2.5 NH3

AL 445,497 459,880 2,534,778 584,665 232,229 105,341 67,970

FL 1,291,562 930,086 7,710,376 589,069 408,902 205,450 61,643

GA 765,063 623,645 5,013,024 653,362 408,736 195,654 100,134

KY 286,752 466,403 1,730,622 580,341 148,290 50,981 57,220

MS 302,374 239,547 1,203,899 103,679 180,816 43,533 63,765

NC 655,950 616,583 4,097,444 546,429 179,242 84,513 172,976

SC 382,836 323,976 2,064,423 286,781 165,699 78,356 35,400

TN 473,244 511,151 2,601,059 442,589 165,095 75,458 42,738

VA 448,205 461,628 3,034,414 416,190 109,848 47,004 55,057

WV 135,819 348,576 802,262 569,373 48,423 27,807 12,341

VISTAS 5,187,303 4,981,474 30,792,301 4,772,477 2,047,281 914,096 669,243

BaseG Annual Emissions - 2002 Typical (Tons)

Table 4-4. 2018 Base Case Annual Emissions Summary. 

State VOC NOx CO SO2 PM-10 PM-2.5 NH3

AL 327,850 268,067 1,994,607 305,938 258,179 114,681 84,513

FL 990,629 448,443 6,099,425 260,963 483,328 226,529 73,455

GA 585,528 357,169 3,820,095 358,570 472,376 211,406 124,237

KY 236,983 277,271 1,356,496 320,525 166,918 58,559 63,959

MS 247,932 173,893 850,056 62,627 205,761 54,912 76,040

NC 421,965 275,907 2,702,315 164,067 208,015 100,253 196,577

SC 300,291 193,247 1,527,341 163,491 189,358 88,891 42,883

TN 374,093 247,827 1,692,551 228,035 187,066 84,117 46,984

VA 311,835 276,525 2,001,939 294,209 131,708 57,993 64,276

WV 107,675 150,777 576,198 190,683 54,736 31,678 14,400

VISTAS 3,904,780 2,669,125 22,621,023 2,349,107 2,357,445 1,029,017 787,325

BaseG Annual Emissions - 2018 Base Case (Tons)

The review was conducted in a top down fashion starting with an analysis of the major source 

categories in the domains of interest to determine which major categories had the highest 

residual contribution to the area. Once the highest source types were identified, subcategories 

within those source types were reviewed. Again, a ranking of the highest residual sub source 

types was performed and additional analyses on these categories were conducted. Using the 

extinction weighted analysis, the emission reviews and summaries like that presented in Figure 

4-8, VISTAS made the decision to further review only potential point sources for control. 

In addition to reviewing the residual emission categories in the future year base, it was important 

to identify reductions that had already occurred within each category or at specific units. This 

allowed VISTAS States to determine if certain source categories that had yet to be controlled 

under the future year base case had the potential for reduction. 

 
Finally, once each subcategory was identified, unit level tables of emission comparisons from 

2002 to 2018 were developed allowing VISTAS States to review existing emission reductions. 

These tables presented comparisons of 2002 and 2018 emission levels, for SO2 by source. 

Ultimately, the final decisions will include the application of BART subject source reductions in 

the future year base case. 

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

West Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

West Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Figure 4-8. VISTAS Base G2 SO2 Emissions Contribution by Major Source Sector. 

5.0 REASONABLE PROGRESS ASSESSMENT 

ADEM concluded that SO2 emissions from EGU and non-EGU point sources in geographic 

Areas of Influence (AoIs) are sources to consider for further controls. VISTAS developed source 

matrices for SO2 AoIs for each Class I area, using data delivered by ENVIRON for 2002 and 

2018 SO2 emissions multiplied by SO4 extinction weighted residence time plots. 

Spreadsheets were developed for each Class I area with: 

• Plant name 

• Point ID 

• Actual Tons of SO2 projected for 2018 

• Q (tons) 

• Current control efficiency, CE (%) 

• Stationary source distance to Class I area, d (km) 

• Analysis of emissions per distance from source, Q/d and Q/d2

• RTMax, the maximum percentage of time that winds pass over that area on the way to 

the Class I area on the 20% worst days 

 
The ranking refers to the source rank by Q/d when sources from all states are included.

In an analysis of emissions per distance from s source, Q/d2

 is more representative when d is less 

than 20 km because plumes are still dispersing in two dimensions. After about 100 km, plumes 

only disperse in one dimension. The distance calculation is based on a single stack at a unit 

(when more than one are represented in the inventory) and is calculated in distance in km to the 

IMPROVE monitor at each Class I area. The residence time for the county where the source is 

located was reviewed. It was generally agreed that states would focus on those sources where 

RTMax was equal to or greater than 10%. A second matrix for sources in the SO2 AoI was 

developed that combined the RTMax and Q/d metric. Using this metric, ADEM calculated the 

fractional contribution from all the emission units within the SO2 AoI for each Class I area and 

identified those units with a contribution of 1% or more to the total impairment of that Class I 

area. 

Next, ADEM elected to focus on those units that contributed at least 1% to sulfate visibility 

impairment at a given Class I area. This was based on several regulatory programs that use a 

higher threshold than 1% for evaluation thresholds. 

• The BART rule specified that a maximum impact of 0.5 dv is an acceptable threshold for 

establishing significance. This threshold is representative of a 5% change in visible 

perception. 

• The NOx SIP call established a significance level for 126 petitions (the level at which a 

state’s contribution to another state’s ozone was considered significant) at 4 parts per 

billion. This threshold is representative of approximately 3.75% of the 1 hour ozone 

standard of 125 parts per billion, which was the standard at the time. 

• The CAIR rule established a PM contribution threshold of 0.2 μg/m3 as significant. This 

threshold represents 1.3% of the Annual PM2.5 standard of 15 μg/m3. 

• The NAAQS assign significant impact levels for human health standards based on a 

sources’ contribution to air quality. These significance levels represent a percentage of 

the NAAQS. Those facilities that is able to demonstrate that a new or modified sources’ 

contribution is less than a particular significance level is relieved of further modeling. 

ADEM examined all the averaging periods for the criteria pollutants and determined that 

the 1 percent threshold contribution chosen for reasonable further progress was as 

stringent as any significant impact level, the most restrictive being NO2 at 1 μg/m3

 or 1%. 

(NO2 NAAQS 100 μg/m3) 

Finally, ADEM considered available resources to evaluate the sources in the each Class I area’s 

sulfate AoI. ADEM recognized that there was neither sufficient time nor resources available to 

evaluate all units within a given AoI. Therefore, a threshold needed to be established to 

determine which units would be evaluated. Table 5-1 shows that a 1% contribution threshold 

captures greater than 55% of the total point source SO2 contribution at the Sipsey Wilderness 

area, requiring an evaluation of 22 sources. At the neighboring areas, the 1% threshold 

represented 61 to 73% of the total contribution. ADEM believes the 1% threshold is appropriate, 

 
given the contribution to the total visibility impairment at each Class I area, and the limited 

resources available to conduct the unit-by-unit evaluation for reasonable progress.

Table 5-1. Numbers and percentage of 2018 Alabama SO2 emission units that contribute to 

Class I areas within 300 km. 

SIPS BRET GRSM COHU SAMA OKEF 

Total # Units Contributing > 

1% 

22 27 10 23 27 20 

Percentage of total contribution 56.7% 62.8% 61% 62.7% 66.5% 72.8% 

Alabama Units Contributing > 

1% 

20 6 0 2 3 0 

Percentage of total 

contribution- AL 

54.5% 12.1% 0.0% 3.4% 5.0% 0.0% 

The following five tables, 5-2 through 5-7, show the analysis for SIPS, BRET, GRSM, COHU, 

SAMA and OKEF for sources that met the above criteria. The full spreadsheets containing all 

VISTAS Class I area results can be found in Attachment H-1. 

Table 5-2. Sipsey Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Sources that 

are 1% or greater of Q/d*RTMax) 

SIPSEY g.t. 1% of Q/d*RTMax Q/d % of Q/d

StatePlant Name Pt ID 2002G 2018G CEDist(km) Q/d RTMax RTMax RTMax

AL AL POWER CO- GORGAS 004 8,150 9,854 0 78.80 125.05 74.85 9359.99 10.28 

AL AL POWER CO- GORGAS 005 9,443 8,091 0 78.80 102.67 74.85 7684.85 8.44 

AL SOLUTIA, INC 009 1,831 2,244 0 44.06 50.93 74.85 3812.11 4.19 

AL TVA COLBERT 014 31,769 4,598 90 64.99 70.75 46.90 3318.18 3.64 

AL SOLUTIA, INC 015 1,863 1,849 4 44.06 41.95 74.85 3139.96 3.45 

AL SOLUTIA, INC 013 1,686 1,673 4 44.06 37.97 74.85 2842.05 3.12 

AL SOLUTIA, INC 014 1,622 1,610 4 44.06 36.53 74.85 2734.27 3.00 

AL AL POWER CO-GORGAS 008 22,082 2,798 90 78.80 35.51 74.85 2657.92 2.92 

AL AL POWER CO-EC GASTON 006 52,378 7,542 90 147.15 51.25 45.10 2311.38 2.54 

AL INTERNATIONAL PAPER CO 006 1,059 1,238 0 43.78 28.27 74.85 2116.01 2.32 

AL CARGILL, INC 020 966 1,101 0 42.82 25.72 74.85 1925.14 2.11 

AL TVA - WIDOWS CREEK 008 9,181 10,185 90 157.42 64.70 29.13 1884.71 2.07 

AL TVA - WIDOWS CREEK 009 8,588 6,712 90 157.42 42.64 29.13 1242.10 1.36 

AL AL POWER CO MILLER 001 11,834 1,284 90 83.24 15.43 74.85 1154.94 1.27 

AL AL POWER CO MILLER 002 11,375 1,284 90 83.24 15.42 74.85 1154.19 1.27 

AL AL POWER CO MILLER 004 10,590 1,256 90 83.24 15.09 74.85 1129.49 1.24 

AL AL POWER CO MILLER 005 12,056 1,236 90 83.34 14.83 74.85 1110.03 1.22 

GA GA POWER CO YATES SG07 14,024 16,530 0 245.30 67.39 15.03 1012.87 1.11 

GA GA POWER CO YATES SG06 15,175 16,367 0 245.30 66.72 15.03 1002.80 1.10 

AL TVA - WIDOWS CREEK 005 4,122 4,839 0 157.42 30.74 29.13 895.46 0.98 

AL TVA - WIDOWS CREEK 004 4,667 4,828 0 157.42 30.67 29.13 893.42 0.98 

AL TVA - WIDOWS CREEK 002 4,031 4,821 0 157.42 30.63 29.13 892.25 0.98 

 
Table 5-3. Breton Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Sources that 

are 1% or greater of Q/d*RTMax) 

Breton g.t. 1% of Q/d*RTMax Pt Dist Q/d * % Q/d 

State Plant Name ID 2002G 2018G CE (km) Q/d RTMax RTMax RTMax 

MS 

MS POWER CO PLANT 

JACK WA 004 7,266 7,640 0 148.07 51.60 28.09 1449.44 5.22 

LA 

CONOCOPHILLIPS 

ALLIANCE 11 1,388 1,664 0 97.80 17.02 76.94 1309.52 4.72 

LA 

CII CARBON LLC 

CHALMETTE 81 2,235 2,792 0 117.99 23.66 55.27 1307.69 4.71 

LA 

CONOCOPHILLIPS 

ALLIANCE 10 1,386 1,662 0 97.80 16.99 76.94 1307.21 4.71 

FL GULF POWER CO- CRIST 6 10,889 12,421 0 250.15 49.65 18.70 928.46 3.35 

AL AL POWER CO - BARRY 004 7,801 9,329 0 239.94 38.88 22.80 886.46 3.19 

LA 

DUPONT CHEM. 

BURNSIDE 01 9,747 13,275 0 199.52 66.54 12.20 811.79 2.93 

LA CHALMETTE REFINERY 29 1,246 1,494 0 117.60 12.70 55.27 701.93 2.53 

LA CHALMETTE REFINERY 28 1,219 1,462 0 117.60 12.43 55.27 687.01 2.48 

AL AL POWER CO - BARRY 006 24,676 6,790 90 239.94 28.30 22.80 645.24 2.33 

AL 

ESCAMBIA OPERATING 

CO 014 15,420 14,695 0 279.40 52.59 11.97 629.50 2.27 

LA PCS NITROGEN GEISMAR 01 7,929 10,799 0 215.29 50.16 12.20 611.95 2.21 

LA 

MOTIVA ENTERPRISES 

CONVENT 16 7,193 9,459 0 197.24 47.96 12.20 585.11 2.11 

LA 

COLUMBIAN CHEM 

 NORTH BEND 81 6,595 11,825 0 226.92 52.11 10.76 560.70 2.02 

LA 

MURPHY OIL 

MERAUX REFINERY 28 831 1,093 0 115.38 9.47 55.27 523.41 1.89 

MS 

CHEVRON PRODUCTS 

PASCAGOULA REF 051 1,780 2,239 4 123.85 18.08 28.09 507.87 1.83 

AL AL POWER CO- BARRY 003 3,970 5,235 0 239.94 21.82 22.80 497.50 1.79 

AL AL POWER CO - BARRY 002 3,550 5,145 0 239.94 21.44 22.80 488.83 1.76 

FL GULF POWER CO- CRIST 7 21,546 4,648 90 250.15 18.58 18.70 347.45 1.25 

LA 

CHEVRON ORONITE 

OAK POINT 06 291 492 0 109.57 4.49 76.94 345.46 1.24 

LA 

LA GENERATING/BIG 

CAJUN 

2 PWR PLNT 01 19,851 17,918 0 275.00 65.15 5.27 343.34 1.24 

MS 

DUPONT DELISLE 

FACILITY 024 1,657 1,645 4 137.98 11.92 28.09 334.83 1.21 

LA 

LA GENERATING BIG 

CAJUN 

2 PWR PLNT 02 17,018 17,354 0 275.14 63.07 5.27 332.38 1.20 

MS 

DUPONT DELISLE 

FACILITY 025 1,639 1,627 4 137.98 11.79 28.09 331.18 1.19 

LA 

LA GENERATING BIG 

CAJUN 

2 PWR PLNT 03 15,136 16,691 0 275.28 60.63 5.27 319.52 1.15 

AL AL POWER CO - BARRY 005 10,185 3,267 90 239.94 13.62 22.80 310.54 1.12 

MS 

CHEVRON PRODUCTS 

CO PASCAGOULA REF 017 1,902 1,356 45 123.85 10.95 28.09 307.59 1.11 

 
Table 5-4. Great Smokies Q/d, Q/d^2, RTMax, and fractional contribution analysis. 

(Sources that are 1% or greater of Q/d*RTMax) 

Great Smokies g.t. 1% of total 

Q/dRTMax Dist Q/d 

% 

 Q/d 

State Plant Name Pt ID 2002G 2018G CE (km) Q/d RTMax RTMax RTMax 

TN TVA BULL RUN 001 36,729 8,657 90 47.31 182.97 84.37 15437.18 14.14 

TN 

ALUMINUM CO OF 

AMERICA-SOUTH 16 1,856 2,370 0 16.49 143.71 83.87 12052.96 11.04 

TN 

ALUMINUM CO OF 

AMERICA-SOUTH 17 1,817 2,320 0 16.49 140.69 83.87 11799.67 10.81 

TN 

A.E. STALEY MANUF 

CO 005 3,005 2,982 4 36.00 82.83 79.99 6625.57 6.07 

TN 

EASTMAN CHEMICAL 

CO 021520 16,855 16,729 4 160.39 104.30 41.30 4307.59 3.95 

TN APAC-TN/HARRISON 002 153 200 0 3.97 50.32 83.87 4220.34 3.87 

TN U.S. DOE Y-12 PLANT 002 2,354 2,336 4 48.58 48.09 84.37 4057.35 3.72 

TN 

BOWATER NEWS/DIR 

CALHOUN 015 5,232 5,871 4 82.82 70.89 57.01 4041.44 3.70 

TN 

ALUMINUM CO OF 

AMERICA - SOUTH 09 424 541 0 16.49 32.80 83.87 2750.94 2.52 

NC 

BLUE RIDGE PAPER 

 PRO-CANTON G-25 2,195 2,565 0 100.17 25.61 50.35 1289.46 1.18 

 
Table 5-5. Joyce Kilmer Q/d, Q/d^2, RTMax, and fractional contribution analysis. 

(Sources that are 1% or greater of Q/d*RTMax) 

Joyce Kilmer g.t. 1% of 

 total Q/dRTMax

State Plant Name Pt ID 2002G 2018G CE Dist 

(km) 

Q/d RTMax 

Q/d 

RTMax 

% Q/d 

RTMax BART 

Facility 

Number 

TN BOWATER 

NEWS&DIRECTORYCALHOUN 

015 5,232 5,871 4 71.46 82.16 65.67 5395.45 8.77 NO 471070012 

TN TVA BULL RUN FOSSIL 

PLANT 

001 36,729 8,657 90 73.92 117.12 44.66 5230.58 8.50 YES 470010009 

TN A.E. STALEY 

MANUFACTURING CO 

005 3,005 2,982 4 50.89 58.59 64.11 3756.20 6.11 NO 471050081 

TN ALUMINUM CO OF 

AMERICA - SOUTH 

16 1,856 2,370 0 45.21 52.42 64.11 3360.65 5.46 YES 470090008 

TN ALUMINUM CO OF 

AMERICA - SOUTH 

17 1,817 2,320 0 45.21 51.32 64.11 3290.13 5.35 YES 470090008 

TN INTERTRADE 

HOLDINGS, INC. 

001 1,837 2,530 4 55.89 45.26 65.67 2972.22 4.83 YES 471390004 

TN U.S. DEPT OF ENERGY, 

Y-12 PLANT 

002 2,354 2,336 4 72.75 32.12 44.66 1434.48 2.33 NO 470011020 

SC DUKE ENERGY:LEE 003 4,384 7,274 0 164.50 44.22 27.54 1217.82 1.98 NO 0200-0004 

GA GEORGIA POWER CO 

YATES 

SG07 14,024 16,530 0 229.18 72.13 16.05 1157.69 1.88 YES 0011 

GA GEORGIA POWER CO 

YATES 

SG06 15,175 16,367 0 229.18 71.42 16.05 1146.29 1.86 YES 0011 

TN EASTMAN CHEMICAL 

COMPANY 

021520 16,855 16,729 4 181.93 91.95 12.09 1111.68 1.81 YES 471630003 

GA GEORGIA POWER CO 

SCHERER 

SG03 18,149 27,735 0 258.20 107.42 8.94 960.33 1.56 YES 0008 

GA GEORGIA POWER CO 

SCHERER 

SG04 20,771 26,616 0 258.20 103.09 8.94 921.62 1.50 YES 0008 

GA GEORGIA POWER CO 

SCHERER 

SG01 25,286 26,264 0 258.20 101.72 8.94 909.38 1.48 YES 0008 

GA GEORGIA POWER CO 

SCHERER 

SG02 24,966 26,075 0 258.20 100.99 8.94 902.85 1.47 YES 0008 

TN ALUMINUM CO OF 

AMERICA - SOUTH 

09 424 541 0 45.21 11.97 64.11 767.40 1.25 YES 470090008 

SC DUKE ENERGY:LEE 001 2,386 4,347 0 164.54 26.42 27.54 727.61 1.18 NO 0200-0004 

SC DUKE ENERGY:LEE 002 2,643 4,140 0 164.50 25.17 27.54 693.18 1.13 NO 0200-0004 

GA GEORGIA POWER CO SG04 42,634 6,294 90 163.76 38.44 17.63 677.70 1.10 YES 0011 

 
BOWEN 

NC BLUE RIDGE PAPER 

PRO-CANTON 

G-25 2,195 2,565 0 104.38 24.58 26.88 660.71 1.07 NO 3708700159 

GA GEORGIA POWER CO 

BOWEN 

SG03 42,900 6,111 90 163.76 37.32 17.63 657.95 1.07 YES 0011 

AL TVA - WIDOWS CREEK 008 9,181 10,185 90 170.64 59.69 10.74 641.07 1.04 YES 10210008 

GA INLAND 

PAPERBOARD/PKG -LIN 

F4 3,293 3,696 4 175.70 21.04 29.12 612.68 1.00 NO 0021 

*-The TVA Widow’s Creek Facility was identified as having a unit with an impact of greater than 1% of the total 

impact at the Joyce Kilmer Class I area. It is ADEM’s decision, however, that for the 2018 progress goal, the CAIR 

is equivalent to Reasonable Progress for Class I areas projected to meet or exceed their 2018 progress goal, as is the 

case for the Joyce Kilmer Class I area. 

Table 5-6. Cohutta Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Sources that 

are 1% or greater of Q/d*RTMax) 

Cohutta g.t. 1% of total 

 Q/dRTMAx Dist Q/d 

% of 

Q/d 

State Plant Name Pt ID 2002G 2018G CE (km) Q/d RTMax RTMax RTMax 

TN BOWATER CALHOUN 015 5,232 5,871 4 58.30 100.71 82.90 8348.86 8.59 

TN INTERTRADE HOLDINGS 001 1,837 2,530 4 32.47 77.92 82.90 6459.57 6.65 

GA GA POWER CO YATES SG07 14,024 16,530 0 149.41 110.63 39.91 4415.24 4.54 

GA GA POWER CO YATES SG06 15,175 16,367 0 149.41 109.54 39.91 4371.74 4.50 

GA GA POWER CO BOWEN SG04 42,634 6,294 90 78.34 80.35 44.32 3561.11 3.67 

GA GA POWER CO BOWEN SG03 42,900 6,111 90 78.34 78.01 44.32 3457.40 3.56 

GA INLAND PBRD/PKG -LIN F4 3,293 3,696 4 87.55 42.22 78.87 3329.89 3.43 

GA 

GA POWER CO 

HAMMOND SG04 18,089 3,455 90 88.75 38.93 78.87 3070.41 3.16 

GA GA POWER CO BOWEN SG02 35,266 4,865 90 78.34 62.10 44.32 2752.27 2.83 

GA GA POWER CO BOWEN SG01 33,050 4,831 90 78.34 61.67 44.32 2733.21 2.81 

AL TVA - WIDOWS CREEK 008 9,181 10,185 90 103.54 98.37 20.39 2005.76 2.06 

GA GA POWER CO YATES SG05 5,009 6,643 0 149.41 44.46 39.91 1774.40 1.83 

GA GA POWER CO YATES SG04 4,842 6,500 0 149.41 43.50 39.91 1736.09 1.79 

TN TVA BULL RUN 001 36,729 8,657 90 144.05 60.10 24.66 1482.07 1.53 

TN 

EI DUPONT 

 DENEMOURS 0002 1,286 1,173 0 67.08 17.48 83.31 1456.26 1.50 

GA 

GA POWER CO 

 SCHERER SG03 18,149 27,735 0 206.59 134.25 10.72 1439.16 1.48 

GA 

GA POWER CO 

 SCHERER SG04 20,771 26,616 0 206.59 128.84 10.72 1381.16 1.42 

GA 

GA POWER CO 

 SCHERER SG01 25,286 26,264 0 206.59 127.14 10.72 1362.94 1.40 

GA 

GA POWER CO 

 SCHERER SG02 24,966 26,075 0 206.59 126.22 10.72 1353.08 1.39 

AL TVA - WIDOWS CREEK 009 8,588 6,712 90 103.54 64.83 20.39 1321.88 1.36 

TN A.E. STALEY MANUFAC, 005 3,005 2,982 4 109.35 27.27 38.49 1049.62 1.08 

GA GA POWER CO YATES SG03 3,237 3,916 0 149.41 26.21 39.91 1046.04 1.08 

GA INLAND PBRD/PKG -LIN F2 1,023 1,148 4 87.55 13.11 78.87 1033.99 1.06 

 
Table 5-7. St. Marks. FL Q/d, Q/d^2, RTMax, and fractional contribution analysis. 

