# 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 resu lts compared to Uniform Rate of Progress at the Sipsey Wilderness. ......................................................................................................................... 23

3.0 GEORGIA INSTITUTE OF TECHNO LOGY (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 PR OGRESS 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 E nvironmental Impacts of Compliance ....................................1 6.1-4 Remaining Useful Life of the Source ......................................................................................2 6.2 Evaluating Four Statutory Factors for Specific SO 2 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 Applyi ng Statutory Factors ................................................................................. 4 7.0 Best Available Retrofit Technology (BART) ........................................................................... 67.1 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 Orga nic Compounds (VOCs) for BART Purposes .. 11 7.5.1 Method

............................................................................................................................... ....11 7.5.2 Conclusions ............................................................................................................................13 7.6 Treatment of Ammonia (NH 3 ) 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 C onsidered 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 th e State’s strategy for complying with the requirement to set and meet Reas onable Progress Goals (RPGs) as part of our Regional Haze SIP under 40 CFR 51.308(d)(1), and the requirements for establishing best ava ilable retrofit (BART) controls under 40 CFR 51.308(e).

In the 1977 amendments to the Clean Air Act (C AA), Congress set a national goal for visibility as “the prevention of any future, and the remedyi ng of any existing, impairment of visibility in mandatory Federal Class I areas which impair ment results from manmade pollution”. The Regional Haze Rule (RHR) at 51.308 (d) requires states to de monstrate 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 gr aphically show what would be a “uniform rate of progress” toward natural conditions for each Cl ass I area. This is known as the “glidepath”. The RHR then requires states to establish RPGs fo r 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) coveri ng the period from the present until 2018. This appendix provides an overview of this first LTS . In addition, a specifi c 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 st rategy 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 un iform rate of progress, or “glidepath” for the Sipsey Wilderness area. III. Discussion of emissions sensitivity model r uns to help determine which pollutants and source categories are contributi ng the most to visibility impairment at Class I areas (runs conducted by Georgia Institute of Technology). IV. Examination of SO 2 Area of Influence (AoIs) projections for the Sipsey Wilderness area, and also for any surrounding states’ Cla ss 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 “sta tutory 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 fo r BART-eligible sources.

IX. BART determinations for sources subject to BART. X. Modeling demonstration of vi sibility improvement afte r inclusion of BART and reasonable progress control determinations. XI. Determination of RPGs based on the vi sibility improvement expected by 2018.

### 1.0 BASE G CAA CONTROLS

2009 and 2018 emissions projections include the fo llowing existing state a nd 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 (SO 2 ) and nitrogen oxides (NO x ) in the eastern United States. CAIR achieves large reductions of SO 2 and/or NO x emissions across 28 eastern states a nd the District of Columbia. When fully implemented, CAIR will reduce SO 2 emissions in these states by over 70% and NO x emissions by over 60% from 2003 levels.

• NO x SIP Call. Phase I of the NO x SIP call applies to certain Electric Generating Units (EGUs) and large non-EGUs, including large indu strial boilers and tu rbines, and cement kilns. States in the VISTAS region affected by the NO x SIP call have developed rules for the control of NO x 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 NO x Allowance Tracking System – Allowances Held Report was also obtained a nd reviewed. Since these controls are to be in effect by the year 2007, we capped the emissions for NO x SIP call affected sources at 2007 levels and carried forward the cappe d levels for the 2009/2018 future year inventories. This rule resu lted in a 68% reduction in NO x 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 s eason 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 (NO x ) emissions by 2009 and a 73% cut in sulfur dioxide (SO 2 ) 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 stringe nt pollution limits; implement a series of interim pollution-reduction measures to reduce emissions while the permanent controls are designed and inst alled; and retire polluti on emission allowances that Tampa Electric or others could use, or sell to others, to emit additional NO x , SO 2 , and PM.

• Virginia Electric and Power Co. (VEPCO) agreed to spend $1.2 billion by 2013 to eliminate 237,000 tons of SO 2 and NO x 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 NO x 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/SO 2 /NO x emissions; comply with system-wide annual PM/SO 2 /NO x emissions limits; agree not to buy, sell or trade PM/SO 2 /NO x 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 SO 2 and 8,000 tons of NO x ) by installing/operating selective catalytic reduct ion (SCR) technology; low-NO x burners, and PM and Mercury Continuous Emissions Monitoring at the utility’s Spurlock, Dale and Cooper Plants. According to the EPA, th e plant’s total emissions will drop from between 50 – 75% from 2005 levels. As w ith all federal Cons ent Decrees, EKPC is precluded from using reductions requi red under other programs, such as the Clean Air Interstate Rule (CAIR). EK PC 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 redu ce emissions of sulfur dioxide (SO 2 ) and nitrogen oxides (NO x ) from Boiler Units 3 and 4 at its Plant Miller in Quinton, Alabama. The plant is required to reduce SO 2 by installing flue gas desulfurization (FGD) and is required to reduce NO x by installing selective catalytic reduction (SCR) equipment. The Consent Decree requires APC to commence continuous year-round operation of SCR equipment for control of NO x emissions by May 1, 2008. APC is also requ ired to begin year-round operation of the FGD equipment for control of SO 2 emissions by December 31, 2011. The installation and operatio n of these controls are expect ed to result in the reduction of 4,953 tons per year of NO x and 22,788 tons per year of SO 2 . APC is also required to install and operate by De cember 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 SO 2 emissions allowances.

• 1-hr Ozone SIPs (Atlanta / Birmingham / No rthern Kentucky). The purpose of a State Implementation Plan (SIP) is demonstrate atta inment 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 Standar d. 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 NO x and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr a nd 0.14 g/ bhp-hr, respectively. These NO x andNMHC standards will be phased in togeth er 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 w ill require a 97% reduction in the sulfur content of highway diesel fuel from its curre nt 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 averagi ng program, modeled after the California LEV II standards. Manufacturers can produce vehicles with emissi ons ranging from relatively dirty to zero, but the mix of vehicles a manufacturer sells each year must have average NO x 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 H eater/RICE MACTs. The EPA issued final rules to substantially reduce emissions of toxic air polluta nts from industrial, commercial and institutional boilers, proce ss heaters and from stationa ry reciprocating internal combustion engines (RICE). These rules re duce emissions of a number of toxic air pollutants, including hydrogen chloride, ma nganese, lead, arsenic and mercury by 2009. This rule also reduces emissions of SO 2 and PM in conjuncti on with the toxic air pollutant reductions. The applied Maximu m Achievable Control Technology (MACT) control efficiencies were 4% for SO 2 and 40% for PM 10 and PM 2.5 . 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 projec tion inventories do not include the NO x cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which EPA estim ates 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 Federa l Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD ) staff. We did not apply reductions for MACT standards with an init ial compliance date of 2001 or earlier, assuming that the effects of these controls ar e already accounted for in th e 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 Elect ric 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 emi ssion control programs, to include CAIR and CAMR. The IPM results were adjusted base d 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 inve ntories 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 propos ed 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 subtra ction of future emission controls based on the best available data from state rules, enfor cement 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 determ inations 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 Determ inations Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories.

NO x Emission Controls SO 2 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 Scru bber 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 Sc rubber Scrubber Scrubber

4BLR SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions Scrubber Scrubb er ScrubberTable 1-1 (continued)

NO x Emission Controls SO 2 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 Sc rubber 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 Scrubb er Scrubber

KY Ghent 1 None SCR SCR SCR Scrubb er Scrubber Scru bber Scrubber

ORISID=1356 2 None None SCR SCR None Scrubber Scrubber Scrubber
3, 4 None SCR SCR SCR None Scrubber Scru bber 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 Sc rubber Scrubber Scrubber Scrubber

H2 None SCR SCR SCR Scrubber Scrubber Scru bber ScrubberTable 1-1 (continued)
NO x Emission Controls SO 2 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 No ne 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=3947Table 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 (ORI S10333) 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 Cycl e facility became commercial June 1, 2005. Added 346 tons of NO x and 121 tons of SO 2 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 NO x and 3,227 tons of SO 2 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 SO 2 emissions are much lower than IPM, but their expected NO x 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 em ission 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 resu lts 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 resu lts 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 Cogentrixof 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; Up grade 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 SO 2 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 PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate
Unit 2: Install low NO x burners that meet 0.46 lb/mmBTU from 0.9 by May 1, 2004. Recalculated NO x 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 PM 10 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 PM 10 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 PM 10 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 NO x control technology by April 30, 2006 to meet 0.27 lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NO x emissions using IPM heat input and 0.27 lbs/mmBtu

Generic Unit
ORISID=900545 All All predictions for generic un its appear reason able 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 IP M results using VADEQ’s growth and control estimates.

AEP Glen Lyn
ORISID=3776 51, 52, 6 Replaced all 2009/2018 IPM re sults using VADEQ’s growth and control estimates.

Dominion Clover
ORISID=7213 1, 2 Replaced all 2009/2018 IP M results using VADEQ’s growth and control estimates.

Dominion Bremo
ORISID=3796 3, 4 Replaced all 2009/2018 IP M results using VADEQ’s growth and control estimates.

Dominion Chesterfield
ORISID=3797 3, 4, 5, 6 Replaced all 2009/2018 IPM re sults 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 IP M 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 NO x 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 inpu t 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 a ll 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 SO 2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO 2 Permit Rate of 0.678 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018

Mt. Storm
ORISID=3954 1, 2, 3 SO 2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. Used SO 2 Permit Rate of 0.15 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 20181.1.2 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 c ontrol 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, stat e, 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) requirement s 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 em ission 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 co ntrols are already acc ounted for in the 2002 inventories supplied by the States . Emission reductions were applied only for MACT standards with an initial compliance da te of 2002 or greater.

The final Phase II NO x SIP call rule was finalized on Ap ril 21, 2004. States had until April 21, 2005, to submit SIPs meeting the Phase II NO x 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 sa me 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 contro l 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 invent ories include:

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

• Industrial Boiler/Proces s Heater/RICE MACT. The applie d MACT control efficiencies were 4% for SO 2 and 40% for PM 10 and PM 2.5 to account for the co-benefit from installation of acid gas sc rubbers and other control equipment to reduce HAPs.

• NO x RACT in 8-hr NAA SIPs.

• NO x SIP Call Phase I- except where States have adopted II already. Phase I of the NO x SIP call applies to certain large non-EGUs, incl uding large industrial boilers and turbines, and cement kilns. States in the VISTAS region affected by the NO x SIP call havedeveloped rules for the control of NO x emissions that have been approved by EPA. State rules and guidance documents were reviewed to determine the affect ed sources and ozone season allowances.

• Petroleum Refinery Initiativ e (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 near ly 77% of domestic refining capacity. Three refineries in the VISTAS region are a ffected 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) th e 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 Standard s. The point source MACTs and associated emission reductions were designed from Federa l Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD ) staff. Reductions for MACT standards with an initial compliance da te of 2001 or earlier, were not applied, assuming that the effects of these controls are already accounted for in th e 2002 inventories supplied by the States.

• Combustion Turbine MACT. The projecti on inventories do not include the NO x cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which EPA estim ates to be small compared to the overall inventory.

• NO x SIP Call (Phase II – remain ing 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 eff ectiveness and rule penetration) provided by the States or originally developed for use in estim ating projected emissions for U.S. EPA’s Heavy Duty Diesel (HDD) rulemaking em ission projections and used in the Clean Air Interstate Rule (CAIR) projections were used to calculate controlled emissions.

The controls obtained by MA CTEC (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 y ears were prepared using a straig ht-line interpolation of control level between 2007 and 2020.State submitted controls had precedence over th e U.S. EPA developed controls. Control measures submitted by the Alabama Department of Environmental Management (ADEM) include Stage I controls for gasoline disp ensing facilities, and open burning controls.

As part of the air toxics progr am, 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 insp ecting Stage I controls. If a facility is not found to be pr operly maintaining the control e quipment, 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 in formation 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 pene tration 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 disp osal in rural areas. Ma terials burned generally include household trash, agri cultural 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, re sidential 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 untr eated wood, tree trimmings and brus h or plant growth generated by clearing or maintenance of land and from construction and demolition operations. Provided there are no local or state ordi nances which would restrict th e activity, burning the materials listed above may take place during the other seven m onths 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, pape r, treated wood, plasti c, 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 in spection (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 presump tion 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. Howe ver, if a State planned change s, we requested information on those plans. In the final implementation of the in ventory, Stage II controls were exercised in thearea source component of the inventory, since th e 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 fo r aircraft, locomotives, and commercial marine vessels (CMV) prepared as de scribed earlier in this doc ument, corresponding emission projections for 2009 and 2018 were developed. Deta iled 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 interpol ation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the Stat e-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 de pict pollutant totals for NH 3 , PM 2.5 , NO x , and SO 2 for the various sectors by st ate for 2002, 2009, and 2018 Base G2 modeling.0 20 40 60 80 100 120 140 160 180 200

A l abama Florida Georgia Ke nt

u ck

y Mississippi

N

or

th Car ol

ina

S outh C

arolina Tenness ee
V irginia West Virgini aAnnual NH3 (Thousand Tons) Miscellaneous
Nonroad Onroad
Industrial Other Fuel Combustion
EGU 2002 Typical 2009 OTW 2018 OTW

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

0 20 40 60 80 100 120 140 160 180 200

Alabama Flor i da Georgia Kentucky

M i ss

is

sipp i

No r t h Caro lin

a

S

ou

t h

Car

o li n a

T e n n es

s ee
V i rgin

i a
We st

Vi

r gin

i aAnnual PM-2.5 (Thousand Tons) Miscellaneous
Nonroad Onroad
Industrial Other Fuel Combustion
EGU

2002 Typical 2009 2018 OTW

Figure 1-2. Annual PM 2.5 emissions – Base G2.0 100 200 300 400 500 600 700 800 900 1,000

A

l a b

a ma
F lo

ri da Georgia Ken t uc

k

y

Mi

s si

s sip p i North C

ar

o l in

a South Carolina Ten nes see Vi r g i ni

a West V

irginiaAnnual NOx (Thousand Tons) Miscellaneous
Nonroad Onroad
Industrial Other Fuel Combustion
EGU 2002 Typical

2009 OTW

2018 OTW

Figure 1-3. Annual NO x emissions – Base G2.

