# Appendix H Reasonable Progress Evaluation and Long Term StrategyReasonable Progress Evaluation/Long Term Strategy Appendix H - 1 Regional Haze SIP for Class I Areas April 4, 2008 

### TABLE OF CONTENTS

LIST OF ATTACHMENTS ........................................................................................................... 2

PURPOSE ....................................................................................................................... ................ 3

1.0 EMISSIONS CONTROLS MODELED ................................................................................... 4
1.1 Point Source Controls ..................................................................................................... ...... 7 1.1.1 Electric Generating Units ............................................................................................... 7 1.1.2 Non-EGUs................................................................................................................. ... 13 1.2 Area Source Controls ...................................................................................................... .... 15 1.3 Mobile Sources ............................................................................................................ ....... 16 1.4 Non-Road .................................................................................................................. .......... 16 1.5 Conclusion ................................................................................................................ .......... 17

2.0 UNIFORM RATE OF PROGRESS ....................................................................................... 19 3.1 Evaluation for Great Smoky Mountains National Park ...................................................... 22 3.3 Summary ................................................................................................................... .......... 24

4.0 REASONABLE PROGRE SS EVALUATION ...................................................................... 25 4.1 Area of Influence Analyses ................................................................................................ . 25 4.2 Source Type Analyses ...................................................................................................... .. 26 4.3 Back Trajectory Analyses .................................................................................................. . 27 4.4 Area of Influence (AoI) Data and Displays ........................................................................ 30 4.5 Importance of Pollutants Other Than Sulfate ..................................................................... 37 4.6 Summary of Emission Inventories Used in Reasonable Further Progress (Cost Curve) Analysis ...................................................................................................................... ........ 38 4.7 Process in Preparing Files for Cost Effectiveness Curve Development ............................. 40 4.8 Application of AirControlNET Technologies .................................................................... 41 4.9 Development of AoI-Based Cost Curves ............................................................................ 42

5.0 REASONABLE PROGR ESS ASSESSMENT ...................................................................... 43

6.0 FOUR FACTOR ANALYSIS ................................................................................................ 50 6.1 The Four Statutory Factors ................................................................................................ . 50 6.1-1 Cost of Compliance ..................................................................................................... 50 6.1-2 Time Necessary for Compliance ................................................................................. 50 6.1-3 Energy and Non-Air Quality Envi ronmental Impacts of Compliance ........................ 51 6.1-4 Remaining Useful Life of the Source .......................................................................... 51 6.2 Evaluating Four Statutory Factors for Speci fic SO2 Emissions Sources in Each Area of Influence (AoI) ............................................................................................................... .... 51 6.2-1 Cost of Compliance ..................................................................................................... 52 6.2-2 Time Necessary for Compliance ................................................................................. 53 6.2-3 Energy and Non-Air Environmental Impacts .............................................................. 53 6.2-4 Remaining Useful Life ................................................................................................ 53 6.3 Process of Applying Statutory Factors ............................................................................... 53 Table 6-3. Tennessee Sources Impacti ng Class I Areas within 300 km ................................... 57Reasonable Progress Evaluation/Long Term Strategy Appendix H - 2 Regional Haze SIP for Class I Areas April 4, 2008 Table 6-6. INVISTS Extract From EP A Table 1A (EPA-F/452-03-34) .................................. 61 for Boilers<2,000 MMBtu/hr .................................................................................................... 61 Table 6-7. INVISTA SUMMARY OF CONTROLS ............................................................... 61 Table 6-8. INVISTA TIME FOR COMPLIANCE .................................................................. 61 Table 6-9. INVISTA ENERGY & NON- AIR ENVIRONMENTAL IMPACTS .................... 61 7.0 Best Available Retrofit Technology ....................................................................................... 64 7.1 Background ................................................................................................................ ......... 64 7.2 Summary of BART Determinations ................................................................................... 64 8.0 FINAL LONG TERM STRATEGY (LTS) AND REASONABLE PROGRESS GOALS (RPGs)......................................................................................................................... .................. 65 8.1 Long-Term Strategy (LTS) ................................................................................................. 65 8.2 What Additional Emissions Controls Were C onsidered as Part of the Long-Term Strategy for Visibility Improvement by 2018? ................................................................................. 67 8.3 Reasonable Progress Goals (RPGs) .................................................................................... 68

REFERENCES: ................................................................................................................... ......... 70



### LIST OF ATTACHMENTS

Appendix H.1 – VISTAS AOIs for Class I Areas

Appendix H.2 – VISTAS Control Costs

Appendix H.3 – Electric Generating Units C ontrols Applied in Regional Haze Modeling

Appendix H.4 – EPA Guidance for Setting Reasonable Progress Goals

Appendix H.5 – Four Factor Analysis Source Reports

Appendix H.6 - TDEC-APC Rule fo r Control of Fugitive Dust

Appendix H.7 – RPG Source PermitsReasonable Progress Evaluation/Long Term Strategy Appendix H - 3 Regional Haze SIP for Class I Areas April 4, 2008 

### 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 available retrofit technology (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 Class I Federal areas which impair ment results from manmade pollution”. The regional haze rule (RHR) at 51.308(d) requires stat es to demonstrate reasonable progress toward meeting the goal of a return to natural visibil ity conditions by 2064. As a guide for reasonable progress, the RHR directs states to graphically sh ow what would be a “uniform rate of progress” toward natural conditions for each Class I area. This is known as the “glidepath. The RHR then requires states to establish RPGs for visibili ty improvement at each affected Class I area covering each approximately 10-year period until 2064. Therefore, our first set of RPGs will comprise our long term strategy (LTS) covering the period from the present until 2018. This appendix provides an overview of this first LTS . In addition, a 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.

Tennessee’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 Great Smokys National Park (GRSM) and Joyce Kilmer –Slickrock (JOKI) National 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 impa irment at Class I areas (runs conducted by Georgia Institute of Technology). IV. Examination of SO2 Area of Influence (AoIs) projections for GRSM and JOKI, and also for any surrounding states’ Class I areas whos e AoI includes any Tennessee sources, to determine which specific sources are mo st 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 for 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.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 4 Regional Haze SIP for Class I Areas April 4, 2008 

### 1.0 EMISSIONS CONTROLS MODELED

2009 and 2018 (Base G) emissions projections incl ude the following existing state and federal regulations:

• Clean Air Interstate Rule (CAIR) + Clean Air Mercury Rule (CAMR)

. Utility projections are based on Integrated Planning Model ® (IPM ® )

. CAIR will permanently cap emissions of sulfur dioxide (SO2) and ni trogen oxides (NOx) in the eastern United States. CAIR achieves large reductions of SO2 and/or NOx emissions across 28 eastern states and the District of Columbia. When fully implemented, CAIR will reduce SO2 emissions in these states by over 70 percent and NOx emissions by over 60 percent from 2003 levels. The Clean Air Mercury Rule w ill build on EPA’s Clean Air Interstate Rule (CAIR) to significantly reduce emissions from coal-fired power plants -- the largest remaining sources of mercury emissions in the country. When fully implemented, these rules will reduce utility emissions of mercury from 48 tons a year to 15 tons, a reduction of nearly 70 percent.

• NOx 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 Visibility Improvement– State and Tribal Association of the Southeast (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 determ ine 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 (NOx) emissions by 2009 and a 73% cut in sulfur dioxide (SO2) emissions by 2013.

• Consent Agreements (TECO, VEPCO, Gulf Power Crist 7, Santee Cooper, EKPC and APCO Plant Miller).

• Under a settlement agreement, by 2008, Tampa Electric will install permanent emissionscontrol equipment to meet stringent pollu tion limits; implement a series of interim pollution-reduction measures to reduce emi ssions while the permanent controls areReasonable Progress Evaluation/Long Term Strategy Appendix H - 5 Regional Haze SIP for Class I Areas April 4, 2008 designed and installed; and retire pollution 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 beginning in early 2005. The Crist plant is a significant source of NO x emissions in the Pensacola area.

• A 2004 consent agreement calls for Santee C ooper to install and commence operation of continuous emissions cont rol equipment for PM/SO 2 /NO x emissions; comply with system-wide annual PM/SO 2 /NO x emissions limits; agree no t to buy, sell or trade PM/SO 2 /NO x allowances allocated to Santee Co oper System as a result of said agreement; and to comply with emi ssion unit limits of said agreement.

• A July 2, 2007 consent agreement between the U.S. EPA and East Kentucky Power Cooperative (EKPC) requires th e 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 reduction (SCR) technology; low-NO x burners, and PM and Mercury Continuous Emissions Monitoring at the ut ility’s Spurlock, Dale and C ooper Plants. According to the EPA, the plant’s total emissions will drop from between 50 – 75% from 2005 levels. As with all federal Consent Decrees, EKPC is precluded from using reductions required under other programs, such as the Clean Air In terstate Rule (CAIR). EKPC is expected to spend over $600 million on pollution controls.