(Sources that are 1% or greater of Q/d*RTMax) 

SAMA g.t. 1% of Q/d*RTMax Q/d 

% of 

Q/d 

State Plant Name Pt ID 2002G 2018G CE Dist(km) Q/d RTMax RTMax RTMax 

FL 

PROGRESS ENERGY 

 CRYSTAL RI 2 20,728 15,241 0 189.58 80.39 17.27 1388.34 6.50 

FL 

PROGRESS ENERGY 

 CRYSTAL RI 1 18,998 13,537 0 189.58 71.40 17.27 1233.08 5.78 

FL BUCKEYE FL, LTD 4 736 860 4 61.48 13.99 75.55 1056.94 4.95 

FL BUCKEYE FL, LTD 7 621 726 0 61.48 11.80 75.55 891.49 4.18 

FL BUCKEYE FL, LTD 6 554 647 0 61.48 10.53 75.55 795.54 3.73 

FL BUCKEYE FL, LTD 2 449 524 0 61.48 8.53 75.55 644.44 3.02 

FL ST. MARKS POWDER, INC. 11 107 86 0 11.65 7.40 75.55 559.07 2.62 

FL 

PROGRESS ENERGY 

CRYSTAL RI 4 24,635 6,120 90 189.58 32.28 17.27 557.48 2.61 

FL BUCKEYE FL, LTD 11 385 450 0 61.48 7.32 75.55 553.03 2.59 

GA GA POWER CO MITCHELL SG03 4,173 4,930 0 150.49 32.76 16.16 529.40 2.48 

FL GULF POWER CO SCHOLZ 1 320 1,980 0 95.55 20.72 25.02 518.41 2.43 

FL GULF POWER CO SCHOLZ 2 465 1,980 0 95.55 20.72 25.02 518.41 2.43 

AL ESCAMBIA OPERATING CO 014 15,420 14,695 0 325.51 45.14 10.91 492.48 2.31 

FL GULF POWER CO - CRIST 6 10,889 12,421 0 298.97 41.55 11.11 461.62 2.16 

GA GA POWER CO SCHERER SG03 18,149 27,735 0 331.91 83.56 5.17 432.01 2.02 

FL STONE CONTAINER CORP 16 1,871 2,108 4 142.53 14.79 28.59 422.85 1.98 

GA GA POWER CO SCHERER SG04 20,771 26,616 0 331.91 80.19 5.17 414.58 1.94 

GA GA POWER CO SCHERER SG01 25,286 26,264 0 331.91 79.13 5.17 409.10 1.92 

GA GA POWER CO SCHERER SG02 24,966 26,075 0 331.91 78.56 5.17 406.16 1.90 

AL SANDERS LEAD CO 003 4,048 6,404 0 256.39 24.98 12.50 312.22 1.46 

AL SANDERS LEAD CO 008 3,948 5,488 0 256.39 21.40 12.50 267.56 1.25 

FL 

PROGRESS ENERGY 

CRYSTAL RI 3 26,436 3,634 90 189.58 19.17 17.27 331.07 1.55 

GA LONGLEAF ENERGY STAT BOIL1 0 3,227 0 154.52 20.88 12.89 269.14 1.26 

GA LONGLEAF ENERGY STAT BOIL2 0 3,227 0 154.52 20.88 12.89 269.14 1.26 

GA GA POWER CO YATES SG07 14,024 16,530 0 381.77 43.30 5.07 219.53 1.03 

GA 

GA PACIFIC CORP 

CEDAR SPRIN U501 2,257 2,533 4 149.70 16.92 12.89 218.10 1.02 

GA GA POWER CO YATES SG06 15,175 16,367 0 381.77 42.87 5.07 217.35 1.02 

 
 

Table 5-8. Okefenokee Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Sources 

that are 1% or greater of Q/d*RTMax) 

OKEFENOKEE g.t. 1% of total Q/dRTMax Dist Q/d 

% of 

Q/d 

State Plant Name Pt ID 2002G 2018G CE (km) Q/d RTMax RTMax RTMax 

FL SAINT JOHNS RIVER 17 10,185 7,420 90 65.12 113.95 65.70 7486.52 15.43 

FL SAINT JOHNS RIVER 16 11,076 5,882 90 65.12 90.33 65.70 5934.68 12.23 

FL JEFFERSON SMURFIT CORP 15 3,242 3,639 4 64.58 56.35 71.58 4033.53 8.32 

FL CEDAR BAY GENERATING CO GEN1 0 2,227 0 61.17 36.41 65.70 2392.14 4.93 

GA GA-PACIFIC BRUNSWICK F1 1,642 1,842 4 75.48 24.41 71.47 1744.58 3.60 

FL RAYONIER PRFORMCE FIBERS 6 1,075 1,256 0 63.34 19.83 71.58 1419.43 2.93 

FL SEMINOLE ELECTRIC COOP 1 10,912 6,779 95 121.83 55.64 22.94 1276.38 2.63 

FL SEMINOLE ELECTRIC COOP 2 12,775 6,508 95 121.83 53.42 22.94 1225.45 2.53 

GA 

RAYONIER PRFORMCE 

FIBERS-JESUP PB03 1,423 1,597 4 106.27 15.03 71.58 1075.85 2.22 

FL WHITE SPRINGS AGRI. CHEM 66 1,140 1,496 0 69.96 21.39 48.81 1044.05 2.15 

FL WHITE SPRINGS AGRI. CHEM 67 996 1,308 0 69.96 18.69 48.81 912.26 1.88 

FL IFF CHEMICAL HOLDINGS, INC. 3 624 733 0 56.66 12.94 65.70 850.16 1.75 

GA GA POWER CO SCHERER SG03 18,149 27,735 0 302.93 91.56 9.11 834.11 1.72 

GA GA POWER CO SCHERER SG04 20,771 26,616 0 302.93 87.86 9.11 800.40 1.65 

FL 

GA-PACIFIC CORP. 

PULP/PAPER MILL 15 3,703 4,329 0 125.55 34.48 22.94 790.97 1.63 

GA GA POWER CO SCHERER SG01 25,286 26,264 0 302.93 86.70 9.11 789.84 1.63 

GA GA POWER CO SCHERER SG02 24,966 26,075 0 302.93 86.07 9.11 784.10 1.62 

GA 

INTERNATIONAL PAPER 

 SAVANNAH PB13 7,643 8,578 4 179.54 47.78 15.53 742.02 1.53 

FL 

MILLENNIUM SPECIALTY 

CHEM. 6 505 590 0 60.46 9.76 65.70 641.23 1.32 

GA 

SAVANNAH ELECTRIC 

 MCINTOSH SG01 7,089 7,015 0 201.59 34.80 15.51 539.75 1.11 

Spreadsheets were developed for each Class I area source with Q/d*RTMax > 1%, indicating the 

plant name, industry description, emissions projections for 2018, current control efficiency 

(CE%), distance from Class I area, Q/d, Q/d2

, RT average, RT maximum, Q/d*RTMax, and the 

percentage a single source contributes to the total Q/d*RT for a Class I area. CE% is important 

because it gives a sense of which facilities are already controlled by what percent and which may 

be controlled further. 

Next, sources were evaluated based on expected controls (i.e. CAIR, BART) and sources were 

defined for which the Four Factor Analysis was to be conducted. The same few categories of 

point sources contribute to the majority of SO2 emissions, those being fuel combustion from 

electric utilities and fuel combustion from industrial sources, with little contribution from other 

sources. 
6.0 FOUR FACTOR ANALYSIS 

Section 169A(g)(1) of the Clean Air Act (CAA) and 40 CFR 51.308(d)(1)(i)(A) 

outline four statutory factors that have been identified as mandatory for purposes of establishing 

reasonable progress goals (RPGs) for any mandatory Class I area within a State: cost of 

compliance, time necessary for compliance, energy and non-air quality environmental impacts of 

compliance, and remaining useful life of any existing source subject to such requirements. These 

statutory factors would be specific to the sources being considered for additional controls. 

6.1 The Four Statutory Factors 

6.1-1 Cost of Compliance 

The “cost of compliance” is a factor used to determine whether compliance costs for sources are 

reasonable compared to the emission reduction and visibility improvement they will achieve. 

Note that visibility improvement is not only related to tons of pollutant removed, but also 

involves how the pollutant or chemical compound affects the extinction coefficient in each Class 

I area. For example, on a pound to pound comparison, sulfate particulate impairs visibility 

greater than coarse particulate. Costs should be determined for one-time capital costs, as well as, 

ongoing annual operation and maintenance. 

6.1-2 Time Necessary for Compliance 

The “time necessary for compliance” factor may be used to adjust the RPGs to reflect the degree 

of improvement achievable within the long-term strategy (LTS) period, as opposed to the 

improvement expected at full implementation of a control measure, if the time needed for full 

compliance exceeds the length of the LTS period. For instance, if implementation of a control 

measure could not be completed within the schedule outlined by the control strategy, the RPG 

should reflect what visibility improvement could be expected within the strategy period. 

For example, if construction labor availability constraints preclude the installation of controls at 

all sources of a particular category within the LTS period, the RPG should reflect the visibility 

improvement anticipated from installation of controls at the percentage of sources that could be 

controlled within the strategy period. (The SIP could still include control strategies that extend 

beyond the 2018 milestone; in the above example, the visibility improvement anticipated from 

installation of controls at the percentage of sources that could not be controlled within the first 

strategy period would have to be counted in a later SIP). 

6.1-3 Energy and Non-Air Quality Environmental Impacts of Compliance 

The “energy and non-air quality environmental impacts of compliance” factor is meant to 

consider whether the energy requirements of the control technology result in energy penalties or 

benefits. For example, controls on diesel engines may decrease the overall efficiency and require 

a significant increase in diesel fuel consumption. The State should also consider any significant 

or unusual non-air environmental impacts, such as a waste stream that may be generated by a 

particular control technology 

 Appendix H - 1 
6.1-4 Remaining Useful Life of the Source 

The statutory factor of the “remaining useful life of the source” is applicable only to those 

measures, which would require retrofitting of control devices (or possibly production changes) at 

existing sources. In such cases, this factor should be treated as one element of the overall cost 

analysis. For purposes of this analysis, the remaining useful life is the difference between the 

year of the reasonable progress analysis and the date the facility permanently stops operations. 

The remaining useful life of a source affects the annualized costs of retrofit controls. 

6.2 Evaluating Four Statutory Factors for Specific SO2 Emissions Sources in Each Area of 

Influence (AoI) 

The next step was to identify emission reductions that have already occurred within each source 

category and at specific units. Unit level tables of emission comparisons from 2002 to 2018 

were developed, allowing VISTAS States to review existing emission reductions. These tables 

assigned future year control technology from IPM forecasting and State modification for EGU 

and from control efficiency tables for non-EGU point sources. 

Once emission control profiles for specific units were defined, the next step is to determine what, 

if any, additional control measures would feasibly be available, and to assign costs to those 

control measures. 

For EGUs, the 2018 IPM file used by VISTAS for EGU sources was obtained and matched to 

the 2018 base case inventory of EGU sources. This step was conducted to ensure that 

incremental controls assigned to these source types did not duplicate existing base case 

assumptions. 

The Regional Haze Rule (RHR) requires that states consider the following factors and 

demonstrate how these factors were taken into consideration in selecting the RPG: 

• the costs of compliance 

• the time necessary for compliance 

• the energy and non-air quality environmental impacts of compliance, and 

• the remaining useful life of any potentially affected sources. 

6.2-1 Cost of Compliance 

Coal-fired electric utilities and coal-fired industrial boilers were the largest source categories 

contributing to SO2 in 2018 in the AoI defined for the Sipsey Wilderness area. Industrial boilers 

using oil and commercial and institutional boilers using coal or oil had smaller contributions to 

SO2 in 2018. 

Sulfur dioxide emissions from utility, industrial, commercial, or institutional boilers can be 

controlled either by switching the fuel source to a lower sulfur fuel content or by installing postcombustion controls. Costs vary by fuel source and boiler type and require source specific 

analyses for accuracy. 

 Appendix H - 2 
Bituminous coal is commonly burned in boilers in the eastern U.S. Switching to another 

bituminous coal with lower sulfur content or blending bituminous coals can reduce SO2

emissions with least impact to boiler performance. While sub-bituminous coal has a lower sulfur 

content than bituminous coal, it also has a lower heat rate and so more coal has to be burned to 

generate the same energy output. For boilers that are designed for bituminous coal, only a small 

fraction of the fuel can be switched to low sulfur sub-bituminous coal without affecting boiler 

operations. Costs of boiler modifications to accommodate low sulfur sub-bituminous coal may 

make switching to sub-bituminous coal impractical. Contract initiation and termination costs, 

differential fuel prices and heat rates, transportation costs, and modification to boiler operations, 

fuel handling and waste handling systems will have to be considered specific to each source. 

Flue-gas desulfurization is the common post-combustion control for coal-fired boilers. Flue gas 

is passed through an absorbent for sulfur dioxide (generally limestone or lime) in either a wet 

scrubber, dry scrubber, or spray dryer. A calcium sulfate byproduct is produced that may be 

further processed to produce gypsum as a commercial byproduct. Costs of flue-gas 

desulfurization include initial construction costs and ongoing operational and maintenance costs 

for the absorber tower, sorbent handling, and waste product handling facilities. Costs per ton 

vary with boiler size, type, and facility siting considerations. 

For oil-fired boilers, lower sulfur oil may be an option. Costs need to consider differential fuel 

prices and heat rate, boiler modifications, fuel handling costs, and maintenance costs. 

Conceptually, post-combustion controls can be used for oil boilers, but there is little precedence 

for such installations. 

6.2-2 Time Necessary for Compliance 

For fuel switching, the time necessary to terminate existing fuel contracts and initiate new 

contracts needs to be considered. Generally two to three years may be required. Instillation of 

post-combustion controls will require three or more years depending on market availability of 

labor and materials and utility system-wide priorities. Time necessary for compliance will need 

to be refined for specific sources. 

6.2-3 Energy and Non-Air Environmental Impacts 

Switching to lower sulfur fuel or installing post-combustion controls may reduce boiler heat rate 

and energy output. Scrubbers and spray dryers will require additional safeguards for fuel 

handling and waste handling systems to avoid additional non-air environmental impacts such as 

increased effluents in waste water discharges and storm water runoff. These factors will need to 

be considered specific to individual sources. Carbon dioxide may be emitted as a byproduct of 

flue gas desulfurization (particularly if limestone is used), therefore impacts of increased carbon 

emissions will need to be considered, especially if carbon emissions are limited in the future 

under climate change mitigation strategies. 

 Appendix H - 3 
6.2-4 Remaining Useful Life 

 Remaining useful live is specific to the facility for which controls are considered. 

6.3 Process of Applying Statutory Factors 

ADEM has completed its Reasonable Progress Assessment for the first Regional Haze SIP. The 

following is ADEM’s Process on Reasonable Progress for the current time period (from the 

present to 2018): 

Step 1: Determine pollutants of concern. 

VISTAS evaluated the species contribution on the 20% worst visibility days and concluded that 

sulfate accounted for greater than 70% of the visibility impairing pollution. The VISTAS States 

concluded that controlling SO2 emissions was the appropriate step in addressing the Reasonable 

Progress Assessment for 2018. The VISTAS findings were consistent with the findings of the 

Southern Appalachian Mountain Initiative (SAMI). SAMI confirmed that sulfate particles 

account for the greatest portion of the haze affecting Class I areas in the Southern Appalachian 

region and that these sulfates were produced in large part from SO2 emissions from coal 

combustion. 

Step 2: Determine which source sectors should be evaluated for reasonable progress. 

Since SO2 point source emissions in 2018 are projected to represent greater than 95% of the total 

SO2 emissions inventory, the VISTAS States concluded that the focus should be on electric 

generating utility (EGU) and non-EGU point sources of SO2 emissions. 

Step 3: Determine if the Clean Air Interstate Rule (CAIR) is sufficient for reasonable progress 

for subject EGU’s. 

ADEM evaluated the amount of SO2 reduction from the EGU sector resulting from the 

implementation of CAIR. The EGUs in Alabama are expected to reduce their SO2 emissions by 

approximately 70% between 2002 (2002 emissions approximately 447,828 tons per year) and 

2018 (2018 emissions approximately 135,851 tons per year). ADEM intends to re-evaluate the 

IPM predictions of SO2 reductions for CAIR at the time of the next periodic report in 2012 to 

ensure that the reductions currently predicted by IPM for CAIR are in fact taking place. As such, 

ADEM has concluded that at this time the CAIR program constitutes reasonable measures for 

Alabama EGUs during this first assessment period (between baseline and 2018). Please refer to 

Section 7.7 of the SIP Narrative for further discussion. 

Step 4: Determine which emission units would be evaluated based on impact. 

ADEM calculated the fractional contribution from all emission units within the SO2 AoI for a 

given Class I area and identified those emission units with a contribution of 1% or more. 

 Appendix H - 4 
Step 5: Evaluate the four factors. 

Each emission unit identified in Step 4 above was evaluated using the statutory and regulatory 

factors of 1) cost of compliance, 2) time necessary for compliance, 3) the energy and non-air 

quality environmental impacts of compliance, and 4) the remaining useful life of the emissions 

unit. ADEM believes that the cost of compliance is the typically the dominant factor in whether 

a source will be required to install controls. Therefore, most of the emphasis was placed on cost 

of control as part of this reasonable progress assessment, as compared to the other three statutory 

factors. In addition, ADEM believes that a fifth factor, visibility improvement, is considered by 

focusing the evaluation on those units that contribute at least 1% to visibility impairment at a 

given Class I area. 

For the limited purpose of evaluating the cost for the Reasonable Progress Assessment in this 

first Regional Haze SIP, ADEM believes it is not equitable to require non-EGUs to bear a greater 

economic burden than EGUs for a given control strategy. Using the CAIR rule as a guide, a cost 

of $2,000 was used as a determiner of effectiveness. 

Based on the AoI analysis, ADEM focused the reasonable progress assessments on specific units 

at the following non-EGU facility in the State based on the 1% criteria discussed later in this 

document: 

Cargill Sweeteners North America 

The following is a summary of the assessment for the facility. 

Cargill Sweeteners North America Decatur, Alabama 

Unit on an AOI list with control options with costs < $10K/ton: 

Keeler Stoker Boiler; 179.74 mm BTU/hr; sulfur content used since 1999 ranges from 1.2 to 

1.3 lb/MMBtu 

The following control technology options were considered for the above mentioned unit: 

 Lower sulfur coals 

 Wet scrubbers 

 Dry scrubbers 

Cargill evaluated switching to lower sulfur content coals. Currently, the company is using 

1.49% sulfur coal in the Keeler Stoker boiler a BACT limit resulting from a PSD review in 1998, 

Cargill states that lower sulfur coal would have to be obtained from western USA, such as 

Powder River Basin, to achieve any reductions in SO2. According to the company, available 

information indicates that lower sulfur coal is largely under contract and may not be available to 

new users. Cargill also states that their boiler was not designed to burn a low sulfur western coal 

and would require significant modification to accommodate this type coal. Cargill further states 

that burning such coal would compromise their combustion integrity due to a higher dust content 

 Appendix H - 5 
that would result in an increase risk of spontaneous combustion in bunkers, silos, and hoppers. 

Due to availability and restriction on boiler design, Cargill determined that this option was not 

technically feasible. 

Cargill also evaluated add-on controls. Specifically, Cargill evaluated wet and dry scrubbers. 

The typical SO2 content of the coal currently burned in Keeler Stoker boiler is 1.3 lb/MMBtu. 

Based on an annual heat input of 1.2x106

 MMBtu/yr, a baseline mass emission would equate to 

780 TPY of SO2. Based on this information, Cargill estimates that it would cost $2,946/ton to 

control SO2 emissions with these technologies. 

It should also be noted that Cargill has entered into a Consent Decree agreement with EPA and 

affiliated states that would reduce SO2 emissions by 50% from current levels at its US plants. 

Summary:

During the current reasonable progress assessment no units in Alabama were identified for 

additional control since no measures were found to be below the $2,000 cost threshold 

(discussed in Step 5). In addition to costs, the statutory factors include time necessary for 

compliance, remaining useful life of the facility, and energy and non-air environmental impacts 

of the control installation. However, since no cost effective control measures were identified for 

these specific sources with contributions to Alabama or neighboring States’ Class I areas, ADEM 

did not invest in an exhaustive review of the remaining three factors beyond those described 

control options for major SO2 source sectors. 

It should be noted that, in order to show continued progress past 2018, the criteria will likely be 

different in the next reasonable progress assessment in order to maintain a continuous downward 

glidepath toward natural background conditions by 2064, and while no additional controls were 

identified during this reasonable progress assessment, possible SO2 reduction strategies will be 

evaluated for the next round of regional haze State Implementation Plan (SIP) development. 

7.0 Best Available Retrofit Technology (BART) 

7.1 Background

As required by the CAA, EPA included in the final RHR a requirement for BART for certain 

large stationary sources that were placed in operation between 1962 and 1977. The BARTeligible sources are those sources which have the potential to emit 250 tons or more of a 

visibility-impairing air pollutant, were placed in operation between August 7, 1962 and August 

7, 1977, and whose operations fall within one or more of 26 specifically listed source categories. 

Under the CAA, BART is required for any BART-eligible source that a State determines ‘‘emits 

any air pollutant which may reasonably be anticipated to cause or contribute to any impairment 

of visibility in any such area.’’ Accordingly, for stationary sources meeting these criteria, States 

must address the BART requirement when they develop Regional Haze SIPs. 1

 EPA has set 

guidance for identifying BART-eligible sources in 40 CFR Part 51 Appendix Y. 

 Appendix H - 6 
A BART-eligible source that is responsible for a 1.0 deciview (dv) change or more is considered 

to “cause” visibility impairment. Although the appropriate threshold may vary, the guidelines 

state that the contribution threshold used for BART applicability should not be higher than 0.5 

deciviews (dv).1 Thus, a BART-eligible source that is responsible for a 0.5 dv change or more is 

considered to “contribute” to visibility impairment. Any source determined to cause or contribute 

to visibility impairment in any Class I area is subject to BART. 

The guidelines direct that States should include SO2, NOx, and direct particulate matter (PM) 

emissions, including both PM10 and PM2.5, in determining whether sources cause or contribute to 

visibility impairment. States may use their best judgment to determine whether VOC or 

ammonia emissions are likely to have an impact on visibility in an area.1 

To determine which BART-eligible sources are subject to BART, states have several options. A 

State may consider all BART-eligible sources subject to BART; may perform an analysis 

showing that the full group of BART-eligible sources in a State cumulatively may not be 

reasonably anticipated to cause or contribute to any visibility impairment in any Class I areas; or 

may consider the individualized contribution of a BART-eligible source to determine whether a 

specific BART-eligible source is subject to BART. 

Sources that are subject to BART must undergo a BART determination. Section 169A(g)(7) of 

the CAA requires that States must consider the following factors in making BART 

determinations: (1) The costs of compliance, (2) The energy and non-air quality environmental 

impacts of compliance, (3) Any existing pollution control technology in use at the source, (4) 

The remaining useful life of the source, and (5) The degree of improvement in visibility which 

may reasonably be anticipated to result from the use of such technology. 1 

To demonstrate the degree of improvement in visibility from various BART control options, the 

States may run CALPUFF or another appropriate dispersion model to predict visibility impacts. 

Scenarios would be run for the pre-controlled and post-controlled emission rates for each of the 

BART control options under review. The maximum 24 hour emission rates would be modeled 

for a period of three or five years of meteorological data. States have the flexibility to develop 

their own methods to evaluate model results. 1 

7.2 Approach to Implementation of BART Requirements 

In order to meet the SIP submittal deadline, Alabama used a multifaceted approach to implement 

the RHR BART requirements. The approach consists of source identification efforts, use of a 

permitting process to establish any resulting BART limits for inclusion in the SIP submittal as 

well as participation in VISTAS BART subgroup to resolve technical issues spanning states in 

the VISTAS region, and ongoing consultation with affected sources, and EPA and FLMs 

throughout the BART process. 

 Appendix H - 7 
7.3 Identification of BART-Eligible Sources 

EPA provided guidance for identifying BART-eligible sources in 40 CFR Part 51 Appendix Y. 

Alabama followed this guidance in identifying its BART-eligible sources. The Alabama 2002 air 

emissions inventory was reviewed to determine the population of potential BART-eligible 

sources. The data were initially queried for any sources emitting SO2, NOx, PM10, VOC, or 

ammonia. The data set was refined based on emissions, whether emission units fit in any of the 

twenty-six listed source categories for BART, and available date information obtained through 

review of permit and inspection reports and discussion with permitters and regional office staff 

familiar with the facilities. 

Notification of BART was sent to and additional information was collected from the sources 

regarding potential emissions and BART eligibility from the standpoint of source category and 

date criteria. Through this iterative review process, the list of potential BART-eligible sources 

was pared down to the 37 BART-eligible sources listed below. The facilities include eight 

electric utilities, nine pulp and paper facilities, four chemical manufacturers, three natural gas 

processing facilities, three limestone manufacturers, two oil refineries, three cement 

manufacturers, three iron and steel mills, one coking by-products manufacturer, one coal 

cleaning operation, and one secondary lead smelter. 

Alabama BART Eligible Facility List: 

Alabama Electric Coop Lowman International Paper Co Prattville 

Alabama Power Co Barry International Paper Co Riverdale 

Alabama Power Co EC Gaston International Paper Co Courtland 

Alabama Power Co Gorgas JSC Brewton (Smurfit Stone) 

Alabama Power Co Greene Co Lehigh Cement – JCDH 

Alabama Power Co Miller- JCDH MeadWestvaco Mahrt Mill 

American Cast Iron Pipe- JCDH National Cement Co of Alabama 

Boise White Paper Oak Grove Resources- JCDH 

Bowater Inc.- Alabama Sanders Lead Co 

BP Amoco Chemicals Shell Chemical Co Saraland 

Carmeuse Lime & Stone Solutia- Decatur 

CEMEX, Inc. Sloss Industries- JCDH 

Chemical Lime Co Alabaster TVA, Colbert 

Chemical Lime Co Montevallo TVA, Widows Creek 

ConocoPhillips Co Chatom US Pipe & Co- Bessemer- JCDH 

Degussa Corporation US Steel- Fairfield- JCDH 

Escambia Operating Co Big Escambia Creek Vintage Petroleum 

Ft James-Pennington, Naheola Weyerhaeuser 

Hunt Refining Co, Tuscaloosa 

A spreadsheet of Alabama’s BART-eligible source emissions is included as Attachment H-3. A 

spreadsheet of Alabama’s BART-eligible sources’ SO2 emissions and distance to Class I areas is 

included as Attachment H-4. 

 Appendix H - 8 
Alabama’s BART-eligible sources were presumed to be subject to BART but were provided the 

opportunity to submit modeling demonstrations showing that they did not contribute to visibility 

impairment, i.e., had less than 0.5 deciview (dv) impact, on any Class I area within 300 km. 