0 100 200 300 400 500 600 700

A

labama Flor i da
G e o r gia Ke n tuck y

Mi s siss i pp

i

N

o rth Ca r ol

i na
Sou t h Carolin a Tenn e ss

e e Vir g in

i a
We

st Vir g in

i aAnnual SO2 (Thousand Tons) Miscellaneous
Nonroad Onroad
Industrial Other Fuel Combustion
EGU 2002 Typical

2009 OTW

2018 OTW

Figure 1-4. Annual SO 2 emissions – Base G2.

### 2.0 UNIFORM RATE OF PROGRESS

The linear rate of improvement suff icient to attain natural conditions by 2064 is referred to as the “uniform rate of progress” or “glide path”. Th e 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 Pr otected Visual Environments (IMPROVE) monitoring data, the deciview (dv) values for th e 20% best days in each year are averaged together, producing a single aver age dv value for the best days. Similarly, the dv values for the 20% worst days in each year are averaged to gether, producing a single average dv value for the worst days. Extinction from i ndividual PM components is calculated from the IMPROVE equation (EPA, 2003; Hand and Malm, 2006). EPA de fined 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 natu ral background. Most re cently, the scientific community has reviewed the assumptions used to calculate current and natural background visibility and has agre ed to revised methods (Hand and Malm, 2006, Pitchford, 2006). VISTAS intends to present both the original and revise d methods to calculate visibility and visibility improvement. Figure 2.1 illustrates the averag e 20% worst visibility days in the 2000-2004 baseline period for the Sipsey Wilderness area, the target natural cond ition 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 orig inal 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 YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction Figure 2-1. CMAQ 2018 Base G2 results compa red 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 PM 2.5 , and 8-hour ozone concentrat ions 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 im pairment at each Class I area were identified, the sources or source categories responsible for emitting these pollutants or pollutant precursors were determined. Emissions sensitivity anal yses were conducted using CMAQ with 2009 Base D inventory and considering 30% reductions from major pollutant s and source categories. The sensitivity runs were initially designed to consider pollutant cont ributions in 2009 to PM 2.5 in urban areas; results were also considered for Clas s I areas even though the full benefit of controls anticipated by 2018 are not included in these sens itivity analyses. Resu lts 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 contribu tions from each state or source sector, the results do indicate rela tive level of response among pollu tants, sectors, and geographic

areas.

3.1 Evaluation for the Sipsey Wilderness Area, AL

Figure 3-1 shows the results of emissions sensitiv ity run for Sipsey for summer (since summer is when 20% worst days occur). CMAQ was r un using 30% reductions from the 2009 Base D inventory assumptions for implementing existing state and federal regulat ions (Section 1.0) for major source categories of SO 2 , NO x , 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 Orga nizations (RPOs). The greatest benefits at Sipsey in 2009 are projected to come from further reducing SO 2 from electric generating utilities (EGUs). Additional, smaller benefits are projected from additional SO 2 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, o ff road engines, and area sources) and reductions of primar y carbon from point or ground leve l sources are projected to be significantly less beneficial than reductions in SO 2 emissions. Reductions in anthropogenic VOC emissions show no response in visibili ty, 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 SO 2 emissions from electricity generating utilities in Alabama, Georgia and Tennessee would have the greatest benefit for SIPS1; reductions from electric genera ting 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 _ EG

U

SO

2 _

non EG

U NOx_ G

rou

nd

NO x _Point N H3 VOCs
PC _ Gr

o und PC_Po in

t PC_FiresΔBext(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 sugge st 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 effectiv e in improving visibility in wintertime than further reductions in SO 2 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 _ EG

U

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U NOx_ G

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nd

NO x _Point N H3 VOCs
PC _ Gr

o und PC_Po in

t PC_FiresΔBext(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 SO 4 at SIPS1 on the 20% worst days modeled in the June episode in response to further reductions in 2009 SO 2 emissions from EGUs (Figure 3-3). For this sensitivity run, beyond c ontrolling Alabama EGUs, further reducing SO 2 emissions from electricity generating utilities in Tennessee, Georgia, an d West Virginia would have the greatest benefit for SIPS1; reductions fr om 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 SO 2 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 St ate 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

%

10 WV

2

13%
4 1 10%

3

3 M K 23%

2 AL

Figure 3-3. Utility Contributions , by State and Region to SO 4 at SIPS1 for 20% worst days using 2009 Base D emissions.

3.2 Summary

Emissions sensitivity analyses show the relative benefits of reducing di fferent pollutants from different source categories and geographic areas. These 2009 sensitivity analyses indicate that further reductions in SO 2 emissions from EGUs would be mo st beneficial for visibility at VISTAS Class I areas, followed by SO 2 reductions from industrial po int sources. Controlling NO x or primary carbon emissions from either po int or ground level sour ces would have little benefit to visibility. Contro lling 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 Cla ss I areas on the 20% worst visibility days. Thisinformation will be used by the State as part of the evaluation and demonstration of reasonable progress toward visibility impr ovement in Class I areas.

VISTAS’ contribution assessment based on IMPR OVE monitoring data (Brewer and Adlhoch, 2005) demonstrated that ammonium sulf ate is the major contributor to PM 2.5 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 accoun ted for greater than 70% of the calculated light extinc tion at Class I areas in the So uthern Appalachians and greater than 60% of the calculated light extinction for coastal sites in the VI STAS states (excepting Everglades). In contrast, ammonium nitrate co ntributed less than 5% of the calculated light extinction at VISTAS Class I areas on the 20% wo rst 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 car bon) accounted for 10-20% of light extinction on 20% worst visibility days (except Everglad es where organic carbon accounted for 40%).

0 50 100 150 200 250 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1CADI1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (Mm-1) Sea Salt CM Soil EC POM Amm NO3 Amm SO4 Rayleigh

0 50 100 150 200 250 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1CADI1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (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 an alyses using the CMAQ regional ai r quality model project that reductions in SO 2 emissions from EGU and non-EGU industr ial point sources wi ll result in the greatest improvements in visibility at VISTAS Class I areas. EGU and non-EGU industrial point sources comprise 95+% of the SO 2 emissions inventory in the VI STAS states. The emissions sensitivity analyses also indicate that impr ovements in visibility from reductions in NO x or primary carbon emissions from ground level sources or point sources would be small. Based on these analyses, VISTAS states chose to focus th eir reasonable progress evaluation for the firstRegional Haze SIP on potential controls of SO 2 emissions from EGU and non-EGU point sources. To select the specific point sources that w ould be considered for each Class I area, states first identified the geographi c areas that most likely influen ce visibility in each Class I area and then identified the major SO 2 point sources in th at 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 SO 2 emissions (Table 4-1), with 85% of 2018 SO 2 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%

V ISTAS 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 greate st impact on each Class I area. Initial focus on AoIs is on SO 2 emissions because SO 4 contributes greater than 60% of the calculated light extinction on the haziest days. In fact, in th e previous section, Figure 4-1 shows that for the mountain areas (SIPS1), SO 4 contributes roughly 80% to the calculated light extinction on the haziest days. To better understand th e sources that should be consider ed in a four factor analysis for reasonable progress, VISTAS contracted ENVIRON to partner with VISTAS’s Data Analysiscontractor, Air Resource Speci alists (ARS), to provide SO 2 AoIs for each VISTAS and six neighboring Class I areas. ARS generated meteor ological back trajectories for IMPROVE sites in VISTAS and neighboring states . Back trajectory analyses us e 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 traj ectories account for the im pact 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 usi ng the Hybrid-Single Particle Lagr angian Integrated Trajectory (HYSPLIT) model developed by the National Oceanic and Atmospheric Administration’s (NOAA) Air Resources Laborat ory (ARL). HYSPLIT uses archived 3-dimensional meteorological fields generated from observations and short-term forecasts. HYSPLIT can be run to generate forward or b ackward trajectories using severa l 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 Sy stem (EDAS). The EDAS fields are archived by the ARL across the continental U.S., including a buffer zone, at a hori zontal resolution of 80 km before 2004, and at a horizontal resolution of 40 km starting in 2004. Detailed information regarding the trajectory m odel 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 thos e listed in Table 4-2.

Table 4-2. Back Trajectory Model Parame ters 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 traj ectories generated and the final attribution analyses. In particular, trajec tories tend to become increasingly uncertain the further back in time they are used. Vertical motion in the m odel is sometimes best represented by following actual vertical motion measuremen ts (represented by mode l data), surfaces of constant entropy, or surfaces of constant pressure, depending on th e meteorological conditions at a given location and time. The impact of receptor height (or e nd height) on an individual trajectory is also important. Low-ending trajectorie s represent air parcels nearer to ground level and high-ending trajectories may represent more accurate bound ary 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 tr ajectories, 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 calcula ted 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 applie d 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 exti nction, and by extinction components including ammonium sulfate (AmmSO 4 ), ammonium nitrate (AmmNO 3 ), particulate organic material (POM), Light Absorbing Carbon (LAC), Soil, and Coarse Mass (CM). Wei ghing trajectories for the 20% worst days by sulfate extinction gave greater importance to days influenced by SO 2 emissions and lesser importance to days influe nced by organic carbon (POM) emissions. This allowed a geographic AoI to be identified base d on sulfate contributions and not skewed by contributions from fire.

These data files were provided to ENVIRO N. ENVIRON was char ged 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 sinc e it does not account for emissions and removal processes, it does not necessar ily imply specific areas contri buted 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 ofdata used in these analyses include backtrajectory residence time data, provided by AR S as described above, and the VISTAS 2002 and 2018 36-km gridded emissions data (B ase G, Aug 2006 inventory version).

Extinction weighted back trajec tory 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-proje cted (i.e., geodetic lat/long 1 degree by 1 degree) grid and transferred to ENVIRON for further GIS processing and analysis. Back traj ectories 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 Co nformal Projection domain. Once the data were re-projected, the data were mapped to the 36-km grid cells in the RPO pr ojection using an areaweighted mapping routine. The re-projected extinction weighted back-trajectory residence timeswere then plotted on the VISTAS 12-km modeling do main. As sulfate is the primary visibility impairing component of the total ex tinction in the Southeast, the SO 4 weighted residence time trajectories were chosen as the basic data set for display. For clarity, thes e 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 st art height, the State has defined the SO 2 AoI as the area with grid cells showing 10% (area shaded in yellow in following pl ots) 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 2000-2 004. Residence time over an area is indicative of general flow patterns, but si nce it does not account for emissi ons and removal processes, it does not necessarily imply specific areas cont ributed significantly to haze compounds at a receptor site. Figure 4-3 shows the extinction we ighted residence time plots for SIPS1 for 100-m and 500-m trajectory start heights.Figure 4-3. Sipsey Wilderness SO 4 extinction-weighted residence time plots for the period 2000-2004.

As an aid to the analysis, all regions with sc aled residence time values greater than 5% and greater than 10% were noted on the display. Fi nally, county boundaries we re overlaid to identify those counties and 36-km modeling grid cells fo r which the extinction-we ighted residence time back-trajectories exceeded 5% and 10%. Thes e 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 imp act from emission sources within the regions identified from the extinction-weighted back-traj ectory residence time displays and analyses.

Previous VISTAS contribution assessment, em issions sensitivity modeling, and inventory analyses have indicated that SO 4 is the largest contributor to haze on the 20% worst visibility days and that EGUs and industrial point sources are the larges t contributors to SO 4 levels at the Class I areas. These two source cate gories make up 95% of the VISTAS SO 2 inventory. Therefore these two source categories were identifi ed as the highest priority for evaluation of reasonable progress in 2018 at the Class I areas.The potential impacts of SO 2 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 SO 2 emissions from the VISTAS modeling databases, for 2002 and 2018, re spectively. These data were processed by summing all vertical layers for each grid colu mn and then summing across all days to obtain annual emission totals for each grid cell.

Figure 4-4. Annual point source SO 2 emissions for the VISTAS region for in tons/year. (2002 Base G)Figure 4-5. Annual point source SO 2 emissions for the VISTAS region for in tons/year. (2018 Base G)

As a way of incorporating the e ffects of transport, deposition, and chemical transformation of point source emissions along the path of the trajec tories, 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 SO 2 emissions are then combined with the gr idded extinction-weight ed back-trajectory residence times at a spatial resolution of 36-km.

The final step in the development of the displa ys and datasets involved the combination of the residence times and gridded emission data. Th e distance weighted (1/d ) gridded point source SO 2 emissions are multiplied by the total extincti on-weighted back-trajectory residence times (SO 2 * 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 extin ction-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 SO 2 emissions and extinction-weighted residence times are overlayed with county bounda ries 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% 2018 SO2 emissions 2002 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 SO 2 Emissions * SO 4 extinction-weighted residence time plots. The following plot (Figures 4-7) shows the 2018 SO 2 Emissions multiplied by the SO 4 extinction-weighted residence time plots for the Sipsey Wilderness areas. These were produced the same way as the previous plots, only us ing 2018 emissions instead of 2002 emissions.

To understand how emissions have change d by 2018, Figure 4-7 compares 2002 and 2018 SO 2 multiplied by residence time.Figure 4-7. Sipsey Wilderness 2002 vs. 2018 SO 2 emissions multiplied by residence time. 

## 2002 vs 2018 SO2 Emissions weighted by Residence Time Sips ey, AL (100m start height) 2018 SO2 emissions 2002 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 reside nce time weighted by sulfate extinction plots of gridded SO 2 emissions and defined the SO 2 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 plot s for Class I areas indicate that the areas of probable influence for sulfate contribution to visibi lity impairment are similar to t hose 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 ap propriate to focus on sour ces 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 SO 2 emissions for the sulfate extinction-weighted residence time plots indicate that large emissions s ources 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 ev aluated 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 discus sion of the importance of other PM components and contributing source categories. If NOx controls are considered, slightly greater than 50% ofNO x is from point sources (see Tables 4.1), appr oximately 25% is from highway vehicles, and roughly 20% is from nonroad engines. Elevated organic carbon (OC) a nd 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 (NH 4 NO 3 ) levels in winter can be significant and are dependent on availability of NH 3 ; 87% of NH 3 is from area sources (e.g. ag riculture). In Alabama, the major source of ammonia is agriculture and livestock. However, given that sulfate contributes greate r than 70% at SIPS1 on the 20% worst visibility days, ADEM believ es it is appropriate to focus on SO 2 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 thor ough review of the emissi on inventories that are used in the modeling of the futu re year base case. These i nventories 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 (B ase 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 fo r all sources with emissions over distance (Q/d) greater than 5 and maximum residence time (R Tmax) greater than 5. States independently defined the criteria for selecti ng which sources from this list w ould be considered for reasonable control measures.