• Alabama Power Company – Plant Miller (Je fferson County) On April 25, 2006, the U.S. EPA and the Department of Justice announ ced a settlement with Alabama Power Company (APC) to reduce 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 desulfurizati on (FGD) and is required to reduce NO x by installing selective catalytic reducti on (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 al so required to begin year-round operation of the FGD equipment for control of SO 2 emissions by December 31, 2011. The installation and operation of these controls are expected to result in the reduction of 4,953 tons per year of NO x and 22,788 tons per year of SO 2 . APC is also required to install and operate by December 31, 2008, a me rcury continuous emission monitoring system. APC is precluded from using th e emissions reductions required under other programs, such as the Clean Air Interstate Ru le (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 (Federal Regist er: June 15, 2005 (Volume 70, Number 114)) / Birmingham (March 12, 2004 (Volume 69, Number 49))/ Northern Kentucky (FederalReasonable Progress Evaluation/Long Term Strategy Appendix H - 6 Regional Haze SIP for Class I Areas April 4, 2008 Register: September 16, 2004 (Volume 69, Nu mber 179)). The purpose of a state implementation plan (SIP) is to demonstrat e attainment or maintenance of the 1-hour ozone National Ambient Air Quality Standard (NAAQS). States must determine which Clean Air Act requirements are applicable to their area and submit plans to EPA for public comment and approval.

• Heavy Duty Diesel (2007) Engine 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 in cludes standards for NOx and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/ bhp-hr, respectively. These NOx and NMHC standards will be phased in 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 will require a 97 percent 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 averag ing program, modeled after the California Low Emissions Vehicle Program (LEV II) standard s. Manufacturers can pr oduce vehicles with emissions 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 commercial marine vessels (CMV) and locomotive emissions.

• Industrial Boiler / Process Heat er / Reciprocating Internal Combustion Engines (RICE) Maximum Achievable Control Technology (MAC T) standards. The EPA issued final rules to substantially reduce emissions of toxi c air pollutants from industrial, commercial and institutional boilers, process heaters a nd stationary RICE. These rules reduce emissions of a number of toxic air pollut ants, including hydrogen chloride, manganese, lead, arsenic and mercury by 2009. This rule also reduces emissions of sulfur dioxide and particulate matter in conj unction with the toxic air pol lutant reductions. The applied MACT control efficiencies were 4 percent for SO 2 and 40 percent for PM10 and PM2.5. The EPA’s industrial boiler MACT rules we re vacated on June 8, 2007. However, the EPA is required under the Clean Air Act to i ssue revised boiler MA CT rules. Should the EPA not do so in a timely manner, section 112(j ) of the Clean Air Act requires individual States to issue MACT determinations for thes e sources. As such, it is more likely than not that by 2018 MACT controls will be requi red for industrial boile rs. Therefore, the VISTAS States decided to include control assumptions for industrial boilers due to MACT.

• Combustion Turbine MACT standard. The projection inventorie s do not include the NOx co-benefit effects of the MACT regulati ons for Gas Turbines or stationary RICE, which EPA estimates to be small compared to the overall inventory.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 7 Regional Haze SIP for Class I Areas April 4, 2008 • Volatile Organic Chemical (VOC) 2-, 4-, 7- , and 10-year MACT Standards. The point source MACTs and associated emission reducti ons were designed from Federal Register (FR) notices and discussions with EPA’s Em ission Standards Divi sion (ESD) staff. We did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these c ontrols are already accounted for in the 2002 inventories supplie d 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 E GU and the non-EGU sectors of the point source inventory:

• For the EGUs, the State relied primarily on the Integrated Planning Model ® (IPM ®

- version 2.1.9) to project future generation as well as to calculate the impact of future emission control programs, to include CAIR and CAMR. The IPM results were adjusted based on state and local 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 supplemente d these data with available state and local 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 proposed federal, state, local, and site-specific control programs as of July 1, 2004.

1.1.1 Electric Generating Units

State and local (S/L) agencies specified a number of changes to the IPM results to better reflect current information on when and where future co ntrols would occur. These changes to the IPM results primarily involved S/L agen cy addition or subtraction of future emission controls based on the best available data from state rules, en forcement agreements, compliance plans, permits, and discussions/commitments fr om individual companies.

Table 1-1 lists adjustments to IPM control determ inations specified by S/L agencies for the Base G 2009/2018 EGU modeling inventorie s. Table 1-2 lists other adjustments to IPM results specified by S/L agencies for Base G modeling inve ntories. Appendix H-3 - EGU Control List is a list of all EGUs in the VISTAS region and the post combustion controls modeled for both 2009 and 2010 by facility name.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 8 Regional Haze SIP for Class I Areas April 4, 2008 Table 1-1. Adjustments to IPM Control Dete rminations Specified by State and Local Agencies for the Base G 2009/201 8 EGU Modeling 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 yr round due to CAIR SCR during

ozone

season SCR probable yr round due to CAIR None None None None

3 & 4 SCR during

ozone

season SCR yr round from Consent Decree SCR during

ozone

season SCR yr round from Consent Decree None Scrubber None Scrubber

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

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

5 None None SCR SCR None None Scrubber None

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

ORISID=26 5 SCR SCR SCR SCR Scrubber None Scrubber None Gorgas 6 & 7 None None None None None None None None

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

10 SCR SCR SCR SCR None Scrubber Scrubber Scrubber

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

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

GA Bowen 1BLR SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions None Scrubber Scrubber

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

3BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber

4BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber

Wansley 1 SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions Scrubber Scrubb er Scrubber

ORISID=6052 2 SCR SCR SCR SCR 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 NoneReasonable Progress Evaluation/Long Term Strategy Appendix H - 9 Regional Haze SIP for Class I Areas April 4, 2008 Table 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 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 Scrubb er Scrubber

4 SCR SCR SCR SCR Scrubber Scrubber Scrubber 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 Scrubber Scrubber

Coleman C1 None None SCR SCR None Scrubber Scrubber Scrubber

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

C3 None None SCR SCR None Scrubber Scrubber Scrubber

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

H2 None SCR SCR SCR Scrubber Scrubber Scru bber Scrubber

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 Scrubb er Scrubber

SC Jeffries 3 SCR None SCR None None None None None

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

Wateree WAT1 SCR SCR SCR SCR None Scrubber None Scrubber

ORISID=3297 WAT2 SCR SCR SCR SCR None Scrubber Scrubber Scrubber Canadys CAN1 None None None None None None None None

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

CAN3 None None None None None Scrubber None Scrubber Rainey CT1A None SCR None SCR None None None None

ORISID=7834 CT1B None SCR None SCR None None None None TN Kingston 1 – 8 SCR SCR SCR SCR None None Scrubber Scrubber

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

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

ORISID=3406

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

ORISID=3946

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

ORISID=3947Reasonable Progress Evaluation/Long Term Strategy Appendix H - 10 Regional Haze SIP for Class I Areas April 4, 2008 Table 1-2. Other Adjustments to IPM Results Specified by State and Local Agencies for Base G 2009/2018 EGU Modeling 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.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 11 Regional Haze SIP for Class I Areas April 4, 2008 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 Energy’s North Carolina 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 North Carolina 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.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 12 Regional Haze SIP for Class I Areas April 4, 2008 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.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 13 Regional Haze SIP for Class I Areas April 4, 2008 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 2018

1.1.2 Non-EGUs

The general approach for assembling future year data was to use recently updated growth and control data consistent with the data used in EPA’s CAIR analyses, supplement these data with available stakeholder input, and provide the results for stakeholder review to ensure credibility.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 14 Regional Haze SIP for Class I Areas April 4, 2008 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 initia l 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 internal combustion (IC) engines, which are primarily used in pipeline transmission service at compressor stations. Affected units were id entified using the same methodology as was used by EPA in the proposed Phase II rule (i.e., a larg e IC engine is one that emitted, on average, more than 1 ton per day during 2002). The final ru le reflects a control level of 82% for natural gas-fired IC engines and 90% 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 appr oach used by EPA in the proposed Phase II rule.

A summary of Non-EGU poi nt source control programs included in 2009/2018 projection invent ories include:

• Atlanta / Northern Kentucky / Birmingham 1-hr 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 PM2.5 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 nonattainme nt area (NAA) SIPs.

• NO x SIP Call Phase I- except where States have adopted Phase II already. Phase I of the NO x SIP Call applies to certain large non-E GUs, including large industrial boilers and turbines, 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. State rules and guidance documents were review ed to determine the affected 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 theReasonable Progress Evaluation/Long Term Strategy Appendix H - 15 Regional Haze SIP for Class I Areas April 4, 2008 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, Mississi ppi; (2) the Ergon refinery in Vicksburg, Mississippi; and (3) the Ergon refinery in Newell, West Virginia.

• Reasonable Further Progress 3% plans where in place for one hour plans (Metropolitan Washington, DC, and Atlanta, Georgia).

• 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 ESD staff. Reductions for MACT standards with an initial compliance date of 2001 or earlier, were not a pplied, assuming that the eff ects of these controls are already accounted for in the 2002 in ventories 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 (RICE), which EP A estimates to be small compared to the overall inventory.

• NOx 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 CAIR projections were used to calculate cont rolled 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.

The State enforces Stage I controls for gasoline dispensing facilities in 23 counties and Stage II for four counties . The State also enforces open burning controls.

Stage I is the vapor recovery technology on the underground st orage tanks and reduces the emissions during the tank filling operations at service stations. Stage II controls address dispensing of gasoline from the pump to the vehicle.