Sipsey 

Wilderness

Figure 7-1. Alabama’s BART-Eligible Sources 

 

Lauderdale

Limestone

Autauga

Baldwin

Barbour

Bibb

Blount

Bullock

Butler

Calhoun

Chambers

Cherokee

Chilton

Choctaw

Clarke

Clay

Cleburne 

Coffee

Colbert

Conecuh

Coosa

Covington

 Crenshaw

Cullman

Dale

Dallas

 De 

Elmore

Escambia

Etowah

Fayette

Franklin

Geneva

 

Hale

Henry

Houston

Jackson

Jefferson

Lamar

 Lawrence

Madison

Morgan

Marshall

Marion

Walker

St Clair

Pickens

Talladega

 Tuscaloosa

Shelby

 

Lee Sumter

Perry

Macon

Russell

Marengo

Montgomer Lowndes y

Wilcox

Pike

Monroe

Washington

Mobile

 Appendix H - 9 
7.4 Contribution Threshold 

Determining whether a source causes or contributes to visibility impairment is one step in the 

BART review process. The Guidelines for BART Determinations Under the Regional Haze 

Rule1

 state that “A single source that is responsible for a 1.0 deciview change or more shou

considered to ‘cause’ visibility impairment.” The guideline document also states that “the 

appropriate threshold for determining whether a source ‘contributes to visibility impairment’ 

may reasonably differ across states,” but, “As a general matter, any threshold that you use for 

determining whether a source ‘contributes’ to visibility impairment should not be higher than 0.5 

deciviews.” The rationale for these instructions is provided in the preamble to the BART 

guidance, in the statement, “If ‘causing’ visibility impairment means causing a humanly 

perceptible change in visibility in virtually all situations (i.e. a 1.0 dv change), then 

‘contributing’ to visibility impairment must mean having some lesser impact on the conditions 

affecting visibility that need not rise to the level of human perception.”

ld be 

 

2

 The Guidance itself also 

states that, “States remain free to use a threshold lower than 0.5 dv if they conclude that the 

location of a large number of BART-eligible sources within the State and in proximity to a Class 

I area justify this approach.” 

The EPA’s documents strive to set these thresholds in the context of the human perception of 

visibility change. As noted above, the EPA considers a 1.0 dv change in visibility to be humanly 

perceptible “in virtually all situations.” Also, the preamble to the BART guidance3

 cites an 

analysis in an appendix of a NAPAP (National Acid Precipitation Assessment Program) report, 

which asserts that “changes in light extinction of 5% will evoke just noticeable changes in most 

landscapes.” 4 (A 5% change is approximately 0.5 dv.) But, as noted above, the preamble also 

states that perceptibility is not a prerequisite for choosing a contribution threshold. Putting all 

this together, it appears that “causing” visibility impairment means having a humanly perceptible 

impact (for which EPA considers the practical threshold to be 1.0 dv) while “contributing” to 

visibility impairment means having a smaller impact (for which EPA considers the threshold to 

be 0.5 dv or some smaller value) that may or may not be perceptible. 

ADEM retained the threshold of 0.5 dv for evaluating significance. First, there is a clear spatial 

variability of sources across the state which can be seen in Figure 7-2. Additionally, ADEM is 

electing to use half of the threshold established by EPA for causing visibility impairment. 

Lastly, the BART rule is a source specific rule and ADEM does not have a technical justification 

for lowering the threshold based on concerns of multiple plume interaction. As such, ADEM 

concluded that the EPA suggested contribution threshold of 0.5 dv was appropriate in for 

evaluating facility contributions at Class I areas that Alabama sources impact. 

1

 40 CFR 51, Appendix Y, Section III.A.1 

2

 70 FR 39120. Footnote 31 

3

 70 FR 39119. Footnote 28 

4

 “The Quadratic Detection Model” by W. Malm. Appendix D in Acidic Deposition: State of Science and 

Technology, Report 24, Visibility: Existing and Historical Conditions -- Causes and Effects. National 

Acid Precipitation Assessment Program, Washington, DC. 1990. 

 Appendix H - 10 
Figure 7.2 Location of VISTAS BART-Eligible Sources 

7.5 Exemption of Point Source Volatile Organic Compounds (VOCs) for BART Purposes 

The State of Alabama has determined through modeling that VOCs from point sources are not 

anticipated to cause or contribute significantly to the impairment of visibility in any Class I area 

and should be exempt for BART purposes. 

7.5.1 Method 

It was determined through modeling that VOCs from point sources are not anticipated to cause 

or contribute significantly to the impairment of visibility in any Class I area. 

Modeling was conducted through the Visibility Improvement State and Tribal Association of the 

Southeast (VISTAS). VISTAS is a collaborative effort of state governments, tribal governments, 

and various federal agencies established to initiate and coordinate activities associated with the 

management of regional haze, visibility and other air quality issues in the Southeastern U.S. 

VISTAS contracted with Georgia Institute of Technology (GA Tech) to perform model 

sensitivity runs to determine the impact of point source VOCs on visibility in Class I areas. 

GA Tech performed emission sensitivities to examine the impact of emission reductions on 

Regional Haze, annual PM2.5, and 8-hour Ozone concentrations using CMAQv4.4_SOAmods on 

 Appendix H - 11 
the VISTAS 12 km modeling domain, using the 2009 OTW (on the way) Base D emissions. 

One such sensitivity run reduced anthropogenic, point source VOCs by 100%. The purpose was 

to quantify the impact of VOC emissions from VISTAS BART sources on Class I areas. Two 

episodes were examined: June 1-July 10, 2002 and November 19 – December 19, 2002. The 

approach included calculating the extinction coefficient in deciviews (dv), then determining the 

maximum impact of point source VOCs. Figure 7-3 shows the impact on the following twentytwo Class I areas within the VISTAS domain. 2 

BRET = Breton, LA 

BRIG = Brigantine NWR, NJ 

CACR = Caney Creek, AR 

CHAS = Chassahowitzka, FL 

COHU = Cohutta, GA 

DOSO = Dolly Sods, WV 

EVER = Everglades, FL 

GRSM = Great Smoky Mountains National Park 

HEGL = Hercules Glade, MO 

JARI = James River Face, VA 

LIGO = Linville Gorge, NC 

MACA = Mammoth Cave, KY 

MING = Mingo, MO 

OKEF = Okefenokee, GA 

ROMA = Cape Romain, SC 

SAMA = Saint Marks, FL 

SHEN = Shenandoah, VA 

SHRO = Shining Rock, NC 

SIPS = Sipsey Wilderness, AL 

SWAN = Swanquarter, NC 

UPBU = Upper Buffalo Wilderness, AR 

WOLF = Wolf Island, GA 

 Appendix H - 12 
Maximum Point VOC Impact

Maximum VOC Impact

0.0

0.1

0.2

0.3

0.4

0.5

0.6

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV

Figure 7-3. Maximum Point VOC Impact in VISTAS and surrounding Class I Areas. 

7.5.2 Conclusions 

The results show that the maximum impact from eliminating all point source VOC emissions in 

the VISTAS 12 km domain is less than a 0.5 dv for all Class I areas in the VISTAS domain. 

Given that the fraction of the total point source VOC emissions would be less than the emissions 

from BART-eligible sources in Alabama, the expected impact of controlling VOCs from a 

BART source would be much less than the 0.5 dv threshold. Therefore, VISTAS and the State 

of Alabama concluded that VOCs from point sources are not a visibility impairing pollutant for 

BART purposes and that BART-eligible sources do not need to consider VOC emissions. 

7.6 Treatment of Ammonia (NH3) Emissions for BART Purposes 

Similar to its treatment of VOCs, EPA guidance allows States the discretion to decide whether or 

not NH3 emissions are to be considered for BART purposes based on evaluations of the 

contributions of the emissions to haze at Class I areas. One approach a State can use to determine 

whether applying BART will be needed is to evaluate the haze impacts of all BART-eligible 

emissions of NH3. If the impact at the Class I area is less than the contribution threshold 

established by the State, 0.5 dv for Alabama, then source by source analysis for BART is not 

needed. 

The State of Alabama has determined through modeling that NH3 emissions from point sources 

are not anticipated to cause or contribute significantly to any impairment of visibility in Class I 

areas and should be exempt for BART purposes. 

 Appendix H - 13 
7.6.1 Method 

It was determined through modeling that NH3 emissions from point sources are not anticipated to 

cause or contribute significantly to any impairment of visibility in any Class I area affected by 

Alabama sources. 

VISTAS contracted with GA Tech to perform model sensitivity runs to determine the impact of 

point source NH3 on visibility in Class I areas. 

GA Tech performed emission sensitivities to examine the impact of emission reductions on 

Regional Haze using CMAQv4.5 with SOA mods on the VISTAS 12 km modeling domain, 

using the VISTAS 2009 OTW (on the way) Base F4 emissions. One such sensitivity run 

reduced BART-eligible source ammonia by 100%. The purpose was to quantify the impact of 

NH3 emissions from VISTAS BART sources on Class I areas. Two episodes were examined: 

June 1-July 10, 2002 and November 19 – December 19, 2002. The approach included 

calculating the extinction coefficient in deciviews (dv), then determining the maximum impact of 

BART-eligible source NH3. Figure 7-4 below, taken from the VISTAS report BART in the 

VISTAS Region: Sensitivity to VOC, NH3, and Primary PM Emissions, included as Attachment 

H-4, shows the impact on the following twenty-two Class I areas within the VISTAS domain. 2 

Maximum NH3 Impact

0.0

0.5

1.0

1.5

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV

 Figure 7-4. Maximum NH3 Impact - Maximum contributions of all BART-eligible NH3 point 

sources in the VISTAS region to haze in Class I areas during the CMAQ-modeled periods. 

The chart shows the largest haze impact in delta dv over the two timeframes at each Class I area. 

These delta dv changes represent the haze contribution of all BART source ammonia emissions 

relative to assumed natural haze levels. The natural haze levels are based on EPA-default annual 

average natural concentrations for the East and monthly-varying “climatologically 

representative” relative humidity at each Class I area. 

 Appendix H - 14 
During the periods modeled, the NH3 emissions from all BART-eligible sources contributed 

more than 0.5 dv to haze at Mammoth Cave National Park (MACA), Kentucky; Mingo 

Wilderness (MING), Missouri, Cape Romain National Wildlife Refuge Area (ROMA) South 

Carolina, and Swanquarter National Wildlife Refuge (SWAN), North Carolina. 

The majority of ammonia emissions in VISTAS region come from four BART-eligible sources 

as shown in Table 7-1 below. 

Table 7-1. Major BART NH3 Sources in the VISTAS Region 

Facility State NH3 Emissions 

(tpy) 

Distance to Nearest 

Class 1 Area (km) 

Meadwestvaco Corp. SC 174 30 

PCS Phosphate NC 206 31 

PCS Nitrogen TN 1252 180 

PCS Nitrogen GA 1765 220 

None of the above sources are significant contributors to the Sipsey Wilderness area. 

7.6.2 Conclusions 

The BART requirements of the RHR allow states to determine whether or not ammonia is to be 

considered a visibility impairing pollutant to be addressed for BART purposes. NH3 emissions 

from BART sources may impair visibility; however the majority of NH3 emissions in the 

VISTAS region are from a few BART sources. Removal of the large NH3 emission sources 

results in minimal impact on visibility at Class I areas in the VISTAS region. At their discretion 

states may ask those few large sources to evaluate NH3 impacts and potential controls for NH3. 

Based on the CMAQ sensitivity analyses of the impact of ammonia emissions, Alabama 

identified no large sources of ammonia emissions affecting the Sipsey Wilderness or neighboring 

Class I areas. As a result, Alabama has concluded that NH3 emissions from point sources are not 

a visibility impairing pollutant for BART purposes and that BART-eligible sources need not 

consider NH3 emissions. 

8.0 Explanation of BART Exemption Modeling 

8.1 Background 

Alabama opted to consider its BART-eligible sources subject to BART unless the source 

demonstrated exemption via modeling. BART-eligible sources can be excluded from BART 

determinations by demonstrating that the source cannot be reasonably expected to cause or 

contribute to visibility impairment in a Class I area. The threshold for determining that a source 

causes visibility impairment is set at 1.0 dv change from natural conditions over a 24 hour 

averaging period. The BART guidelines also propose that the threshold at which a source may 

“contribute” to visibility impairment should not be higher than 0.5 dv. 

 Appendix H - 15 
As stated in the BART regulation, EPA’s preferred approach for determining cause or 

contribution is an assessment with an air quality model such as CALPUFF or other appropriate 

model followed by comparison of the estimated 24 hour visibility impacts against a threshold 

above estimated natural conditions to be determined by the State. EPA recommends that the 98th

percentile value from the modeling be compared to the State’s chosen contribution threshold to 

determine if a source does not contribute to visibility impairment. Comparison of the 98th

percentile value to the threshold must be made for each Class I area. For an annual period, this 

implies the 8th highest 24 hr value at a particular Class I area is compared to the contribution 

threshold. For a 3-year modeling period, the 98th percentile value may be interpreted as the 

highest of the three annual 98th percentile values at a particular Class I area or the 22nd highest 

value in the combined three year record, whichever is more conservative. 

ADEM worked with the Regional Planning Organization (RPO) VISTAS on development of the 

VISTAS Protocol for the Application of the CALPUFF Model for Analyses of Best Available 

Retrofit Technology (BART) (Attachment H-5). The common protocol was established to 

provide the basis for a common understanding among the organizations performing BART 

analyses or reviewing BART modeling results in the VISTAS region. 

The VISTAS protocol describes common procedures for carrying out air quality modeling to 

support BART determinations that are consistent with the 40 CFR Part 51 Appendix Y 

guidelines. The protocol provides a consistent model, CALPUFF, and modeling guidelines for 

BART determinations, clearly delineated modeling steps, a common CALPUFF configuration, 

guidance for site-specific modeling, and common expectations for reporting model results. 

Details of the CALPUFF system can be found in Chapter 3 of the VISTAS protocol, specific 

recommendations for its application for BART purposes are found in Chapter 4, and specific 

information that should be included in site-specific protocols is found in Chapter 5. 

VISTAS contracted EarthTech to develop a version of the CALPUFF model appropriate for 

BART purposes. The VISTAS version of the CALPUFF modeling system is CALPUFF Version 

5.754 and CALMET Version 5.7. 

For BART modeling purposes, VISTAS made publicly available 12 km CALMET output files 

for the entire VISTAS modeling domain (Eastern U.S.) and provided CALMET output files for 

five 4 km grid subdomains covering the VISTAS states and all VISTAS Class I areas as well as 

several peripheral Class I areas. To generate the CALMET input files, the VISTAS contractor 

used the MM5 databases developed by EPA for 2001, VISTAS for 2002, and Midwest RPO for 

2003. For the 12 km grid large domain covering the entire VISTAS region, the No-Obs setting 

was used. For the 4 km grid, available surface and upper air observations were used in addition 

to MM5 meteorological model outputs. Specific model settings were provided with the 

CALMET files and via the CALPUFF website so that work could be replicated. 

For CALPUFF modeling, source emissions were to be defined using the maximum 24 hr actual 

emission rate during normal operation for the most recent 3 or 5 years. If maximum 24 hr actual 

emissions were not available, continuous emission data, permit allowable emissions, potential 

emissions, and emission factors from AP-42 source profiles could be used as available. 

 Appendix H - 16 
Key points on specific CALPUFF, CALPOST, and POSTUTIL configuration that were to be 

used for BART modeling are: 

• After running CALPUFF for an individual facility, NO3 should be repartitioned in 

POSTUTIL. 

• Ozone data from non-urban monitors should be used as the background ozone input. 

• The Pasquill-Gifford dispersion method should be used. 

• In CALPOST Method 6 with monthly average RH for calculating extinction as 

recommended by EPA should be used. 

• EPA default calculations of light extinction under current and natural background 

conditions should be used. In addition, a source may also calculate visibility using the 

recently revised IMPROVE algorithm. 

Additional discussion of the CALPUFF model and VISTAS recommended settings can be found 

in the VISTAS protocol in Attachment H-5. 

8.2 Alabama BART Sources Exemption Modeling 

ADEM requested that its sources follow the VISTAS modeling protocol in development of their 

site specific protocols and explain any deviations that they proposed to use. In the site-specific 

modeling demonstrations submitted by Alabama’s BART-eligible sources, the CALPUFF model 

incorporating three years of pre-processed MM5 meteorological data was used to evaluate the 

deciview change compared to natural background conditions at each of the Class I areas within 

300 km of the source. Both the 4 km and 12 km MM5 datasets prepared by VISTAS were used. 

Facilities submitted site-specific modeling protocols and subsequent modeling demonstrations 

based upon the VISTAS modeling protocol. The site-specific protocols are found in Attachment 

H-5 and the demonstrations are found in Attachment H-6. The protocols and demonstrations 

were reviewed by ADEM’s Industrial Chemicals and Industrial Minerals Sections as well as the 

Meteorological Section. 

The individual facility modeling demonstrations were shared with both EPA and FLMs for their 

review and comment. The resulting comments were in turn shared with the facilities. ADEM 

worked throughout the process to resolve many of the issues and concerns reflected in their 

comments. ADEM staff reviewed the demonstrations to determine whether sources 

demonstrated impacts of 0.5 deciview (dv) or less on any Class I area within 300 km of the 

source. Sources demonstrating less than a 0.5 dv impact are considered exempt. Sources 

contributing 0.5 dv impact or greater were considered subject to BART and were required to 

proceed to an analysis of what control measures, if any, constitute BART for the source. 

Review of the demonstrations submitted led to the determination of which BART-eligible 

sources were exempt from BART determination requirements. Based upon these 

demonstrations, ADEM proposed to exempt 37 facilities. Table 8-1 below provides a summary 

of the impacts of each BART-eligible facility on the affected Class I areas.

 Appendix H - 17 
Table 8-1. BART Exemption Modeling Results 

Impact Class I Grid 

Facility Name Change(DV) Area Spacing 

Alabama Electric Coop Lowman 0.34 Breton 4 km 

Alabama Power Co Barry 0.22 Breton 4 km 

Alabama Power Co EC Gaston 0.17 Sipsey 4 km 

Alabama Power Co Gorgas 0.25 Sipsey 4 km 

Alabama Power Co Greene Co 0.13 Sipsey 4 km 

Alabama Power Co Miller 0.34 Sipsey 4 km 

American Cast Iron Pipe- JCDH 0.082 Sipsey 12 km 

Boise White Paper 0.162 Breton 12 km 

Bowater Inc.- Alabama 0.166 Sipsey 12 km 

BP Amoco Chemicals 0.486 Sipsey 4 km 

Carmeuse Lime & Stone 0.215 Sipsey 12 km 

CEMEX, Inc. 0.308 Breton 4 km 

Chemical Lime Co Alabaster 0.188 Sipsey 4 km 

Chemical Lime Co Montevallo 0.484 Cohutta 4 km 

ConocoPhillips Co Chatom 0.303 Breton 4 km 

Degussa Corporation 0.466 Breton 12 km 

Escambia Oper. Co Big Escambia Crk 0.498 Breton 4 km 

Ft Jms-Pennington, Naheola 0.241 Breton 4 km 

Hunt Refining Co, Tuscaloosa 0.327 Sipsey 4 km 

International Paper Co Prattville 0.271 Sipsey 4 km 

International Paper Co Riverdale 0.246 Sipsey 12 km 

International Paper Co Courtland 2.392 Sipsey 4 km 

JSC Brewton (Smurfit Stone) 0.295 Breton 12 km 

Lehigh Cement – JCDH 0.301 Sipsey 4 km 

MeadWestvaco Mahrt Mill 0.229 St. Marks 4 km 

National Cement Co of Alabama 0.192 Sipsey 4 km 

Oak Grove Resources- JCDH 0.021 Sipsey 12 km 

Sanders Lead Co 0.223 St. Marks 4 km 

Shell Chemical Co Saraland 0.066 Breton 12km 

Sloss Industries- JCDH 0.088 Sipsey 12 km 

Solutia, Inc, Decatur Plant 4.435 Sipsey 4 km 

TVA, Colbert 0.476 Sipsey 4 km 

TVA, Widows Creek 0.183 Cohutta 4 km 

US Pipe & Co- Bessemer- JCDH 0.036 Sipsey 12 km 

US Steel Corporation Fairfield- JCDH 0.205 Sipsey 12 km 

Vintage Petroleum, Inc, Flomaton 0.179 Breton 4 km 

Weyerhaeuser 0.247 Breton 4 km 

 Appendix H - 18 
Additionally, consistent with BART regulation requirements and EPA guidance, BART-eligible 

sources at electric utilities complying with EPA’s Clean Air Interstate Rule (CAIR) that wished 

to demonstrate exemption were allowed to model only direct PM fine emissions. Compliance 

with CAIR constitutes BART for these sources for emissions of NOx and SO2. 

Alabama adopted it CAIR rules with a state effective date of July 2006 and amended these rules 

to comply with EPA’s revisions to the model rule effective April 2007. The final revision of 

Alabama’s CAIR SIP was submitted on March 7, 2007. EPA took final action to approve the 

SIP on October 1, 2007. This rulemaking does not have a direct impact on existing BARTeligible EGUs and should not impact their compliance for BART purposes. 

Eight of Alabama’s BART-eligible sources are electric generating units (EGUs). The EPA has 

determined that, as a whole, the CAIR cap-and-trade program improves visibility more than 

implementing BART for individual sources in states affected by CAIR. A state that opts to 

participate in the CAIR program under part 96 AAA-EEE need not require affected BARTeligible EGU to install, operate, and maintain BART for SO2 or NOx emissions. Given that 

many of the BART-eligible units are installing scrubbers and NOx controls, and since Alabama is 

participating in CAIR and accepts EPA’s overall finding that CAIR “substitutes” for BART for 

NOx and SO2, Alabama’s EGUs were allowed to submit BART exemption modeling 

demonstrations for PM emissions only. All eight EGUs demonstrated that they do not contribute 

to visibility impairment in any Class I area. 

Table 8-3. BART Exemption Modeling Results–EGUs 

Impact Class I Grid 

Facility Name Change(DV) Area Spacing 

Alabama Electric Coop Lowman 0.34 Breton 4 km 

Alabama Power Co Barry 0.22 Breton 4 km 

Alabama Power Co EC Gaston 0.15 Sipsey 4 km 

Alabama Power Co Gorgas 0.25 Sipsey 4 km 

Alabama Power Co Greene Co 0.13 Sipsey 4 km 

Alabama Power Co Miller 0.32 Sipsey 4 km 

TVA, Colbert 0.181 Cohutta 4 km 

TVA, Widows Creek 0.476 Sipsey 4 km 

Two of the facilities were unable to demonstrate less than a 0.5 dv impact via modeling. The 

visibility impact results for these two facilities are included in Table 8-4 below. 

Table 8-4. BART Subject Sources Exemption Modeling Results 

Impact Class I Grid 

Facility Name Change(DV) Area Spacing 

International Paper Co Courtland 2.392 Sipsey 12 km 

Solutia, Inc- Decatur Plant 7.21 Sipsey 12 km 

 Appendix H - 19 
Table 8-5 lists each BART eligible source and the associated Class I areas those facilities 

impacted. 

Table 8-5. Class I Areas within 300 km of Alabama Sources 

* Great Smokies represents Great Smokies and Joyce Kilmer 

Alabama BART-Eligible Class I Area 

Sources SIPS BRET GRSM* COHU SAMA OKEF MACA 

Alabama Electric Coop Lowman X 

Alabama Power Co Barry X 

Alabama Power Co EC Gaston X X 

Alabama Power Co Gorgas X X 

Alabama Power Co Greene Co X 

Alabama Power Co Miller X X 

American Cast Iron Pipe- JCDH X X X 

Boise White Paper X X 

Bowater Inc.- Alabama X X X 

Carmeuse Lime & Stone X X 

CEMEX, Inc. X X 

Chemical Lime Co Alabaster X X 

ConocoPhillips Co Chatom X 

Degussa Corporation X 

EOC Big Escambia Creek X 

Ft Jms-Pennington, Naheola X X 

Hunt Refining Co, Tuscaloosa X 

International Paper Co Prattville X X X 

International Paper Co Riverdale X X 

International Paper Co Courtland X X X X 

JSC Brewton (Smurfit Stone) X X 

Lehigh Cement - JCDH X X X 

MeadWestvaco Mahrt Mill X X X X 

National Cement Co of Alabama X X X 

Oak Grove Resources- JCDH X X 

Sanders Lead Co X 

Shell Chemical Co Saraland X 

Sloss Industries- JCDH X X 

Solutia, Inc, Decatur Plant X X 

TVA, Colbert X X 

TVA, Widows Creek X X X X 

US Pipe & Co- Bessemer- JCDH X X 

US Steel Corp-Fairfield- JCDH X X 

Vintage Petroleum, Inc, Flomaton X X 

Weyerhaeuser X X 

BP Amoco Chemicals X X X X 

Chemical Lime Co Montevallo X X 

 Appendix H - 20 
Thirty eight Alabama BART-eligible sources modeled impacts at the Class I areas within 300 

km, but only two contributed to visibility impairment, both at the Sipsey Wilderness Area. 

Additionally, although several modeled impacts, none of the BART-eligible sources contributed 

to visibility impairment at Class I areas outside of Alabama. 

8.3 Use of New IMPROVE Equation 

During the Regional Haze SIP development process, the IMPROVE Steering Committee made 

recommendations for a new IMPROVE equation. Among other things, the new equation includes 

components that take into account the effects of sea salt and site specific Rayleigh scattering. 

Additional discussion of the new IMPROVE equation can be found in Appendix C. 

VISTAS contracted Dr. Ivar Tombach to develop a post processor to allow CALPOST outputs to 

be used with the new IMPROVE equation. A discussion of the rationale for use of the new 

IMPROVE equation follows. The new IMPROVE postprocessor and instructions are included in 

the request to EPA for approval of its use in Attachment H-11. 

Rationale for Need for Use of New IMPROVE Equation

The new IMPROVE equation is a much better representation of the effects of particulate matter 

on light extinction than the old equation and takes into account the latest scientific understanding 

of several parameters. 

1. The new algorithm overcomes biases of the old algorithm on the haziest days and the 

clearest days as demonstrated by comparing the measured light extinction from 

nephelometers at Class I areas to light extinction calculated using each of the equations. 

2. The new algorithm recognizes spatial and temporal variation in light extinction as size 

distribution of the aerosol changes by increasing extinction efficiency as sulfate, nitrate 

and organics concentrations increase. 