The NIF formatted and SMOKE-ready modeling f iles 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 fo r 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 inve ntory values) is included in th e 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 structur es when such emissions are used in regional scale modeling analyses.Table 4-3. VISTAS 2002 Base Year Annual Emissions Summary.

State V OC 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

V ISTA S 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 V OC 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

V ISTA S 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 st arting 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 highe st source types were identified, subcategories within those source types were reviewed. Ag ain, 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 review s and summaries like that presented in Figure 4-8, VISTAS made the decision to further revi ew only potential point sources for control.

In addition to reviewing the resi dual emission categories in the futu re year base, it was important to identify reductions that had alr eady occurred within each categor y 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 ha d the potential for reduction.Finally, once each subcategory was identified, un it 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 SO 2 by source. Ultimately, the final decisions will include the app lication of BART subject source reductions in the future year base case.

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Figure 4-8. VISTAS Base G2 SO 2 Emissions Contribution by Major Source Sector.



### 5.0 REASONABLE PROGRESS ASSESSMENT

ADEM concluded that SO 2 emissions from EGU and non-EGU point sources in geographic Areas of Influence (AoIs) are sources to consid er for further controls. VISTAS developed source matrices for SO 2 AoIs for each Class I area, using da ta delivered by ENVIRON for 2002 and 2018 SO 2 emissions multiplied by SO 4 extinction weighted residence time plots

. Spreadsheets were developed for each Class I area with:

• Plant name

• Point ID

• Actual Tons of SO 2 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/d 2

• RTMax, the maximum percentage of time that winds pass over that area on the way to the Class I area on the 20% worst daysThe 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/d 2 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 ca lculation is based on a single stack at a unit (when more than one are represente d in the inventory) and is calcul ated in distance in km to the IMPROVE monitor at each Class I area. The re sidence time for the county where the source is located was reviewed. It was ge nerally agreed that states would focus on those sources where RTMax was equal to or greater than 10%. A second matrix for sources in the SO 2 AoI was developed that combined the RTMax and Q/d me tric. Using this metric, ADEM calculated the fractional contribution from all th e emission units within the SO 2 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 c ontributed at least 1% to sulfate visibility impairment at a given Class I area. This wa s based on several regulatory programs that use a higher threshold than 1% for evaluation thresholds.

• The BART rule specified that a maximum im pact of 0.5 dv is an acceptable threshold for establishing significance. This threshold is representative of a 5% change in visible perception.

• The NO x SIP call established a significance level for 126 petitions (the level at which a state’s contribution to anothe r 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, wh ich was the standard at the time.

• The CAIR rule established a PM contribution threshold of 0.2 μg/m 3 as significant. This threshold represents 1.3% of the Annual PM 2.5 standard of 15 μg/m 3

.

• 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 pa rticular significance level is re lieved of further modeling. ADEM examined all the averaging periods for the criteria pollutants and determined that the 1 percent threshold cont ribution chosen for reasonabl e further progress was as stringent as any significant impact level, the most restrictive being NO 2 at 1 μg/m 3 or 1%. (NO 2 NAAQS 100 μg/m 3 )

Finally, ADEM considered available resources to ev aluate the sources in th e each Class I area’s sulfate AoI. ADEM recognized that there was neith er sufficient time nor resources available to evaluate all units within a give n AoI. Therefore, a threshold needed to be established to determine which units would be evaluated. Tabl e 5-1 shows that a 1% contribution threshold captures greater than 55% of the total point source SO 2 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 th e 1% threshold is appropriate,given the contribution to the total visibility im pairment at each Class I area, and the limited resources available to co nduct the unit-by-unit evalua tion for reasonable progress. Table 5-1. Numbers and percentage of 2018 Alabama SO 2 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 contribut ion 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 fracti onal 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 State Plant Name Pt ID 2002G 2018G CE Dist(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 0.98Table 5-3. Breton Q/d, Q/d^2, RTMax, and fracti onal 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 1.11Table 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 1.18Table 5-5. Joyce Kilmer Q/d, Q/d^2, RTMax, a nd 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 CE 2002G 2018G Dist (km) Q/d RTMax Q/d RTMax % Q/d RTMax BART Facility Number

TN BOWATERNEWS&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 0011BOWEN
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 proj ected 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 fracti onal 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 1.06Table 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 1.02Table 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 ar ea source with Q/d*RTMax > 1%, indicating the plant name, industry description, emissions proj ections for 2018, current control efficiency (CE%), distance from Class I area, Q/d, Q/d 2 , RT average, RT maximum, Q/d*RTMax, and the percentage a single source contri butes to the total Q/d*RT for a Cl ass 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 SO 2 emissions, those being fuel combustion from electric utilities and fuel com bustion 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 mandato ry Class I area within a State: cost of compliance, time necessary for compliance, ener gy and non-air quality environmental impacts of compliance, and remaining useful life of any exis ting source subject to such requirements. These statutory factors would be speci fic to the sources being consid ered for additional controls.

6.1 The Four Statutory Factors

6.1-1 Cost of Compliance

The “cost of compliance” is a factor used to de termine 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 re lated to tons of pollutant removed, but also involves how the pollutant or chemical compound a ffects the extinction coefficient in each Class I area. For example, on a pound to pound compar ison, sulfate particulat e 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-te rm strategy (LTS) peri od, as opposed to the improvement expected at full implementation of a control measure, if th e 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 sc hedule outlined by the control strategy, the RPG should reflect what visibility improvement coul d 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 contro ls at the percentage of sources that could be controlled within the strategy peri od. (The SIP could still include control strategi es that extend beyond the 2018 milestone; in the a bove example, the visibility improvement anticipated from installation of controls at the pe rcentage 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 E nvironmental Impacts of Compliance

The “energy and non-air quality environmental impacts of comp liance” factor is meant to consider whether the energy requi rements of the control technology result in energy penalties or benefits. For example, controls on diesel engi nes may decrease the overall efficiency and require a significant increase in diesel fuel consumption. The State s hould 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 - 16.1-4 Remaining Useful Life of the Source

The statutory factor of the “remaining useful life of the source” is a pplicable only to those measures, which would require retrofitting of c ontrol devices (or possibl y 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 rema ining 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 SO 2 Emissions Sources in Each Area of Influence (AoI)

The next step was to identify emission reductions th at have already occurred within each source category and at specific units. Unit level tables of emission comp arisons from 2002 to 2018 were developed, allowing VISTAS States to re view existing emission re ductions. These tables assigned future year control technology from IPM forecasting and State modification for EGU and from control efficiency tabl es 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 fo r 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 sour ce types did not duplic ate existing base case assumptions.

The Regional Haze Rule (RHR) requires that st ates consider the following factors and demonstrate how these factors were taken in to consideration in selecting the RPG:

• the costs of compliance

• the time necessary for compliance

• the energy and non-air quality environm ental 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 SO 2 in 2018 in the AoI defined for the Sipsey Wilderness area. Industrial boilers using oil and commercial and institu tional boilers using coal or o il had smaller contributions to SO 2 in 2018.

Sulfur dioxide emissions from utility, industria l, commercial, or inst itutional 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 re quire source specific analyses for accuracy.

Appendix H - 2Bituminous 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 SO 2 emissions with least impact to boiler performance. While sub-b ituminous coal has a lower sulfur content than bituminous coal, it al so 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 sulf ur sub-bituminous coal without affecting boiler operations. Costs of boiler modi fications 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, transpor tation costs, and modifica tion 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-combus tion control for coal-fir ed 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 cal cium 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 a nd ongoing operational and maintenance costs for the absorber tower, sorbent handling, and wa ste product handling facilities. Costs per ton vary with boiler size, type, and f acility 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 n ecessary to terminate existing fu el contracts and initiate new contracts needs to be considere d. 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 priori ties. 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-combus tion 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 add itional 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 indi vidual sources. Carbon dioxide ma y be emitted as a byproduct of flue gas desulfurization (particu larly if limestone is used), th erefore impacts of increased carbon emissions will need to be considered, especia lly if carbon emissions are limited in the future under climate change mitigation strategies.

Appendix H - 36.2-4 Remaining Useful Life

Remaining useful live is specific to the fac ility for which controls are considered.

6.3 Process of Applying Statutory Factors

ADEM has completed its Reasonable Progress Asse ssment for the first Regional Haze SIP. The following is ADEM’s Process on Reasonable Progr ess for the current time period (from the present to 2018):

Step 1: Determine pollutants of concern.

VISTAS evaluated the species c ontribution on the 20% worst visibi lity days and concluded that sulfate accounted for greater than 70% of the visibility impairi ng pollution. The VISTAS States concluded that controlling SO 2 emissions was the appropriate st ep in addressing the Reasonable Progress Assessment for 2018. The VISTAS findings were consistent with the findings of the Southern Appalachian Mountain Initiative (SAMI). SAMI conf irmed that sulfate particles account for the greatest portion of the haze affect ing Class I areas in the Southern Appalachian region and that these sulfates were produced in large part from SO 2 emissions from coal combustion.

Step 2: Determine which source sectors s hould be evaluated for reasonable progress.

Since SO 2 point source emissions in 2018 are projected to represent greater th an 95% of the total SO 2 emissions inventory, the VISTAS States concluded that the focus should be on electric generating utility (EGU) and non-EGU point sources of SO 2 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 SO 2 reduction from the EGU sect or resulting from the implementation of CAIR. The EGUs in Alabama are expected to reduce their SO 2 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 SO 2 reductions for CAIR at the time of the next periodic report in 2012 to ensure that the reductions currently predicted by IP M for CAIR are in fact taking place. As such, ADEM has concluded that at this time the CA IR program constitutes reasonable measures for Alabama EGUs during this first assessment period (b etween baseline and 2018). Please refer to Section 7.7 of the SIP Narrativ e 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 SO 2 AoI for a given Class I area and identifie d those emission units with a c ontribution of 1% or more.

Appendix H - 4Step 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 n ecessary 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 instal l controls. Therefore, most of the emphasis was placed on cost of control as part of this reas onable progress assessment, as compar ed to the other three statutory factors. In addition, ADEM believe s that a fifth factor, visibility improvement, is considered by focusing the evaluation on those units that contribut e at least 1% to visib ility 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 stra tegy. Using the CAIR rule as a guide, a cost of $2,000 was used as a determin er of effectiveness.

Based on the AoI analysis, ADEM focused the r easonable progress assessments on specific units at the following non-EGU facility in the State base d 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 c ontent coals. Currently, the company is using 1.49% sulfur coal in the Keeler St oker boiler a BACT limit resulti ng from a PSD review in 1998, Cargill states that lower sulfur coal would have to be obtaine d from western USA, such as Powder River Basin, to ach ieve any reductions in SO 2 . According to the company, available information indicates that lower su lfur 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 accomm odate this type coal. Cargill further states that burning such coal would compromise their combustion integrity due to a higher dust content

Appendix H - 5that would result in an increas e risk of spontaneous combustion in bunkers, silos, and hoppers. Due to availability and restrict ion on boiler design, Ca rgill determined that this option was not technically feasible.

Cargill also evaluated add-on controls. Specifi cally, Cargill evaluated wet and dry scrubbers. The typical SO 2 content of the coal currently burned in Keeler Stoker boil er is 1.3 lb/MMBtu. Based on an annual heat input of 1.2x10 6 MMBtu/yr, a baseline mass emission would equate to 780 TPY of SO 2 . Based on this information, Cargill estimates that it would cost $2,946/ton to control SO 2 emissions with these technologies.

It should also be noted that Cargill has entere d into a Consent Decree agreement with EPA and affiliated states that would reduce SO 2 emissions by 50% from current levels at its US plants.

Summary:

During the current reasonable progress assessm ent 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 facil ity, and energy and non-air environmental impacts of the control installation. Howe ver, since no cost effective cont rol measures were identified for these specific sources with contributions to Alabama or neighboring St ates’ Class I areas, ADEM did not invest in an exhaustiv e review of the remaining thr ee factors beyond those described control options for major SO 2 source sectors.

It should be noted that, in orde r to show continued progress past 2018, the criteria will likely be different in the next reasonable progress assessm ent 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 assessme nt, possible SO2 reducti on strategies will be evaluated for the next round of regional haze Stat e Implementation Plan (SIP) development.



### 7.0 Best Available Retrofit Technology (BART)

7.1 Background

As required by the CAA, EPA included in the fi nal RHR a requirement for BART for certain large stationary sources that were pla ced 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 mo re of 26 specifically li sted 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 anticipa ted 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 - 6A BART-eligible source that is re sponsible for a 1.0 deciview (dv) change or more is considered to “cause” visibility impairment. Although the a ppropriate 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 res ponsible for a 0.5 dv change or more is considered to “contribute” to visibility impairme nt. 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 SO 2 , NO x , and direct particulate matter (PM) emissions, including both PM 10 and PM 2.5 , 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 s ubject 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 visi bility 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 dete rmination. Section 169A(g)(7) of the CAA requires that States must consid er 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 pollutio n 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 re sult 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 anothe r 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 maxi mum 24 hour emission rate s would be modeled for a period of three or five year s of meteorological data. States have the flexibility to develop their own methods to ev aluate model results. 1

7.2 Approach to Implementati on of BART Requirements

In order to meet the SIP submittal deadline, Alab ama used a multifaceted approach to implement the RHR BART requirements. The approach consis ts of source identifica tion 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 issu es spanning states in the VISTAS region, and ongoing consultation w ith affected sources, and EPA and FLMs throughout the BART process.