The Compliance Validation Section of TDEC-APC is tasked with in specting Stage I controls. If a facility is not found to be properly maintaini ng the control equipment, then TDEC-APC sends aReasonable Progress Evaluation/Long Term Strategy Appendix H - 16 Regional Haze SIP for Class I Areas April 4, 2008 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, agricu ltural refuse, landscaping refuse, or scrap wood. The open burning emissions inventory includes source category code (SCC) 2610030000, residential open burning of household waste and SCC 2610000100, open bur ning of yard trimmings. Since it is illegal to burn within th e municipal corporate limits, the ru ral population in each county is used to estimate emissions. The municipal corporate limits are established by local jurisdiction. Open burning of other types of materials, such as ga rbage, shingles, rubber products, paper, treated wood, plastic, salvage materials, insulation etc. is prohibited at all tim es 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 inspec tion and maintenance (I/M) programs, Stage II vapor recovery programs, anti-tam pering programs, etc. By nature , the assumptions used for the 2002 initial base year inventory vary across the VISTAS region, but our presumption is that these data accurately reflected each State’s s ituation as it existed in 2002. If a State had no plans to change program requirements between 2002 and 2018, we proposed to maintain the 2002 program descriptions without change. However, if a State planned changes, we requested information on those plans. In the final implemen tation of the inventory, St age II controls were exercised in the area source component of the inve ntory, since the units used to develop Stage II refueling estimates are different betw een 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 CAIR Technical Support Document. Usi ng these data, combined growth and control factors for the period 2002-2009 and 2002-2018 were es timated using straight-line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-SCC-pollutant leve l 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 th at affects both future CMV and locomotive emissions.

For more information on the development of non -road source inventories, see Appendix D.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 17 Regional Haze SIP for Class I Areas April 4, 2008 1.5 Conclusion

In conclusion of this discussion on source sector controls, Figures 1.1-1.4 de pict pollutant totals for NH3, PM2.5, NOx, and SO2 for the various sectors by state for 2002, 2009, and 2018 Base G2 modeling.

Figure 1-1. Annual NH3 emissions – Base G2. 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 OTWReasonable Progress Evaluation/Long Term Strategy Appendix H - 18 Regional Haze SIP for Class I Areas April 4, 2008 Figure 1-2. Annual PM2.5 emissions – Base G2.

Figure 1-3. Annual NOx 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

N o 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

0 100 200 300 400 500 600 700 800 900 1,000

A

l abama
F l o rida
G eor

gia

K e n tucky Miss i ssippi Nort h C

arolina
Sou th C arolina

T e n ne

ss

ee
V irg

inia

West Vi r giniaAnnual NOx (Thousand Tons) Miscellaneous
Nonroad Onroad
Industrial Other Fuel Combustion EGU 2002 Typical

2009 OTW

2018 OTWReasonable Progress Evaluation/Long Term Strategy Appendix H - 19 Regional Haze SIP for Class I Areas April 4, 2008 Figure 1-4. Annual SO2 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 values for the 20% best days in each year are averaged together, producing a single average deciview value for the best days. Similarly, the deciview values for the 20% worst days in each year are averaged together, producing a single average deciview value for the worst days. Extinction from indi vidual PM components is calculated from the IMPROVE equation (EPA, 2003; Hand and Malm, 2006).

The EPA has defined target natural conditions in 2064 for each Class I area (EPA, 2003). For each VISTAS Class I area, a baseline visibili ty using 2000-2004 IMPROVE data and uniform rate of progress was establishe d, using EPA default assumptions for calculating visibility and natural background (i.e., Method 1 predictions). This work was performed by VISTAS. Most recently, the scientific community has reviewed the assumptions used to calculate current and natural background visibility and has agreed to revised methods (Hand and Malm, 2006, Pitchford, 2006). VISTAS intends to present both the original and revised methods to calculate visibility and visibility improvement. Figures 2.1 and 2.2 illustrate th e predicted visibility improvement by 2018 resulting from the inventory that represents implementation of existing federal and state regulations, compared to th e reasonable progress assessment for Great Smoky 0 100 200 300 400 500 600 700

Al

abama Florida
G eor

gia Ke n tucky

M issi ssippi North C

arolina

S

ou

th C a r olina

T e n ne

s see
V irg

inia
We s t V

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

2009 OTW

2018 OTWReasonable Progress Evaluation/Long Term Strategy Appendix H - 20 Regional Haze SIP for Class I Areas April 4, 2008 Mountains National Park and Joyce Kilmer - Sl ickrock Wilderness Area. In the figures, the purple lines show the uniform rate of progress to natural condition in 2064 for the 20% worst days or 20% best days, and the incremental deci view changes resulting from a uniform rate of progress between current (2000-2004 baseline) a nd natural conditions in 2064. The lines show the improvement expected from existing and pla nned emission controls during the period of the first long term strategy. As prev iously stated, the visibility improvement for Joyce Kilmer – Slickrock Wilderness Area is represented by the results for the Great Smoky Mountains National Park.

(Method 1 Prediction = default ca lculation per EPA guidance) Figure 2-2. CMAQ 2018 (Base Best&Final) modelin g results compared to Uniform Rate of Progress at Great Smoky Mountains. Uniform Rate of Reasonable Progress Glide Path Great Smoky Mountains - W20% Data Days New Improve Equation, 12 km grid

30.28 28.67 25.79 22.59 19.38 16.18 12.97 11.05 26.72 23.50



### 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 Uniform rate of p ro g ress = 4.5 dv b y 2018Reasonable Progress Evaluation/Long Term Strategy Appendix H - 21 Regional Haze SIP for Class I Areas April 4, 2008 (Method 1 Prediction = default ca lculation per EPA guidance) Figure 2-3. CMAQ 2018 (Base Best&Final) modelin g results compared to Uniform Rate of Progress at Joyce Kilmer. Uniform Rate of Reasonable Progress Glide Path Joyce Kilmer - Slickrock - W20% Data Days New Improve Equation, 12 km grid

30.28 28.67 25.79 22.59 19.38 16.18 12.97 11.05 26.72 23.50



### 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 Uniform rate of p ro g ress = 4.5 dv b y 2018Reasonable Progress Evaluation/Long Term Strategy Appendix H - 22 Regional Haze SIP for Class I Areas April 4, 2008 3.0 GEORGIA TECH SENSITIVITIES

Georgia Tech performed emission sensitivities to examine the impact of emission reductions on regional haze, annual PM2.5, and 8-hour ozone concentrations using CMAQv4.4_SOAmods on the VISTAS 12 km modeling domain, using the 2009 OTW (on the way) Base D emissions. Once the key pollutants contributing to visibility 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 analyses were c onducted using CMAQ with the 2009 Base D inventory and considering 30% reductions from major pollutants a nd source categories. Emissions sensitivities were in itially conducted using 30% reductio ns to evaluate responses in the range where pollutant values are known to be linearly responsive to changes in emissions. Organic carbon and sulfate are assumed to be lin early responsive to ch anges in primary carbon and SO2, respectively, but nitrate and ozone chemis try are linear only in a range less than 50%. Thirty percent was chosen to be conservative. The sensitivity runs were initially designed to consider pollutant contributions in 2009 to PM2.5 in urban areas; results were also considered for Class I areas even though the fu ll benefit of controls antici pated by 2018 are not included in these sensitivity analyses. While the 2009 sensitiv ity analyses cannot be used to judge absolute contributions from each state or source sector, th e results do indicate relative level of response among pollutants, sectors, and geographic areas.

3.1 Evaluation for Great Smok y Mountains National Park

Figure 3-1 shows the results of an emissions sensitivity run for GRSM for summer (since summer is when 20% worst days occur). CM AQ was run using 30% reductions from the 2009 Base D inventory assumptions for implementing existing state and federa l regulations (Section 1.0) for major source categories of SO2, NOx, VOC, and PM. The results identify geographic origins for visibility impairing pollutants, and serve as a good starting point when considering potential air quality benefits from additional co ntrols for specific source sectors in VISTAS states or neighboring Regional Pl anning Organizations (RPOs). Th e greatest benefits at GRSM in 2009 are projected to come from further re ducing SO2 emissions from electric generating utilities (EGUs). Additional, smaller benef its are projected from additional SO2 emission reductions from non-utility, industrial point sources. Reducti ons of nitrogen oxide emissions from point sources (EGU and non-EGU) or ground level sources (on road vehicles, off road engines, and area sources) and reductions of primary carbon from point or ground level sources are projected to be significantly less beneficial than reductions in SO2 emissions. Reductions in anthropogenic VOC emissions show no response in visibility, while a 30% reduction in biogenic VOC emissions result in a measurable improve ment. However, controlling the VOCs from vegetation is not possi ble or appropriate.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 23 Regional Haze SIP for Class I Areas April 4, 2008 

# Great_Smoky_Mountains, TN (Summer)

-12.00
-10.00

-8.00
-6.00
-4.00
-2.00
0.00
2.00

SO2_E G

U SO2_no n EGU
NO

x_Ground NO

x_Poi n t NH3 VO C

s

P

C_G r ound PC_P oin t

P

C_Fires∆Bext(Mm-1) Bio.
Antro.
BCs
MRPO
M-VU
CEN
VISTAS
WV
VA
TN
SC
NC
MS
KY
GA
FL
AL Figure 3-1. Summertime sensitivity results for 2009 Base D emissions – Great Smoky Mountains.