3. The new algorithm incorporates a term to reflect the contribution of fine sea salt and 

its hygroscopic growth with increasing relative humidity recognizing research findings 

showing that fine sea salt can be an important contributor to light extinction in coastal 

areas. 

4. The new algorithm reflects research finding that the mass concentration of particulate 

organic matter in rural areas is greater than represented by the old equation. 

5. The new algorithm includes a NO2 term to represent times when light absorption by 

NO2 is a meaningful contributor to light extinction. 

6. The new algorithm incorporates site-specific Rayleigh scattering values to better 

represent sites close to sea level or with very hot or cold climates. 

With this combination of revisions to the IMPROVE equation, the resulting apportionment of 

extinction to various components is more accurate on the haziest and clearest days. This is 

important for development of emission control strategies since the benefits of control of 

concentrations of each species will be represented more correctly with the new algorithm. 

 Appendix H - 21 
Two of Alabama’s BART eligible sources elected to use the new IMPROVE equation The 

spreadsheet developed by Dr. Tombach to implement the entire new IMPROVE equation for use 

with CALPUFF contains a modification of CALPOST that calculates the light extinction from 

the CALPUFF output. In their review of the spreadsheet and supporting documentation, EPA 

Region 4 staff commented that the VISTAS methodology contained in the spreadsheet developed 

by Dr. Tombach appropriately implements the features of the new IMPROVE equation, with the 

exception of the nitrogen dioxide term. EPA Region 4 further stated that with the addition of 

their recommendation for addressing the NO2 term, the VISTAS methodology to incorporate the 

new IMPROVE equation is acceptable. In addition to its impact for the two non-EGU sources in 

Alabama, use of the full new IMPROVE equation was used in Base G modeling. 

 

Table 8-6. BART Exemption Modeling Results New IMPROVE Equation 

Impact Class I Grid 

Facility Name Change (DV) Area Spacing 

BP Amoco Chemicals 0.486 Sipsey 4 km 

Chemical Lime Co Montevallo 0.484 Cohutta 4 km 

8.4 Source Limits to Exempt from BART 

The BART Guidelines list specific criteria that must be met in order for sources to be considered 

BART eligible. One of the criteria for a source to be considered BART eligible was the limited 

potential emissions from all affected emission units considering all federally enforceable permit 

limits, were greater than 250 tons or more per year of any of these visibility-impairing pollutants: 

SO2, NOx, and PM10.. Alabama had three sources which chose to take emissions limits in order 

to be exempt from the entire BART process. By taking an emissions limit, Gulf States Paper 

Corporation, Kerr-McGee Chemical LLC, and Mobile Energy Services Company no longer have 

BART eligible sources. These limits will be written into and enforced through the permits for 

each applicable source at the facility. 

8.5 Conclusions 

In total 35 of Alabama’s 37 BART-eligible sources were able to demonstrate that they did not 

cause or contribute to visibility impairment in any Class I area within 300 km of the source. Two 

sources used the new IMPROVE equation in efforts to demonstrate exemption. Two sources, 

Solutia, Inc. in Decatur, Alabama, and International Paper Courtland in Courtland, Alabama 

were unable to demonstrate a contribution of less than 0.5 dv at all Class I areas within 300 km 

from their BART-eligible sources which resulted in those sources being considered “subject to 

BART”. These two sources are required to revise the permits for the affected sources. 

Discussion of the BART determinations for these two sources is included in Section 9.0 below. 

A spreadsheet summarizing all the BART-eligible sources in Alabama, the distance to and 

impact on Class I areas, version(s) of the IMPROVE equation used and difference in results, 

whether a BART determination was required, the facilities’ potential emissions, the version of 

 Appendix H - 22 
CALPUFF and its components used, who conducted the modeling, existing controls, and 

proposed controls resulting from BART determinations is included as Attachment H-8 

The BART Guidelines list specific criteria that must be met in order for sources to be considered 

BART eligible. One of the criteria for a source to be considered BART eligible was that a 

source emits 250 tons per year of NOx, PM10, SO2, VOCs, or NH3. Alabama had three sources 

which chose to take emissions limits in order to be exempt from the entire BART process. By 

taking an emissions limit, Gulf States Paper Corporation, Kerr-McGee Chemical LLC, and 

Mobile Energy Services Company no longer have BART eligible sources. These limits will be 

written into and enforced through the permits for each applicable source at the facility, and 

incorporated into the Regional Haze SIP. 

9.0 BART Determinations 

For those facilities subject to BART, the state must determine what constitutes BART controls 

for the source by considering various control options and selecting the best alternative taking into 

consideration any pollution control equipment in use at the source, the costs of compliance with 

control options, the remaining useful life of the facility, the energy and non air-quality 

environmental impacts of compliance, and the degree of improvement in visibility that may 

reasonably be anticipated to result from the use of such technology. Under Alabama’s approach, 

facilities that are subject to BART were required to propose BART considering these factors via 

a permitting process. 

9.1 BART Subject Sources 

Only two BART-eligible sources in Alabama emit any air pollutants which may reasonably be 

anticipated to cause or contribute to any impairment of visibility in any Class I area. The two 

facilities, Solutia, Inc. in Decatur, AL and International Paper, in Courtland, AL, were unable to 

demonstrate less than a 0.5 dv impact on one or more Class I areas and thus are subject to 

BART. 

In accordance with the BART rule, the two facilities submitted analyses proposing BART for 

their sources (Attachment H-6). Upon receipt, the proposed BART determinations were provided 

to U.S. EPA Region 4 and the FLMs for their review and comment. ADEM also held conference 

calls with U.S. EPA Region 4 to discuss their comments and concerns regarding each of the 

facilities’ submittals. 

ADEM permitting staff reviewed the analyses proposing BART. 

9.1.1 BART-Eligible Units and Existing Control 

Solutia, Inc. has five BART-eligible emission units that comprise the BART-eligible source. The 

majority of these units are currently controlled. Descriptions of these units are as follows: 

 Appendix H - 23 
Boiler No. 5 (X005): This unit is a 290 MMBTU/hr coal-fired spreader-stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Boiler No. 6 (X006): This unit is a 320 MMBTU/hr coal-fired spreader-stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Boiler No. 7 (X015): This unit is a 536.1 MMBTU/hr pulverized coal-fired boiler. This boiler is 

permitted to burn propionitrile (PN) vapor. The boiler is equipped with an electrostatic 

precipitator for particulate control. Soutia has installed a ROFA (rotating opposed fired air) 

system to reduce NOx formation on this boiler. This unit is subject to NSPS, Subpart D. As 

required by Subpart D, this boiler has limitations for particulate, SO2, and NOx emissions. The 

SO2 emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Coking Boiler No. 1 (X007): This unit is a 384 MMBTU/hr coal-fired stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Coking Boiler No. 2 (X008): This unit is a 384 MMBTU/hr coal-fired stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

International Paper’s Courtland Mill has seven BART-eligible emission units that comprise the 

BART-eligible source. The majority of these units are currently controlled. Descriptions of these 

units are as follows. 

No. 1 Combination Boiler: This unit is a 398 MMBTU/hr combination fuel boiler that is 

designed to fire bark, natural gas, and fuel oil and is operated as a swing boiler. Bark from the 

woodyard is fed to a bark bin which supplies both the No.1 and No.2 Combination Boilers. In 

addition the No. 1 Combination Boiler has the capability to combust the dilute non-condensable 

gas (HVLC) stream from the pulp mill and chemical recovery areas. The No. 1 Combination 

Boiler is vented to a venturi scrubber where the gases are scrubbed with water to remove 

particulate matter. 

No. 2 Combination Boiler: This unit is a 679 MMBTU/hr combination fuel boiler that fires 

coal, bark, and natural gas. The primary fuel for this boiler is bark, which is supplied to the 

boiler by the bark handling system. The other primary fuel for this boiler is coal. There are 

three coal mills associated with the No.2 Combination Boiler which consist of a pulverizer and a 

primary air fan that is used to dry the coal and blow the coal in the boiler a well has provide 

excess air for the combustion of the coal. Each of the pulverizers provides coal to two burners, 

and each of the burners is equipped with a gas igniter. The No. 2 Combination Boiler also has 

 Appendix H - 24 
the capability to combust the dilute non-condensable gas (HVLC) stream from the pulp mill and 

chemical recovery areas. The No. 2 Combination Boiler is vented to two electrostatic 

precipitators to remove particulate matter. The flue gas is then vented to a high pressure venturi 

scrubber for the removal of SO2.

Package Boiler: This unit is a 365 MMBTU/hr boiler that is utilized as a back-up boiler and is 

fired by natural gas. The Package Boiler has no external emissions control devices.

No. 2 Recovery Furnace: This unit is a 470 MMBTU/hr recovery furnace that is designed to 

fire black liquor, with natural gas and fuel oil as supplemental fuels. In the furnace the liquor is 

dried and burned. The organic portion of the liquor burns which provides heat for steam 

generation. The inorganic portion of the liquor is recovered to produce cooking liquor for the 

digesters. The combustion gases from the furnace are vented to an electrostatic precipitator for 

particulate matter control

No.2 Smelt Dissolving Tank: This unit is a recovery operation for the No. 2 Recovery Furnace. 

The inorganics in the Recovery Furnace accumulate on the furnace floor and drain into the No. 2 

Smelt Dissolving Tank as molten smelt. The smelt is mixed with weak wash to form green 

liquor which is sent to the causticizing area. The No. 2 Smelt Dissolving Tank is vented through 

a separate scrubber system for particulate matter control.

No. 1 Lime Kiln: Lime mud from the Causticizing Area is converted to lime in this unit. Both 

the No. 1 and No. 2 Lime Kilns are fired with natural gas and/or fuel oil and have low-NOx

burners. Concentrated non-condensable gases (LVHC) and the foul condensate stripper gases 

are incinerated in the lime kilns. The No.1 Lime Kiln is vented to a scrubber to control 

particulate emissions.

No. 2 Lime Kiln: Lime mud from the Causticizing Area is converted to lime in this unit. Both 

the No. 1 and No. 2 Lime Kilns are fired with natural gas and/or fuel oil and have low-NOx

burners. Concentrated non-condensable gases (LVHC) and the foul condensate stripper gases 

are incinerated in the lime kilns. The No.1 Lime Kiln is vented to a scrubber to control 

particulate emissions. 

9.2 Baseline Contribution 

Solutia’s BART source baseline contribution to the 98th percentile visibility impairment was 

4.470 dv at Sipsey Wilderness. IP Courtland’s BART source baseline contribution to visibility 

impairment is 2.392 dv at Sipsey Wilderness. 

9.3 BART Determination Analysis 

Section 169A(g)(7) of the CAA requires that States must consider the following factors in 

making BART determinations: (1) The costs of compliance, (2) The energy and non-air quality 

environmental impacts of compliance, (3) Any existing pollution control technology in use at the 

source, (4) The remaining useful life of the source, and (5) The degree of improvement in 

 Appendix H - 25 
visibility which may reasonably be anticipated to result from the use of such technology. These 

factors are incorporated in the BART regulation and 40 CFR Part 51 Appendix Y and Alabama’s 

BART rule as well. Although these factors are to be considered, according to the BART 

guidelines states have flexibility in how the factors are weighted in making their determinations 

regarding what constitutes BART. (See 70 FR 39170, 1st col., July 6, 2005.) 

9.3.1 Control Scenarios Considered 

Each facility reviewed several potential control alternatives. The control alternatives that have 

been considered and the associated visibility improvement that would result are summarized in 

the tables below: 

 Appendix H - 26 
Table. 9-1 Solutia Summary of Visibility Improvements for Control Technologies 

Visibility Improvement 

Relative to Base Emissions 

Scenario (deciviews)1

BART-Eligible 

Emissions Unit 

Control 

Technology Pollutant 

Pollutant 

Control 

Efficiency 

(%) 

Maximum 

24-Hour 

98th Percentile 

24-Hour 

Boiler 52 Low Sulfur Coal SO2 46 0.07 0.32 

Boiler 52 ROFA/FSI SO2 60 0.07 0.34 

Boiler 52 Wet Scrubber SO2 90 0.11 0.40 

Boiler 52 ROFA/Rotamix NOx 58 0.04 0.00 

Boiler 52 SCR NOx 95 0.06 0.00 

Boiler 52 Baghouse PM 99.9 0.66 0.21 

Boiler 6 Low Sulfur Coal SO2 46 0.07 0.32 

Boiler 6 ROFA/FSI SO2 60 0.07 0.34 

Boiler 6 Wet Scrubber SO2 90 0.11 0.40 

Boiler 6 ROFA/Rotamix NOx 58 0.04 0.00 

Boiler 6 SCR NOx 95 0.06 0.00 

Boiler 6 Baghouse PM 99.9 0.66 0.21 

Boiler 7 Low Sulfur Coal SO2 7 0.01 0.03 

Boiler 7 ROFA/FSI SO2 60 0.05 0.24 

Boiler 7 Wet Scrubber SO2 90 0.07 0.36 

Boiler 7 ROFA/Rotamix NOx 78 0.06 0.00 

Boiler 7 SCR NOx 95 0.09 0.00 

Boiler 7 Baghouse PM 99.9 1.12 0.52 

One Coker Low Sulfur Coal SO2 16 0.01 0.05 

One Coker ROFA/FSI SO2 60 0.04 0.18 

One Coker ROFA/Rotamix NOx 58 0.04 0.00 

One Coker SCR NOx 95 0.07 0.00 

One Coker Baghouse PM 99.9 0.41 0.19 

Cokers Wet Scrubber SO2 90 0.12 0.41 

Notes: 

1

The predicted visibility impact of the five BART-eligible emission units for the base emission 

scenario was 7.241 deciviews (maximum 24-hour value) and 4.470 deciviews (98th percentile 

24-hour value). 

2

Visibility improvements results for Boiler 6 were used for Boiler 5 because of the similarities of 

the boilers and their operation. Boiler 6 is slightly larger than Boiler 5, therefore the visibility 

improvements indicated are a conservative representation for Boiler 5. 

 Appendix H - 27 
Table. 9-2 IP Courtland Summary of Visibility Improvements for Control Technologies 

Visibility Improvement 

Relative to Base Emissions 

Scenario (deciviews)1

BART-Eligible 

Emissions Unit Control Technology Pollutant

Pollutant 

Control 

Efficiency 

(%) 

Maximum 

24-Hour 

98th Percentile 

24-Hour 

No. 1 Combo SNCR NOx 35 0.02 0.02 

No. 1 Combo Low NOx Burners NOx 30 0.013 

No. 1 Combo Addition of Caustic 

to Scrubber SO2 93 0.014 0.013 

No. 1 Combo Dry Scrubbing SO2 93 0.014 0.013 

No. 1 Combo Semi-dry Scrubbing SO2 93 0.014 0.013 

No. 2 Combo SNCR NOx 35 0.097 

No. 2 Combo Low NOx Burners NOx 30 0.15 0.083 

Package Boiler SCR NOx 90 0.037 

Package Boiler SNCR NOx 50 0.041 0.017 

Package Boiler Low NOx w/ FGR NOx 50 0.041 0.017 

No. 2 Rec. High ∆P Wet 

Scrubbing SO2 93 0.17 0.063 

No. 2 Rec High ∆P Wet 

Scrubbing / WESP SO2 93 0.17 0.063 

Notes: 

1

The predicted visibility impact of the seven BART-eligible emission units for the base emission 

scenario was 2.392 deciviews (maximum 24-hour value) and 1.341 deciviews (98th percentile 24-

hour value). 

Since both the No.1 and No.2 Lime Kilns currently employ Low-NOx Burners in the form of 

combustion flame tuning to reduce NOx emissions, and no other controls where deemed feasible, 

a cost effectiveness review and visibility study was not conducted as allowed by 40 CFR Part 51, 

Appendix Y. 

Although both the Package Boiler and the No. 2 Smelt Tank are BART eligible sources for SO2, 

a control effectiveness review study was not performed since both of these sources only emit 

approximately 1 tpy of SO2. Due to this fact; emissions from these units are minimal and there 

would be virtually no impact on visibility, therefore no BART controls were reviewed. 

The No. 1 and No. 2 Lime Kilns are BART eligible sources for SO2; however 40 CFR Part 51, 

Appendix Y exempts units that are complying with MACT Standards from performing a 

technical feasibility study and a cost effectiveness review and visibility study. Since both these 

 Appendix H - 28 
Lime Kilns are subject to and are complying with 40 CFR Part 63 Subpart MM through the use 

of wet scrubbers, and since the inherit nature of lime kilns minimize SO2 emissions, the current 

approach to MACT II compliance should serve as BART for SO2 for these Lime Kilns. 

The No.2 Recovery, No. 2 Smelt Tank, No. 1 and No. 2 Lime Kilns are BART eligible sources 

for PM10; however 40 CFR Part 51, Appendix Y exempts these units from performing a 

technical feasibility study and a cost effectiveness review and visibility study since these units 

are subject to and complying with a MACT Standard, which regulates particulate emissions (40 

CFR Part 63, Subpart MM). 

9.3.2 Costs of Compliance 

For Solutia, the 98th percentile 24-hour visibility improvement ranged from 0.00 dv improvement 

to 0.52dv at costs ranging from $1667.72/ton/dv to $380,928.57/ton/dv, respectively. The costs 

for each of the scenarios considered are summarized in Table 9-3 below: 

 Appendix H - 29 
Table 9-3 Solutia Summary of Cost Effectiveness for Control Technologies

BART- Control Cost-Effectiveness 

Eligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Tons 

Removed 

($/ton 

Removed)

($/ton/deciview 

improvement) 

Boiler 5 Low Sulfur Coal SO2 1438.88 1065.54 3329.81 

Boiler 5 ROFA/FSI SO2 1876.79 663.45 1951.32 

Boiler 5 Wet Scrubber SO2 2815.19 1,075.46 2688.65 

Boiler 5 ROFA/Rotamix NOx 52.84 15,529 - 

Boiler 5 SCR NOx 86.54 8675 - 

Boiler 5 Baghouse PM 21.5 79,995 380,928.57 

Boiler 6 Low Sulfur Coal SO2 1587.72 1065.54 3329.81 

Boiler 6 ROFA/FSI SO2 2070.95 615.80 1811.18 

Boiler 6 Wet Scrubber SO2 3106.42 977.86 2444.65 

Boiler 6 ROFA/Rotamix NOx 57.28 18,091 - 

Boiler 6 SCR NOx 93.81 5,461 - 

Boiler 6 Baghouse PM 44.96 38,316 182,457 

Boiler 7 Low Sulfur Coal SO2 168.09 16,034.55 534,485 

Boiler 7 ROFA/FSI SO2 1440.8 931.95 3883.13 

Boiler 7 Wet Scrubber SO2 2161.21 1854.90 5152.50 

Boiler 7 ROFA/Rotamix1 NOx 217.35 4118 - 

Boiler 7 SCR1 NOx 654.84 1986 - 

Boiler 7 Baghouse PM 409.57 1065.54 10,503.85 

Coker 1 Low Sulfur Coal SO2 302.09 8739 174,780 

Coker 1 ROFA/FSI SO2 1599.10 1090.20 3028.33 

One 

Coker ROFA/Rotamix NOx 265 4510 - 

One 

Coker SCR NOx 435 2607 - 

One 

Coker Baghouse PM 120 13,709 72,152.63 

Cokers Wet Scrubber SO2 4797.30 600.20 1667.22 

1-The cost, emissions, and improvements are based on the addition of the SNCR/SCR to the 

ROFA system, which is considered as existing control for Boiler 7. 

In reviewing the cost of controls based on emissions removed, Solutia indicated that the 

additional controls for particulate and NOx emissions would not be cost effective. The current 

particulate controls (ESPs) achieve removal efficiencies between 96%-99% and adequately 

controls the particulate emissions. The additional NOx controls indicated relatively small to no 

reduction in visibility impacts for the reported costs. The costs for additional SO2 controls appear 

 Appendix H - 30 
to be more cost effective and provide some visibility improvement. Solutia has indicated that the 

cost of installation and operation of the FSI system or wet scrubbers would severely impact the 

facility’s sustainability and viability. For both of the coking units, Solutia has indicated that the 

addition of any controls would negate the viability of the coking units. The requirement of the 

additional controls would result in a net loss and thus require the units to be shutdown. 

For IP Courtland, the 98th percentile 24-hour visibility improvement ranged from 0.00 dv 

improvement to 0.097dv at costs ranging from $7,048/ton/dv to $1,121,077/ton/dv. The costs for 

each of the scenarios considered are summarized in Table 9-4 below: 

Table 9-4 IP Courtland Summary of Cost Effectiveness for Control Technologies

Control Cost-Effectiveness BARTEligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Tons 

Remove

d 

($/ton 

Removed) 

($/ton/deciview 

improvement) 

No. 1 

Combo SNCR NOx 142.8 $6,097 $304,850 

No. 1 

Combo 

Low NOx

Burners NOx 122.3 $1,188 $91,385 

No. 1 

Combo 

Addition of 

Caustic to 

Scrubber 

SO2 180.7 $7,260 $558,462 

No. 1 

Combo Dry Scrubbing SO2 180.7 $14,574 $1,121,077 

No. 1 

Combo 

Semi-dry 

Scrubbing SO2 180.7 $11,420 $878,462 

No. 2 

Combo SNCR NOx 518.2 $2,081 $21,454 

No. 2 

Combo 

Low NOx

Burners NOx 444.2 $585 $7,048 

Package 

Boiler SCR NOx 108 $12,375 $334,459 

Package 

Boiler SNCR NOx 60 $16,024 $801,200 

Package 

Boiler 

Low NOx w/ 

FGR NOx 60 $2,767 $138,350 

No. 2 Rec. High ∆P Wet 

Scrubbing SO2 1149 $3,633 $57,667 

No. 2 Rec 

High ∆P Wet 

Scrubbing / 

WESP 

SO2 1149 $4,336 $68,825 

 Appendix H - 31 
In reviewing the cost of controls based on the amount of emissions removed, IP has indicated 

that additional controls for SO2 would not be cost effective at the Courtland Mill. IP has also 

indicated that the Control of NOx is only cost effective for the No. 2 Combination Boiler and that 

no other add-on controls would be cost effective for all other sources. The current add-on 

controls which control particles at the Courtland mill have efficiencies of greater than 90% 

therefore any additional controls would not be a cost effective option. 

9.3.3 Energy and Non-air Quality Impacts 

Solutia has indicated that the additional SO2 controls would generate additional waste. Solutia 

estimated that the FSI system would generated an additional 14,000 tons of fly ash per boiler and 

the addition of the wet scrubber would generate 20 tons/day of sludge. 

IP has indicated that there would be a reduced energy efficiency and an increase in fuel usage as 

a result of the installation of Low NOx burners on the No. 1 Combo and No. 2 Combo boilers. 

The Department has reviewed these concerns and had determined that the small reduction in 

energy efficiency and increase in fuel usage for the No. 2 Combo boiler does not offset the 

visibility improvements or the cost effectiveness of $585/ton of NOx removed. IP has also 

indicated that additional NOx controls for other units would cause significant impacts to the 

energy efficiencies and potentially allow other pollutants to be emitted to the atmosphere. 

IP has suggested that any additional control of SO2 at any of the BART eligible sources at IP 

would cause an significant increase in energy usages and/or generate a waste stream that would 

have to be disposed; thereby incurring disposal costs and possible permitting issues with other 

medias. 

9.3.4 Existing Control 

Existing control on the BART subject sources is described in Section 9.1.1. 

9.3.5 Remaining Useful Life 

Remaining useful life did not play a role in the determination of controls. 

9.3.6 Degree of Visibility Improvement 

As previously stated, modeling was conducted to show the predicted visibility impact on the 

closest Class I Area (Sipsey Wilderness Area). From the chosen options for Solutia, an 

improvement of 0.32 dv is expected from each of Boiler 5 and 6, and an improvement of 0.24 dv 

for Boiler 7 from SO2 controls. The summary of the costs and visibility improvements for the 

chosen options are shown in the table below: 

 Appendix H - 32 
Table 9-5. Solutia Visibility Improvement and Cost Results of Proposed Options 

BARTEligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Pollutant 

Control 

Efficiency 

(%) 

($/ton 

Removed) 

Visibility 

Improvement 

Relative to 

Base 

Emissions 

Scenario 

(deciviews)1

Boiler 5 

Low Sulfur 

Coal SO2 46 1065.54 0.32 

Boiler 6 

Low Sulfur 

Coal SO2 46 1065.54 0.32 

Boiler 7 ROFA/FSI SO2 60 931.95 0.24 

1-98th Percentile 24-Hour 

For the IP Courtland facility the modeled visibility improvement as a result of installing the 

proposed add on BART controls, federally enforceable limits, and operational limitations would 

range between 0.2 and 0.4 deciviews improvement in the Sipsey Wilderness Area. Although this 

is a small visibility improvement it has a large reduction in the number of days above 0.5 dv at 

the Sipsey Wilderness Area. Relative to the base case of 98 days above 0.5 dv, the three 

modeled scenarios indicate only 40, 59, and 56 days above 0.5 dv, which equates is an average 

improvement of 45 days. The summary of the costs and visibility improvements for the chosen 

options are shown in the table below: 

Table 9-6. IP Courtland Visibility Improvement and Cost Results of Proposed Options 

BARTEligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Pollutant 

Control 

Efficiency 

(%) 

($/ton 

Removed) 

Visibility 

Improvement 

Relative to 

Base 

Emissions 

Scenario 

(deciviews)1

No. 1 Combo2 Low NOx

Burners NOx 30 $1,188 0.32 

No. 2 Combo Low NOx

Burners NOx 30 $585 0.013 

1-98th Percentile 24-Hour 

2- IP has to either install low NOx Burners or only operate the No. 1 Combination Boiler when 

one of the following emissions units is either not operating or in periods of start-up of shutdown: 

the No. 2 Combination Boiler the No. 2 Recovery Furnace, the No. 3 Combination Boiler, or the 

No. 3 Recovery Furnace.