Appendix H - 77.3 Identification of BART-Eligible Sources

EPA provided guidance for identifying BART-eligib le 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 determ ine the population of pot ential BART-eligible sources. The data were initially queried for any sources emitting SO 2 , NO x , PM 10 , VOC, or ammonia. The data set was refined based on emissions, whether emi ssion units fit in any of the twenty-six listed source categories for BART, a nd 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 eligibil ity from the standpoint of source category and date criteria. Through this iterative review proces s, 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’ SO 2 emissions and distance to Class I areas is included as Attachment H-4.

Appendix H - 8Alabama’s BART-eligible sources were presumed to be subject to BART but were provided the opportunity to submit modeling demons trations showing that they di d 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

A utauga

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 y Lowndes

Wilcox

Pike

Monroe

Washington

Mobile

Appendix H - 97.4 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 Rule 1 state that “A single source th at 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 ‘contri butes’ to visibility impairment should not be higher than 0.5 deciviews.” The rationale for these instructions is provided in the pr eamble to the BART guidance, in the statement, “If ‘causing’ vi sibility 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 ri se to the level of human perception.” ld be

2 The Guidance itself also states that, “States remain free to use a threshol d 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 threshol ds in the context of the human perception of visibility change. As noted above, the EPA consider s a 1.0 dv change in visibility to be humanly perceptible “in virtually all situations.” Also, the preamble to the BART guidance 3 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 contribu tion threshold. Putting all this together, it appears that “causing” visibil ity impairment means having a humanly perceptible impact (for which EPA consider s the practical threshold to be 1.0 dv) while “contributing” to visibility impairment means having a smaller imp act (for which EPA considers the threshold to be 0.5 dv or some smaller value) th at may or may not be perceptible.

ADEM retained the threshold of 0.5 dv for evaluating significance. First, th ere 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 contributi on threshold of 0.5 dv wa s appropriate in for evaluating facility contributions at Cla ss 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. A ppendix D in Acidic Deposition: State of Science and Technology, Report 24, Visibility: Existing and Hist orical Conditions -- Causes and Effects. National Acid Precipitation Assessment Program, Washington, DC. 1990.

Appendix H - 10Figure 7.2 Location of VISTAS BART-Eligible Sources

7.5 Exemption of Point Source Volatile Organ ic Compounds (VOCs) for BART Purposes

The State of Alabama has determined through m odeling that VOCs from point sources are not anticipated to cause or c ontribute 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 fro m 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 Impr ovement State and Tribal Association of the Southeast (VISTAS). VISTAS is a collaborative effort of state governments, tribal governments, and various federal agencies esta blished to initiate and coordinate activities associated with the management of regional haze, visi bility and other air qua lity 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 poi nt source VOCs on visibility in Class I areas.

GA Tech performed emission sensitivities to examine the impact of emission reductions on Regional Haze, annual PM 2.5 , and 8-hour Ozone concentrations using CMAQv4.4_SOAmods on

Appendix H - 11the 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 coeffi cient in deciviews (dv), then determining themaximum 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 0.6BRETBRIGCACRCHASCOHUDOSOEVERGRSMHEGLJARILIGOMACAMINGOKEFROMASAMASHENSHROSIPSSWANUPBUWOLFΔdV

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 fo r 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 sour ces are not a visibility impairing pollutant for BART purposes and that BART-eligible sources do not need to cons ider VOC emissions.

7.6 Treatment of Ammonia (NH 3 ) Emissions for BART Purposes

Similar to its treatment of VOCs, EPA guidance allows States the discretion to decide whether or not NH 3 emissions are to be considered for BA RT 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 ev aluate the haze impacts of all BART-eligible emissions of NH 3 . If the impact at the Class I area is less than the c ontribution 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 dete rmined through modeling that NH 3 emissions from point sources are not anticipated to cause or c ontribute significantly to any impai rment of visibility in Class I areas and should be exempt for BART purposes.

Appendix H - 137.6.1 Method

It was determined through modeling that NH 3 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 NH 3 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 th e way) Base F4 emissions. One such sensitivity run reduced BART-eligible source a mmonia by 100%. The purpose was to quantify the impact of NH 3 emissions from VISTAS BART sources on Cl ass 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 NH 3 . Figure 7-4 below, take n 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 NH 3 

## Impact

0.0 0.5 1.0 1.5BRETBRIGCACRCHASCOHUDOSOEVERGRSMHEGLJARILIGOMACAMINGOKEFROMASAMASHENSHROSIPSSWANUPBUWOLFΔdV

Figure 7-4. Maximum NH 3 Impact - Maximum contributio ns of all BART-eligible NH 3 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 delt a dv over the two timeframes at each Class I area. These delta dv changes represent the haze contri bution 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 Ea st and monthly-varying “climatologically representative” relative humi dity at each Class I area.

Appendix H - 14During the periods modeled, the NH 3 emissions from all BART-e ligible sources contributed more than 0.5 dv to haze at Mammoth Cave National Park (MACA), Kentucky; Mingo Wilderness (MING), Missouri, Ca pe Romain National Wildlife Refuge Area (ROMA) South Carolina, and Swanquarter National Wild life 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 NH 3 Sources in the VISTAS Region
Facility State NH 3 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 co ntributors 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. NH 3 emissions from BART sources may impair visi bility; however the majority of NH 3 emissions in the VISTAS region are from a few BART sources. Removal of the large NH 3 emission sources results in minimal impact on visibility at Class I areas in the VISTAS re gion. At their discretion states may ask those few large sources to evaluate NH 3 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 NH 3 emissions from point sources are not a visibility impairing pollutant for BART purpos es and that BART-eligible sources need not consider NH 3 emissions.



### 8.0 Explanation of BART Exemption Modeling

8.1 Background

Alabama opted to consider its BART-eligibl e sources subject to BART unless the source demonstrated exemption via modeling. BART-elig ible sources can be excluded from BART determinations by demonstrating that the source cannot be reasonably ex pected to cause or contribute to visibility impairment in a Class I area. The threshol d 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 - 15As stated in the BART regulation, EPA’s pr eferred approach for determining cause or contribution is an assessment with an air quali ty model such as CALPUF F or other appropriate model followed by comparison of the estimated 24 hour visibility impacts against a threshold above estimated natural conditions to be determ ined by the State. EPA recommends that the 98 th percentile value from the modeling be compared to the State’s chosen c ontribution threshold to determine if a source does not contribute to visibility impairment. Comparison of the 98 th percentile value to the threshold must be made for each Class I area. For an annual period, this implies the 8 th highest 24 hr value at a particular Class I area is co mpared to the contribution threshold. For a 3-year modeling period, the 98 th percentile value may be interpreted as the highest of the three annual 98 th percentile values at a part icular Class I area or the 22 nd highest value in the combined three year reco rd, whichever is more conservative.

ADEM worked with the Regional Planning Organi zation (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 comm on understanding among the orga nizations performing BART analyses or reviewing BART modeli ng results in the VISTAS region.

The VISTAS protocol describes common procedur es for carrying out air quality modeling to support BART determinations that are cons istent with the 40 CFR Part 51 Appendix Y guidelines. The protocol provides a consistent model, CALP UFF, and modeling guidelines for BART determinations, clearly delineated modeling steps, a common CALPUFF configuration, guidance for site-specific mode ling, 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 applica tion for BART purposes are found in Chapter 4, and specific information that should be included in si te-specific protocols is found in Chapter 5.

VISTAS contracted EarthTech to develop a ve rsion 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, VI STAS made publicly availabl e 12 km CALMET output files for the entire VISTAS modeling domain (Easte rn U.S.) and provided CALMET output files for five 4 km grid subdomains covering the VISTAS st ates 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 fo r 2001, VISTAS for 2002, and Midwest RPO for 2003. For the 12 km grid large domain covering th e entire VISTAS region, the No-Obs setting was used. For the 4 km grid, available surface an d upper air observations were used in addition to MM5 meteorological model outputs. Specifi c 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 re cent 3 or 5 years. If maximum 24 hr actual emissions were not available, continuous emi ssion data, permit allowable emissions, potential emissions, and emission factors from AP-42 source profiles could be used as available.

Appendix H - 16Key points on specific CALPUFF, CALPOST, and POSTUTIL configuration that were to be used for BART modeling are:

• After running CALPUFF for an individual facility, NO 3 should be repartitioned in POSTUTIL.

• Ozone data from non-urban monitors shoul d be used as the background ozone input.

• The Pasquill-Gifford disper sion method should be used.

• In CALPOST Method 6 with monthly aver age RH for calculating extinction as recommended by EPA should be used.

• EPA default calculations of light extin ction 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 a nd 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 VIST AS 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 pr e-processed MM5 meteorological da ta 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 Attach ment H-6. The protocols and demonstrations were reviewed by ADEM’s Industrial Chemicals and Industrial Minerals Sec tions as well as the Meteorological Section.

The individual facility modeli ng demonstrations were shared with both EPA and FLMs for their review and comment. The resul ting comments were in turn sh ared with the facilities. ADEM worked throughout the process to resolve many of the issues and concerns reflected in their comments. ADEM staff reviewed the demons trations 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 measur es, 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 determ ination requirements. Based upon these demonstrations, ADEM proposed to exempt 37 faci lities. Table 8-1 below provides a summary of the impacts of each BART-eligible f acility on the affected Class I areas.

Appendix H - 17Table 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 - 18Additionally, consistent with BART regulation requirements a nd 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 mo del only direct PM fine emissions. Compliance with CAIR constitutes BART for these sources for emissions of NO x and SO 2
. 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 no t 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 requ ire affected BARTeligible EGU to install, operate, and maintain BART for SO 2 or NO x emissions. Given that many of the BART-eligible units are installing scrubbers and NO x controls, and since Alabama is participating in CAIR and accepts EPA’s overall finding that CAIR “substitutes” for BART for NO x and SO 2 , 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 una ble to demonstrate less than a 0.5 dv impact via modeling. The visibility impact results for these two f acilities 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 - 19Table 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 Class I Area Alabama BART-Eligible 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 - 20Thirty eight Alabama BART-eligible sources m odeled impacts at the Class I areas within 300 km, but only two contributed to visibility impa irment, both at the Sipsey Wilderness Area. Additionally, although several modeled impacts, none of the BART-eligible sources contributed to visibility impairment at Cla ss I areas outside of Alabama.

8.3 Use of New IMPROVE Equation

During the Regional Haze SIP development proc ess, 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 specif ic Rayleigh scattering. Additional discussion of the new IMPROV E equation can be found in Appendix C.

VISTAS contracted Dr. Ivar Tombach to develo p a post processor to allow CALPOST outputs to be used with the new IMPROVE equation. A di scussion of the rationale for use of the new IMPROVE equation follows. The new IMPROVE postp rocessor and instructi ons 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 repres entation of the effects of particulate matter on light extinction than the old e quation 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 compar ing the measured light extinction from nephelometers at Class I areas to light exti nction calculated using each of the equations. 2. The new algorithm recognizes spatial and tem poral variation in light extinction as size distribution of the aerosol changes by increasi ng 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 in creasing relative humidity recognizing research findings showing that fine sea salt can be an importa nt 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 greate r than represented by the old equation. 5. The new algorithm includes a NO 2 term to represent times when light absorption by NO 2 is a meaningful contribu tor to light extinction. 6. The new algorithm incorporates site-speci fic 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 IM PROVE equation, the resulting apportionment of extinction to various components is more accura te on the haziest and clearest days. This is important for development of emission control st rategies since the benefits of control of concentrations of each species will be repres ented more correctly with the new algorithm.

Appendix H - 21Two of Alabama’s BART eligible sources el ected to use the new IMPROVE equation The spreadsheet developed by Dr. Tombach to impl ement the entire new IMPROVE equation for use with CALPUFF contains a modification of CALP OST that calculates the light extinction from the CALPUFF output. In their review of th e spreadsheet and supporting documentation, EPA Region 4 staff commented that the VISTAS methodology contained in the spreadsheet developed by Dr. Tombach appropriately implements the f eatures 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 NO 2 term, the VISTAS metho dology 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 mu st 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 aff ected emission units considering all federally enforceable permit limits, were greater than 250 tons or more per year of any of these visibility-impairing pollutants: SO 2 , NO x , and PM 10 .. Alabama had three sources which chos e 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 Mob ile 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 demonstr ate 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 Intern ational Paper Courtland in Courtland, Alabama were unable to demonstrate a contribution of less than 0.5 dv at all Cla ss 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 revi se the permits for the affected sources. Discussion of the BART determinations for thes e two sources is include d 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 IM PROVE equation used and difference in results, whether a BART determination was required, the f acilities’ potential emissions, the version of

Appendix H - 22CALPUFF and its components used, who conduc ted the modeling, existing controls, and proposed controls resulting from BART dete rminations is include d as Attachment H-8

The BART Guidelines list specific criteria that mu st 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 NO x , PM 10 , SO 2 , VOCs, or NH 3 . 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 Pa per 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 fo r 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 vari ous control options and selecting the best alternative taking into consideration any pollution control equipment in use at the so urce, 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 de gree of improvement in visibility that may reasonably be anticipated to result from the us e of such technology. Under Alabama’s approach, facilities that are subject to BA RT 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 pollutan ts which may reasonably be anticipated to cause or contribute to any impairment of visi bility 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, th e proposed BART determinations were provided to U.S. EPA Region 4 and the FLMs for their revi ew and comment. ADEM also held conference calls with U.S. EPA Region 4 to discuss their comments and concerns re garding 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 curr ently controlled. Descriptions of these units are as follows:

Appendix H - 23Boiler No. 5 (X005): This unit is a 290 MMBTU/hr coal-fir ed spreader-stoker boiler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Boiler No. 6 (X006): This unit is a 320 MMBTU/hr coal-fir ed spreader-stoker boiler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Boiler No. 7 (X015): This unit is a 536.1 MMB TU/hr pulverized coal-fired boiler. This boiler is permitted to burn propionitrile (PN) vapor. The boiler is equipped with an electrostatic precipitator for particulate cont rol. 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, SO 2 , and NOx emissions. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Coking Boiler No. 1 (X007): This unit is a 384 MMBTU/hr co al-fired stoker bo iler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Coking Boiler No. 2 (X008): This unit is a 384 MMBTU/hr co al-fired stoker bo iler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 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 bo th the No.1 and No.2 Combination Boilers. In addition the No. 1 Combination Boiler has the ca pability to combust the dilute non-condensable gas (HVLC) stream from the pulp mill and chem ical recovery areas. The No. 1 Combination Boiler is vented to a venturi scrubber where th e gases are scrubbed with water to remove particulate matter.