Several states contribute to modeled reductio ns in SO4 at GRSM on the 20% worst days modeled in these two episodes in response to further reductions in 2009 SO2 emissions from EGUs (Figure 3-2). For this sensitivity run, further reducing SO2 emissions from electricity generating utilities in Georgia, Alabama, and South Carolina woul d have the greatest benefit for GRSM; reductions from electric generating util ities in other VISTAS states would have additional but smaller benefits at GRSM. Approxi mately one third of the benefit at GRSM from further SO2 emission reductions would co me from outside VISTAS states.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 24 Regional Haze SIP for Class I Areas April 4, 2008 AL
FL
GA
KY
MS
NC
SC
TN
VA
WV CEN
M-VU
MRPO
BCs Utility Contributions, by State and Region, to SO4 at Great Smoky Mtn ., Using 2009 Emissions and CMAQ model run for 20% Worst Days 2002

GA = 18%

KY = 5% FL = 1%

MS = 0.5% Northeast = 2%

VA = 4% Central = 1%

NC = 5%

WV = 4%

SC = 12% TN = 7% Eastern US = 14% (Boundary 12-km domain)

Midwest = 12% AL = 12%

Figure 3-2. Utility Contributions, by State and Region to SO4 at GRSM for 20 percent worst days using 2009 emissions.

Similar sensitivity analyses were performed for wintertime using the 2009 inventory. These results suggest that in wintertim e, reductions in ammonia emissions could be more beneficial for reducing ammonium nitrate contribu tions to visibility impairment than further reducing nitrogen oxide emissions from either ground or point sour ces. Reducing ammonia emissions could also be more effective in improving visibility in wint ertime than further reducti ons in SO2 emissions. The largest sources of ammonia emissi ons in this region are agricultural.

3.3 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 SO2 emissions from EGUs would be most benefici al for visibility at VISTAS Class I areas, followed by SO2 reductions from industrial point sources. Controlling NOx 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.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 25 Regional Haze SIP for Class I Areas April 4, 2008 

### 4.0 REASONABLE PROGRESS EVALUATION

4.1 Area of Influence Analyses

The objective of the VISTAS Area of Influence (A oI) analyses is to identify the geographic source regions that are contributi ng to visibility impairment at th e Class I areas on the 20% worst visibility days. This information will be used by the State as part of the evaluation and demonstration of reasonable progress toward visibility improvement in Class I areas.

VISTAS’ contribution assessment based on IMPR OVE monitoring data (Brewer and Adlhoch, 2005) demonstrated that ammonium sulfate is the major contribut or to PM2.5 mass and visibility impairment at Class I areas in the VISTAS and neighboring states. As illustrated in Figure 4-1, on the 20% worst visibility days in 2000-2004, ammonium sulfate 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%).

Figure 4-1. Average Extinction for 20% Worst Visibility Days in 2000-2004 using New IMPROVE Equation (data fr om VIEWS Sep 2006). 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 RayleighReasonable Progress Evaluation/Long Term Strategy Appendix H - 26 Regional Haze SIP for Class I Areas April 4, 2008 VISTAS emissions sensitivity an alyses using the CMAQ regional ai r quality model project that reductions in SO2 emissions from Electric Ge nerating Utilities (EGU) and non-EGU industrial point sources will result in the greatest improveme nts in visibility at VISTAS Class I areas. EGU and non-EGU industrial point sources comprise 95+% of the SO2 emissions inventory in the VISTAS states. The emissions sens itivity analyses also indicate that improvements in visibility from reductions in NOx or primary carbon emissi ons from ground- level sources or point sources would be small. Based on these analyses, VI STAS states chose to focus their reasonable progress evaluation for the first regional haze SI P on potential controls of SO2 emissions from EGU and non-EGU point sources. To select the specific point sources that would be considered for each Class I area, states first identified th e geographic areas that most likely influence visibility in each Class I area a nd then identified the major SO2 point sources in that geographic

area.
4.2 Source Type Analyses

The following analyses are illustrative of an in itial approach from September 2005 to evaluate potential control strategies. Th ese analyses rely on the 200 km area surrounding the Class I area and the Base F4 model run.

VISTAS emissions inventory for the simplest AoI, the 200 km concentric circle, indicated for GRSM in 2018 that fuel combustion from electric utilities and industrial processes produces the majority of the remaining SO2 emissions (Table 4-1), with 90% of 2018 SO2 total coming from fuel combustion.

Table 4-1. Source types 2018 Base G2 modeling GRSM – Percentage.
Annual 2018 Emissions (%) Tier VOC NOX CO SO2 PM-10 PM-2.5 NH3 Fuel Comb. Elec. Util. 0% 22% 1% 54% 11% 21% 1% Fuel Comb. Industrial 1% 18% 2% 30% 3% 5% 0% Fuel Comb. Other 5% 6% 3% 6% 5% 12% 1% Chemical & Allied Product Mfg 2% 0% 0% 2% 1% 1% 0% Metals Processing 1% 1% 2% 3% 2% 5% 0% Petroleum & Related Industries 0% 0% 0% 1% 0% 0% 0% Other Industrial Processes 6% 5% 1% 3% 8% 11% 0% Solvent Utilization 44% 1% 0% 0% 0% 1% 0% Storage & Transport 6% 0% 0% 0% 0% 1% 0% Waste Disposal & Recycling 4% 2% 3% 0% 5% 11% 0% Highway Vehicles 18% 25% 48% 0% 2% 2% 11% Off-highway 11% 18% 35% 1% 2% 4% 0% Miscellaneous 1% 1% 5% 0% 59% 26% 86% VISTAS Total 100% 100% 100% 100% 100% 100% 100%Reasonable Progress Evaluation/Long Term Strategy Appendix H - 27 Regional Haze SIP for Class I Areas April 4, 2008 4.3 Back Trajectory Analyses

TDEC-APC defined AoIs to id entify 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 SO2 emissions because SO4 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 (GRSM), SO4 contri butes roughly 80% to the calcu lated 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 Analysis contractor, Air Resource Specia lists (ARS), to provide SO2 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 mReasonable Progress Evaluation/Long Term Strategy Appendix H - 28 Regional Haze SIP for Class I Areas April 4, 2008 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 we re 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, North Carolina (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. Sipsy 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 perfor med for the Great Smoky Mtns. National Park.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 29 Regional Haze SIP for Class I Areas April 4, 2008 

### Back Trajectories for 2002 20% Worst Days Great Smoky Mtns. National Park

Figure 4-2. Example 72-hour back trajectori es for 20% worst visibility days in 2002 for Great Smoky Mtns. National Park.

Based on the five years of individual back tr ajectories, ARS generate d extinction-weighted residence time data for each IMPROVE site. Each hourly trajectory point was tagged with its associated sample (or end) date. Back traj ectories 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 la titude and longitude.

Extinction data is based on the IMPROVE Regiona l Haze Rule dataset, as available from the VIEWS website ( http://vista.cira.colostate.edu/views/Web/IMPROVE/SummaryData.aspx ) in November 2005 and is calculated based on the or iginal IMPROVE algorithm. For sites with less than three complete years of data, ARS developed and applied a data substitution protocol to fill missing data. Organic carbon and elemental carbon values were filled based on correlations to hydrogen and sulfate values for the same site. Othe r components were filled based on data from nearby sites.

Trajectory data were weighted by total exti nction, and by extinction components including ammonium sulfate (AmmSO4), a mmonium nitrate (AmmNO3), pa rticulate 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 SO2 emissions and lesser importance to days influen ced by organic carbon emissions. This allowed a geographic AoI to be identified based on sulfate contributions a nd not skewed by contributions from fire.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 30 Regional Haze SIP for Class I Areas April 4, 2008 These data files were provided to ENVIRO N. ENVIRON was char ged with developing residence time plots to define the geographic ar ea with highest probability of influencing the receptor on the 20% worst days dominated by sulfat e. 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.

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 and described above, and the VISTAS 2002 and 2018 36-km gridded emissions data (Bas e G, August 2006 inventory version).

Extinction weighted back-traject ory 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/lon 1 degree by 1 degree) grid and transferred to ENVIRON for further GIS processing and analysis. Back-trajectories were run for 100-meter and 500-meter start heights. Because the back-trajectories were to be combined with gridded emissions data, the first step in the analysis and GIS processing involved re-projecting these data to the Inter-RPO Unified Lambert 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 exti nction weighted back-trajectory residence times were then plotted on the VISTAS 12-km modeling do main. As sulfate is the primary visibility impairing component of the tota l extinction in the Southeast, the SO4-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 th e Class I area were labeled.

Using the trajectories with the 100-m start height , the State has defined the SO2 AoI as the area with grid cells showing 10% (area shaded in yellow in following 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. Figures 4-3 and 4-4 show the extinction weighted residence time plots for GRSM and COHU respectively for 100-m and 500- m trajectory start heights.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 31 Regional Haze SIP for Class I Areas April 4, 2008 Define SO2 Area of Influence as area > 10% Residence Time (area in yellow) using trajectories with 100-m Start Height (left plot)

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%. Max Bext Value = 724558 Max Value = 84%

Figure 4-3. Great Smoky Mountains SO4 extinc tion-weighted residence time plots for the period 2000-2004.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 32 Regional Haze SIP for Class I Areas April 4, 2008 

### SO2 Area of Influence for Cohutta, GA

Green circles indicate 100-km and 200-km radii from Class I area. Red line perimeter indicate Area of Influence with Residence Time > 10% (weighted by sulfate extinction and normalized by total extinction). Orange line perimeter indicate Area of Influence with Residence Time > 5%.
Figure 4-4. Cohutta SO4 extinction-weighte d 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 re sidence 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 disp lays and analyses.