 Appendix H - 33 
9.4 Final BART Determination 

Proposed BART Limitations for Solutia

The Table below presents the summarized BART emission limits for Solutia. 

Table 9-7 Solutia BART Emission Limitations 

Emission Limitations Emission Unit NOx SO2 PM10

Boiler 5 101.22 lb/hr 1.40 lb/MMbtu & 

406 lb/hr 

0.12 lb/MMbtu & 34.8 

lb/hr 

Boiler 6 109.72 lb/hr 1.40 lb/MMbtu & 

448 lb/hr 

0.12 lb/MMbtu & 38.4 

lb/hr 

Boiler 7 0.36 lb/MMbtu & 193 

lb/hr 

0.47 lb/MMbtu & 

252 lb/hr 

0.10 lb/MMbtu & 

64.33 lb/hr 

Coker 1 104.43 lb/hr 3.57 lb/MMbtu & 

1,370.1 lb/hr 0.12 lb/MMbtu 

Coker 2 104.43 lb/hr 3.57 lb/MMbtu & 

1,370.1 lb/hr 0.12 lb/MMbtu 

The Department concurs with the proposed BART limitations. For Boiler 7, Solutia would be 

required to install a continuous emission monitor system (CEMS) for determining compliance 

with the SO2 and NOx emission limitations. Solutia would be required to comply with the BART 

limitations by January 1, 2013. 

Proposed BART Limitations for IP Courtland

The Table below presents the summarized BART emission limits for the IP Courtland Mill. 

Table 9-8 IP Courtland BART Emission Limitations 

Emission Limitations Emission Unit NOx SO2 PM10

No. 1 Combo 93.15 lb/hr or operational 

limitations 1 147.3 lb/hr 0.17 gr/sdcf @ 50% Excess Air 

No. 2 Combo 338.13 lb/hr 1.20 lb/MMbtu & 

65.5 lb/hr 0.10 lb/MMbtu 

Package Boiler 

0.20 MMbtu & 

<1,200,000 ft3 of natural 

gas / 12 month period 

1.80 lb/MMbtu 0.10 lb/MMbtu 

No. 2 Recovery 152 lb/hr 432 lb/hr 0.044 grains/SDCF at 8 

% O2 and 67 lb/hr 

No. 2 Smelt Tank NA 0.20 lb/hr 0.20 lb/ ton of black 

liquor solids 

No. 1 Lime Kiln 3.5 lb/hr 0.10 lb/hr 1.0 lb/air dried ton of 

pulp 

No. 2 Lime Kiln 19.40 lb/hr 0.23 lb/hr 0.067 gr/sdcf at 10% 

O2

 Appendix H - 34 
I- IP has to either install low NOx Burners or only operate the No. 1 Combination Boiler when 

one of the following emissions units is either not operating or in periods of start-up of shutdown: 

the No. 2 Combination Boiler the No. 2 Recovery Furnace, the No. 3 Combination Boiler, or the 

No. 3 Recovery Furnace.

The Department concurs with the proposed BART limitations. IP would be required to install 

low NOx burners on the No. 1 Combination Boiler if as change in the operational status of this 

boiler is changed in the future due to process demands. IP will be required to comply with the 

BART limitations by January 1, 2013. 

These limitations will be written into air permits and will be effective by January 1, 2013. The 

limitations established under BART (Best Available Retrofit Technology) may be changed 

through the NSR (New Source Review) permit process which should include a visibility analysis 

prior to the modification. 

9.5 BART Subject Sources in Other States Within 300 km of Alabama Class I Areas 

There were no sources outside Alabama that contributed to visibility impairment at the Sipsey 

Wilderness area. 

9.6 Conclusions 

Only two sources in Alabama, Solutia in Decatur and IP Courtland in Courtland were subject to 

BART. For Solutia, all of the BART units are already each equipped with an electrostatic 

precipitator, which range in efficiency from 96% to 99%. The ESPs adequately controls 

particulate emissions for the units. The proposed BART limitations for Boilers 5-7 appear to 

adequately comply with the BART requirements. As previously stated, the addition of any 

controls would negate the viability of the coking units; therefore, no additional controls would be 

required for BART. 

The No. 2 Recovery Furnace, No. 2 Smelt, No. 1 Lime Kiln and the No. 2 Lime Kiln of IP 

Courtland’s BART-subject sources are already well controlled via compliance with the Pulp and 

Paper MACT’s (40 CFR Part 63, Subparts MM and S). There are limited additional control 

options available. Based on review of the available control options, associated costs and 

visibility benefits, BART is determined to be equivalent to the MACT standards and the 

installation of low NOx burners on the No. 2 Combination Boiler and either install low NOx

burners or only operate the No. 1 Combination Boiler when one of the following emissions units 

is either not operating or in periods of start-up of shutdown: the No. 2 Combination Boiler the 

No. 2 Recovery Furnace, the No. 3 Combination Boiler, or the No. 3 Recovery Furnace. 

 Appendix H - 35 
10.0 FINAL LONG TERM STRATEGY (LTS) AND REASONABLE 

PROGRESS GOALS (RPGs) 

As stated in Section 2.0 above, the RHR requires States to establish Reasonable Progress Goals 

(RPGs), expressed in deciviews (dv), for visibility improvement at each affected Class I area 

covering each (approximately) 10 year period until 2064. This first set of RPGs must be met 

through measures contained in the state’s LTS covering the period from the baseline until 2018. 

This Section discusses development of Alabama’s LTS. 

10.1 Long-Term Strategy (LTS) 

Ammonium sulfate is the most important contributor to visibility impairment and fine particle 

mass on the 20% worst and 20% best visibility days at the Sipsey Wilderness area. Sulfate levels 

on the 20% worst days account for greater than 70% of the visibility impairment. Across the 

VISTAS region, sulfate levels are higher at the Southern Appalachian sites than at the coastal 

sites. On the 20% clearest days, sulfate levels are more uniform across the region. Reduction of 

SO2 emissions would be the most effective means of reducing ammonium sulfate. Greater than 

85% of SO2 emissions in Alabama are attributable to electric generating facilities and industrial 

point sources. Thus, the LTS for this first Regional Haze SIP focused on reductions in SO2 

emissions. 

In Alabama and across the region there are significant controls programs in place to reduce SO2

emissions between the baseline period and 2018. Most notably, CAIR is predicted to result in a 

70% reduction from EGU SO2 emissions in Alabama. Overall the SO2 emissions in Alabama are 

predicted to decrease from 2002 levels at 447,828 tons per year to 135,851 tons per year in 2018. 

Such large SO2 reductions are predicted to result in significant improvements in visibility. 

Alabama’s CAIR rule is attached as Attachment H-10. 

At the Sipsey Wilderness area in Alabama, visibility improvements on the 20% worst days are 

expected to be better than the uniform rate of progress glidepath by 2018 based solely on 

reductions from existing and planned emissions controls. Specifically for Sipsey, a 4.2 deciview 

improvement in visibility would meet uniform rate of progress in 2018; expected emissions 

reductions by 2018 are projected to achieve a 5.3 deciview improvement. In fact, visibility 

improvements at all the VISTAS mountain Class I areas and most of the coastal Class I areas are 

projected to be better than the uniform rate of progress. The percentage of the target reduction 

achieved for the Sipsey Wilderness areas using the new IMPROVE equation is between 120- 

130%. This reflects a rate of improvement of 20-30% greater than the uniform rate of progress 

by 2018. 

In addition to improving visibility on the 20% worst visibility days, states are also required to 

protect visibility on the 20% best days at the Class I areas. Visibility on the 20% best days is 

projected to improve in 2018 at all VISTAS Class I areas as a result of the 2018 Base G2 

emissions reductions. The percentage of the target achieved for the Sipsey Wilderness area is 

about -7.7%. Zero percent change would mean no change in visibility; -7.7% means that 

visibility is better than no change, or a 7.7% improvement (values lower than current 

conditions.) 

 Appendix H - 36 
ADEM completed a reasonable progress assessment after modeling the Clean Air Act controls 

discussed above. The assessment did not identify any cost effective control measures for the SO2

non-EGU units that contributed greater than 1% to visibility impairment at the Sipsey 

Wilderness or any Class I area in neighboring States. 

10.2 What Additional Emissions Controls Were Considered as Part of the Long-Term 

Strategy for Visibility Improvement by 2018? 

Section 308(d)(3)(v) of the regional haze rule lists several factors that must be addressed in each 

SIP. These factors include the role of fire at Class I areas and status of state planning for smoke 

management, the role of dust and fine soil at Class I areas and status of state plans to mitigate 

emissions from construction activities and the role of NH3 and potential benefits if emissions 

from agricultural sources were mitigated. 

As discussed in Section 4.1 and demonstrated in Figure 17, elemental carbon (sources include 

agriculture, prescribed wildland fires, and wildfires) is a relatively minor contributor to visibility 

impairment at the Class I areas in Alabama. However, the ADEM has an approved smoke 

management program that addresses the issues laid out in EPA’s 1998 draft guidance for smoke 

management plans. ADEM intends to include the smoke management program as part of the 

final Regional Haze SIP submittal in December, 2007, and for the resulting plan to be sufficient 

to satisfy the directive in section 308(d)(3)(v)(E). 

In regard to construction activities and fugitive dust emission sources, the ADEM has issued 

regulations addressing control of fugitive dust from construction activities and to control 

particulates from fugitive dust emission sources generated within plant boundaries. ADEM 

Admin. Code 335-3-4-.02, reads as follows: 

(1) No person shall cause, suffer, allow, or permit any materials to be handled, transported, or 

stored; or a building, its appurtenances, or a road to be used, constructed, altered, repaired, or 

demolished without taking reasonable precautions to prevent particulate matter from becoming 

airborne. Such reasonable precautions shall include, but not be limited to, the following: 

(a) Use, where possible, of water or chemicals for control of dust in the demolition of existing 

buildings or structures, construction operations, the grading of roads, or the clearing of land; 

(b) Application of asphalt, oil, water, or suitable chemicals on dirt roads, materials stock piles, 

and other surfaces which create airborne dust problems; 

(c) Installation and use of hoods, fans, and fabric filters (or other suitable control devices) to 

enclose and vent the handling of dusty materials. Adequate containment methods shall be 

employed during sandblasting or other similar operations. 

(2) Visible Emissions Restrictions Beyond Lot Line. No person shall cause or permit the 

discharge of visible fugitive dust emissions beyond the lot line of the property on which the 

emissions originate. 

 Appendix H - 37 
(3) When dust, fumes, gases, mist, odorous matter, vapors, or any combination thereof escape 

from a building or equipment in such a manner and amount as to cause a nuisance or to violate 

any rule or regulation, the Director may order that the building or equipment in which processing, 

handling, and storage are done be tightly closed and ventilated in such a way that all air and gases 

and air or gas-borne material leaving the building or equipment are treated by removal or 

destruction of air contaminants before discharge to the open air. 

In regard to agricultural ammonia, the ADEM has no regulations. 

A final CMAQ modeling run will be performed in the fall of 2007 to account for the cumulative 

benefits of the Base G2a emissions controls, BART controls, and additional measures to achieve 

reasonable progress by 2018. The final Regional Haze SIP will contain revised RPGs for the 

Sipsey Wilderness Area reflecting these final decisions. 

10.3 Reasonable Progress Goals (RPGs) 

The RHR at 40 CFR section 51.308(d)(1) requires States to establish RPGs for each Class I area 

within the state (expressed in deciviews) that provide for reasonable progress towards achieving 

natural visibility. In addition, EPA released guidance on June 7, 2007 to use in setting RPGs. 

The goals must provide improvement in visibility for the most impaired days, and ensure no 

degradation in visibility for the least impaired days over the State Implementation Plan (SIP) 

period. The State must also provide an assessment of the number of years it would take to attain 

natural visibility conditions if improvement continues at the rate represented by the RPGs. 

In accordance with the requirements of 40 CFR §51.308(d)(1), this Regional Haze SIP 

establishes RPGs for the Sipsey Wilderness area in Alabama. To calculate the rate of progress 

represented by each RPG, ADEM compared baseline visibility conditions to natural visibility 

conditions at the Sipsey Wilderness area and determined the uniform rate of visibility 

improvement (in deciviews) that would need to be maintained during each implementation 

period in order to attain natural visibility conditions by 2064. ADEM has summarized expected 

visibility improvements under existing federal and state regulations, BART determinations in 

Alabama and neighboring states, and any additional control measures found to be reasonable to 

implement in this review period. These controls will be modeled in CMAQ as part of the LongTerm Strategy (LTS). At this time ADEM has determined that the RPGs will be at least as 

stringent as the uniform rate of progress “glidepath”. VISTAS has already demonstrated that the 

2018 Base G2a control scenario provides for an improvement in visibility better than the uniform 

rate of progress for the Sipsey Wilderness area for the most impaired days over the period of the 

implementation plan and ensures no degradation in visibility for the least impaired days over the 

same period. In addition, it is expected that IMPROVE monitoring results for 2018 will at that 

time be used to establish a new baseline for the next planning period. 

 Appendix H - 38 
Table 10-1. Alabama RPGs for the Sipsey Wilderness Area. 

Class I Area Baseline 

Visibility 

(dv) 

RPG (dv) Improvement 

Expected by 2018, 20% 

Worst Days) 

RPG (Expected 

Visibility Improvement, 

20% Best Days) 

Dv Improvement 

Needed 2018-2064 

(20% Worst Days) 

Sipsey 

Wilderness 29.03 6.62 1.43 12.35 

A final CMAQ modeling run was performed in the winter of 2007 to account for the cumulative 

benefits of the Base G2a emissions controls, BART controls, and additional measures to achieve 

reasonable progress by 2018. 

 Appendix H - 39 
 Appendix H - 40 

REFERENCES: 

1. Boylan Ph.D., James, 2006, VISTAS Joint Tech Analysis-Planning Call. Power Point 

Presentation: Summary BART_VOC_NH3_PM.ppt. 

2. Brewer, P.F.; and Adloch, J.P., 2005, Trends in Speciated Fine Particulate Matter and 

Visibility across Monitoring Networks in the Southeastern United States. J Air and Waste 

Management Association, 55, 1663-1674. 

3. Federal Register / Vol. 70, No. 128 / Wednesday, July 6, 2005 / Rules and Regulations. 

4. Hand, J.L.; and Malm, W.C.,2006, Review of the IMPROVE Equation for Estimating 

Ambient Light Extinction Coefficients - Final Report. March 2006. Prepared for 

Interagency Monitoring of Protected Visual Environments (IMPROVE), Colorado State 

University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO. 

5. MACTEC, 2006, Documentation of the Base G 2002 Base Year, 2009 and 2018, 

Emissions Inventory VISTAS. 

6. Pechan, E.H., and Associates, Inc., 2005, AirControlNET User Guide. 

7. Pitchford, Marc., 2006, Natural Haze Levels II: Application of the New IMPROVE 

Alogrithm to Natural Species Concentrations Estimates. Final Report of the Natural 

Haze Levels II Committee to the RPO Monitoring/Data Analysis Workgroup. Sep 2006. 

8. Sorrels, Larry, 2006, AirControlNET 4.1 Software; US EPA, OAQPS, Research Triangle 

Park, NC. 

9. U.S. Environmental Protection Agency. (2003). Guidance for Tracking Progress under 

the Regional Haze Program; EPA-54/B-03-004, 2003. 
Appendix H 

Reasonable Progress Evaluation 

and Long Term Strategy 

 
6.0 FOUR FACTOR ANALYSIS 

Section 169A(g)(1) of the Clean Air Act (CAA) and 40 CFR 51.308(d)(1)(i)(A) 

outline four statutory factors that have been identified as mandatory for purposes of establishing 

reasonable progress goals (RPGs) for any mandatory Class I area within a State: cost of 

compliance, time necessary for compliance, energy and non-air quality environmental impacts of 

compliance, and remaining useful life of any existing source subject to such requirements. These 

statutory factors would be specific to the sources being considered for additional controls. 

6.1 The Four Statutory Factors 

6.1-1 Cost of Compliance 

The “cost of compliance” is a factor used to determine whether compliance costs for sources are 

reasonable compared to the emission reduction and visibility improvement they will achieve. 

Note that visibility improvement is not only related to tons of pollutant removed, but also 

involves how the pollutant or chemical compound affects the extinction coefficient in each Class 

I area. For example, on a pound to pound comparison, sulfate particulate impairs visibility 

greater than coarse particulate. Costs should be determined for one-time capital costs, as well as, 

ongoing annual operation and maintenance. 

6.1-2 Time Necessary for Compliance

The “time necessary for compliance” factor may be used to adjust the RPGs to reflect the degree 

of improvement achievable within the long-term strategy (LTS) period, as opposed to the 

improvement expected at full implementation of a control measure, if the time needed for full 

compliance exceeds the length of the LTS period. For instance, if implementation of a control 

measure could not be completed within the schedule outlined by the control strategy, the RPG 

should reflect what visibility improvement could be expected within the strategy period. 

For example, if construction labor availability constraints preclude the installation of controls at 

all sources of a particular category within the LTS period, the RPG should reflect the visibility 

improvement anticipated from installation of controls at the percentage of sources that could be 

controlled within the strategy period. (The SIP could still include control strategies that extend 

beyond the 2018 milestone; in the above example, the visibility improvement anticipated from 

installation of controls at the percentage of sources that could not be controlled within the first 

strategy period would have to be counted in a later SIP). 

6.1-3 Energy and Non-Air Quality Environmental Impacts of Compliance 

The “energy and non-air quality environmental impacts of compliance” factor is meant to 

consider whether the energy requirements of the control technology result in energy penalties or 

benefits. For example, controls on diesel engines may decrease the overall efficiency and require 

a significant increase in diesel fuel consumption. The State should also consider any significant 

or unusual non-air environmental impacts, such as a waste stream that may be generated by a 

particular control technology 

 Appendix H - 1 
6.1-4 Remaining Useful Life of the Source 

The statutory factor of the “remaining useful life of the source” is applicable only to those 

measures, which would require retrofitting of control devices (or possibly production changes) at 

existing sources. In such cases, this factor should be treated as one element of the overall cost 

analysis. For purposes of this analysis, the remaining useful life is the difference between the 

year of the reasonable progress analysis and the date the facility permanently stops operations. 

The remaining useful life of a source affects the annualized costs of retrofit controls. 

6.2 Evaluating Four Statutory Factors for Specific SO2 Emissions Sources in Each Area of 

Influence (AoI) 

The next step was to identify emission reductions that have already occurred within each source 

category and at specific units. Unit level tables of emission comparisons from 2002 to 2018 

were developed, allowing VISTAS States to review existing emission reductions. These tables 

assigned future year control technology from IPM forecasting and State modification for EGU 

and from control efficiency tables for non-EGU point sources. 

Once emission control profiles for specific units were defined, the next step is to determine what, 

if any, additional control measures would feasibly be available, and to assign costs to those 

control measures. 

For EGUs, the 2018 IPM file used by VISTAS for EGU sources was obtained and matched to 

the 2018 base case inventory of EGU sources. This step was conducted to ensure that 

incremental controls assigned to these source types did not duplicate existing base case 

assumptions. 

The Regional Haze Rule (RHR) requires that states consider the following factors and 

demonstrate how these factors were taken into consideration in selecting the RPG: 

• the costs of compliance 

• the time necessary for compliance 

• the energy and non-air quality environmental impacts of compliance, and 

• the remaining useful life of any potentially affected sources. 

6.2-1 Cost of Compliance 

Coal-fired electric utilities and coal-fired industrial boilers were the largest source categories 

contributing to SO2 in 2018 in the AoI defined for the Sipsey Wilderness area. Industrial boilers 

using oil and commercial and institutional boilers using coal or oil had smaller contributions to 

SO2 in 2018. 

Sulfur dioxide emissions from utility, industrial, commercial, or institutional boilers can be 

controlled either by switching the fuel source to a lower sulfur fuel content or by installing postcombustion controls. Costs vary by fuel source and boiler type and require source specific 

analyses for accuracy. 

 Appendix H - 2 
Bituminous coal is commonly burned in boilers in the eastern U.S. Switching to another 

bituminous coal with lower sulfur content or blending bituminous coals can reduce SO2

emissions with least impact to boiler performance. While sub-bituminous coal has a lower sulfur 

content than bituminous coal, it also has a lower heat rate and so more coal has to be burned to 

generate the same energy output. For boilers that are designed for bituminous coal, only a small 

fraction of the fuel can be switched to low sulfur sub-bituminous coal without affecting boiler 

operations. Costs of boiler modifications to accommodate low sulfur sub-bituminous coal may 

make switching to sub-bituminous coal impractical. Contract initiation and termination costs, 

differential fuel prices and heat rates, transportation costs, and modification to boiler operations, 

fuel handling and waste handling systems will have to be considered specific to each source. 

Flue-gas desulfurization is the common post-combustion control for coal-fired boilers. Flue gas 

is passed through an absorbent for sulfur dioxide (generally limestone or lime) in either a wet 

scrubber, dry scrubber, or spray dryer. A calcium sulfate byproduct is produced that may be 

further processed to produce gypsum as a commercial byproduct. Costs of flue-gas 

desulfurization include initial construction costs and ongoing operational and maintenance costs 

for the absorber tower, sorbent handling, and waste product handling facilities. Costs per ton 

vary with boiler size, type, and facility siting considerations. 

For oil-fired boilers, lower sulfur oil may be an option. Costs need to consider differential fuel 

prices and heat rate, boiler modifications, fuel handling costs, and maintenance costs. 

Conceptually, post-combustion controls can be used for oil boilers, but there is little precedence 

for such installations. 

6.2-2 Time Necessary for Compliance 

For fuel switching, the time necessary to terminate existing fuel contracts and initiate new 

contracts needs to be considered. Generally two to three years may be required. Instillation of 

post-combustion controls will require three or more years depending on market availability of 

labor and materials and utility system-wide priorities. Time necessary for compliance will need 

to be refined for specific sources. 

6.2-3 Energy and Non-Air Environmental Impacts 

Switching to lower sulfur fuel or installing post-combustion controls may reduce boiler heat rate 

and energy output. Scrubbers and spray dryers will require additional safeguards for fuel 

handling and waste handling systems to avoid additional non-air environmental impacts such as 

increased effluents in waste water discharges and storm water runoff. These factors will need to 

be considered specific to individual sources. Carbon dioxide may be emitted as a byproduct of 

flue gas desulfurization (particularly if limestone is used), therefore impacts of increased carbon 

emissions will need to be considered, especially if carbon emissions are limited in the future 

under climate change mitigation strategies. 

6.2-4 Remaining Useful Life 

 Appendix H - 3 
 Remaining useful live is specific to the facility for which controls are considered. 

6.3 Process of Applying Statutory Factors 

ADEM has completed its Reasonable Progress Assessment for the first Regional Haze SIP. The 

following is ADEM’s Process on Reasonable Progress for the current time period (from the 

present to 2018): 

Step 1: Determine pollutants of concern. 

VISTAS evaluated the species contribution on the 20% worst visibility days and concluded that 

sulfate accounted for greater than 70% of the visibility impairing pollution. The VISTAS States 

concluded that controlling SO2 emissions was the appropriate step in addressing the Reasonable 

Progress Assessment for 2018. The VISTAS findings were consistent with the findings of the 

Southern Appalachian Mountain Initiative (SAMI). SAMI confirmed that sulfate particles 

account for the greatest portion of the haze affecting Class I areas in the Southern Appalachian 

region and that these sulfates were produced in large part from SO2 emissions from coal 

combustion. 

Step 2: Determine which source sectors should be evaluated for reasonable progress. 

Since SO2 point source emissions in 2018 are projected to represent greater than 95% of the total 

SO2 emissions inventory, the VISTAS States concluded that the focus should be on electric 

generating utility (EGU) and non-EGU point sources of SO2 emissions. 

Step 3: Determine if the Clean Air Interstate Rule (CAIR) is sufficient for reasonable progress 

for subject EGU’s. 

ADEM evaluated the amount of SO2 reduction from the EGU sector resulting from the 

implementation of CAIR. The EGUs in Alabama are expected to reduce their SO2 emissions by 

approximately 70% between 2002 (2002 emissions approximately 447,828 tons per year) and 

2018 (2018 emissions approximately 135,851 tons per year). ADEM intends to re-evaluate the 

IPM predictions of SO2 reductions for CAIR at the time of the next periodic report in 2012 to 

ensure that the reductions currently predicted by IPM for CAIR are in fact taking place. As such, 

ADEM has concluded that at this time the CAIR program constitutes reasonable measures for 

Alabama EGUs during this first assessment period (between baseline and 2018). 

Step 4: Determine which emission units would be evaluated based on impact. 

ADEM calculated the fractional contribution from all emission units within the SO2 AoI for a 

given Class I area and identified those emission units with a contribution of 1% or more. 

 Appendix H - 4 
Step 5: Evaluate the four factors. 

Each emission unit identified in Step 4 above was evaluated using the statutory and regulatory 

factors of 1) cost of compliance, 2) time necessary for compliance, 3) the energy and non-air 

quality environmental impacts of compliance, and 4) the remaining useful life of the emissions 

unit. ADEM believes that the cost of compliance is the typically the dominant factor in whether 

a source will be required to install controls. Therefore, most of the emphasis was placed on cost 

of control as part of this reasonable progress assessment, as compared to the other three statutory 

factors. In addition, ADEM believes that a fifth factor, visibility improvement, is considered by 

focusing the evaluation on those units that contribute at least 1% to visibility impairment at a 

given Class I area. 

For the limited purpose of evaluating the cost for the Reasonable Progress Assessment in this 

first Regional Haze SIP, ADEM believes it is not equitable to require non-EGUs to bear a greater 

economic burden than EGUs for a given control strategy. Using the CAIR rule as a guide, a cost 

of $2,000 was used as a determiner of effectiveness. 