No. 2 Combination Boiler: This unit is a 679 MMBTU/hr co mbination fuel boiler that fires coal, bark, and natural gas. The primary fuel fo r this boiler is bark, which is supplied to the boiler by the bark handling system. The other prim ary fuel for this boiler is coal. There are three coal mills associated with the No.2 Combin ation Boiler which consist of a pulverizer and a primary air fan that is used to dry the coal a nd 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 ig niter. The No. 2 Combination Boiler also has

Appendix H - 24the capability to combust the dilute non-condens able gas (HVLC) stream from the pulp mill and chemical recovery areas. The No. 2 Combina tion Boiler is vented to two electrostatic precipitators to remove particulat e matter. The flue gas is then vented to a high pressure venturi scrubber for the removal of SO 2
. 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 recove ry furnace that is designed to fire black liquor, with natural gas and fuel oil as supplemental fuel s. In the furnace the liquor is dried and burned. The organic portion of th e liquor burns which provides heat for steam generation. The inorganic porti on of the liquor is recovered to produce cooking liquor for the digesters. The combustion gases from the furnace are vented to an electro static 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 sme lt 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 fo r 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-NO x 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-NO x 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 98 th percentile visibility impairment was 4.470 dv at Sipsey Wilderness. IP Courtland’s BART source baseline contri bution to visibility impairment is 2.392 dv at Sipsey Wilderness.

9.3 BART Determination Analysis

Section 169A(g)(7) of the CAA requires that St ates 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 ex isting pollution control t echnology in use at the source, (4) The remaining useful life of the source, and (5) The degree of improvement in

Appendix H - 25visibility which may reasonably be anticipated to result from th e use of such technology. These factors are incorporated in the BART regula tion 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, 1 st col., July 6, 2005.)

9.3.1 Control Scenarios Considered

Each facility reviewed several po tential 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 - 26Table. 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 98 th Percentile 24-Hour Boiler 5 2 Low Sulfur Coal SO 2 46 0.07 0.32 Boiler 5 2 ROFA/FSI SO 2 60 0.07 0.34 Boiler 5 2 Wet Scrubber SO 2 90 0.11 0.40 Boiler 5 2 ROFA/Rotamix NOx 58 0.04 0.00 Boiler 5 2 SCR NOx 95 0.06 0.00 Boiler 5 2 Baghouse PM 99.9 0.66 0.21 Boiler 6 Low Sulfur Coal SO 2 46 0.07 0.32 Boiler 6 ROFA/FSI SO 2 60 0.07 0.34 Boiler 6 Wet Scrubber SO 2 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 SO 2 7 0.01 0.03 Boiler 7 ROFA/FSI SO 2 60 0.05 0.24 Boiler 7 Wet Scrubber SO 2 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 SO 2 16 0.01 0.05 One Coker ROFA/FSI SO 2 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 SO 2 90 0.12 0.41

Notes:

1 The predicted visibility impact of the five BA RT-eligible emission units for the base emission scenario was 7.241 deciviews (maximum 24-hour value) and 4.470 decivi ews (98th percentile 24-hour value).

2 Visibility improvements results fo r Boiler 6 were used for Boiler 5 because of the similarities of the boilers and their operation. Boiler 6 is slight ly larger than Boiler 5, therefore the visibility improvements indicated are a conser vative representation for Boiler 5.

Appendix H - 27Table. 9-2 IP Courtland Summary of Visibi lity 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 98 th Percentile 24-Hour
No. 1 Combo SNCR NO x 35 0.02 0.02

No. 1 Combo Low NO x Burners NO x 30 0.013

No. 1 Combo Addition of Caustic to Scrubber SO 2 93 0.014 0.013

No. 1 Combo Dry Scrubbing SO 2 93 0.014 0.013

No. 1 Combo Semi-dry Scrubbing SO 2 93 0.014 0.013

No. 2 Combo SNCR NO x 35 0.097

No. 2 Combo Low NO x Burners NO x 30 0.15 0.083 Package Boiler SCR NO x 90 0.037 Package Boiler SNCR NO x 50 0.041 0.017 Package Boiler Low NO x w/ FGR NO x 50 0.041 0.017

No. 2 Rec. High ∆ P Wet Scrubbing SO 2 93 0.17 0.063

No. 2 Rec High ∆ P Wet Scrubbing / WESP SO 2 93 0.17 0.063

Notes:

1 The predicted visibility impact of the seven BA RT-eligible emission units for the base emission scenario was 2.392 deciviews (maximum 24-hour value) and 1.341 deciview s (98th percentile 24- hour value).

Since both the No.1 and No.2 Lime Kilns currently employ Low-NO x Burners in the form of combustion flame tuning to reduce NO x 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 an d the No. 2 Smelt Tank are BART eligible sources for SO 2 , a control effectiveness review study was not performed sin ce both of these sources only emit approximately 1 tpy of SO 2 . 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 SO 2 ; 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 vi sibility study. Since both these

Appendix H - 28Lime Kilns are subject to and are complying with 40 CFR Part 63 Subpart MM through the use of wet scrubbers, and since the inheri t nature of lime kilns minimize SO 2 emissions, the current approach to MACT II complian ce should serve as BART for SO 2 for these Lime Kilns.

The No.2 Recovery, No. 2 Smelt Tank, No. 1 and N o. 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 vi sibility study si nce these units are subject to and complying with a MACT Sta ndard, which regulates pa rticulate emissions (40 CFR Part 63, Subpart MM).

9.3.2 Costs of Compliance

For Solutia, the 98 th percentile 24-hour visi bility 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 ar e summarized in Table 9-3 below:

Appendix H - 29Table 9-3 Solutia Summary of Cost E ffectiveness for Control Technologies

Control Cost-Effectiveness BART- Eligible Emissions Unit Control Technology Pollutant Tons Removed ($/ton Removed) ($/ton/deciview improvement) Boiler 5 Low Sulfur Coal SO 2 1438.88 1065.54 3329.81 Boiler 5 ROFA/FSI SO 2 1876.79 663.45 1951.32 Boiler 5 Wet Scrubber SO 2 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 SO 2 1587.72 1065.54 3329.81 Boiler 6 ROFA/FSI SO 2 2070.95 615.80 1811.18 Boiler 6 Wet Scrubber SO 2 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 SO 2 168.09 16,034.55 534,485 Boiler 7 ROFA/FSI SO 2 1440.8 931.95 3883.13 Boiler 7 Wet Scrubber SO 2 2161.21 1854.90 5152.50 Boiler 7 ROFA/Rotamix 1 NOx 217.35 4118 - Boiler 7 SCR 1 NOx 654.84 1986 - Boiler 7 Baghouse PM 409.57 1065.54 10,503.85 Coker 1 Low Sulfur Coal SO 2 302.09 8739 174,780 Coker 1 ROFA/FSI SO 2 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 em issions removed, Solutia indicated that the additional controls for particulate and NOx emissi ons would not be cost effective. The current particulate controls (ESPs) achieve removal e fficiencies between 96%-99% and adequately controls the particulate emissions. The additional NOx controls indicated relatively small to no reduction in visibility impacts for the re ported costs. The costs for additional SO 2 controls appear

Appendix H - 30to be more cost effective and provide some visi bility improvement. Solutia has indicated that the cost of installation and operation of the FSI sy stem or wet scrubbers would severely impact the facility’s sustainability and viab ility. For both of the coking units , Solutia has indicated that the addition of any controls would negate the viabil ity of the coking units. The requirement of the additional controls would result in a net loss and thus require the uni ts to be shutdown.

For IP Courtland, the 98 th 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-EffectivenessBARTEligible Emissions Unit Control Technology Pollutant Tons Remove d ($/ton Removed) ($/ton/deciview improvement) No. 1 Combo SNCR NO x 142.8 $6,097 $304,850

No. 1 Combo Low NO x Burners NO x 122.3 $1,188 $91,385

No. 1 Combo Addition of Caustic to Scrubber SO 2 180.7 $7,260 $558,462

No. 1 Combo Dry Scrubbing SO 2 180.7 $14,574 $1,121,077

No. 1 Combo Semi-dry Scrubbing SO 2 180.7 $11,420 $878,462

No. 2 Combo SNCR NO x 518.2 $2,081 $21,454

No. 2 Combo Low NO x Burners NO x 444.2 $585 $7,048
Package Boiler SCR NO x 108 $12,375 $334,459
Package Boiler SNCR NO x 60 $16,024 $801,200
Package Boiler Low NO x w/ FGR NO x 60 $2,767 $138,350

No. 2 Rec. High ∆ P Wet Scrubbing SO 2 1149 $3,633 $57,667

No. 2 Rec High ∆ P Wet Scrubbing / WESP SO 2 1149 $4,336 $68,825

Appendix H - 31In reviewing the cost of controls based on th e amount of emissions removed, IP has indicated that additional controls for SO 2 would not be cost effective at the Courtland Mill. IP has also indicated that the Control of NO x is only cost effective for the N o. 2 Combination Boiler and that no other add-on controls would be cost effec tive for all other sources. The current add-on controls which control particles at the Courtla nd mill have efficiencies of greater than 90% therefore any additional c ontrols would not be a cost effective option.

9.3.3 Energy and Non-air Quality Impacts

Solutia has indicated that the additional SO 2 controls would generate additional waste. Solutia estimated that the FSI system w ould generated an additional 14,000 tons of fly ash per boiler and the addition of the wet sc rubber 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 an d had determined that the small reduction in energy efficiency and increase in fuel usage fo r the No. 2 Combo boiler does not offset the visibility improvements or the cost effectiven ess of $585/ton of NOx removed. IP has also indicated that additional NOx controls for othe r units would cause sign ificant impacts to the energy efficiencies and potentially allow other pollutants to be emitted to the atmosphere.

IP has suggested that any additional control of SO 2 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 s ources is described in Section 9.1.1.

9.3.5 Remaining Useful Life

Remaining useful life did not play a ro le 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 SO 2 controls. The summary of the costs and visibility improvements for the chosen options are shown in the table below:

Appendix H - 32Table 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 SO 2 46 1065.54 0.32

Boiler 6 Low Sulfur Coal SO 2 46 1065.54 0.32

Boiler 7 ROFA/FSI SO 2 60 931.95 0.24 1-98 th Percentile 24-Hour

For the IP Courtland facility the modeled visibility improvement as a result of installing the proposed add on BART controls, federally enforc eable 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 larg e reduction in the number of days above 0.5 dv at the Sipsey Wilderness Area. Relative to th e base case of 98 days above 0.5 dv, the three modeled scenarios indicate onl y 40, 59, and 56 days above 0.5 dv, which equates is an average improvement of 45 days. The summary of the co sts and visibility improvements for the chosen options are shown in the table below:

Table 9-6. IP Courtland Visibility Improveme nt 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 Combo 2 Low NO x Burners NO x 30 $1,188 0.32

No. 2 Combo Low NO x Burners NO x 30 $585 0.013 1-98th Percentile 24-Hour 2- IP has to either install low NO x 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 - 339.4 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 NO x SO 2 PM 10
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 monito r system (CEMS) for determining compliance with the SO 2 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 NO x SO 2 PM 10
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 ft 3 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 % O 2 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% O 2

Appendix H - 34I- IP has to either install low NO x 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 NO x burners on the No. 1 Combination Boiler if as change in the operat ional 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 pe rmits and will be effective by January 1, 2013. T he limitations established under BA RT (Best Available Retrofit Technology) may be changed through the NSR (New Source Revi ew) permit process which should include a visibility analysis prior to the modification.

9.5 BART Subject Sources in Other States Within 300 km of Al abama Class I Areas

There were no sources outside Alabama that contri buted to visibility impairment at the Sipsey Wilderness area.

9.6 Conclusions

Only two sources in Alabama, Solutia in Decatur and IP Courtland in Cour tland 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 av ailable control options, associated costs and visibility benefits, BART is determined to be equivalent to the MACT standards and the installation of low NO x burners on the No. 2 Combination Boiler and either install low NO x burners or only operate the No. 1 Combination Boiler when one of the following emissions units is either not operating or in pe riods of start-up of shutdown: th e No. 2 Combination Boiler the No. 2 Recovery Furnace, the No. 3 Combinati on Boiler, or the No. 3 Recovery Furnace.

Appendix H - 35

### 10.0 FINAL LONG TERM STRA TEGY (LTS) AND REASONABLE PROGRESS GOALS (RPGs)

As stated in Section 2.0 above, the RHR requires States to esta blish Reasonable Progress Goals (RPGs), expressed in deciviews (d v), for visibility improvement at each affected Class I area covering each (approximately) 10 ye ar 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 vi sibility 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 Appalach ian sites than at the coastal sites. On the 20% clearest days, sulfate levels are more uniform across the region. Reduction of SO 2 emissions would be the most effective means of reducing ammonium su lfate. Greater than 85% of SO 2 emissions in Alabama are attributable to electric generating faci lities and industrial point sources. Thus, the LTS for this firs t Regional Haze SIP focused on reductions in SO 2 emissions.

In Alabama and across the region there are signif icant controls programs in place to reduce SO 2 emissions between the baseline period and 2018. Mo st notably, CAIR is pr edicted to result in a 70% reduction from EGU SO 2 emissions in Alabama. Overall the SO 2 emissions in Alabama are predicted to decrease from 2002 le vels at 447,828 tons per year to 135,851 tons per year in 2018. Such large SO 2 reductions are predicted to result in significant impr ovements in visibility. Alabama’s CAIR rule is a ttached as Attachment H-10.