Previous VISTAS contribution assessment, em issions sensitivity modeling, and inventory analyses have indicated that SO4 is the larges t contributor to haze on th e 20% worst visibility days and that EGUs and industrial point sources ar e the largest contributors to SO4 levels at the Class I areas. These two source categories ma ke up 95% of the VISTAS SO2 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 SO2 point source emi ssions 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 4-5 and 4-6 display the gridded point source SO2 emissions from the VISTAS modeling databases, for 2002 and 2018, re spectively. These data were processed byReasonable Progress Evaluation/Long Term Strategy Appendix H - 33 Regional Haze SIP for Class I Areas April 4, 2008 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 4-5. Annual 2002 (Base G) point source SO2 emission s for the VISTAS region for in tons/year.

Figure 4-6. Annual 2018 (Base G) point source SO2 emission s for the VISTAS region for in tons/year.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 34 Regional Haze SIP for Class I Areas April 4, 2008 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 weightin g of 1/9 was applied. The distance-weighted point source SO2 emissions are then combined with the gridded extinction-weighted backtrajectory residence times at a sp atial resolution of 36-km.

The final step in the development of the displa ys and datasets involve the combination of the residence times and gridded emission data. The distance weighted (1/d) gridded point source SO2 emissions are multiplied by the total extinc tion-weighted back-traj ectory residence times (SO2 * Bext-weighted RT * (1/d)) on a grid ce ll 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. Figures 4-7 and 4-8 display the result of this final analysis step. Note that the outlined regions (in red and light orange) represen t the extent of the >10% and >5% sulfate extincti on-weighted residence times, determ ined from the first step in the analysis (see Figures 4-3 and 4-4). As with the residence time analysis, the results of the combined distance-weighted SO2 emissions a nd extinction-weighted residence times are overlayed with county boundaries and exported to comma-delimited ASCII data files for further analyses of emissions and contro l options for specific sources.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 35 Regional Haze SIP for Class I Areas April 4, 2008 Sources identified outside the SO2 Area of Influence have large emissions even if trajectories over those sources are infre q uent. 

### 2002 SO2 Emissions weighted by Residence Time

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%. 2002 SO2 emissions 2002 SO2 emissions

Max Value = 46%

Figure 4-7. Great Smoky Mountains 2002 SO 2 Emissions * SO4 extinction-weighted residence time plots.

The following sets of plots show the 2018 SO2 Emissions multiplied by the SO4 extinctionweighted residence time plots. These were produ ced the same way as the previous plots, only using 2018 emissions instead of 2002 emissions.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 36 Regional Haze SIP for Class I Areas April 4, 2008 

### 2018 SO2 Emissions weighted by Residence Time Great Smoky Mtn. TN

2018 SO2 emissions 2018 SO2 emissions

Green circles indicate 100-km and 200-km radii from Class I area. Red line perimeter indicate Area of Influence with Residence Time > 10%. Orange line perimeter indicate Area of Influence with Residence Time > 5%. Max Value = 20%

Figure 4-8. Great Smoky 2018 SO 2 Emissions * SO4 extinction -weighted residence time plots. To understand how emissions have changed by 2018, Figure 4-9 compares 2002 and 2018 SO2 emissions multiplied by residence time.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 37 Regional Haze SIP for Class I Areas April 4, 2008 

### Comparison 2002 vs 2018 SO2 Emissions * Residence Time Using 100 m Start Height 

### – Great Smoky Mtn., TN

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%. 2002 SO2 emissions

Max Value = 46% 2018 SO2 emissions

Figure 4-9. Great Smoky Mountain 2002 vs. 2018 SO2 emissions multip lied by residence time. VISTAS states evaluated these plots of reside nce time weighted by sulfate extinction plots of gridded SO2 emissions and defined the SO2 AoIs as those areas with residence time greater than 10%, based on trajectories with start height of 100m and 4 start times per day.

Extinction-weighted residence 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 sour ces. Gridded SO2 emissions for the sulfate extinction-weighted residence time plots indicate that large emissions sour ces at great distance from the Class I area can contribute to visi bility 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 cont rols are considered, ap proximately 54% of NOx is from point sources (see Table 4.1), approxima tely 25% is from highway vehicles, and roughlyReasonable Progress Evaluation/Long Term Strategy Appendix H - 38 Regional Haze SIP for Class I Areas April 4, 2008 20% from nonroad engines. Elevated orga nic carbon (OC) and el emental 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 ag ricultural burning.

Nitrate (NH4NO3) levels in winter can be signif icant and are dependent on availability of NH3; 86% of NH3 is from area sources (e .g. agriculture). Given that sulf ate contributes greater than 70% at GRSM and JOKI on the 20% worst visibility days (Figur e 4-1), the TDEC-APC believes it is appropriate to focus on SO2 reducti ons in this first Regional Haze SIP.

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

A necessary component of control strategy desi gn is a thorough review of the emission inventories that are used in the modeling of the future year base case. These inventories can shed light on the residual emissions from sources or source categories de fined to be within areas of transport or impact of a Class I area. The most current (Base G, Fall 2006) VISTAS future year (2018) base case and 2002 base year emissions were used to conduct this control cost analysis. For purposes of listing sources with in the AoI, data were provided for all sources with emissions over distance (Q/d) greater than 5 and maximum residence time (RTmax) greater than 5. States independently defined the criteria for selecting wh ich sources from this list would 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.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 39 Regional Haze SIP for Class I Areas April 4, 2008 Table 4-4. 2018 Base Case Annual Emissions Summary.

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, these emission re views and summaries like those presented in Figure 4-10, VISTAS made a decision to further re view 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 Stat es to review existing emission reductions. These tables presented compar isons of 2002 and 2018 emission levels, for SO2, and future year control technology assignment (by IPM forecasting and State modification) for point sources. 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)

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)Reasonable Progress Evaluation/Long Term Strategy Appendix H - 40 Regional Haze SIP for Class I Areas April 4, 2008 Non-EGU unit-specific technology a ssignments were identified us ing the control efficiency tables provided by the VISTAS emissi ons inventory contractor, MACTEC.

Ultimately, the final control strategy decisions will include the application of BART subject source reductions in the fu ture year base case.

Figure 4-10. VISTAS Base G2 SO2 Emissi ons Contribution by Major Source Sector.

4.7 Process in Preparing Files for Co st Effectiveness Curve Development

The 2018 IPM file used by VISTAS for EGU sour ces (RPO 2.1.9) was obtained and matched to the 2018 base case inventory of EGU sources. This step was conducte d to ensure that incremental controls assigned to these sour ce types did not duplic ate existing base case assumptions. Because IPM does not assign a contro l efficiency with each control device applied to SO 2 and NO X , some assumptions were made based on IPM documentation as to what pollutant specific level of reduction was applied in the future year base case runs. These assumptions, by primary and secondary c ontrol device code combinations for SO 2, are presented in Table 4-5.

Since many of the control tec hnology control cost equations within AirControlNET require additional unit-level characteristic data, matc hes were made of the SMOKE IDA files to VISTAS NIF, EPA NEI, or EPA CAMD CEM data sets to obtain these variables when missing. Unit level boiler capacity (MMBtu/hr) or NETD C (MW) values are required for capital and operating and maintenance cost cal culations for many of the SO2 applied technologies. In cases where these nameplate capacity values could no t be identified, emission weighted capacities (based on the final EPA 2002 NEI) were assigned to boilers using a primary (highest emitting) A

l a b

a m

a F l o r i d

a

K e n t u c k

y G

e o r g ia
M i s s i s s i p p i

S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a

T e n n e s s e e V i r g i n i a
W e s t V

i r g i n i a 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2 0

0

2

2 0

0

9

2 0

1 8

A

l a b

a m

a F l o r i d

a

K e n t u c k

y G

e o r g ia
M i s s i s s i p p i

S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a

T e n n e s s e e V i r g i n i a
W e s t V

i r g i n i a 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2 0

0

2

2 0

0

9

2 0

1 8 Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2 0

0

2

2 0

0

9

2 0

1 8Reasonable Progress Evaluation/Long Term Strategy Appendix H - 41 Regional Haze SIP for Class I Areas April 4, 2008 SCC. Table 4-6 presents these weighted capacities. Additionally, stack flow, sulfur content, and primary SCC assignment were necessary to cr oss-reference available incremental control technologies to the base case em issions inventory data. These variables were obtained where matches could be found, in priority order of VISTAS, CAMD, and other EPA datasets, respectively.

Table 4-5. IPM Post Processing Assigned Device Codes and Applied SO 2 Control Efficiencies.

Primary Device Code Secondary Device Code Description CE RE
0 0 No Control 0 0 119 0 Dry Scrubber 90 100
141 0 Wet Scrubber 90 100

Table 4-6. Emissions Weighted NETDC (MW) Association.

4.8 Application of AirControlNET Technologies

AirControlNET is a control technology analysis t ool developed to support the U.S. EPA in its analyses of air pollution polic ies and regulations (Pechan, 2005) . The tool provides data on emission sources, potential pollution control meas ures and emission reductions, and the costs of implementing those controls.