Based on the AoI analysis, ADEM focused the reasonable progress assessments on specific units 

at the following non-EGU facility in the State based on the 1% criteria discussed later in this 

document: 

Cargill Sweeteners North America 

The following is a summary of the assessment for the facility. 

Cargill Sweeteners North America Decatur, Alabama 

Unit on an AOI list with control options with costs < $10K/ton: 

Keeler Stoker Boiler; 179.74 mm BTU/hr; sulfur content used since 1999 ranges from 1.2 to 

1.3 lb/MMBtu 

The following control technology options were considered for the above mentioned unit: 

 Lower sulfur coals 

 Wet scrubbers 

 Dry scrubbers 

Cargill evaluated switching to lower sulfur content coals. Currently, the company is using 

1.49% sulfur coal in the Keeler Stoker boiler a BACT limit resulting from a PSD review in 1998, 

Cargill states that lower sulfur coal would have to be obtained from western USA, such as 

Powder River Basin, to achieve any reductions in SO2. According to the company, available 

information indicates that lower sulfur coal is largely under contract and may not be available to 

new users. Cargill also states that their boiler was not designed to burn a low sulfur western coal 

and would require significant modification to accommodate this type coal. Cargill further states 

that burning such coal would compromise their combustion integrity due to a higher dust content 

that would result in an increase risk of spontaneous combustion in bunkers, silos, and hoppers. 

 Appendix H - 5 
Due to availability and restriction on boiler design, Cargill determined that this option was not 

technically feasible. 

Cargill also evaluated add-on controls. Specifically, Cargill evaluated wet and dry scrubbers. 

The typical SO2 content of the coal currently burned in Keeler Stoker boiler is 1.3 lb/MMBtu. 

Based on an annual heat input of 1.2x106 MMBtu/yr, a baseline mass emission would equate to 

780 TPY of SO2. Based on this information, Cargill estimates that it would cost $2,946/ton to 

control SO2 emissions with these technologies. 

It should also be noted that Cargill has entered into a Consent Decree agreement with EPA and 

affiliated states that would reduce SO2 emissions by 50% from current levels at its US plants. 

Summary:

During the current reasonable progress assessment no units in Alabama were identified for 

additional control since no measures were found to be below the $2,000 cost threshold 

(discussed in Step 5). In addition to costs, the statutory factors include time necessary for 

compliance, remaining useful life of the facility, and energy and non-air environmental impacts 

of the control installation. However, since no cost effective control measures were identified for 

these specific sources with contributions to Alabama or neighboring States’ Class I areas, ADEM 

did not invest in an exhaustive review of the remaining three factors beyond those described 

control options for major SO2 source sectors. 

It should be noted that, in order to show continued progress past 2018, the criteria will likely be 

different in the next reasonable progress assessment in order to maintain a continuous downward 

glidepath toward natural background conditions by 2064, and while no additional controls were 

identified during this reasonable progress assessment, possible SO2 reduction strategies will be 

evaluated for the next round of regional haze State Implementation Plan (SIP) development. 

7.0 Best Available Retrofit Technology (BART) 

7.1 Background

As required by the CAA, EPA included in the final RHR a requirement for BART for certain 

large stationary sources that were placed in operation between 1962 and 1977. The BARTeligible sources are those sources which have the potential to emit 250 tons or more of a 

visibility-impairing air pollutant, were placed in operation between August 7, 1962 and August 

7, 1977, and whose operations fall within one or more of 26 specifically listed source categories. 

Under the CAA, BART is required for any BART-eligible source that a State determines ‘‘emits 

any air pollutant which may reasonably be anticipated to cause or contribute to any impairment 

of visibility in any such area.’’ Accordingly, for stationary sources meeting these criteria, States 

must address the BART requirement when they develop Regional Haze SIPs. 1

 EPA has set 

guidance for identifying BART-eligible sources in 40 CFR Part 51 Appendix Y. 

 Appendix H - 6 
A BART-eligible source that is responsible for a 1.0 deciview (dv) change or more is considered 

to “cause” visibility impairment. Although the appropriate threshold may vary, the guidelines 

state that the contribution threshold used for BART applicability should not be higher than 0.5 

deciviews (dv).1 Thus, a BART-eligible source that is responsible for a 0.5 dv change or more is 

considered to “contribute” to visibility impairment. Any source determined to cause or contribute 

to visibility impairment in any Class I area is subject to BART. 

The guidelines direct that States should include SO2, NOx, and direct particulate matter (PM) 

emissions, including both PM10 and PM2.5, in determining whether sources cause or contribute to 

visibility impairment. States may use their best judgment to determine whether VOC or 

ammonia emissions are likely to have an impact on visibility in an area.1 

To determine which BART-eligible sources are subject to BART, states have several options. A 

State may consider all BART-eligible sources subject to BART; may perform an analysis 

showing that the full group of BART-eligible sources in a State cumulatively may not be 

reasonably anticipated to cause or contribute to any visibility impairment in any Class I areas; or 

may consider the individualized contribution of a BART-eligible source to determine whether a 

specific BART-eligible source is subject to BART. 

Sources that are subject to BART must undergo a BART determination. Section 169A(g)(7) of 

the CAA requires that States must consider the following factors in making BART 

determinations: (1) The costs of compliance, (2) The energy and non-air quality environmental 

impacts of compliance, (3) Any existing pollution control technology in use at the source, (4) 

The remaining useful life of the source, and (5) The degree of improvement in visibility which 

may reasonably be anticipated to result from the use of such technology. 1 

To demonstrate the degree of improvement in visibility from various BART control options, the 

States may run CALPUFF or another appropriate dispersion model to predict visibility impacts. 

Scenarios would be run for the pre-controlled and post-controlled emission rates for each of the 

BART control options under review. The maximum 24 hour emission rates would be modeled 

for a period of three or five years of meteorological data. States have the flexibility to develop 

their own methods to evaluate model results. 1 

7.2 Approach to Implementation of BART Requirements 

In order to meet the SIP submittal deadline, Alabama used a multifaceted approach to implement 

the RHR BART requirements. The approach consists of source identification efforts, use of a 

permitting process to establish any resulting BART limits for inclusion in the SIP submittal as 

well as participation in VISTAS BART subgroup to resolve technical issues spanning states in 

the VISTAS region, and ongoing consultation with affected sources, and EPA and FLMs 

throughout the BART process. 

 Appendix H - 7 
7.3 Identification of BART-Eligible Sources 

EPA provided guidance for identifying BART-eligible sources in 40 CFR Part 51 Appendix Y. 

Alabama followed this guidance in identifying its BART-eligible sources. The Alabama 2002 air 

emissions inventory was reviewed to determine the population of potential BART-eligible 

sources. The data were initially queried for any sources emitting SO2, NOx, PM10, VOC, or 

ammonia. The data set was refined based on emissions, whether emission units fit in any of the 

twenty-six listed source categories for BART, and available date information obtained through 

review of permit and inspection reports and discussion with permitters and regional office staff 

familiar with the facilities. 

Notification of BART was sent to and additional information was collected from the sources 

regarding potential emissions and BART eligibility from the standpoint of source category and 

date criteria. Through this iterative review process, the list of potential BART-eligible sources 

was pared down to the 40 BART-eligible sources listed below. The facilities include eight 

electric utilities, nine pulp and paper facilities, four chemical manufacturers, three natural gas 

processing facilities, three limestone manufacturers, two oil refineries, three cement 

manufacturers, three iron and steel mills, one coking by-products manufacturer, one coal 

cleaning operation, and one secondary lead smelter. 

Alabama BART Eligible Facility List: 

3M Company, Decatur Plant Hunt Refining Co, Tuscaloosa 

Alabama Electric Coop Lowman International Paper Co Prattville 

Alabama Power Co Barry International Paper Co Riverdale 

Alabama Power Co EC Gaston International Paper Co Courtland 

Alabama Power Co Gorgas JSC Brewton (Smurfit Stone) 

Alabama Power Co Greene Co Lehigh Cement – JCDH 

Alabama Power Co Miller- JCDH MeadWestvaco Mahrt Mill 

American Cast Iron Pipe- JCDH National Cement Co of Alabama 

Boise White Paper Oak Grove Resources- JCDH 

Bowater Inc.- Alabama Sanders Lead Co 

BP Amoco Chemicals Shell Chemical Co Saraland 

Carmeuse Lime & Stone Solutia- Decatur 

CEMEX, Inc. Sloss Industries- JCDH 

Chemical Lime Co Alabaster TVA, Colbert 

Chemical Lime Co Montevallo TVA, Widows Creek 

Ciba Specialty Chemicals Corp US Pipe & Co- Bessemer- JCDH 

ConocoPhillips Co Chatom US Steel- Fairfield- JCDH 

Degussa Corporation Weyerhaeuser 

Escambia Operating Co Big Escambia Creek Wise Alloys LLC, Alloys Plant 

Ft Jms-Pennington, Naheola Vintage Petroleum, Inc, Flomaton 

A spreadsheet of Alabama’s BART-eligible source emissions is included as Attachment H-3. A 

spreadsheet of Alabama’s BART-eligible sources’ SO2 emissions and distance to Class I areas is 

included as Attachment H-4. 

 Appendix H - 8 
Alabama’s BART-eligible sources were presumed to be subject to BART but were provided the 

opportunity to submit modeling demonstrations showing that they did not contribute to visibility 

impairment, i.e., had less than 0.5 deciview (dv) impact, on any Class I area within 300 km. 

Baldwin

Barbour

Chambers

Chilton

Choctaw

Cleburne 

Coffee

Butler

Coosa

Covington

Cullman

Dale

Elmore

Escambia

Etowah

Cherokee

Fayette

Geneva

Hale

Henry

Houston

Jackson

 De 

Lamar

Lauderdale

Limestone

Colbert

Franklin

 Lawrence

Lowndes

Macon

Lee

Russell

Madison

Marion

Marshall

Morgan

Mobile

Washington

Clarke

Monroe

Conecuh

Montgomer

y

 

Perry

Pickens

Pike

 Crenshaw

Bullock

Blount

Shelby

Talladega

St Clair

Clay

Calhoun

Sumter

 

Wilcox

Marengo

Dallas

Tuscaloosa

Bibb

Walker

Jefferson

 

Sipsey 

Wilderness

Autauga

Figure 7-1. Alabama’s BART-Eligible Sources 

 

 Appendix H - 9 
7.4 Contribution Threshold 

Determining whether a source causes or contributes to visibility impairment is one step in the 

BART review process. The Guidelines for BART Determinations Under the Regional Haze 

Rule1

 state that “A single source that is responsible for a 1.0 deciview change or more shou

considered to ‘cause’ visibility impairment.” The guideline document also states that “the 

appropriate threshold for determining whether a source ‘contributes to visibility impairment’ 

may reasonably differ across states,” but, “As a general matter, any threshold that you use for 

determining whether a source ‘contributes’ to visibility impairment should not be higher than 0.5 

deciviews.” The rationale for these instructions is provided in the preamble to the BART 

guidance, in the statement, “If ‘causing’ visibility impairment means causing a humanly 

perceptible change in visibility in virtually all situations (i.e. a 1.0 dv change), then 

‘contributing’ to visibility impairment must mean having some lesser impact on the conditions 

affecting visibility that need not rise to the level of human perception.”

ld be 

 

2

 The Guidance itself also 

states that, “States remain free to use a threshold lower than 0.5 dv if they conclude that the 

location of a large number of BART-eligible sources within the State and in proximity to a Class 

I area justify this approach.” 

The EPA’s documents strive to set these thresholds in the context of the human perception of 

visibility change. As noted above, the EPA considers a 1.0 dv change in visibility to be humanly 

perceptible “in virtually all situations.” Also, the preamble to the BART guidance3

 cites an 

analysis in an appendix of a NAPAP (National Acid Precipitation Assessment Program) report, 

which asserts that “changes in light extinction of 5% will evoke just noticeable changes in most 

landscapes.” 4 (A 5% change is approximately 0.5 dv.) But, as noted above, the preamble also 

states that perceptibility is not a prerequisite for choosing a contribution threshold. Putting all 

this together, it appears that “causing” visibility impairment means having a humanly perceptible 

impact (for which EPA considers the practical threshold to be 1.0 dv) while “contributing” to 

visibility impairment means having a smaller impact (for which EPA considers the threshold to 

be 0.5 dv or some smaller value) that may or may not be perceptible. 

ADEM retained the threshold of 0.5 dv for evaluating significance. First, there is a clear spatial 

variability of sources across the state which can be seen in Figure 7-2. Additionally, ADEM is 

electing to use half of the threshold established by EPA for causing visibility impairment. 

Lastly, the BART rule is a source specific rule and ADEM does not have a technical justification 

for lowering the threshold based on concerns of multiple plume interaction. As such, ADEM 

concluded that the EPA suggested contribution threshold of 0.5 dv was appropriate in for 

evaluating facility contributions at Class I areas that Alabama sources impact. 

1

 40 CFR 51, Appendix Y, Section III.A.1 

2

 70 FR 39120. Footnote 31 

3

 70 FR 39119. Footnote 28 

4

 “The Quadratic Detection Model” by W. Malm. Appendix D in Acidic Deposition: State of Science and 

Technology, Report 24, Visibility: Existing and Historical Conditions -- Causes and Effects. National 

Acid Precipitation Assessment Program, Washington, DC. 1990. 

 Appendix H - 10 
Figure 7.2 Location of VISTAS BART-Eligible Sources 

7.5 Exemption of Point Source Volatile Organic Compounds (VOCs) for BART Purposes 

The State of Alabama has determined through modeling that VOCs from point sources are not 

anticipated to cause or contribute significantly to the impairment of visibility in any Class I area 

and should be exempt for BART purposes. 

7.5.1 Method 

It was determined through modeling that VOCs from point sources are not anticipated to cause 

or contribute significantly to the impairment of visibility in any Class I area. 

Modeling was conducted through the Visibility Improvement State and Tribal Association of the 

Southeast (VISTAS). VISTAS is a collaborative effort of state governments, tribal governments, 

and various federal agencies established to initiate and coordinate activities associated with the 

management of regional haze, visibility and other air quality issues in the Southeastern U.S. 

VISTAS contracted with Georgia Institute of Technology (GA Tech) to perform model 

sensitivity runs to determine the impact of point source VOCs on visibility in Class I areas. 

 Appendix H - 11 
GA Tech performed emission sensitivities to examine the impact of emission reductions on 

Regional Haze, annual PM2.5, and 8-hour Ozone concentrations using CMAQv4.4_SOAmods on 

the VISTAS 12 km modeling domain, using the 2009 OTW (on the way) Base D emissions. 

One such sensitivity run reduced anthropogenic, point source VOCs by 100%. The purpose was 

to quantify the impact of VOC emissions from VISTAS BART sources on Class I areas. Two 

episodes were examined: June 1-July 10, 2002 and November 19 – December 19, 2002. The 

approach included calculating the extinction coefficient in deciviews (dv), then determining the 

maximum impact of point source VOCs. Figure 7-3 shows the impact on the following twentytwo Class I areas within the VISTAS domain. 2 

BRET = Breton, LA 

BRIG = Brigantine NWR, NJ 

CACR = Caney Creek, AR 

CHAS = Chassahowitzka, FL 

COHU = Cohutta, GA 

DOSO = Dolly Sods, WV 

EVER = Everglades, FL 

GRSM = Great Smoky Mountains National Park 

HEGL = Hercules Glade, MO 

JARI = James River Face, VA 

LIGO = Linville Gorge, NC 

MACA = Mammoth Cave, KY 

MING = Mingo, MO 

OKEF = Okefenokee, GA 

ROMA = Cape Romain, SC 

SAMA = Saint Marks, FL 

SHEN = Shenandoah, VA 

SHRO = Shining Rock, NC 

SIPS = Sipsey Wilderness, AL 

SWAN = Swanquarter, NC 

UPBU = Upper Buffalo Wilderness, AR 

WOLF = Wolf Island, GA 

 Appendix H - 12 
Maximum Point VOC Impact

Maximum VOC Impact

0.0

0.1

0.2

0.3

0.4

0.5

0.6

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV

Figure 7-3. Maximum Point VOC Impact in VISTAS and surrounding Class I Areas. 

7.5.2 Conclusions 

The results show that the maximum impact from eliminating all point source VOC emissions in 

the VISTAS 12 km domain is less than a 0.5 dv for all Class I areas in the VISTAS domain. 

Given that the fraction of the total point source VOC emissions would be less than the emissions 

from BART-eligible sources in Alabama, the expected impact of controlling VOCs from a 

BART source would be much less than the 0.5 dv threshold. Therefore, VISTAS and the State 

of Alabama concluded that VOCs from point sources are not a visibility impairing pollutant for 

BART purposes and that BART-eligible sources do not need to consider VOC emissions. 

7.6 Treatment of Ammonia (NH3) Emissions for BART Purposes 

Similar to its treatment of VOCs, EPA guidance allows States the discretion to decide whether or 

not NH3 emissions are to be considered for BART purposes based on evaluations of the 

contributions of the emissions to haze at Class I areas. One approach a State can use to determine 

whether applying BART will be needed is to evaluate the haze impacts of all BART-eligible 

emissions of NH3. If the impact at the Class I area is less than the contribution threshold 

established by the State, 0.5 dv for Alabama, then source by source analysis for BART is not 

needed. 

The State of Alabama has determined through modeling that NH3 emissions from point sources 

are not anticipated to cause or contribute significantly to any impairment of visibility in Class I 

areas and should be exempt for BART purposes. 

 Appendix H - 13 
7.6.1 Method 

It was determined through modeling that NH3 emissions from point sources are not anticipated to 

cause or contribute significantly to any impairment of visibility in any Class I area affected by 

Alabama sources. 

VISTAS contracted with GA Tech to perform model sensitivity runs to determine the impact of 

point source NH3 on visibility in Class I areas. 

GA Tech performed emission sensitivities to examine the impact of emission reductions on 

Regional Haze using CMAQv4.5 with SOA mods on the VISTAS 12 km modeling domain, 

using the VISTAS 2009 OTW (on the way) Base F4 emissions. One such sensitivity run 

reduced BART-eligible source ammonia by 100%. The purpose was to quantify the impact of 

NH3 emissions from VISTAS BART sources on Class I areas. Two episodes were examined: 

June 1-July 10, 2002 and November 19 – December 19, 2002. The approach included 

calculating the extinction coefficient in deciviews (dv), then determining the maximum impact of 

BART-eligible source NH3. Figure 7-4 below, taken from the VISTAS report BART in the 

VISTAS Region: Sensitivity to VOC, NH3, and Primary PM Emissions, included as Attachment 

H-4, shows the impact on the following twenty-two Class I areas within the VISTAS domain. 2 

Maximum NH3 Impact

0.0

0.5

1.0

1.5

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV

 Figure 7-4. Maximum NH3 Impact - Maximum contributions of all BART-eligible NH3 point 

sources in the VISTAS region to haze in Class I areas during the CMAQ-modeled periods. 

The chart shows the largest haze impact in delta dv over the two timeframes at each Class I area. 

These delta dv changes represent the haze contribution of all BART source ammonia emissions 

relative to assumed natural haze levels. The natural haze levels are based on EPA-default annual 

average natural concentrations for the East and monthly-varying “climatologically 

representative” relative humidity at each Class I area. 

 Appendix H - 14 
During the periods modeled, the NH3 emissions from all BART-eligible sources contributed 

more than 0.5 dv to haze at Mammoth Cave National Park (MACA), Kentucky; Mingo 

ilderness (MING), Missouri, Cape Romain National Wildlife Refuge Area (ROMA) South 

he majority of ammonia emissions in VISTAS region come from four BART-eligible sources 

as shown in Tab

e

St NH3 E

(tpy) 

Distance to Nearest 

Class 1 Area (km) 

W

Carolina, and Swanquarter National Wildlife Refuge (SWAN), North Carolina. 

T

le 7-1 below. 

Table 7-1. Major BART NH3 Sources in th VISTAS Region 

Facility ate missions 

Meadwestvaco Corp. SC 174 30 

PCS Phosphate NC 206 31 

PCS Nitrogen TN 1252 180 

PCS Nitrogen GA 1765 220 

None of the above sources are significant contributors to the Sipsey Wilderness area. 

to be 

s 

retion 

ing 

 Alabama has concluded that NH3 emissions from point sources are not 

 visibility impairing pollutant for BART purposes and that BART-eligible sources need not 

onsider NH3 emissions. 

n of BART Exemption Modeling 

ns over a 24 hour 

veraging period. The BART guidelines also propose that the threshold at which a source may 

7.6.2 Conclusions 

The BART requirements of the RHR allow states to determine whether or not ammonia is 

considered a visibility impairing pollutant to be addressed for BART purposes. NH3 emission

from BART sources may impair visibility; however the majority of NH3 emissions in the 

VISTAS region are from a few BART sources. Removal of the large NH3 emission sources 

results in minimal impact on visibility at Class I areas in the VISTAS region. At their disc

states may ask those few large sources to evaluate NH3 impacts and potential controls for NH3. 

Based on the CMAQ sensitivity analyses of the impact of ammonia emissions, Alabama 

identified no large sources of ammonia emissions affecting the Sipsey Wilderness or neighbor

Class I areas. As a result,

a

c

8.0 Explanatio

8.1 Background 

Alabama opted to consider its BART-eligible sources subject to BART unless the source 

demonstrated exemption via modeling. BART-eligible sources can be excluded from BART 

determinations by demonstrating that the source cannot be reasonably expected to cause or 

contribute to visibility impairment in a Class I area. The threshold for determining that a source

causes visibility impairment is set at 1.0 dv change from natural conditio

a

“contribute” to visibility impairment should not be higher than 0.5 dv. 

 Appendix H - 15 
As stated in the BART regulation, EPA’s preferred approach for determining cause or 

contribution is an assessment with an air quality model such as CALPUFF or other appropriate 

model followed by comparison of the estimated 24 hour visibility impacts against a threshold 

above estimated natural conditions to be determined by the State. EPA recommends that th th

percentile value from the modeling be compared to the State’s chosen contribution threshold to 

determine if a source does not contribute to visibility impairment. Comparison of the 98th

percentile value to the threshold must be made for each Class I area. For an annual period, th

implies the 8th highest 24 hr value at a particular Class I area is compared to the contribution 

threshold. For a 3-year modeling period, the 98th percentile value may be in

th

e 98

is 

terpreted as the 

highest of the three annual 98 percentile values at a particular Class I area or the 22nd highest 

of the 

e 

was established to 

rovide the basis for a common understanding among the organizations performing BART 

or 

, 

 specific 

commendations for its application for BART purposes are found in Chapter 4, and specific 

evelop a version of the CALPUFF model appropriate for 

BART purposes. The VISTAS version of the CALPUFF modeling system is CALPUFF Version 

setting 

ed in addition 

 MM5 meteorological model outputs. Specific model settings were provided with the 

r actual 

missions were not available, continuous emission data, permit allowable emissions, potential 

value in the combined three year record, whichever is more conservative. 

ADEM worked with the Regional Planning Organization (RPO) VISTAS on development 

VISTAS Protocol for the Application of the CALPUFF Model for Analyses of Best Availabl

Retrofit Technology (BART) (Attachment H-5). The common protocol 

p

analyses or reviewing BART modeling results in the VISTAS region. 

The VISTAS protocol describes common procedures for carrying out air quality modeling to 

support BART determinations that are consistent with the 40 CFR Part 51 Appendix Y 

guidelines. The protocol provides a consistent model, CALPUFF, and modeling guidelines f

BART determinations, clearly delineated modeling steps, a common CALPUFF configuration

guidance for site-specific modeling, and common expectations for reporting model results. 

Details of the CALPUFF system can be found in Chapter 3 of the VISTAS protocol,

re

information that should be included in site-specific protocols is found in Chapter 5. 

VISTAS contracted EarthTech to d

5.754 and CALMET Version 5.7. 

For BART modeling purposes, VISTAS made publicly available 12 km CALMET output files 

for the entire VISTAS modeling domain (Eastern U.S.) and provided CALMET output files for

five 4 km grid subdomains covering the VISTAS states and all VISTAS Class I areas as well as 

several peripheral Class I areas. To generate the CALMET input files, the VISTAS contractor 

used the MM5 databases developed by EPA for 2001, VISTAS for 2002, and Midwest RPO for 

2003. For the 12 km grid large domain covering the entire VISTAS region, the No-Obs 

was used. For the 4 km grid, available surface and upper air observations were us

to

CALMET files and via the CALPUFF website so that work could be replicated. 

For CALPUFF modeling, source emissions were to be defined using the maximum 24 hr actual

emission rate during normal operation for the most recent 3 or 5 years. If maximum 24 h

e

emissions, and emission factors from AP-42 source profiles could be used as available. 

 Appendix H - 16 
Key points on specific CALPUFF, CALPOST, and POSTUTIL configuration that were to be 

put. 

 should be used. 

ion under current and natural background 

conditions should be used. In addition, a source may also calculate visibility using the 

dditional discussion of the CALPUFF model and VISTAS recommended settings can be found 

l 

eciview change compared to natural background conditions at each of the Class I areas within 

 

s are found in Attachment H-6. The protocols and demonstrations 

ere reviewed by ADEM’s Industrial Chemicals and Industrial Minerals Sections as well as the 

eir 

 ADEM 

ontributing 0.5 dv impact or greater were considered subject to BART and were required to 

these 

used for BART modeling are: 

• After running CALPUFF for an individual facility, NO3 should be repartitioned in 

POSTUTIL. 

• Ozone data from non-urban monitors should be used as the background ozone in

• The Pasquill-Gifford dispersion method

• In CALPOST Method 6 with monthly average RH for calculating extinction as 

recommended by EPA should be used. 

• EPA default calculations of light extinct

recently revised IMPROVE algorithm. 

A

in the VISTAS protocol in Attachment H-5. 