At the Sipsey Wilderness area in Alabama, vi sibility 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. Specifical ly 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 mo untain Class I areas and most of the coastal Class I areas are projected to be better than the uniform rate of progress. The pe rcentage of the target reduction achieved for the Sipsey Wilderness areas usi ng the new IMPROVE equation is between 120- 130%. This reflects a rate of improvement of 20- 30% greater than the un iform rate of progress by 2018.

In addition to improving visibility on the 20% worst visibi lity days, states ar e 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 Cl ass I areas as a result of the 2018 Base G2 emissions reductions. The percentage of the targ et achieved for the Sipsey Wilderness area is about -7.7%. Zero percent change would mean no change in visibili ty; -7.7% means that visibility is better than no change, or a 7.7% improvement (values lower than current conditions.)

Appendix H - 36ADEM completed a reasonable prog ress assessment after modeling the Clean Air Act controls discussed above. The assessment did not identify any cost effective control measures for the SO 2 non-EGU units that contributed greater than 1% to visibil ity impairment at the Sipsey Wilderness or any Class I area in neighboring States.

10.2 What Additional Emission s 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 Cla ss I areas and status of state plans to mitigate emissions from construction ac tivities and the role of NH 3 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 th e smoke management program as part of the final Regional Haze SIP submittal in December, 2 007, 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 fug itive dust emission sources, the ADEM has issued regulations addressing control of fugitive dust from construction activities and to control particulates from fugitive dust emission source s generated within plant boundaries. ADEM Admin. Code 335-3-4-.02, reads as follows:

(1) No person shall cause, suffer, allow, or perm it 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 in clude, 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, th e grading of roads, or the clearing of land;

(b) Application of asphalt, oil, wa ter, 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 materi als. 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 ma tter, 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 th at the building or equipment in which processing, handling, and storage are done be tightly closed a nd 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 ammoni a, 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 refl ecting these final decisions.

10.3 Reasonable Progress Goals (RPGs)

The RHR at 40 CFR section 51.308(d)(1) requires Stat es to establish RPGs for each Class I area within the state (expressed in deciviews) that provide for reasonable progress towards achieving natural visibility. In additi on, EPA released guidance on June 7, 2007 to use in setting RPGs. The goals must provide improvement in visibil ity 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 de termined the uniform rate of visibility improvement (in deciviews) that would need to be maintained during each implementation period in order to attain natu ral visibility conditions by 2064. ADEM has summarized expected visibility improvements under existing federal a nd state regulations, BART determinations in Alabama and neighboring states, and any additional control measures found to be reasonable toimplement 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 im provement 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 ba seline for the next planning period.

Appendix H - 38Table 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 th e 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 - 39Appendix H - 40 

### REFERENCES:

1. Boylan Ph.D., James, 2006, VISTAS Joint T ech 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 Monito ring 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 (IMPR OVE), Colorado State University, Cooperative Institute for Resear ch 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 mandato ry Class I area within a State: cost of compliance, time necessary for compliance, ener gy and non-air quality environmental impacts of compliance, and remaining useful life of any exis ting source subject to such requirements. These statutory factors would be speci fic to the sources being consid ered for additional controls.

6.1 The Four Statutory Factors

6.1-1 Cost of Compliance

The “cost of compliance” is a factor used to de termine 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 re lated to tons of pollutant removed, but also involves how the pollutant or chemical compound a ffects the extinction coefficient in each Class I area. For example, on a pound to pound compar ison, sulfate particulat e 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 us ed to adjust the RPGs to reflect the degree of improvement achievable within the long-te rm strategy (LTS) peri od, as opposed to the improvement expected at full implementation of a control measure, if th e 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 sc hedule outlined by the control strategy, the RPG should reflect what visibility improvement coul d 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 contro ls at the percentage of sources that could be controlled within the strategy peri od. (The SIP could still include control strategi es that extend beyond the 2018 milestone; in the a bove example, the visibility improvement anticipated from installation of controls at the pe rcentage 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 Envi ronmental Impacts of Compliance

The “energy and non-air quality environmental impacts of comp liance” factor is meant to consider whether the energy requi rements of the control technology result in energy penalties or benefits. For example, controls on diesel engi nes may decrease the overall efficiency and require a significant increase in diesel fuel consumption. The State s hould 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 - 16.1-4 Remaining Useful Life of the Source

The statutory factor of the “remaining useful life of the source” is a pplicable only to those measures, which would require retrofitting of c ontrol devices (or possibl y 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 rema ining 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 SO 2 Emissions Sources in Each Area of Influence (AoI)

The next step was to identify emission reductions th at have already occurred within each source category and at specific units. Unit level tables of emission comp arisons from 2002 to 2018 were developed, allowing VISTAS States to re view existing emission re ductions. These tables assigned future year control technology from IPM forecasting and State modification for EGU and from control efficiency tabl es 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 fo r 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 sour ce types did not duplic ate existing base case assumptions.

The Regional Haze Rule (RHR) requires that st ates consider the following factors and demonstrate how these factors were taken in to consideration in selecting the RPG:

• the costs of compliance

• the time necessary for compliance

• the energy and non-air quality environm ental 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 SO 2 in 2018 in the AoI defined for the Sipsey Wilderness area. Industrial boilers using oil and commercial and institu tional boilers using coal or o il had smaller contributions to SO 2 in 2018.

Sulfur dioxide emissions from utility, industria l, commercial, or inst itutional 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 re quire source specific analyses for accuracy.

Appendix H - 2Bituminous 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 SO 2 emissions with least impact to boiler performance. While sub-b ituminous coal has a lower sulfur content than bituminous coal, it al so 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 sulf ur sub-bituminous coal without affecting boiler operations. Costs of boiler modi fications 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, transpor tation costs, and modifica tion 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-combus tion control for coal-fir ed 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 cal cium 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 a nd ongoing operational and maintenance costs for the absorber tower, sorbent handling, and wa ste product handling facilities. Costs per ton vary with boiler size, type, and f acility 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 n ecessary to terminate existing fu el contracts and initiate new contracts needs to be considere d. 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 priori ties. 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-combus tion 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 add itional 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 indi vidual sources. Carbon dioxide ma y be emitted as a byproduct of flue gas desulfurization (particu larly if limestone is used), th erefore impacts of increased carbon emissions will need to be considered, especia lly if carbon emissions are limited in the future under climate change mitigation strategies.

6.2-4 Remaining Useful Life

Appendix H - 3Remaining useful live is specific to the fac ility for which controls are considered.

6.3 Process of Applying Statutory Factors

ADEM has completed its Reasonable Progress Assessm ent for the first Regional Haze SIP. The following is ADEM’s Process on Reasonable Progr ess for the current time period (from the present to 2018):

Step 1: Determine pollutants of concern.

VISTAS evaluated the species c ontribution on the 20% worst visibi lity days and concluded that sulfate accounted for greater than 70% of the visibility impairi ng pollution. The VISTAS States concluded that controlling SO 2 emissions was the appropriate st ep in addressing the Reasonable Progress Assessment for 2018. The VISTAS findings were consistent with the findings of the Southern Appalachian Mountain Initiative (SAMI). SAMI conf irmed that sulfate particles account for the greatest portion of the haze affect ing Class I areas in the Southern Appalachian region and that these sulfates were produced in large part from SO 2 emissions from coal combustion.

Step 2: Determine which source sectors s hould be evaluated for reasonable progress.

Since SO 2 point source emissions in 2018 are projected to represent greater th an 95% of the total SO 2 emissions inventory, the VISTAS States concluded that the focus should be on electric generating utility (EGU) and non-EGU point sources of SO 2 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 SO 2 reduction from the EGU sect or resulting from the implementation of CAIR. The EGUs in Alabama are expected to reduce their SO 2 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 SO 2 reductions for CAIR at the time of the next periodic report in 2012 to ensure that the reductions currently predicted by IP M for CAIR are in fact taking place. As such, ADEM has concluded that at this time the CA IR program constitutes reasonable measures for Alabama EGUs during this first assessmen t 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 SO 2 AoI for a given Class I area and identifie d those emission units with a c ontribution of 1% or more.

Appendix H - 4Step 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 n ecessary 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 instal l controls. Therefore, most of the emphasis was placed on cost of control as part of this reas onable progress assessment, as compar ed to the other three statutory factors. In addition, ADEM believe s that a fifth factor, visibility improvement, is considered by focusing the evaluation on those units that contribut e at least 1% to visib ility 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 stra tegy. Using the CAIR rule as a guide, a cost of $2,000 was used as a determin er of effectiveness.

Based on the AoI analysis, ADEM focused the r easonable progress assessments on specific units at the following non-EGU facility in the State base d 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 c ontent coals. Currently, the company is using 1.49% sulfur coal in the Keeler St oker boiler a BACT limit resulti ng from a PSD review in 1998, Cargill states that lower sulfur coal would have to be obtaine d from western USA, such as Powder River Basin, to ach ieve any reductions in SO 2 . According to the company, available information indicates that lower su lfur 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 accomm odate 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 increas e risk of spontaneous combustion in bunkers, silos, and hoppers.

Appendix H - 5Due to availability and restrict ion on boiler design, Ca rgill determined that this option was not technically feasible.

Cargill also evaluated add-on controls. Specifi cally, Cargill evaluated wet and dry scrubbers. The typical SO 2 content of the coal currently burned in Keeler Stoker boil er is 1.3 lb/MMBtu. Based on an annual heat input of 1.2x10 6 MMBtu/yr, a baseline mass emission would equate to 780 TPY of SO 2 . Based on this information, Cargill estimates that it would cost $2,946/ton to control SO 2 emissions with these technologies.

It should also be noted that Cargill has entere d into a Consent Decree agreement with EPA and affiliated states that would reduce SO 2 emissions by 50% from current levels at its US plants.

Summary:

During the current reasonable progress assessm ent 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 facil ity, and energy and non-air environmental impacts of the control installation. Howe ver, since no cost effective cont rol measures were identified for these specific sources with contributions to Alabama or neighboring St ates’ Class I areas, ADEM did not invest in an exhaustiv e review of the remaining thr ee factors beyond those described control options for major SO 2 source sectors.

It should be noted that, in orde r to show continued progress past 2018, the criteria will likely be different in the next reasonable progress assessm ent 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 assessme nt, possible SO2 reducti on strategies will be evaluated for the next round of regional haze Stat e Implementation Plan (SIP) development.



### 7.0 Best Available Retrofit Technology (BART)

7.1 Background

As required by the CAA, EPA included in the fi nal RHR a requirement for BART for certain large stationary sources that were pla ced 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 mo re of 26 specifically li sted 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 anticipa ted 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 - 6A BART-eligible source that is re sponsible for a 1.0 deciview (dv) change or more is considered to “cause” visibility impairment. Although the a ppropriate 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 res ponsible for a 0.5 dv change or more is considered to “contribute” to visibility impairme nt. 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 SO 2 , NO x , and direct particulate matter (PM) emissions, including both PM 10 and PM 2.5 , 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 s ubject 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 visi bility 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 dete rmination. Section 169A(g)(7) of the CAA requires that States must consid er 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 pollutio n 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 re sult 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 anothe r 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 maxi mum 24 hour emission rate s would be modeled for a period of three or five year s of meteorological data. States have the flexibility to develop their own methods to ev aluate model results. 1

7.2 Approach to Implementati on of BART Requirements

In order to meet the SIP submittal deadline, Al abama used a multifaceted approach to implement the RHR BART requirements. The approach consis ts of source identifica tion 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 issu es spanning states in the VISTAS region, and ongoing consultation w ith affected sources, and EPA and FLMs throughout the BART process.

Appendix H - 77.3 Identification of BART-Eligible Sources

EPA provided guidance for identifying BART-eligib le 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 determ ine the population of pot ential BART-eligible sources. The data were initially queried for any sources emitting SO 2 , NO x , PM 10 , VOC, or ammonia. The data set was refined based on emissions, whether emi ssion units fit in any of the twenty-six listed source categories for BART, a nd 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 eligibil ity from the standpoint of source category and date criteria. Through this iterative review proces s, 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’ SO 2 emissions and distance to Class I areas is included as Attachment H-4.

Appendix H - 8Alabama’s BART-eligible sources were presumed to be subject to BART but were provided the opportunity to submit modeling demons trations showing that they di d 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

A utauga

Figure 7-1. Alabama’s BART-Eligible Sources

Appendix H - 97.4 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 Rule 1 state that “A single source th at 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 ‘contri butes’ to visibility impairment should not be higher than 0.5 deciviews.” The rationale for these instructions is provided in the pr eamble to the BART guidance, in the statement, “If ‘causing’ vi sibility 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 ri se to the level of human perception.” ld be

2 The Guidance itself also states that, “States remain free to use a threshol d 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 threshol ds in the context of the human perception of visibility change. As noted above, the EPA consider s a 1.0 dv change in visibility to be humanly perceptible “in virtually all situations.” Also, the preamble to the BART guidance 3 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 contribu tion threshold. Putting all this together, it appears that “causing” visibil ity impairment means having a humanly perceptible impact (for which EPA consider s the practical threshold to be 1.0 dv) while “contributing” to visibility impairment means having a smaller imp act (for which EPA considers the threshold to be 0.5 dv or some smaller value) th at may or may not be perceptible.

ADEM retained the threshold of 0.5 dv for evaluating significance. First, th ere 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 contributi on threshold of 0.5 dv wa s appropriate in for evaluating facility contributions at Cla ss 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. A ppendix D in Acidic Deposition: State of Science and Technology, Report 24, Visibility: Existing and Hist orical Conditions -- Causes and Effects. National Acid Precipitation Assessment Program, Washington, DC. 1990.

Appendix H - 10Figure 7.2 Location of VISTAS BART-Eligible Sources

7.5 Exemption of Point Source Volatile Organ ic Compounds (VOCs) for BART Purposes

The State of Alabama has determined through m odeling that VOCs from point sources are not anticipated to cause or c ontribute significantly to the impairme nt 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 fro m 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 Impr ovement State and Tribal Association of the Southeast (VISTAS). VISTAS is a collaborative effort of state governments, tribal governments, and various federal agencies esta blished to initiate and coordinate activities associated with the management of regional haze, visi bility and other air qua lity 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 poi nt source VOCs on visibility in Class I areas.