SCC Description NETDC (MW)

10100201 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Wet Bottom (Bituminous Coal) 200

10100202 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Bituminous Coal) 500

10100203 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace (Bituminous Coal) 200

10100212 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Tangential) (Bituminous Coal) 500

10100215 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cell Burner (Bituminous Coal) 1300

10100218 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Atmospheric Fluidized Bed Combustion: Circulating Bed (Bitum. Coal) 200

10100222 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Subbituminous Coal) 400

10100223 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace (Subbituminous Coal) 400

10100226 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom Tangential (Subbituminous Coal) 500 10100401 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Normal Firing 400 10100404 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Tangential Firing 500 10100501 External Combustion Boilers; Electric Generation; Distillate Oil; Grades 1 and 2 Oil 400

10100601 External Combustion Boilers; Electric Generation; Natural Gas; Boilers > 100 Million Btu/hr except Tangential 400 10100701 External Combustion Boilers; Electric Generation; Process Gas; Boilers > 100 Million Btu/hr 200 10100801 External Combustion Boilers; Electric Generation; Petroleum Coke; All Boiler Sizes 600 10101204 External Combustion Boilers; Electric Generation; Solid Waste; Tire Derived Fuel : Shredded 200 10300811 External Combustion Boilers; Commercial/Institutional; Landfill Gas; Landfill Gas 200 20100101 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine 200 20100109 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine: Exhaust 200 20100201 Internal Combustion Engines; Electric Generation; Natural Gas; Turbine 200

All other boilers 100Reasonable Progress Evaluation/Long Term Strategy Appendix H - 42 Regional Haze SIP for Class I Areas April 4, 2008 The core of AirControlNET is a relational databa se system in which control technologies are linked to sources with in EPA emissions inventories. The sy stem contains a database of control measure applicability, efficiency, and cost inform ation for reducing the em issions contributing to ambient concentrations of ozone, PM 10 , PM 2.5 , SO 2 , NO X , as well as visibility impairment (regional haze) from point, ar ea, and mobile sources. PM 10 and PM 2.5 as included in AirControlNET represent primary emissions of PM. The control measure data file in AirControlNET includes not only the technology's control effici ency, and calculated emission reductions for that source, but also estimates th e costs (annual and capital) for application of the control measure.

Since available versions of AirControlNET contain the preprocessed application of control technologies to a predetermined set of EPA emission inventories, direct use of the model in this analysis was not possible. However, Alpine re ceived approval from EPA’s Innovative Strategies and Economics Group (ISEG) to modify the AirC ontrolNET version 4.1 source code (Sorrels, 2006) and data tables in order to make it useful to this study. Th e results of the application of this modified version of the code still retain the applicability, efficien cy, and cost information from the unmodified version of the source code , but were applied to the VISTAS modeling inventories with updated price index scalars to reflect co ntrol costs in 2005-dollars.

Using the modified inventories identified a bove, every available SO2 control strategy was assessed in AirControlNET against the EGU and non-EGU point source inventories to develop a master list of available, incrementalcontrol strategies for the entire VISTAS 36 km domain necessary for VISTAS States to design command-a nd-control or cost-effectiveness based control strategies by source or domain.

4.9 Development of AoI-Based Cost Curves

Each Class I area in the VISTAS modeling domain had an associated AoI as identified earlier in this document. In order to best determine where emission reduction has the greatest benefit, this geography was designed to limit the available source type list from including all sources within the entire domain.

These marginal cost curves include the applicat ion of all available control measures to all applicable point sources within the AoI. The cu rves will allow VISTAS States to determine if, based on the generic application of SO2 control technologies from the a ssociations originally developed in AirControlNET and improved upon w ith stakeholder input will help attain reasonable further progress emission reduction ob jectives while presumably minimizing the number and type of controlled sources in each AoI.

Using a geocoded county list from these AoIs, the master list of incremen tal control measures was parsed from all point sources located within the boundaries of the AoIs. This parsed list was then sorted by incremental cost-effectiveness (mar ginal cost) basis to determine the most cost effective control suite available to attain emi ssion reduction targets for SO2 within each AoI. Each individual source had its own co st effectiveness curve generated.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 43 Regional Haze SIP for Class I Areas April 4, 2008 In aggregate, the result s of these applications are SO2 emi ssion cost curves for all EGU and nonEGU point sources within the geographic domain of the AoI. Incremental controls on area and mobile sources were not consid ered in this analysis.

With each AoI’s cost curve, additional metrics calculated for the distance from the emission release point to the Class I area IMPROVE m onitor (in km), the 2018 residual emissions and distance (Q/d) or squared dist ance (Q/d^2), and the normalized 2018 SO2 point source emissions times distance-weighted residence time (RTMax) values for the county in which the emission release point was located were calculated for in cremental review and consideration. The TDECAPC used these values to furthe r determine control strategy deve lopment for individual Class I

areas.



### 5.0 REASONABLE PROGRESS ASSESSMENT

TDEC-APC concluded that SO2 emissions from EGU and non-EGU point sources in geographic Areas of Influence (AoIs) are sources to consider for further controls. VISTAS developed source matrices for SO2 AoIs for each Class I area , using data delivered by ENVIRON for 2002 and 2018 SO2 emissions multiplied by SO4 extinction weighted residence time plots

. Spreadsheets were developed for each Class I area with:

• Plant name

• Point ID

• Tons SO2 projected for 2018

• Q (tons)

• Current control efficiency, CE (%)

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

• Analysis of emissions per distance from source, Q/d and Q/d 2

• RT Max, the maximum percentage of time that winds pass over that area on the way to the Class I area on the 20% worst days

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

In an analysis of emissions per distance from 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 wo uld focus on those sources where RT max was equal to or greater than 10%. A second matrix fo r sources in the SO2 AoI was developed that combined the RTMax and Q/d me tric. Using this metric, TDEC-APC calculated the fractional contribution from a ll the emission units within the SO2 AoI for each Class I area and identified those units with a contribution of 1% or more to the total impairment of that Class I area.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 44 Regional Haze SIP for Class I Areas April 4, 2008 Next, TDEC-APC elected to focus on those units that contributed at least 1% to sulfate visibility impairment at a given Class I area. This was based on several regulatory programs that use a higher threshold than 1% for evaluation thresholds.

1. The BART rule specifies that a maximum impact of 0.5 dv is an acceptable threshold for establishing significance. This th reshold equates to roughly a 5% change in visible perception. This same significance level is used in the Prev ention of Significant De terioration/ New Source Review (PSD/NSR) program for the visibili ty air quality related value (AQRV).

2. The NOx SIP Call established a significance level for Section 126 peti tions of 4 parts per billion (ppb), that being the leve l to which a State's contribution to another state's ozone problem was considered significant. This level repr esents approximately 3.2% of the 1-hour ozone standard of 125 ppb, which was the standard at the time.

3. The CAIR rule established a PM contribu tion of 0.2 ug/m3 as signi ficant. This threshold represents 1.3% of the Annua l PM2.5 standard of 15 ug/m3.

4. The NAAQS assign significant impact levels (SILs) for human health standards based on a source’s contribution to air quali ty. These significant levels represent a percentage of the NAAQS. Sources that demonstrate th at their "contribution" from th e new or modified sources is less than these significance levels do not have to complete any further modeling. TDEC-APC examined all the averaging periods for the crit eria pollutants and dete rmined that the 1% threshold contribution chosen for reasonable furthe r progress was as stringent as any significant impact level, the most restrictive being the SIL for NO2 at 1 ug/m3 or 1% of the NAAQS (NO2 NAAQS 100 ug/m3).

Finally, TDEC-APC considered av ailable resources to evaluate the sources in the each Class I area’s sulfate AoI. TDEC-APC recognized that there was neither sufficient time nor resources available to evaluate all units within a given AoI. Therefore, a threshold needed to be established to determine which units would be evaluated. Table 5-1 shows that a 1% contribution threshold captures greater than 60 pe rcent of the total point source SO2 contribution to our two Class I areas, while requiring an evaluation of 10 to 22 units. In order to capture a significant percentage of the to tal contribution, the ne xt increment would i nvolve an evaluation of many more units. For example, at Great Sm oky Mountains National Pa rk, 10 units represent 61 percent of the total co ntribution. Ninety-five units repres ent an additional 35% of the total SO2 emissions contributing to visibility impairment at the Class I area. TDEC-APC believes the 1% threshold is appropriate, gi ven the contribution to the total visibility impairment at each Class I area, and the limited resources availa ble to conduct the unit- by-unit evaluation for reasonable progress.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 45 Regional Haze SIP for Class I Areas April 4, 2008 Table 5-1. Numbers and percentage of 2018 SO 2 emission units that contribute to Tennessee Class I areas.

GRSM JOKI # Units Contributing > 1% 10 22 Percentage of total contribution 61% 63%

# Units Contributing > 0.1%, but < 1% 95 101

Percentage of total contribution 35% 34%

# Units Contributing < 0.1% 88 50 Percentage of total contribution 4% 3%

The following tables 5-2 and 5-3 show the analys is for GRSM and tables 5-4 and 5-5 for JOKI for sources that met the above criteria. The full spreadsheets containing a ll VISTAS Class I area results can be found in Attachment H-1.