8.2 Alabama BART Sources Exemption Modeling 

ADEM requested that its sources follow the VISTAS modeling protocol in development of their 

site specific protocols and explain any deviations that they proposed to use. In the site-specific 

modeling demonstrations submitted by Alabama’s BART-eligible sources, the CALPUFF mode

incorporating three years of pre-processed MM5 meteorological data was used to evaluate the 

d

300 km of the source. Both the 4 km and 12 km MM5 datasets prepared by VISTAS were used.

Facilities submitted site-specific modeling protocols and subsequent modeling demonstrations

based upon the VISTAS modeling protocol. The site-specific protocols are found in Attachment 

H-5 and the demonstration

w

Meteorological Section. 

The individual facility modeling demonstrations were shared with both EPA and FLMs for th

review and comment. The resulting comments were in turn shared with the facilities.

worked throughout the process to resolve many of the issues and concerns reflected in their 

comments. ADEM staff reviewed the demonstrations to determine whether sources 

demonstrated impacts of 0.5 deciview (dv) or less on any Class I area within 300 km of the 

source. Sources demonstrating less than a 0.5 dv impact are considered exempt. Sources 

c

proceed to an analysis of what control measures, if any, constitute BART for the source. 

Review of the demonstrations submitted led to the determination of which BART-eligible 

sources were exempt from BART determination requirements. Based upon 

demonstrations, ADEM proposed to exempt 35 facilities. Table 8-1 below provides a summary 

of the impacts of each BART-eligible facility on the affected Class I areas.

 Appendix H - 17 
Table 8-1. BART Exemption Modeling Results 

Impact Class I Grid 

Facility Name Change(DV) Area Spacing 

Alabama Electric Coop Lowman 0.34 Breton 4 km 

Alabama Power Co Barry 0.22 Breton 4 km 

Alabama Power Co EC Gaston 0.17 Sipsey 4 km 

Alabama Power Co Gorgas 0.25 Sipsey 4 km 

Alabama Power Co Greene Co 0.13 Sipsey 4 km 

Alabama Power Co Miller 0.34 Sipsey 4 km 

American Cast Iron Pipe- JCDH 0.082 Sipsey 12 km 

Boise White Paper 0.162 Breton 12 km 

Bowater Inc.- Alabama 0.166 Sipsey 12 km 

BP Amoco Chemicals 0.486 Sipsey 4 km 

Carmeuse Lime & Stone 0.215 Sipsey 12 km 

CEMEX, Inc. 0.308 Breton 4 km 

Chemical Lime Co Alabaster 0.188 Sipsey 4 km 

Chemical Lime Co Montevallo 0.484 Cohutta 4 km 

ConocoPhillips Co Chatom 0.303 Breton 4 km 

Degussa Corporation 0.466 Breton 12 km 

Escambia Oper. Co Big Escambia Crk 0.498 Breton 4 km 

Ft Jms-Pennington, Naheola 0.241 Breton 4 km 

Hunt Refining Co, Tuscaloosa 0.327 Sipsey 4 km 

International Paper Co Prattville 0.271 Sipsey 4 km 

International Paper Co Riverdale 0.246 Sipsey 12 km 

International Paper Co Courtland 2.392 Sipsey 4 km 

JSC Brewton (Smurfit Stone) 0.295 Breton 12 km 

Lehigh Cement – JCDH 0.301 Sipsey 4 km 

MeadWestvaco Mahrt Mill 0.229 St. Marks 4 km 

National Cement Co of Alabama 0.192 Sipsey 4 km 

Oak Grove Resources- JCDH 0.021 Sipsey 12 km 

Sanders Lead Co 0.223 St. Marks 4 km 

Shell Chemical Co Saraland 0.066 Breton 12km 

Sloss Industries- JCDH 0.088 Sipsey 12 km 

Solutia, Inc, Decatur Plant 4.435 Sipsey 4 km 

TVA, Colbert 0.476 Sipsey 4 km 

TVA, Widows Creek 0.183 Cohutta 4 km 

US Pipe & Co- Bessemer- JCDH 0.036 Sipsey 12 km 

US Steel Corporation Fairfield- JCDH 0.205 Sipsey 12 km 

Vintage Petroleum, Inc, Flomaton 0.179 Breton 4 km 

Weyerhaeuser 0.247 Breton 4 km 

 Appendix H - 18 
Additionally, consistent with BART regulation requirements and EPA guidance, BART-eligible 

sources at electric utilities complying with EPA’s Clean Air Interstate Rule (CAIR) that wished 

to demonstrate exemption were allowed to model only direct PM fine emissions. Compliance 

with CAIR constitutes BART for these sources for emissions of NOx and SO2. 

Alabama adopted it CAIR rules with a state effective date of July 2006 and amended these rules 

to comply with EPA’s revisions to the model rule effective April 2007. The final revision of 

Alabama’s CAIR SIP was submitted on March 7, 2007. EPA took final action to approve the 

SIP on October 1, 2007. This rulemaking does not have a direct impact on existing BARTeligible EGUs and should not impact their compliance for BART purposes. 

Eight of Alabama’s BART-eligible sources are electric generating units (EGUs). The EPA has 

determined that, as a whole, the CAIR cap-and-trade program improves visibility more than 

implementing BART for individual sources in states affected by CAIR. A state that opts to 

participate in the CAIR program under part 96 AAA-EEE need not require affected BARTeligible EGU to install, operate, and maintain BART for SO2 or NOx emissions. Given that 

many of the BART-eligible units are installing scrubbers and NOx controls, and since Alabama is 

participating in CAIR and accepts EPA’s overall finding that CAIR “substitutes” for BART for 

NOx and SO2, Alabama’s EGUs were allowed to submit BART exemption modeling 

demonstrations for PM emissions only. All eight EGUs demonstrated that they do not contribute 

to visibility impairment in any Class I area. 

Table 8-3. BART Exemption Modeling Results–EGUs 

Impact Class I Grid 

Facility Name Change(DV) Area Spacing 

Alabama Electric Coop Lowman 0.34 Breton 4 km 

Alabama Power Co Barry 0.22 Breton 4 km 

Alabama Power Co EC Gaston 0.15 Sipsey 4 km 

Alabama Power Co Gorgas 0.25 Sipsey 4 km 

Alabama Power Co Greene Co 0.13 Sipsey 4 km 

Alabama Power Co Miller 0.32 Sipsey 4 km 

TVA, Colbert 0.181 Cohutta 4 km 

TVA, Widows Creek 0.476 Sipsey 4 km 

Two of the facilities were unable to demonstrate less than a 0.5 dv impact via modeling. The 

visibility impact results for these two facilities are included in Table 8-4 below. 

Table 8-4. BART Subject Sources Exemption Modeling Results 

Impact Class I Grid 

Facility Name Change(DV) Area Spacing 

International Paper Co Courtland 2.392 Sipsey 12 km 

Solutia, Inc- Decatur Plant 7.21 Sipsey 12 km 

 Appendix H - 19 
Table 8-5 lists each BART eligible source and the associated Class I areas those facilities 

impacted. 

Table 8-5. Class I Areas within 300 km of Alabama Sources 

* Great Smokies represents Great Smokies and Joyce Kilmer 

Alabama BART-Eligible Class I Area 

Sources SIPS BRET GRSM* COHU SAMA OKEF MACA 

Alabama Electric Coop Lowman X 

Alabama Power Co Barry X 

Alabama Power Co EC Gaston X X 

Alabama Power Co Gorgas X X 

Alabama Power Co Greene Co X 

Alabama Power Co Miller X X 

American Cast Iron Pipe- JCDH X X X 

Boise White Paper X X 

Bowater Inc.- Alabama X X X 

Carmeuse Lime & Stone X X 

CEMEX, Inc. X X 

Chemical Lime Co Alabaster X X 

ConocoPhillips Co Chatom X 

Degussa Corporation X 

EOC Big Escambia Creek X 

Ft Jms-Pennington, Naheola X X 

Hunt Refining Co, Tuscaloosa X 

International Paper Co Prattville X X X 

International Paper Co Riverdale X X 

International Paper Co Courtland X X X X 

JSC Brewton (Smurfit Stone) X X 

Lehigh Cement - JCDH X X X 

MeadWestvaco Mahrt Mill X X X X 

National Cement Co of Alabama X X X 

Oak Grove Resources- JCDH X X 

Sanders Lead Co X 

Shell Chemical Co Saraland X 

Sloss Industries- JCDH X X 

Solutia, Inc, Decatur Plant X X 

TVA, Colbert X X 

TVA, Widows Creek X X X X 

US Pipe & Co- Bessemer- JCDH X X 

US Steel Corp-Fairfield- JCDH X X 

Vintage Petroleum, Inc, Flomaton X X 

Weyerhaeuser X X 

BP Amoco Chemicals X X X X 

Chemical Lime Co Montevallo X X 

 Appendix H - 20 
Thirty eight Alabama BART-eligible sources modeled impacts at the Class I areas within 300 

km, but only two contributed to visibility impairment, both at the Sipsey Wilderness Area. 

Additionally, although several modeled impacts, none of the BART-eligible sources contributed 

to visibility impairment at Class I areas outside of Alabama. 

8.3 Use of New IMPROVE Equation 

During the Regional Haze SIP development process, the IMPROVE Steering Committee made 

recommendations for a new IMPROVE equation. Among other things, the new equation includes 

components that take into account the effects of sea salt and site specific Rayleigh scattering. 

Additional discussion of the new IMPROVE equation can be found in Appendix C. 

VISTAS contracted Dr. Ivar Tombach to develop a post processor to allow CALPOST outputs to 

be used with the new IMPROVE equation. A discussion of the rationale for use of the new 

IMPROVE equation follows. The new IMPROVE postprocessor and instructions are included in 

the request to EPA for approval of its use in Attachment H-11. 

Rationale for Need for Use of New IMPROVE Equation

The new IMPROVE equation is a much better representation of the effects of particulate matter 

on light extinction than the old equation and takes into account the latest scientific understanding 

of several parameters. 

1. The new algorithm overcomes biases of the old algorithm on the haziest days and the 

clearest days as demonstrated by comparing the measured light extinction from 

nephelometers at Class I areas to light extinction calculated using each of the equations. 

2. The new algorithm recognizes spatial and temporal variation in light extinction as size 

distribution of the aerosol changes by increasing extinction efficiency as sulfate, nitrate 

and organics concentrations increase. 

3. The new algorithm incorporates a term to reflect the contribution of fine sea salt and 

its hygroscopic growth with increasing relative humidity recognizing research findings 

showing that fine sea salt can be an important contributor to light extinction in coastal 

areas. 

4. The new algorithm reflects research finding that the mass concentration of particulate 

organic matter in rural areas is greater than represented by the old equation. 

5. The new algorithm includes a NO2 term to represent times when light absorption by 

NO2 is a meaningful contributor to light extinction. 

6. The new algorithm incorporates site-specific Rayleigh scattering values to better 

represent sites close to sea level or with very hot or cold climates. 

With this combination of revisions to the IMPROVE equation, the resulting apportionment of 

extinction to various components is more accurate on the haziest and clearest days. This is 

important for development of emission control strategies since the benefits of control of 

concentrations of each species will be represented more correctly with the new algorithm. 

 Appendix H - 21 
Two of Alabama’s BART eligible sources elected to use the new IMPROVE equation The 

spreadsheet developed by Dr. Tombach to implement the entire new IMPROVE equation for use 

with CALPUFF contains a modification of CALPOST that calculates the light extinction from 

the CALPUFF output. In their review of the spreadsheet and supporting documentation, EPA 

Region 4 staff commented that the VISTAS methodology contained in the spreadsheet developed 

by Dr. Tombach appropriately implements the features of the new IMPROVE equation, with the 

exception of the nitrogen dioxide term. EPA Region 4 further stated that with the addition of 

their recommendation for addressing the NO2 term, the VISTAS methodology to incorporate the 

new IMPROVE equation is acceptable. In addition to its impact for the two non-EGU sources in 

Alabama, use of the full new IMPROVE equation was used in Base G modeling. 

 

Table 8-6. BART Exemption Modeling Results New IMPROVE Equation 

Impact Class I Grid 

Facility Name Change (DV) Area Spacing 

BP Amoco Chemicals 0.486 Sipsey 4 km 

Chemical Lime Co Montevallo 0.484 Cohutta 4 km 

8.4 Source Limits to Exempt from BART 

The BART Guidelines list specific criteria that must be met in order for sources to be considered 

BART eligible. One of the criteria for a source to be considered BART eligible was the limited 

potential emissions from all affected emission units considering all federally enforceable permit 

limits, were greater than 250 tons or more per year of any of these visibility-impairing pollutants: 

SO2, NOx, and PM10.. Alabama had three sources which chose to take emissions limits in order 

to be exempt from the entire BART process. By taking an emissions limit, Gulf States Paper 

Corporation, Kerr-McGee Chemical LLC, and Mobile Energy Services Company no longer have 

BART eligible sources. These limits will be written into and enforced through the permits for 

each applicable source at the facility. 

8.5 Conclusions 

In total 35 of Alabama’s 37 BART-eligible sources were able to demonstrate that they did not 

cause or contribute to visibility impairment in any Class I area within 300 km of the source. Two 

sources used the new IMPROVE equation in efforts to demonstrate exemption. Two sources, 

Solutia, Inc. in Decatur, Alabama, and International Paper Courtland in Courtland, Alabama 

were unable to demonstrate a contribution of less than 0.5 dv at all Class I areas within 300 km 

from their BART-eligible sources which resulted in those sources being considered “subject to 

BART”. These two sources are required to revise the permits for the affected sources. 

Discussion of the BART determinations for these two sources is included in Section 9.0 below. 

A spreadsheet summarizing all the BART-eligible sources in Alabama, the distance to and 

impact on Class I areas, version(s) of the IMPROVE equation used and difference in results, 

whether a BART determination was required, the facilities’ potential emissions, the version of 

 Appendix H - 22 
CALPUFF and its components used, who conducted the modeling, existing controls, and 

proposed controls resulting from BART determinations is included as Attachment H-12 

The BART Guidelines list specific criteria that must be met in order for sources to be considered 

BART eligible. One of the criteria for a source to be considered BART eligible was that a 

source emits 250 tons per year of NOx, PM10, SO2, VOCs, or NH3. Alabama had three sources 

which chose to take emissions limits in order to be exempt from the entire BART process. By 

taking an emissions limit, Gulf States Paper Corporation, Kerr-McGee Chemical LLC, and 

Mobile Energy Services Company no longer have BART eligible sources. These limits will be 

written into and enforced through the permits for each applicable source at the facility, and 

incorporated into the Regional Haze SIP. 

9.0 BART Determinations 

For those facilities subject to BART, the state must determine what constitutes BART controls 

for the source by considering various control options and selecting the best alternative taking into 

consideration any pollution control equipment in use at the source, the costs of compliance with 

control options, the remaining useful life of the facility, the energy and non air-quality 

environmental impacts of compliance, and the degree of improvement in visibility that may 

reasonably be anticipated to result from the use of such technology. Under Alabama’s approach, 

facilities that are subject to BART were required to propose BART considering these factors via 

a permitting process. 

9.1 BART Subject Sources 

Only two BART-eligible sources in Alabama emit any air pollutants which may reasonably be 

anticipated to cause or contribute to any impairment of visibility in any Class I area. The two 

facilities, Solutia, Inc. in Decatur, AL and International Paper, in Courtland, AL, were unable to 

demonstrate less than a 0.5 dv impact on one or more Class I areas and thus are subject to 

BART. 

In accordance with the BART rule, the two facilities submitted analyses proposing BART for 

their sources (Attachment H-13). Upon receipt, the proposed BART determinations were 

provided to U.S. EPA Region 4 and the FLMs for their review and comment. ADEM also held 

conference calls with U.S. EPA Region 4 to discuss their comments and concerns regarding each 

of the facilities’ submittals. 

ADEM permitting staff reviewed the analyses proposing BART. 

9.1.1 BART-Eligible Units and Existing Control 

Solutia, Inc. has five BART-eligible emission units that comprise the BART-eligible source. The 

majority of these units are currently controlled. Descriptions of these units are as follows: 

 Appendix H - 23 
Boiler No. 5 (X005): This unit is a 290 MMBTU/hr coal-fired spreader-stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Boiler No. 6 (X006): This unit is a 320 MMBTU/hr coal-fired spreader-stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Boiler No. 7 (X015): This unit is a 536.1 MMBTU/hr pulverized coal-fired boiler. This boiler is 

permitted to burn propionitrile (PN) vapor. The boiler is equipped with an electrostatic 

precipitator for particulate control. Soutia has installed a ROFA (rotating opposed fired air) 

system to reduce NOx formation on this boiler. This unit is subject to NSPS, Subpart D. As 

required by Subpart D, this boiler has limitations for particulate, SO2, and NOx emissions. The 

SO2 emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Coking Boiler No. 1 (X007): This unit is a 384 MMBTU/hr coal-fired stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

Coking Boiler No. 2 (X008): This unit is a 384 MMBTU/hr coal-fired stoker boiler. The boiler 

is equipped with an electrostatic precipitator for particulate control. The particulate and SO2

limits for the unit are based upon the state fuel burning equipment regulations. The SO2

emissions were further limited to correct for modeled SO2 NAAQS exceedances in the area. 

International Paper’s Courtland Mill has seven BART-eligible emission units that comprise the 

BART-eligible source. The majority of these units are currently controlled. Descriptions of these 

units are as follows. 

No. 1 Combination Boiler: This unit is a 398 MMBTU/hr combination fuel boiler that is 

designed to fire bark, natural gas, and fuel oil and is operated as a swing boiler. Bark from the 

woodyard is fed to a bark bin which supplies both the No.1 and No.2 Combination Boilers. In 

addition the No. 1 Combination Boiler has the capability to combust the dilute non-condensable 

gas (HVLC) stream from the pulp mill and chemical recovery areas. The No. 1 Combination 

Boiler is vented to a venturi scrubber where the gases are scrubbed with water to remove 

particulate matter. 

No. 2 Combination Boiler: This unit is a 679 MMBTU/hr combination fuel boiler that fires 

coal, bark, and natural gas. The primary fuel for this boiler is bark, which is supplied to the 

boiler by the bark handling system. The other primary fuel for this boiler is coal. There are 

three coal mills associated with the No.2 Combination Boiler which consist of a pulverizer and a 

primary air fan that is used to dry the coal and blow the coal in the boiler a well has provide 

excess air for the combustion of the coal. Each of the pulverizers provides coal to two burners, 

and each of the burners is equipped with a gas igniter. The No. 2 Combination Boiler also has 

 Appendix H - 24 
the capability to combust the dilute non-condensable gas (HVLC) stream from the pulp mill and 

chemical recovery areas. The No. 2 Combination Boiler is vented to two electrostatic 

precipitators to remove particulate matter. The flue gas is then vented to a high pressure venturi 

scrubber for the removal of SO2.

Package Boiler: This unit is a 365 MMBTU/hr boiler that is utilized as a back-up boiler and is 

fired by natural gas. The Package Boiler has no external emissions control devices.

No. 2 Recovery Furnace: This unit is a 470 MMBTU/hr recovery furnace that is designed to 

fire black liquor, with natural gas and fuel oil as supplemental fuels. In the furnace the liquor is 

dried and burned. The organic portion of the liquor burns which provides heat for steam 

generation. The inorganic portion of the liquor is recovered to produce cooking liquor for the 

digesters. The combustion gases from the furnace are vented to an electrostatic precipitator for 

particulate matter control

No.2 Smelt Dissolving Tank: This unit is a recovery operation for the No. 2 Recovery Furnace. 

The inorganics in the Recovery Furnace accumulate on the furnace floor and drain into the No. 2 

Smelt Dissolving Tank as molten smelt. The smelt is mixed with weak wash to form green 

liquor which is sent to the causticizing area. The No. 2 Smelt Dissolving Tank is vented through 

a separate scrubber system for particulate matter control.

No. 1 Lime Kiln: Lime mud from the Causticizing Area is converted to lime in this unit. Both 

the No. 1 and No. 2 Lime Kilns are fired with natural gas and/or fuel oil and have low-NOx

burners. Concentrated non-condensable gases (LVHC) and the foul condensate stripper gases 

are incinerated in the lime kilns. The No.1 Lime Kiln is vented to a scrubber to control 

particulate emissions.

No. 2 Lime Kiln: Lime mud from the Causticizing Area is converted to lime in this unit. Both 

the No. 1 and No. 2 Lime Kilns are fired with natural gas and/or fuel oil and have low-NOx

burners. Concentrated non-condensable gases (LVHC) and the foul condensate stripper gases 

are incinerated in the lime kilns. The No.1 Lime Kiln is vented to a scrubber to control 

particulate emissions. 

9.2 Baseline Contribution 

Solutia’s BART source baseline contribution to the 98th percentile visibility impairment was 

4.470 dv at Sipsey Wilderness. IP Courtland’s BART source baseline contribution to visibility 

impairment is 2.392 dv at Sipsey Wilderness. 

9.3 BART Determination Analysis 

Section 169A(g)(7) of the CAA requires that States must consider the following factors in 

making BART determinations: (1) The costs of compliance, (2) The energy and non-air quality 

environmental impacts of compliance, (3) Any existing pollution control technology in use at the 

source, (4) The remaining useful life of the source, and (5) The degree of improvement in 

 Appendix H - 25 
visibility which may reasonably be anticipated to result from the use of such technology. These 

factors are incorporated in the BART regulation and 40 CFR Part 51 Appendix Y and Alabama’s 

BART rule as well. Although these factors are to be considered, according to the BART 

guidelines states have flexibility in how the factors are weighted in making their determinations 

regarding what constitutes BART. (See 70 FR 39170, 1st col., July 6, 2005.) 

9.3.1 Control Scenarios Considered 

Each facility reviewed several potential control alternatives. The control alternatives that have 

been considered and the associated visibility improvement that would result are summarized in 

the tables below: 

 Appendix H - 26 
Table. 9-1 Solutia Summary of Visibility Improvements for Control Technologies 

Visibility Improvement 

Relative to Base Emissions 

Scenario (deciviews)1

BART-Eligible 

Emissions Unit 

Control 

Technology Pollutant 

Pollutant 

Control 

Efficiency 

(%) 

Maximum 

24-Hour 

98th Percentile 

24-Hour 

Boiler 52 Low Sulfur Coal SO2 46 0.07 0.32 

Boiler 52 ROFA/FSI SO2 60 0.07 0.34 

Boiler 52 Wet Scrubber SO2 90 0.11 0.40 

Boiler 52 ROFA/Rotamix NOx 58 0.04 0.00 

Boiler 52 SCR NOx 95 0.06 0.00 

Boiler 52 Baghouse PM 99.9 0.66 0.21 

Boiler 6 Low Sulfur Coal SO2 46 0.07 0.32 

Boiler 6 ROFA/FSI SO2 60 0.07 0.34 

Boiler 6 Wet Scrubber SO2 90 0.11 0.40 

Boiler 6 ROFA/Rotamix NOx 58 0.04 0.00 

Boiler 6 SCR NOx 95 0.06 0.00 

Boiler 6 Baghouse PM 99.9 0.66 0.21 

Boiler 7 Low Sulfur Coal SO2 7 0.01 0.03 

Boiler 7 ROFA/FSI SO2 60 0.05 0.24 

Boiler 7 Wet Scrubber SO2 90 0.07 0.36 

Boiler 7 ROFA/Rotamix NOx 78 0.06 0.00 

Boiler 7 SCR NOx 95 0.09 0.00 

Boiler 7 Baghouse PM 99.9 1.12 0.52 

One Coker Low Sulfur Coal SO2 16 0.01 0.05 

One Coker ROFA/FSI SO2 60 0.04 0.18 

One Coker ROFA/Rotamix NOx 58 0.04 0.00 

One Coker SCR NOx 95 0.07 0.00 

One Coker Baghouse PM 99.9 0.41 0.19 

Cokers Wet Scrubber SO2 90 0.12 0.41 

Notes: 

1

The predicted visibility impact of the five BART-eligible emission units for the base emission 

scenario was 7.241 deciviews (maximum 24-hour value) and 4.470 deciviews (98th percentile 

24-hour value). 

2

Visibility improvements results for Boiler 6 were used for Boiler 5 because of the similarities of 

the boilers and their operation. Boiler 6 is slightly larger than Boiler 5, therefore the visibility 

improvements indicated are a conservative representation for Boiler 5. 

 Appendix H - 27 
Table. 9-2 IP Courtland Summary of Visibility Improvements for Control Technologies 

Visibility Improvement 

Relative to Base Emissions 

Scenario (deciviews)1

BART-Eligible 

Emissions Unit Control Technology Pollutant

Pollutant 

Control 

Efficiency 

(%) 

Maximum 

24-Hour 

98th Percentile 

24-Hour 

No. 1 Combo SNCR NOx 35 0.02 0.02 

No. 1 Combo Low NOx Burners NOx 30 0.013 

No. 1 Combo Addition of Caustic 

to Scrubber SO2 93 0.014 0.013 

No. 1 Combo Dry Scrubbing SO2 93 0.014 0.013 

No. 1 Combo Semi-dry Scrubbing SO2 93 0.014 0.013 

No. 2 Combo SNCR NOx 35 0.097 

No. 2 Combo Low NOx Burners NOx 30 0.15 0.083 

Package Boiler SCR NOx 90 0.037 

Package Boiler SNCR NOx 50 0.041 0.017 

Package Boiler Low NOx w/ FGR NOx 50 0.041 0.017 

No. 2 Rec. High ∆P Wet 

Scrubbing SO2 93 0.17 0.063 

No. 2 Rec High ∆P Wet 

Scrubbing / WESP SO2 93 0.17 0.063 

Notes: 

1

The predicted visibility impact of the seven BART-eligible emission units for the base emission 

scenario was 2.392 deciviews (maximum 24-hour value) and 1.341 deciviews (98th percentile 24-

hour value). 