Appendix H - 11GA Tech performed emission sensitivities to examine the impact of emission reductions on Regional Haze, annual PM 2.5 , 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 coeffi cient in deciviews (dv), then determining themaximum 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 0.6BRETBRIGCACRCHASCOHUDOSOEVERGRSMHEGLJARILIGOMACAMINGOKEFROMASAMASHENSHROSIPSSWANUPBUWOLFΔdV

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 fo r 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 sour ces are not a visibility impairing pollutant for BART purposes and that BART-eligible sources do not need to cons ider VOC emissions.

7.6 Treatment of Ammonia (NH 3 ) Emissions for BART Purposes

Similar to its treatment of VOCs, EPA guidance allows States the discretion to decide whether or not NH 3 emissions are to be considered for BA RT 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 ev aluate the haze impacts of all BART-eligible emissions of NH 3 . If the impact at the Class I area is less than the c ontribution 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 dete rmined through modeling that NH 3 emissions from point sources are not anticipated to cause or c ontribute significantly to any impai rment of visibility in Class I areas and should be exempt for BART purposes.

Appendix H - 137.6.1 Method

It was determined through modeling that NH 3 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 NH 3 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 th e way) Base F4 emissions. One such sensitivity run reduced BART-eligible source a mmonia by 100%. The purpose was to quantify the impact of NH 3 emissions from VISTAS BART sources on Cl ass 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 NH 3 . Figure 7-4 below, take n 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 NH 3 

## Impact

0.0 0.5 1.0 1.5BRETBRIGCACRCHASCOHUDOSOEVERGRSMHEGLJARILIGOMACAMINGOKEFROMASAMASHENSHROSIPSSWANUPBUWOLFΔdV

Figure 7-4. Maximum NH 3 Impact - Maximum contributio ns of all BART-eligible NH 3 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 delt a dv over the two timeframes at each Class I area. These delta dv changes represent the haze contri bution 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 Ea st and monthly-varying “climatologically representative” relative humi dity at each Class I area.

Appendix H - 14During the periods modeled, the NH 3 emissions from all BART-e ligible sources contributed more than 0.5 dv to haze at Mammoth Cave National Park (MACA), Kentucky; Mingo ilderness (MING), Missouri, Ca pe 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 NH 3 E (tpy) Distance to Nearest Class 1 Area (km) W Carolina, and Swanquarter National Wild life Refuge (SWAN), North Carolina.

T le 7-1 below.

Table 7-1. Major BART NH 3 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 co ntributors to the Sipsey Wilderness area.

to be

s

retion

ing Alabama has concluded that NH 3 emissions from point sources are not visibility impairing pollutant for BART purpos es and that BART-eligible sources need not onsider NH 3 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. NH 3 emission from BART sources may impair visi bility; however the majority of NH 3 emissions in the VISTAS region are from a few BART sources. Removal of the large NH 3 emission sources results in minimal impact on visibility at Class I areas in the VISTAS re gion. At their disc states may ask those few large sources to evaluate NH 3 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-eligibl e sources subject to BART unless the source demonstrated exemption via modeling. BART-elig ible 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 threshol d 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 - 15As stated in the BART regulation, EPA’s pr eferred approach for determining cause or contribution is an assessment with an air quali ty model such as CALPUF F or other appropriate model followed by comparison of the estimated 24 hour visibility impacts against a threshold above estimated natural conditions to be determ ined by the State. EPA recommends that th th percentile value from the modeling be compared to the State’s chosen c ontribution threshold to determine if a source does not contribute to visibility impairment. Comparison of the 98 th percentile value to the threshold must be made for each Class I area. For an annual period, th implies the 8 th highest 24 hr value at a particular Class I area is co mpared to the contribution threshold. For a 3-year modeling period, the 98 th percentile value may be in
th e 98

is

terpreted as the highest of the three annual 98 percentile values at a part icular Class I area or the 22 nd highest

of the

e was established to rovide the basis for a comm on understanding among the orga nizations performing BART

or

, specific commendations for its applica tion for BART purposes are found in Chapter 4, and specific

evelop a ve rsion 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. Specifi c model settings were provided with the

r actual missions were not available, continuous emi ssion data, permit allowable emissions, potential value in the combined three year reco rd, whichever is more conservative.

ADEM worked with the Regional Planning Organi zation (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 modeli ng results in the VISTAS region.

The VISTAS protocol describes common procedur es for carrying out air quality modeling to support BART determinations that are cons istent with the 40 CFR Part 51 Appendix Y guidelines. The protocol provides a consistent model, CALP UFF, and modeling guidelines f BART determinations, clearly delineated modeling steps, a common CALPUFF configuration guidance for site-specific mode ling, 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 si te-specific protocols is found in Chapter 5.

VISTAS contracted EarthTech to d

5.754 and CALMET Version 5.7.

For BART modeling purposes, VI STAS made publicly availabl e 12 km CALMET output files for the entire VISTAS modeling domain (Easte rn U.S.) and provided CALMET output files for five 4 km grid subdomains covering the VISTAS st ates 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 fo r 2001, VISTAS for 2002, and Midwest RPO for 2003. For the 12 km grid large domain covering th e entire VISTAS region, the No-Obs was used. For the 4 km grid, available surface an d 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 re cent 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 - 16K ey 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 a nd 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 Attach ment H-6. The protocols and demonstrations ere reviewed by ADEM’s Industrial Chemicals and Industrial Minerals Sec tions as well as the

eir ADEM

ontributing 0.5 dv impact or greater were considered subject to BART and were required to

these u sed for BART modeling are:

• After running CALPUFF for an individual facility, NO 3 should be repartitioned in P OSTUTIL.

• Ozone data from non-urban monitors shoul d be used as the background ozone in

• The Pasquill-Gifford disper sion method

• In CALPOST Method 6 with monthly aver age RH for calculating extinction as recommended by EPA should be used.

• EPA default calculations of light extin ct

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 VIST AS 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 pr e-processed MM5 meteorological da ta 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 modeli ng demonstrations were shared with both EPA and FLMs for th review and comment. The resul ting comments were in turn sh ared with the facilities. worked throughout the process to resolve many of the issues and concerns reflected in their comments. ADEM staff reviewed the demons trations 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 measur es, 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 determ ination requirements. Based upon d emonstrations, ADEM proposed to exempt 35 faci lities. Table 8-1 below provides a summary of the impacts of each BART-eligible f acility on the affected Class I areas.

Appendix H - 17Table 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 - 18Additionally, consistent with BART regulation requirements a nd 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 mo del only direct PM fine emissions. Compliance with CAIR constitutes BART for these sources for emissions of NO x and SO 2
. 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 no t 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 requ ire affected BARTeligible EGU to install, operate, and maintain BART for SO 2 or NO x emissions. Given that many of the BART-eligible units are installing scrubbers and NO x controls, and since Alabama is participating in CAIR and accepts EPA’s overall finding that CAIR “substitutes” for BART for NO x and SO 2 , 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 una ble to demonstrate less than a 0.5 dv impact via modeling. The visibility impact results for these two f acilities 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 - 19Table 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 Class I Area Alabama BART-Eligible 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 - 20Thirty eight Alabama BART-eligible sources modeled impacts at the Class I areas within 300 km, but only two contributed to visibility impa irment, both at the Sipsey Wilderness Area. Additionally, although several modeled impacts, none of the BART-eligible sources contributed to visibility impairment at Cla ss I areas outside of Alabama.

8.3 Use of New IMPROVE Equation

During the Regional Haze SIP development proc ess, 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 specif ic Rayleigh scattering. Additional discussion of the new IMPROV E equation can be found in Appendix C.

VISTAS contracted Dr. Ivar Tombach to develo p a post processor to allow CALPOST outputs to be used with the new IMPROVE equation. A di scussion of the rationale for use of the new IMPROVE equation follows. The new IMPROVE postp rocessor and instructi ons 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 repres entation of the effects of particulate matter on light extinction than the old e quation 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 compar ing the measured light extinction from nephelometers at Class I areas to light exti nction calculated using each of the equations. 2. The new algorithm recognizes spatial and tem poral variation in light extinction as size distribution of the aerosol changes by increasi ng 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 in creasing relative humidity recognizing research findings showing that fine sea salt can be an importa nt 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 greate r than represented by the old equation. 5. The new algorithm includes a NO 2 term to represent times when light absorption by NO 2 is a meaningful contribu tor to light extinction. 6. The new algorithm incorporates site-speci fic 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 IM PROVE equation, the resulting apportionment of extinction to various components is more accura te on the haziest and clearest days. This is important for development of emission control st rategies since the benefits of control of concentrations of each species will be repres ented more correctly with the new algorithm.

Appendix H - 21Two of Alabama’s BART eligible sources el ected to use the new IMPROVE equation The spreadsheet developed by Dr. Tombach to impl ement the entire new IMPROVE equation for use with CALPUFF contains a modification of CALP OST that calculates the light extinction from the CALPUFF output. In their review of th e spreadsheet and supporting documentation, EPA Region 4 staff commented that the VISTAS methodology contained in the spreadsheet developed by Dr. Tombach appropriately implements the f eatures 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 NO 2 term, the VISTAS metho dology 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 mu st 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 aff ected emission units considering all federally enforceable permit limits, were greater than 250 tons or more per year of any of these visibility-impairing pollutants: SO 2 , NO x , and PM 10 .. Alabama had three sources which chos e 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 Mob ile 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 demonstr ate 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 Intern ational Paper Courtland in Courtland, Alabama were unable to demonstrate a contribution of less than 0.5 dv at all Cla ss 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 revi se the permits for the affected sources. Discussion of the BART determinations for thes e two sources is include d 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 IM PROVE equation used and difference in results, whether a BART determination was required, the f acilities’ potential emissions, the version of

Appendix H - 22CALPUFF and its components used, who conduc ted the modeling, existing controls, and proposed controls resulting from BART determinations is included as Attachment H-12

The BART Guidelines list specific criteria that mu st 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 NO x , PM 10 , SO 2 , VOCs, or NH 3 . 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 Pa per 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 fo r 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 vari ous control options and selecting the best alternative taking into consideration any pollution control equipment in use at the so urce, 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 de gree of improvement in visibility that may reasonably be anticipated to result from the us e of such technology. Under Alabama’s approach, facilities that are subject to BA RT 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 pollutan ts which may reasonably be anticipated to cause or contribute to any impairment of visi bility 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 a nd the FLMs for their review and comment. ADEM also held conference calls with U.S. EPA Region 4 to disc uss 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 curr ently controlled. Descriptions of these units are as follows:

Appendix H - 23Boiler No. 5 (X005): This unit is a 290 MMBTU/hr coal-fir ed spreader-stoker boiler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Boiler No. 6 (X006): This unit is a 320 MMBTU/hr coal-fir ed spreader-stoker boiler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Boiler No. 7 (X015): This unit is a 536.1 MMB TU/hr pulverized coal-fired boiler. This boiler is permitted to burn propionitrile (PN) vapor. The boiler is equipped with an electrostatic precipitator for particulate cont rol. 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, SO 2 , and NOx emissions. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Coking Boiler No. 1 (X007): This unit is a 384 MMBTU/hr co al-fired stoker bo iler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 NAAQS exceedances in the area.

Coking Boiler No. 2 (X008): This unit is a 384 MMBTU/hr co al-fired stoker bo iler. The boiler is equipped with an electrosta tic precipitator for particulate control. The particulate and SO 2 limits for the unit are based upon the state fuel burning equipment regulations. The SO 2 emissions were further limited to correct for modeled SO 2 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 bo th the No.1 and No.2 Combination Boilers. In addition the No. 1 Combination Boiler has the ca pability to combust the dilute non-condensable gas (HVLC) stream from the pulp mill and chem ical recovery areas. The No. 1 Combination Boiler is vented to a venturi scrubber where th e gases are scrubbed with water to remove particulate matter.

No. 2 Combination Boiler: This unit is a 679 MMBTU/hr co mbination fuel boiler that fires coal, bark, and natural gas. The primary fuel fo r this boiler is bark, which is supplied to the boiler by the bark handling system. The other prim ary fuel for this boiler is coal. There are three coal mills associated with the No.2 Combin ation Boiler which consist of a pulverizer and a primary air fan that is used to dry the coal a nd 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 ig niter. The No. 2 Combination Boiler also has

Appendix H - 24the capability to combust the dilute non-condens able gas (HVLC) stream from the pulp mill and chemical recovery areas. The No. 2 Combina tion Boiler is vented to two electrostatic precipitators to remove particulat e matter. The flue gas is then vented to a high pressure venturi scrubber for the removal of SO 2
. 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 recove ry furnace that is designed to fire black liquor, with natural gas and fuel oil as supplemental fuel s. In the furnace the liquor is dried and burned. The organic portion of th e liquor burns which provides heat for steam generation. The inorganic porti on of the liquor is recovered to produce cooking liquor for the digesters. The combustion gases from the furnace are vented to an electro static 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 sme lt 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 fo r 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-NO x 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-NO x 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 98 th percentile visibility impairment was 4.470 dv at Sipsey Wilderness. IP Courtland’s BART source baseline contri bution to visibility impairment is 2.392 dv at Sipsey Wilderness.

9.3 BART Determination Analysis

Section 169A(g)(7) of the CAA requires that St ates 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 ex isting pollution control t echnology in use at the source, (4) The remaining useful life of the source, and (5) The degree of improvement in

Appendix H - 25visibility which may reasonably be anticipated to result from th e use of such technology. These factors are incorporated in the BART regula tion 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, 1 st col., July 6, 2005.)