Table 5-2. Great Smoky Mountains Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Tennessee Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID 2002G 2018G (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

TN 0009 TVA BULL RUN FOSSIL PLANT 001 36,729 8,657 90 47.31 182.97 3.87 84.37 15437.18 0.1414

TN 0008 ALUMINUM COMPANY OF AMERICA - SOUTH PLAN 16 1,856 2,370 0 16.49 143.71 8.71 83.87 12052.96 0.1104

TN 0008 ALUMINUM COMPANY OF AMERICA - SOUTH PLAN 17 1,817 2,320 0 16.49 140.69 8.53 83.87 11799.67 0.1081

TN 0081 A.E. STALEY MANUFACTURING COMPANY 005 3,005 2,982 4 36.00 82.83 2.30 79.99 6625.57 0.0607

TN 0003 EASTMAN CHEMICAL COMPANY 021520 16,855 16,729 4 160.39 104.30 0.65 41.30 4307.59 0.0395

TN 0130 APAC-TN, INC./HARRISON CONSTRUCTION DIVI 002 153 200 0 3.97 50.32 12.68 83.87 4220.34 0.0387

TN 0020 U.S. DEPARTMENT OF ENERGY, Y-12 PLANT 002 2,354 2,336 4 48.58 48.09 0.99 84.37 4057.35 0.0372

TN 0012 BOWATER NEWSPRINT & DIRECTORY - CALHOUN 015 5,232 5,871 4 82.82 70.89 0.86 57.01 4041.44 0.0370

TN 0008 ALUMINUM COMPANY OF AMERICA - SOUTH PLAN 09 424 541 0 16.49 32.80 1.99 83.87 2750.94 0.0252

Table 5-3. Great Smoky Mountains Q/d, Q/d^2, RTMax, and fractional contribution analysis.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 46 Regional Haze SIP for Class I Areas April 4, 2008 (Outside Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID (2002 G) (2018 G) (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

NC 3708700159 BLUE RIDGE PAPER PRODUCTS - CANTON MILL G-25 2,195 2,565 0 100.17 25.61 0.26 50.35 1289.46 0.0118

Table 5-4. Joyce Kilmer Q/d, Q/d^2, RTMax, a nd fractional contribution analysis. (Tennessee Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID (2002 G) (2018 G) (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

TN 0012 BOWATER NEWSPRINT & DIRECTORY - CALHOUN 015 5,232 5,871 4 71.46 82.16 1.15 65.67 5395.45 0.0876

TN 0009 TVA BULL RUN FOSSIL PLANT 001 36,729 8,657 90 73.92 117.12 1.58 44.66 5230.58 0.0849

TN 0081 A.E. STALEY MANUFACTURING COMPANY 005 3,005 2,982 4 50.89 58.59 1.15 64.11 3756.20 0.0610

TN 0008 ALUMINUM COMPANY OF AMERICA - SOUTH PLAN 16 1,856 2,370 0 45.21 52.42 1.16 64.11 3360.65 0.0546

TN 0008 ALUMINUM COMPANY OF AMERICA - SOUTH PLAN 17 1,817 2,320 0 45.21 51.32 1.14 64.11 3290.13 0.0534

TN 0004 INTERTRADE HOLDINGS, INC. 001 1,837 2,530 4 55.89 45.26 0.81 65.67 2972.22 0.0482

TN 0020 U.S. DEPARTMENT OF ENERGY, Y-12 PLANT 002 2,354 2,336 4 72.75 32.12 0.44 44.66 1434.48 0.0233

TN 0003 EASTMAN CHEMICAL COMPANY 021520 16,855 16,729 4 181.93 91.95 0.51 12.09 1111.68 0.0180

TN 0008 ALUMINUM COMPANY OF AMERICA - SOUTH PLAN 09 424 541 0 45.21 11.97 0.26 64.11 767.40 0.0125

Table 5-5. Joyce Kilmer Q/d, Q/d^2, RTMax, a nd fractional contribution analysis. (Outside Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID (2002 G) (2018 G) (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

SC 0200-0004 DUKE ENERGY:LEE 003 4,384 7,274 0 164.50 44.22 0.27 27.54 1217.82 0.0198Reasonable Progress Evaluation/Long Term Strategy Appendix H - 47 Regional Haze SIP for Class I Areas April 4, 2008 GA 07700001 GEORGIA POWER COMPANY, YATESSTEAMELECT SG07 14,024 16,530 0 229.18 72.13 0.31 16.05 1157.69 0.0188

GA 07700001 GEORGIA POWER COMPANY, YATESSTEAMELECT SG06 15,175 16,367 0 229.18 71.42 0.31 16.05 1146.29 0.0186

GA 20700008 GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG03 18,149 27,735 0 258.20 107.42 0.42 8.94 960.33 0.0156

GA 20700008 GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG04 20,771 26,616 0 258.20 103.09 0.40 8.94 921.62 0.0150

GA 20700008 GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG01 25,286 26,264 0 258.20 101.72 0.39 8.94 909.38 0.0148

GA 20700008 GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG02 24,966 26,075 0 258.20 100.99 0.39 8.94 902.85 0.0147

SC 0200-0004 DUKE ENERGY:LEE 001 2,386 4,347 0 164.54 26.42 0.16 27.54 727.61 0.0118

SC 0200-0004 DUKE ENERGY:LEE 002 2,643 4,140 0 164.50 25.17 0.15 27.54 693.18 0.0113

GA 01500011 GEORGIA POWER COMPANY, BOWENSTEAMELECT SG04 42,634 6,294 90 163.76 38.44 0.23 17.63 677.70 0.0110

NC 3708700159 BLUE RIDGE PAPER PRODUCTS - CANTON MILL G-25 2,195 2,565 0 104.38 24.58 0.24 26.88 660.71 0.0107

GA 01500011 GEORGIA POWER COMPANY, BOWENSTEAMELECT SG03 42,900 6,111 90 163.76 37.32 0.23 17.63 657.95 0.0107

AL 0008 TVA - WIDOWS CREEK 008 9,181 10,185 90 170.64 59.69 0.35 10.74 641.07 0.0104 Table 5-6. Numbers and percentage of 2018 SO2 em ission units that contribute to Class I areas outside of Tennessee within 300 km.

COHU MACA LIGO SHRO SIPS MING JARI UPBU Total # Units Contributing > 1% 23 19 19 16 19 27 12 25Reasonable Progress Evaluation/Long Term Strategy Appendix H - 48 Regional Haze SIP for Class I Areas April 4, 2008 Percentage of total contribution 61.5 52.6 62.6 67.7 56.8 37.2 49.9 71.0

Tennessee Units Contributing > 1% 5 2 4 2 0 0 0 0

Percentage of totalcontributionTN 19.3 3.4 29.6 5.8 0 0 0 0

The following five tables, 5-7 through 5-10, show the analysis for COHU, MACA, LIGO, and SHRO 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 5-7. Cohutta Q/d, Q/d^2, RTMax, a nd fractional cont ribution analysis. (Tennessee Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID (2002 G) (2018 G) (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

TN 0012 BOWATER NEWSPRINT & DIRECTORY - CALHOUN 015 5,232 5,871 4 58.30 100.71 1.73 82.90 8348.86 0.0858

TN 0004 INTERTRADE HOLDINGS, INC. 001 1,837 2,530 4 32.47 77.92 2.40 82.90 6459.57 0.0664

TN 0009 TVA BULL RUN FOSSIL PLANT 001 36,729 8,657 90 144.05 60.10 0.42 24.66 1482.07 0.0152

TN 2730 E. I. DU PONT DE NEMOURS AND COMPANY 0002 1,286 1,173 0 67.08 17.48 0.26 83.31 1456.26 0.0150

TN 0081 A.E. STALEY MANUFACTURING COMPANY 005 3,005 2,982 4 109.35 27.27 0.25 38.49 1049.62 0.0108

Table 5-8. Mammoth Cave Q/d, Q/d^2, RTMax, and fractional cont ribution analysis. (Tennessee Sources)

SO2 Tons Distance Fraction

State Plant Point ID (2002 G) (2018 G) CE (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

TN TVA CUMBERLAND FOSSIL PLANT 001 7,354 12,073 95 157.50 76.65 0.49 21.87 1676.34 0.0173

TN TVA CUMBERLAND 002 9,165 11,936 95 157.56 75.76 0.48 21.87 1656.87 0.0171Reasonable Progress Evaluation/Long Term Strategy Appendix H - 49 Regional Haze SIP for Class I Areas April 4, 2008 FOSSIL PLANT

Table 5-9. Linville Gorge Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Tennessee Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID (2002 G) (2018 G) (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

TN 0003 EASTMAN CHEMICAL COMPANY 021520 16,855 16,729 4 81.39 205.55 2.53 84.07 17280.59 0.2429

TN 0003 EASTMAN CHEMICAL COMPANY 020101 1,645 1,633 4 81.67 19.99 0.24 84.07 1680.56 0.0236

TN 0003 EASTMAN CHEMICAL COMPANY 261501 1,163 1,202 90 81.03 14.84 0.18 84.07 1247.60 0.0175

TN 0009 TVA BULL RUN FOSSIL PLANT 001 36,729 8,657 90 200.32 43.22 0.22 20.14 870.45 0.0122

Table 5-10. Shining Rock Q/d, Q/d^2, RTMax, and fractional contribution analysis. (Tennessee Sources)

SO2 Tons CE Distance Fraction

State Plant ID Plant Point ID (2002 G) (2018 G) (%)* (km) Q/d Q/d^2 RT Max** Q/d*RTMax Contribution

TN 0003 EASTMAN CHEMICAL COMPANY 021520 16,855 16,729 4 127.07 131.65 1.04 41.01 5398.97 0.0445

TN 0009 TVA BULL RUN FOSSIL PLANT 001 36,729 8,657 90 143.14 60.48 0.42 26.51 1603.32 0.0132

Spreadsheets were developed for each Class I area source with Q/d *RTMax > 1%, indicating the plant name, industry descrip tion, emissions projections for 2018, current control efficiency (CE%), distance from Class I area, Q/d, Q/d 2 , RT maximum, Q/d*RTMax, and the percentage of a single source contribution to the total Q/d*RT fo r a Class I area. Control efficiency, CE%, is important because it gives a sense of which fac ilities are already contro lled by what percent and which may be controlled further.