Since both the No.1 and No.2 Lime Kilns currently employ Low-NOx Burners in the form of 

combustion flame tuning to reduce NOx emissions, and no other controls where deemed feasible, 

a cost effectiveness review and visibility study was not conducted as allowed by 40 CFR Part 51, 

Appendix Y. 

Although both the Package Boiler and the No. 2 Smelt Tank are BART eligible sources for SO2, 

a control effectiveness review study was not performed since both of these sources only emit 

approximately 1 tpy of SO2. Due to this fact; emissions from these units are minimal and there 

would be virtually no impact on visibility, therefore no BART controls were reviewed. 

The No. 1 and No. 2 Lime Kilns are BART eligible sources for SO2; however 40 CFR Part 51, 

Appendix Y exempts units that are complying with MACT Standards from performing a 

technical feasibility study and a cost effectiveness review and visibility study. Since both these 

 Appendix H - 28 
Lime Kilns are subject to and are complying with 40 CFR Part 63 Subpart MM through the use 

of wet scrubbers, and since the inherit nature of lime kilns minimize SO2 emissions, the current 

approach to MACT II compliance should serve as BART for SO2 for these Lime Kilns. 

The No.2 Recovery, No. 2 Smelt Tank, No. 1 and No. 2 Lime Kilns are BART eligible sources 

for PM10; however 40 CFR Part 51, Appendix Y exempts these units from performing a 

technical feasibility study and a cost effectiveness review and visibility study since these units 

are subject to and complying with a MACT Standard, which regulates particulate emissions (40 

CFR Part 63, Subpart MM). 

9.3.2 Costs of Compliance 

For Solutia, the 98th percentile 24-hour visibility improvement ranged from 0.00 dv improvement 

to 0.52dv at costs ranging from $1667.72/ton/dv to $380,928.57/ton/dv, respectively. The costs 

for each of the scenarios considered are summarized in Table 9-3 below: 

Table 9-3 Solutia Summary of Cost Effectiveness for Control Technologies

BART- Control Cost-Effectiveness 

Eligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Tons 

Removed 

($/ton 

Removed)

($/ton/deciview 

improvement) 

Boiler 5 Low Sulfur Coal SO2 1438.88 1065.54 3329.81 

Boiler 5 ROFA/FSI SO2 1876.79 663.45 1951.32 

Boiler 5 Wet Scrubber SO2 2815.19 1,075.46 2688.65 

Boiler 5 ROFA/Rotamix NOx 52.84 15,529 - 

Boiler 5 SCR NOx 86.54 8675 - 

Boiler 5 Baghouse PM 21.5 79,995 380,928.57 

Boiler 6 Low Sulfur Coal SO2 1587.72 1065.54 3329.81 

Boiler 6 ROFA/FSI SO2 2070.95 615.80 1811.18 

Boiler 6 Wet Scrubber SO2 3106.42 977.86 2444.65 

Boiler 6 ROFA/Rotamix NOx 57.28 18,091 - 

Boiler 6 SCR NOx 93.81 5,461 - 

Boiler 6 Baghouse PM 44.96 38,316 182,457 

Boiler 7 Low Sulfur Coal SO2 168.09 16,034.55 534,485 

Boiler 7 ROFA/FSI SO2 1440.8 931.95 3883.13 

Boiler 7 Wet Scrubber SO2 2161.21 1854.90 5152.50 

Boiler 7 ROFA/Rotamix1 NOx 217.35 4118 - 

Boiler 7 SCR1 NOx 654.84 1986 - 

Boiler 7 Baghouse PM 409.57 1065.54 10,503.85 

Coker 1 Low Sulfur Coal SO2 302.09 8739 174,780 

Coker 1 ROFA/FSI SO2 1599.10 1090.20 3028.33 

One ROFA/Rotamix NOx 265 4510 - 

 Appendix H - 29 
Coker 

One 

Coker SCR NOx 435 2607 - 

One 

Coker Baghouse PM 120 13,709 72,152.63 

Cokers Wet Scrubber SO2 4797.30 600.20 1667.22 

1-The cost, emissions, and improvements are based on the addition of the SNCR/SCR to the 

ROFA system, which is considered as existing control for Boiler 7. 

In reviewing the cost of controls based on emissions removed, Solutia indicated that the 

additional controls for particulate and NOx emissions would not be cost effective. The current 

particulate controls (ESPs) achieve removal efficiencies between 96%-99% and adequately 

controls the particulate emissions. The additional NOx controls indicated relatively small to no 

reduction in visibility impacts for the reported costs. The costs for additional SO2 controls appear 

to be more cost effective and provide some visibility improvement. Solutia has indicated that the 

cost of installation and operation of the FSI system or wet scrubbers would severely impact the 

facility’s sustainability and viability. For both of the coking units, Solutia has indicated that the 

addition of any controls would negate the viability of the coking units. The requirement of the 

additional controls would result in a net loss and thus require the units to be shutdown. 

For IP Courtland, the 98th percentile 24-hour visibility improvement ranged from 0.00 dv 

improvement to 0.097dv at costs ranging from $7,048/ton/dv to $1,121,077/ton/dv. The costs for 

each of the scenarios considered are summarized in Table 9-4 below: 

 Appendix H - 30 
Table 9-4 IP Courtland Summary of Cost Effectiveness for Control Technologies

Control Cost-Effectiveness BARTEligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Tons 

Remove

d 

($/ton 

Removed) 

($/ton/deciview 

improvement) 

No. 1 

Combo SNCR NOx 142.8 $6,097 $304,850 

No. 1 

Combo 

Low NOx

Burners NOx 122.3 $1,188 $91,385 

No. 1 

Combo 

Addition of 

Caustic to 

Scrubber 

SO2 180.7 $7,260 $558,462 

No. 1 

Combo Dry Scrubbing SO2 180.7 $14,574 $1,121,077 

No. 1 

Combo 

Semi-dry 

Scrubbing SO2 180.7 $11,420 $878,462 

No. 2 

Combo SNCR NOx 518.2 $2,081 $21,454 

No. 2 

Combo 

Low NOx

Burners NOx 444.2 $585 $7,048 

Package 

Boiler SCR NOx 108 $12,375 $334,459 

Package 

Boiler SNCR NOx 60 $16,024 $801,200 

Package 

Boiler 

Low NOx w/ 

FGR NOx 60 $2,767 $138,350 

No. 2 Rec. High ∆P Wet 

Scrubbing SO2 1149 $3,633 $57,667 

No. 2 Rec 

High ∆P Wet 

Scrubbing / 

WESP 

SO2 1149 $4,336 $68,825 

In reviewing the cost of controls based on the amount of emissions removed, IP has indicated 

that additional controls for SO2 would not be cost effective at the Courtland Mill. IP has also 

indicated that the Control of NOx is only cost effective for the No. 2 Combination Boiler and that 

no other add-on controls would be cost effective for all other sources. The current add-on 

controls which control particles at the Courtland mill have efficiencies of greater than 90% 

therefore any additional controls would not be a cost effective option. 

 Appendix H - 31 
9.3.3 Energy and Non-air Quality Impacts 

Solutia has indicated that the additional SO2 controls would generate additional waste. Solutia 

estimated that the FSI system would generated an additional 14,000 tons of fly ash per boiler and 

the addition of the wet scrubber would generate 20 tons/day of sludge. 

IP has indicated that there would be a reduced energy efficiency and an increase in fuel usage as 

a result of the installation of Low NOx burners on the No. 1 Combo and No. 2 Combo boilers. 

The Department has reviewed these concerns and had determined that the small reduction in 

energy efficiency and increase in fuel usage for the No. 2 Combo boiler does not offset the 

visibility improvements or the cost effectiveness of $585/ton of NOx removed. IP has also 

indicated that additional NOx controls for other units would cause significant impacts to the 

energy efficiencies and potentially allow other pollutants to be emitted to the atmosphere. 

IP has suggested that any additional control of SO2 at any of the BART eligible sources at IP 

would cause an significant increase in energy usages and/or generate a waste stream that would 

have to be disposed; thereby incurring disposal costs and possible permitting issues with other 

medias. 

9.3.4 Existing Control 

Existing control on the BART subject sources is described in Section 9.1.1. 

9.3.5 Remaining Useful Life 

 To be completed later 

9.3.6 Degree of Visibility Improvement 

As previously stated, modeling was conducted to show the predicted visibility impact on the 

closest Class I Area (Sipsey Wilderness Area). From the chosen options for Solutia, an 

improvement of 0.32 dv is expected from each of Boiler 5 and 6, and an improvement of 0.24 dv 

for Boiler 7 from SO2 controls. The summary of the costs and visibility improvements for the 

chosen options are shown in the table below: 

 Appendix H - 32 
Table 9-5. Solutia Visibility Improvement and Cost Results of Proposed Options 

BARTEligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Pollutant 

Control 

Efficiency 

(%) 

($/ton 

Removed) 

Visibility 

Improvement 

Relative to 

Base 

Emissions 

Scenario 

(deciviews)1

Boiler 5 

Low Sulfur 

Coal SO2 46 1065.54 0.32 

Boiler 6 

Low Sulfur 

Coal SO2 46 1065.54 0.32 

Boiler 7 ROFA/FSI SO2 60 931.95 0.24 

1-98th Percentile 24-Hour 

For the IP Courtland facility the modeled visibility improvement as a result of installing the 

proposed add on BART controls, federally enforceable limits, and operational limitations would 

range between 0.2 and 0.4 deciviews improvement in the Sipsey Wilderness Area. Although this 

is a small visibility improvement it has a large reduction in the number of days above 0.5 dv at 

the Sipsey Wilderness Area. Relative to the base case of 98 days above 0.5 dv, the three 

modeled scenarios indicate only 40, 59, and 56 days above 0.5 dv, which equates is an average 

improvement of 45 days. The summary of the costs and visibility improvements for the chosen 

options are shown in the table below: 

Table 9-6. IP Courtland Visibility Improvement and Cost Results of Proposed Options 

BARTEligible 

Emissions 

Unit 

Control 

Technology Pollutant 

Pollutant 

Control 

Efficiency 

(%) 

($/ton 

Removed) 

Visibility 

Improvement 

Relative to 

Base 

Emissions 

Scenario 

(deciviews)1

No. 1 Combo2 Low NOx

Burners NOx 30 $1,188 0.32 

No. 2 Combo Low NOx

Burners NOx 30 $585 0.013 

1-98th Percentile 24-Hour 

2- IP has to either install low NOx Burners or only operate the No. 1 Combination Boiler when 

one of the following emissions units is either not operating or in periods of start-up of shutdown: 

the No. 2 Combination Boiler the No. 2 Recovery Furnace, the No. 3 Combination Boiler, or the 

No. 3 Recovery Furnace.

 Appendix H - 33 
9.4 Final BART Determination 

Proposed BART Limitations for Solutia

The Table below presents the summarized BART emission limits for Solutia. 

Table 9-5 Solutia BART Emission Limitations 

Emission Limitations Emission Unit NOx SO2 PM10

Boiler 5 101.22 lb/hr 1.40 lb/MMbtu & 

406 lb/hr 

0.12 lb/MMbtu & 34.8 

lb/hr 

Boiler 6 109.72 lb/hr 1.40 lb/MMbtu & 

448 lb/hr 

0.12 lb/MMbtu & 38.4 

lb/hr 

Boiler 7 0.36 lb/MMbtu & 193 

lb/hr 

0.47 lb/MMbtu & 

252 lb/hr 

0.10 lb/MMbtu & 

64.33 lb/hr 

Coker 1 104.43 lb/hr 3.57 lb/MMbtu & 

1,370.1 lb/hr 0.12 lb/MMbtu 

Coker 2 104.43 lb/hr 3.57 lb/MMbtu & 

1,370.1 lb/hr 0.12 lb/MMbtu 

The Department concurs with the proposed BART limitations. For Boiler 7, Solutia would be 

required to install a continuous emission monitor system (CEMS) for determining compliance 

with the SO2 and NOx emission limitations. Solutia would be required to comply with the BART 

limitations by January 1, 2013. 

Proposed BART Limitations for IP Courtland

The Table below presents the summarized BART emission limits for the IP Courtland Mill. 

Table 9-6 IP Courtland BART Emission Limitations 

Emission Limitations Emission Unit NOx SO2 PM10

No. 1 Combo 93.15 lb/hr or operational 

limitations 1 147.3 lb/hr 0.17 gr/sdcf @ 50% Excess Air 

No. 2 Combo 338.13 lb/hr 1.20 lb/MMbtu & 

65.5 lb/hr 0.10 lb/MMbtu 

Package Boiler 

0.20 MMbtu & 

<1,200,000 ft3 of natural 

gas / 12 month period 

1.80 lb/MMbtu 0.10 lb/MMbtu 

No. 2 Recovery 152 lb/hr 432 lb/hr 0.044 grains/SDCF at 8 

% O2 and 67 lb/hr 

No. 2 Smelt Tank NA 0.20 lb/hr 0.20 lb/ ton of black 

liquor solids 

No. 1 Lime Kiln 3.5 lb/hr 0.10 lb/hr 1.0 lb/air dried ton of 

pulp 

No. 2 Lime Kiln 19.40 lb/hr 0.23 lb/hr 0.067 gr/sdcf at 10% 

O2

 Appendix H - 34 
I- IP has to either install low NOx Burners or only operate the No. 1 Combination Boiler when 

one of the following emissions units is either not operating or in periods of start-up of shutdown: 

the No. 2 Combination Boiler the No. 2 Recovery Furnace, the No. 3 Combination Boiler, or the 

No. 3 Recovery Furnace.

The Department concurs with the proposed BART limitations. IP would be required to install 

low NOx burners on the No. 1 Combination Boiler if as change in the operational status of this 

boiler is changed in the future due to process demands. IP will be required to comply with the 

BART limitations by January 1, 2013. 

These limitations will be written into air permits and will be effective by January 1, 2013. The 

limitations established under BART (Best Available Retrofit Technology) may be changed 

through the NSR (New Source Review) permit process which should include a visibility analysis 

prior to the modification. 

9.5 BART Subject Sources in Other States Within 300 km of Alabama Class I Areas 

There were no sources outside Alabama that contributed to visibility impairment at the Sipsey 

Wilderness area. 

9.6 Conclusions 

Only two sources in Alabama, Solutia in Decatur and IP Courtland in Courtland were subject to 

BART. For Solutia, all of the BART units are already each equipped with an electrostatic 

precipitator, which range in efficiency from 96% to 99%. The ESPs adequately controls 

particulate emissions for the units. The proposed BART limitations for Boilers 5-7 appear to 

adequately comply with the BART requirements. As previously stated, the addition of any 

controls would negate the viability of the coking units; therefore, no additional controls would be 

required for BART. 

The No. 2 Recovery Furnace, No. 2 Smelt, No. 1 Lime Kiln and the No. 2 Lime Kiln of IP 

Courtland’s BART-subject sources are already well controlled via compliance with the Pulp and 

Paper MACT’s (40 CFR Part 63, Subparts MM and S). There are limited additional control 

options available. Based on review of the available control options, associated costs and 

visibility benefits, BART is determined to be equivalent to the MACT standards and the 

installation of low NOx burners on the No. 2 Combination Boiler and either install low NOx

burners or only operate the No. 1 Combination Boiler when one of the following emissions units 

is either not operating or in periods of start-up of shutdown: the No. 2 Combination Boiler the 

No. 2 Recovery Furnace, the No. 3 Combination Boiler, or the No. 3 Recovery Furnace. 

 Appendix H - 35 
10.0 FINAL LONG TERM STRATEGY (LTS) AND REASONABLE 

PROGRESS GOALS (RPGs) 

As stated in Section 2.0 above, the RHR requires States to establish Reasonable Progress Goals 

(RPGs), expressed in deciviews (dv), for visibility improvement at each affected Class I area 

covering each (approximately) 10 year period until 2064. This first set of RPGs must be met 

through measures contained in the state’s LTS covering the period from the baseline until 2018. 

This Section discusses development of Alabama’s LTS. 

10.1 Long-Term Strategy (LTS) 

Ammonium sulfate is the most important contributor to visibility impairment and fine particle 

mass on the 20% worst and 20% best visibility days at the Sipsey Wilderness area. Sulfate levels 

on the 20% worst days account for greater than 70% of the visibility impairment. Across the 

VISTAS region, sulfate levels are higher at the Southern Appalachian sites than at the coastal 

sites. On the 20% clearest days, sulfate levels are more uniform across the region. Reduction of 

SO2 emissions would be the most effective means of reducing ammonium sulfate. Greater than 

85% of SO2 emissions in Alabama are attributable to electric generating facilities and industrial 

point sources. Thus, the LTS for this first Regional Haze SIP focused on reductions in SO2 

emissions. 

In Alabama and across the region there are significant controls programs in place to reduce SO2

emissions between the baseline period and 2018. Most notably, CAIR is predicted to result in a 

70% reduction from EGU SO2 emissions in Alabama. Overall the SO2 emissions in Alabama are 

predicted to decrease from 2002 levels at 447,828 tons per year to 135,851 tons per year in 2018. 

Such large SO2 reductions are predicted to result in significant improvements in visibility. 

Alabama’s CAIR rule is attached as Attachment H-10. 

At the Sipsey Wilderness area in Alabama, visibility improvements on the 20% worst days are 

expected to be better than the uniform rate of progress glidepath by 2018 based solely on 

reductions from existing and planned emissions controls. Specifically for Sipsey, a 4.2 deciview 

improvement in visibility would meet uniform rate of progress in 2018; expected emissions 

reductions by 2018 are projected to achieve a 5.3 deciview improvement. In fact, visibility 

improvements at all the VISTAS mountain Class I areas and most of the coastal Class I areas are 

projected to be better than the uniform rate of progress. The percentage of the target reduction 

achieved for the Sipsey Wilderness areas using the new IMPROVE equation is between 120- 

130%. This reflects a rate of improvement of 20-30% greater than the uniform rate of progress 

by 2018. 

In addition to improving visibility on the 20% worst visibility days, states are also required to 

protect visibility on the 20% best days at the Class I areas. Visibility on the 20% best days is 

projected to improve in 2018 at all VISTAS Class I areas as a result of the 2018 Base G2 

emissions reductions. The percentage of the target achieved for the Sipsey Wilderness area is 

about -7.7%. Zero percent change would mean no change in visibility; -7.7% means that 

visibility is better than no change, or a 7.7% improvement (values lower than current 

conditions.) 

 Appendix H - 36 
ADEM completed a reasonable progress assessment after modeling the Clean Air Act controls 

discussed above. The assessment did not identify any cost effective control measures for the SO2

non-EGU units that contributed greater than 1% to visibility impairment at the Sipsey 

Wilderness or any Class I area in neighboring States. 

10.2 What Additional Emissions Controls Were Considered as Part of the Long-Term 

Strategy for Visibility Improvement by 2018? 

Section 308(d)(3)(v) of the regional haze rule lists several factors that must be addressed in each 

SIP. These factors include the role of fire at Class I areas and status of state planning for smoke 

management, the role of dust and fine soil at Class I areas and status of state plans to mitigate 

emissions from construction activities and the role of NH3 and potential benefits if emissions 

from agricultural sources were mitigated. 

As discussed in Section 4.1 and demonstrated in Figure 17, elemental carbon (sources include 

agriculture, prescribed wildland fires, and wildfires) is a relatively minor contributor to visibility 

impairment at the Class I areas in Alabama. However, the ADEM has an approved smoke 

management program that addresses the issues laid out in EPA’s 1998 draft guidance for smoke 

management plans. ADEM intends to include the smoke management program as part of the 

final Regional Haze SIP submittal in December, 2007, and for the resulting plan to be sufficient 

to satisfy the directive in section 308(d)(3)(v)(E). 

In regard to construction activities and fugitive dust emission sources, the ADEM has issued 

regulations addressing control of fugitive dust from construction activities and to control 

particulates from fugitive dust emission sources generated within plant boundaries. ADEM 

Admin. Code 335-3-4-.02, reads as follows: 

(1) No person shall cause, suffer, allow, or permit any materials to be handled, transported, or 

stored; or a building, its appurtenances, or a road to be used, constructed, altered, repaired, or 

demolished without taking reasonable precautions to prevent particulate matter from becoming 

airborne. Such reasonable precautions shall include, but not be limited to, the following: 

(a) Use, where possible, of water or chemicals for control of dust in the demolition of existing 

buildings or structures, construction operations, the grading of roads, or the clearing of land; 

(b) Application of asphalt, oil, water, or suitable chemicals on dirt roads, materials stock piles, 

and other surfaces which create airborne dust problems; 

(c) Installation and use of hoods, fans, and fabric filters (or other suitable control devices) to 

enclose and vent the handling of dusty materials. Adequate containment methods shall be 

employed during sandblasting or other similar operations. 

(2) Visible Emissions Restrictions Beyond Lot Line. No person shall cause or permit the 

discharge of visible fugitive dust emissions beyond the lot line of the property on which the 

emissions originate. 

 Appendix H - 37 
(3) When dust, fumes, gases, mist, odorous matter, vapors, or any combination thereof escape 

from a building or equipment in such a manner and amount as to cause a nuisance or to violate 

any rule or regulation, the Director may order that the building or equipment in which processing, 

handling, and storage are done be tightly closed and ventilated in such a way that all air and gases 

and air or gas-borne material leaving the building or equipment are treated by removal or 

destruction of air contaminants before discharge to the open air. 

In regard to agricultural ammonia, the ADEM has no regulations. 

A final CMAQ modeling run will be performed in the fall of 2007 to account for the cumulative 

benefits of the Base G2a emissions controls, BART controls, and additional measures to achieve 

reasonable progress by 2018. The final Regional Haze SIP will contain revised RPGs for the 

Sipsey Wilderness Area reflecting these final decisions. 

10.3 Reasonable Progress Goals (RPGs) 

The RHR at 40 CFR section 51.308(d)(1) requires States to establish RPGs for each Class I area 

within the state (expressed in deciviews) that provide for reasonable progress towards achieving 

natural visibility. In addition, EPA released guidance on June 7, 2007 to use in setting RPGs. 

The goals must provide improvement in visibility for the most impaired days, and ensure no 

degradation in visibility for the least impaired days over the State Implementation Plan (SIP) 

period. The State must also provide an assessment of the number of years it would take to attain 

natural visibility conditions if improvement continues at the rate represented by the RPGs. 

In accordance with the requirements of 40 CFR §51.308(d)(1), this Regional Haze SIP 

establishes RPGs for the Sipsey Wilderness area in Alabama. To calculate the rate of progress 

represented by each RPG, ADEM compared baseline visibility conditions to natural visibility 

conditions at the Sipsey Wilderness area and determined the uniform rate of visibility 

improvement (in deciviews) that would need to be maintained during each implementation 

period in order to attain natural visibility conditions by 2064. ADEM has summarized expected 

visibility improvements under existing federal and state regulations, BART determinations in 

Alabama and neighboring states, and any additional control measures found to be reasonable to 

implement in this review period. These controls will be modeled in CMAQ as part of the LongTerm Strategy (LTS). At this time ADEM has determined that the RPGs will be at least as 

stringent as the uniform rate of progress “glidepath”. VISTAS has already demonstrated that the 

2018 Base G2a control scenario provides for an improvement in visibility better than the uniform 

rate of progress for the Sipsey Wilderness area for the most impaired days over the period of the 

implementation plan and ensures no degradation in visibility for the least impaired days over the 

same period. In addition, it is expected that IMPROVE monitoring results for 2018 will at that 

time be used to establish a new baseline for the next planning period. 

Table 10-1. Alabama RPGs for the Sipsey Wilderness Area. 

 Appendix H - 38 
Class I Area Baseline 

Visibility 

(dv) 

RPG (dv Improvement 

Expected by 2018, 20% 

Worst Days) 

RPG (dv Improvement 

Expected by 2018, 20% 

Best Days) 

Dv Improvement 

Needed 2018-2064 

(20% Worst Days) 

Sipsey 

Wilderness 29.03 5.5 1.4 12.63 

A final CMAQ modeling run was performed in the winter of 2007 to account for the cumulative 

benefits of the Base G2a emissions controls, BART controls, and additional measures to achieve 

reasonable progress by 2018. 

 Appendix H - 39 
 Appendix H - 40 

REFERENCES: 

1. Boylan Ph.D., James, 2006, VISTAS Joint Tech Analysis-Planning Call. Power Point 

Presentation: Summary BART_VOC_NH3_PM.ppt. 

2. Brewer, P.F.; and Adloch, J.P., 2005, Trends in Speciated Fine Particulate Matter and 

Visibility across Monitoring Networks in the Southeastern United States. J Air and Waste 

Management Association, 55, 1663-1674. 

3. Federal Register / Vol. 70, No. 128 / Wednesday, July 6, 2005 / Rules and Regulations. 

4. Hand, J.L.; and Malm, W.C.,2006, Review of the IMPROVE Equation for Estimating 

Ambient Light Extinction Coefficients - Final Report. March 2006. Prepared for 

Interagency Monitoring of Protected Visual Environments (IMPROVE), Colorado State 

University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO. 

5. MACTEC, 2006, Documentation of the Base G 2002 Base Year, 2009 and 2018, 

Emissions Inventory VISTAS. 

6. Pechan, E.H., and Associates, Inc., 2005, AirControlNET User Guide. 

7. Pitchford, Marc., 2006, Natural Haze Levels II: Application of the New IMPROVE 

Alogrithm to Natural Species Concentrations Estimates. Final Report of the Natural 

Haze Levels II Committee to the RPO Monitoring/Data Analysis Workgroup. Sep 2006. 

8. Sorrels, Larry, 2006, AirControlNET 4.1 Software; US EPA, OAQPS, Research Triangle 

Park, NC. 

9. U.S. Environmental Protection Agency. (2003). Guidance for Tracking Progress under 

the Regional Haze Program; EPA-54/B-03-004, 2003.