9.3.1 Control Scenarios Considered

Each facility reviewed several po tential 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 - 26Table. 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 98 th Percentile 24-Hour Boiler 5 2 Low Sulfur Coal SO 2 46 0.07 0.32 Boiler 5 2 ROFA/FSI SO 2 60 0.07 0.34 Boiler 5 2 Wet Scrubber SO 2 90 0.11 0.40 Boiler 5 2 ROFA/Rotamix NOx 58 0.04 0.00 Boiler 5 2 SCR NOx 95 0.06 0.00 Boiler 5 2 Baghouse PM 99.9 0.66 0.21 Boiler 6 Low Sulfur Coal SO 2 46 0.07 0.32 Boiler 6 ROFA/FSI SO 2 60 0.07 0.34 Boiler 6 Wet Scrubber SO 2 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 SO 2 7 0.01 0.03 Boiler 7 ROFA/FSI SO 2 60 0.05 0.24 Boiler 7 Wet Scrubber SO 2 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 SO 2 16 0.01 0.05 One Coker ROFA/FSI SO 2 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 SO 2 90 0.12 0.41

Notes:

1 The predicted visibility impact of the five BA RT-eligible emission units for the base emission scenario was 7.241 deciviews (maximum 24-hour value) and 4.470 decivi ews (98th percentile 24-hour value).

2 Visibility improvements results fo r Boiler 6 were used for Boiler 5 because of the similarities of the boilers and their operation. Boiler 6 is slight ly larger than Boiler 5, therefore the visibility improvements indicated are a conser vative representation for Boiler 5.

Appendix H - 27Table. 9-2 IP Courtland Summary of Visibi lity 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 98 th Percentile 24-Hour
No. 1 Combo SNCR NO x 35 0.02 0.02

No. 1 Combo Low NO x Burners NO x 30 0.013

No. 1 Combo Addition of Caustic to Scrubber SO 2 93 0.014 0.013

No. 1 Combo Dry Scrubbing SO 2 93 0.014 0.013

No. 1 Combo Semi-dry Scrubbing SO 2 93 0.014 0.013

No. 2 Combo SNCR NO x 35 0.097

No. 2 Combo Low NO x Burners NO x 30 0.15 0.083 Package Boiler SCR NO x 90 0.037 Package Boiler SNCR NO x 50 0.041 0.017 Package Boiler Low NO x w/ FGR NO x 50 0.041 0.017

No. 2 Rec. High ∆ P Wet Scrubbing SO 2 93 0.17 0.063

No. 2 Rec High ∆ P Wet Scrubbing / WESP SO 2 93 0.17 0.063

Notes:

1 The predicted visibility impact of the seven BA RT-eligible emission units for the base emission scenario was 2.392 deciviews (maximum 24-hour value) and 1.341 deciview s (98th percentile 24- hour value).

Since both the No.1 and No.2 Lime Kilns currently employ Low-NO x Burners in the form of combustion flame tuning to reduce NO x 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 an d the No. 2 Smelt Tank are BART eligible sources for SO 2 , a control effectiveness review study was not performed sin ce both of these sources only emit approximately 1 tpy of SO 2 . 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 SO 2 ; 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 vi sibility study. Since both these

Appendix H - 28Lime Kilns are subject to and are complying with 40 CFR Part 63 Subpart MM through the use of wet scrubbers, and since the inheri t nature of lime kilns minimize SO 2 emissions, the current approach to MACT II complian ce should serve as BART for SO 2 for these Lime Kilns.

The No.2 Recovery, No. 2 Smelt Tank, No. 1 and N o. 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 vi sibility study si nce these units are subject to and complying with a MACT Sta ndard, which regulates pa rticulate emissions (40 CFR Part 63, Subpart MM).

9.3.2 Costs of Compliance

For Solutia, the 98 th percentile 24-hour visi bility 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 ar e summarized in Table 9-3 below:

Table 9-3 Solutia Summary of Cost E ffectiveness for Control Technologies

Control Cost-Effectiveness BART- Eligible Emissions Unit Control Technology Pollutant Tons Removed ($/ton Removed) ($/ton/deciview improvement) Boiler 5 Low Sulfur Coal SO 2 1438.88 1065.54 3329.81 Boiler 5 ROFA/FSI SO 2 1876.79 663.45 1951.32 Boiler 5 Wet Scrubber SO 2 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 SO 2 1587.72 1065.54 3329.81 Boiler 6 ROFA/FSI SO 2 2070.95 615.80 1811.18 Boiler 6 Wet Scrubber SO 2 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 SO 2 168.09 16,034.55 534,485 Boiler 7 ROFA/FSI SO 2 1440.8 931.95 3883.13 Boiler 7 Wet Scrubber SO 2 2161.21 1854.90 5152.50 Boiler 7 ROFA/Rotamix 1 NOx 217.35 4118 - Boiler 7 SCR 1 NOx 654.84 1986 - Boiler 7 Baghouse PM 409.57 1065.54 10,503.85 Coker 1 Low Sulfur Coal SO 2 302.09 8739 174,780 Coker 1 ROFA/FSI SO 2 1599.10 1090.20 3028.33
One ROFA/Rotamix NOx 265 4510 -

Appendix H - 29Coker
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 em issions removed, Solutia indicated that the additional controls for particulate and NOx emissi ons would not be cost effective. The current particulate controls (ESPs) achieve removal e fficiencies between 96%-99% and adequately controls the particulate emissions. The additional NOx controls indicated relatively small to no reduction in visibility impacts for the re ported costs. The costs for additional SO 2 controls appear to be more cost effective and provide some visi bility improvement. Solutia has indicated that the cost of installation and operation of the FSI sy stem or wet scrubbers would severely impact the facility’s sustainability and viab ility. For both of the coking units , Solutia has indicated that the addition of any controls would negate the viabil ity of the coking units. The requirement of the additional controls would result in a net loss and thus require the uni ts to be shutdown.

For IP Courtland, the 98 th 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 - 30Table 9-4 IP Courtland Summary of Cost Effectiveness for Control Technologies

Control Cost-EffectivenessBARTEligible Emissions Unit Control Technology Pollutant Tons Remove d ($/ton Removed) ($/ton/deciview improvement) No. 1 Combo SNCR NO x 142.8 $6,097 $304,850

No. 1 Combo Low NO x Burners NO x 122.3 $1,188 $91,385

No. 1 Combo Addition of Caustic to Scrubber SO 2 180.7 $7,260 $558,462

No. 1 Combo Dry Scrubbing SO 2 180.7 $14,574 $1,121,077

No. 1 Combo Semi-dry Scrubbing SO 2 180.7 $11,420 $878,462

No. 2 Combo SNCR NO x 518.2 $2,081 $21,454

No. 2 Combo Low NO x Burners NO x 444.2 $585 $7,048
Package Boiler SCR NO x 108 $12,375 $334,459
Package Boiler SNCR NO x 60 $16,024 $801,200
Package Boiler Low NO x w/ FGR NO x 60 $2,767 $138,350

No. 2 Rec. High ∆ P Wet Scrubbing SO 2 1149 $3,633 $57,667

No. 2 Rec High ∆ P Wet Scrubbing / WESP SO 2 1149 $4,336 $68,825

In reviewing the cost of controls based on th e amount of emissions removed, IP has indicated that additional controls for SO 2 would not be cost effective at the Courtland Mill. IP has also indicated that the Control of NO x is only cost effective for the N o. 2 Combination Boiler and that no other add-on controls would be cost effec tive for all other sources. The current add-on controls which control particles at the Courtla nd mill have efficiencies of greater than 90% therefore any additional c ontrols would not be a cost effective option.

Appendix H - 319.3.3 Energy and Non-air Quality Impacts

Solutia has indicated that the additional SO 2 controls would generate additional waste. Solutia estimated that the FSI system w ould generated an additional 14,000 tons of fly ash per boiler and the addition of the wet sc rubber 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 an d had determined that the small reduction in energy efficiency and increase in fuel usage fo r the No. 2 Combo boiler does not offset the visibility improvements or the cost effectiven ess of $585/ton of NOx removed. IP has also indicated that additional NOx controls for othe r units would cause sign ificant impacts to the energy efficiencies and potentially allow other pollutants to be emitted to the atmosphere.

IP has suggested that any additional control of SO 2 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 s ources 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 SO 2 controls. The summary of the costs and visibility improvements for the chosen options are shown in the table below:

Appendix H - 32Table 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 SO 2 46 1065.54 0.32

Boiler 6 Low Sulfur Coal SO 2 46 1065.54 0.32

Boiler 7 ROFA/FSI SO 2 60 931.95 0.24 1-98 th Percentile 24-Hour

For the IP Courtland facility the modeled visibility improvement as a result of installing the proposed add on BART controls, federally enforc eable 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 larg e reduction in the number of days above 0.5 dv at the Sipsey Wilderness Area. Relative to th e base case of 98 days above 0.5 dv, the three modeled scenarios indicate onl y 40, 59, and 56 days above 0.5 dv, which equates is an average improvement of 45 days. The summary of the co sts and visibility improvements for the chosen options are shown in the table below:

Table 9-6. IP Courtland Visibility Improveme nt 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 Combo 2 Low NO x Burners NO x 30 $1,188 0.32

No. 2 Combo Low NO x Burners NO x 30 $585 0.013 1-98th Percentile 24-Hour 2- IP has to either install low NO x 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 - 339.4 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 NO x SO 2 PM 10
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 monito r system (CEMS) for determining compliance with the SO 2 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 NO x SO 2 PM 10
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 ft 3 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 % O 2 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% O 2

Appendix H - 34I- IP has to either install low NO x 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 NO x burners on the No. 1 Combination Boiler if as change in the operat ional 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 pe rmits and will be effective by January 1, 2013. T he limitations established under BA RT (Best Available Retrofit Technology) may be changed through the NSR (New Source Revi ew) permit process which should include a visibility analysis prior to the modification.

9.5 BART Subject Sources in Other States Within 300 km of Al abama Class I Areas

There were no sources outside Alabama that contri buted to visibility impairment at the Sipsey Wilderness area.

9.6 Conclusions

Only two sources in Alabama, Solutia in Decatur and IP Courtland in Cour tland 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 av ailable control options, associated costs and visibility benefits, BART is determined to be equivalent to the MACT standards and the installation of low NO x burners on the No. 2 Combination Boiler and either install low NO x burners or only operate the No. 1 Combination Boiler when one of the following emissions units is either not operating or in pe riods of start-up of shutdown: th e No. 2 Combination Boiler the No. 2 Recovery Furnace, the No. 3 Combinati on Boiler, or the No. 3 Recovery Furnace.

Appendix H - 35

### 10.0 FINAL LONG TERM STRA TEGY (LTS) AND REASONABLE PROGRESS GOALS (RPGs)

As stated in Section 2.0 above, the RHR requires States to esta blish Reasonable Progress Goals (RPGs), expressed in deciviews (d v), for visibility improvement at each affected Class I area covering each (approximately) 10 ye ar 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 vi sibility 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 Appalach ian sites than at the coastal sites. On the 20% clearest days, sulfate levels are more uniform across the region. Reduction of SO 2 emissions would be the most effective means of reducing ammonium su lfate. Greater than 85% of SO 2 emissions in Alabama are attributable to electric generating faci lities and industrial point sources. Thus, the LTS for this firs t Regional Haze SIP focused on reductions in SO 2 emissions.

In Alabama and across the region there are signif icant controls programs in place to reduce SO 2 emissions between the baseline period and 2018. Mo st notably, CAIR is pr edicted to result in a 70% reduction from EGU SO 2 emissions in Alabama. Overall the SO 2 emissions in Alabama are predicted to decrease from 2002 le vels at 447,828 tons per year to 135,851 tons per year in 2018. Such large SO 2 reductions are predicted to result in significant impr ovements in visibility. Alabama’s CAIR rule is a ttached as Attachment H-10.

At the Sipsey Wilderness area in Alabama, vi sibility 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. Specifical ly 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 mo untain Class I areas and most of the coastal Class I areas are projected to be better than the uniform rate of progress. The pe rcentage of the target reduction achieved for the Sipsey Wilderness areas usi ng the new IMPROVE equation is between 120- 130%. This reflects a rate of improvement of 20- 30% greater than the un iform rate of progress by 2018.

In addition to improving visibility on the 20% worst visibi lity days, states ar e 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 Cl ass I areas as a result of the 2018 Base G2 emissions reductions. The percentage of the targ et achieved for the Sipsey Wilderness area is about -7.7%. Zero percent change would mean no change in visibili ty; -7.7% means that visibility is better than no change, or a 7.7% improvement (values lower than current conditions.)

Appendix H - 36ADEM completed a reasonable prog ress assessment after modeling the Clean Air Act controls discussed above. The assessment did not identify any cost effective control measures for the SO 2 non-EGU units that contributed greater than 1% to visibil ity impairment at the Sipsey Wilderness or any Class I area in neighboring States.

10.2 What Additional Emission s 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 Cla ss I areas and status of state plans to mitigate emissions from construction ac tivities and the role of NH 3 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 th e smoke management program as part of the final Regional Haze SIP submittal in December, 2 007, 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 fug itive dust emission sources, the ADEM has issued regulations addressing control of fugitive dust from construction activities and to control particulates from fugitive dust emission source s generated within plant boundaries. ADEM Admin. Code 335-3-4-.02, reads as follows:

(1) No person shall cause, suffer, allow, or perm it 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 in clude, 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, th e grading of roads, or the clearing of land;

(b) Application of asphalt, oil, wa ter, 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 materi als. 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 ma tter, 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 th at the building or equipment in which processing, handling, and storage are done be tightly closed a nd 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 ammoni a, 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 refl ecting 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 additi on, EPA released guidance on June 7, 2007 to use in setting RPGs. The goals must provide improvement in visibil ity 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 de termined the uniform rate of visibility improvement (in deciviews) that would need to be maintained during each implementation period in order to attain natu ral visibility conditions by 2064. ADEM has summarized expected visibility improvements under existing federal a nd state regulations, BART determinations in Alabama and neighboring states, and any additional control measures found to be reasonable toimplement 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 im provement 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 ba seline for the next planning period.

Table 10-1. Alabama RPGs for the Sipsey Wilderness Area.

Appendix H - 38Class 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 th e 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 - 39Appendix H - 40 

### REFERENCES:

1. Boylan Ph.D., James, 2006, VISTAS Joint T ech 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 Monito ring 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 (IMPR OVE), Colorado State University, Cooperative Institute for Resear ch 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.