Next, an analysis of control options, generic cost s of controls, and "Cost/ton" for various units contributing greater than 1% to any Class I area was developed. Spr eadsheets containing unitlevel emissions and other associated data for the Class I areas was matched with data from AirControlNET (Pechan, 2005) to give SO2 contro l efficiency, annual SO2 emissions reduction from 2018 Base Case, total annualized cost (in 2005 dollars), and cost per ton reduced for application of specific control measures.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 50 Regional Haze SIP for Class I Areas April 4, 2008 The TDEC-APC reviewed the sources, emissions , control options, and co sts from the SO2 AoI matrices and defined sources for which the Four Factor Analysis was to be conducted. The same few categories of point sources contribute to the majority of SO2 emissions, those being fuel combustion from electric utilities and fuel co mbustion from industrial sources, with little contribution from other sources. Therefore, the TDEC-APC eliminated other source categories from the Four Factor Analysis. The TDEC-APC next looked at source-specific costs, existing controls, remaining useful life, environmental and energy impacts.



### 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 a reasonable progress goals (RPG s) for any mandatory Class I ar ea 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).Reasonable Progress Evaluation/Long Term Strategy Appendix H - 51 Regional Haze SIP for Class I Areas April 4, 2008 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

6.1-4 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 affect s the annualized costs of retrofit controls.

6.2 Evaluating Four Statutory Factors for Speci fic SO2 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 conducte d to ensure that incremental controls assigned to these sour ce types did not duplic ate existing base case assumptions.

For non-EGUs, VISTAS used EPA’s AirContro NET database, modified for the VISTAS emission inventories. The core of AirControlN ET is a relational database system in which control technologies are linked to sources within EPA emissions inventories. The system contains a database of control measure appli cability, efficiency, and cost information for reducing emissions. The control measure data file in AirControlNET includes not only the technology's control efficiency, and calculated emission reductions for that source, but also estimates the costs (annual and capital) for application of the control measure.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 52 Regional Haze SIP for Class I Areas April 4, 2008 Using the modified inventories identified a bove, VISTAS ran every available SO2 control strategy in AirControlNET against the EGU and non-EGU point source inventories to develop a master list of incremental control strategies for each unit in the VI STAS 36 km domain.

For the sources within the AOIs for each Tennessee Class I area, the master list of incremental control measures was sorted to determine the co sts of incremental control measures. These data were combined in a master spreadsheet with th e distance from the emission release point to the Class I area IMPROVE monitor (in km), the 201 8 residual emissions and distance (Q/d) or squared distance (Q/d^2), and the normalized 2018 SO2 point source emissions times distanceweighted residence time (RTMax) values for the county in which the emission release point was located. Tennessee evaluated these control measures and costs (see Attachment H-2) as part of their review of the statutory factor s for reasonable further progress.

The Regional Haze Rule requires that states cons ider the following fact ors and demonstrate how these factors were taken into considerati on in selecting the re asonable progress goal:

• 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 SO2 in 2018 in the AoI defined for the Great Smokys and Joyce Kilmer Tennessee Class I areas. Industrial boilers usi ng oil and commercial and institutional boilers using coal or oil had small contributions to SO2 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.

Bituminous coal is commonly burned in boilers in the eastern US. Switching to another bituminous coal with lower su lfur content or blending b ituminous coals can reduce SO2 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 beReasonable Progress Evaluation/Long Term Strategy Appendix H - 53 Regional Haze SIP for Class I Areas April 4, 2008 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 3 or more years depending on market availability of labor and materials and utility system-wide priorities. Time necessary for compliance will need to be refined for specific sources.

6.2-3 Energy and Non-Air Environmental Impacts

Switching to lower sulfur fuel or installing post-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 individual sources. Ca rbon dioxide is emitted as a byproduct of flue gas desulfurization, therefore impacts of increased carbon emissions will need to be considered, particularly if carbon emissions are limited in the future under climate change mitigation strategies.

6.2-4 Remaining Useful Life

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

6.3 Process of Applying Statutory Factors

TDEC-APC has completed the Reasonable Progre ss Assessment for the first Regional Haze SIP. The following is TDEC-APC’s Process on Reasonabl e Progress Assessment 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 SO2 emissions was th e appropriate step in addressing the Reasonable Progress Assessment for 2018. The VISTAS findings were consistent with the findings of the Southern Appalachian Mountain Initiative (SAMI). SAMI conf irmed that sulfate particlesReasonable Progress Evaluation/Long Term Strategy Appendix H - 54 Regional Haze SIP for Class I Areas April 4, 2008 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 SO2 emissions from coal combustion.

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

Since SO2 point source emissions in 2018 are projected to represent greater than 95% of the total SO2 emissions inventory, the VISTAS States co ncluded that the focus should be on electric generating unit (EGU) and non-EGU point sources of SO2 emissions.

Step 3: Determine if the Clean Air Interstate Rule (CAIR) is sufficient for reasonable progress for subject EGU’s.

TDEC-APC evaluated the amount of SO2 reduction from the EGU sector resulting from implementation of CAIR. The EGUs in Tennessee (Tables 6-1 and 6-2) are expected to reduce their SO2 emissions by approximately 75% between 2002 (2002 missi ons approximately 333,884 tons per year) and 2018 (2018 emissions approximately 84,185 tons per year).

Table 6-1. Tennessee TVA Plants Heat Input Values

Facility Name 2006 Heat Input (mmBtu) 2006 Net Output (GWH) Allen 55,883,612 5,291 Bull Run 45,085,485 4,696 Cumberland 185,663,408 18,743 Gallatin 75,755,960 7,524 John Sevier 49,978,425 5,044 Johnsonville 88,835,413 7,555 Kingston 107,167,323 10,378 2006 heat inputs were obtained from Acid Rain Program monitoring data, and 2006 net outputs were obtained from TVA.

Table 6-2. Tennessee TVA Plants EmissionsReasonable Progress Evaluation/Long Term Strategy Appendix H - 55 Regional Haze SIP for Class I Areas April 4, 2008 To further support EGUs subject to CAIR is suff icient for reasonable progress, a discussion in the CAIR rule highlighted below (70 FR 25197) a ddresses the reasonable pr ogress factors of cost and time necessary for compliance for these EGUs, and provide the necessary support for a State's four factor reasonable progress analys is that must accompany a State’s assertion that CAIR is sufficient for reasonable progress for subject EGU’s during the first planning period.

From past experience in examining multi-pollu tant emissions trading programs for SO2 and NOX, EPA recognized that the air polluti on control retrofits that result from a program to achieve highly cost-effective reduc tions are quite significant and can not be immediately installed. Such retr ofits require a large pool of specialized labor resources, in particular, boilermakers, the availability of which will be a major limiting factor in the amount and timing of reductions.

Also, EPA recognized that the regulated indus try will need to secure large amounts of capital to meet the control requirements while managing an already large debt load, and is facing other large capital requirements to improve the transmission system. Furthermore, allowing pollution control retrofits to be installed over time enables the industry to take advantage of planned outage s at power plants (unplanned outages can lead to lost revenue) and to enable project m anagement to learn from early installations how to deal with some of the engineering c hallenges that will exist, especially for the smaller units that often present space limitations.

Based on these and other considerations, EPA de termined in the NPR that the earliest reasonable deadline for compliance with the final highly cost-effective control levels for reducing emissions was 2015 (taking into consid eration the existing ban k of title IV SO2 allowances). First, the Agency confirmed that the levels of SO2 and NOX emissions it believed were reasonable to set as annual emissi ons caps for 2015 lead to highly costeffective controls for the CAIR region.

Once EPA determined the 2015 emissions reduc tions levels, the Agency determined a proposed first (interim) phase control le vel that would commence January 1, 2010, the earliest the Agency believed initial pollution controls could be fully operational (in today's final action, the first NOX control phase commences in 2009 instead of in 2010, as explained in detail in section IV.C). The first phase would be the initial step on the Facility Name PM 10 Emissions (tons) SO 2 Emissions (tons) NO X Emissions (tons) 2002 2009 2018 2002 2009 2018 2002 2009 2018 Allen 866 981 981 19,030 21,263 21,263 14,510 2,061 2,061 Bull Run 1,919 2,267 2,267 42,188 8,657 8,657 17,909 2,078 2,078 Cumberland 1,831 1,690 1,690 16,661 24,009 24,009 49,939 5,762 5,762 Gallatin 611 594 594 34,157 47 ,391 2,157 11,782 11,461 11,456 John Sevier 160 151 163 35,488 32,327 1,846 10,234 10,109 1,574 Johnsonville 5,561 2,661 2,661 108,789 22,216 22,216 23,879 13,329 1,333 Kingston 3,574 3,766 4,056 77,571 71,120 4,037 26,089 3,238 3,633
Emissions from 2002, 2009, and 2018 are from the VISTAS Base G/G2 emission inventory. 2002 emissions are based on the VISTAS 2002 actual emissions inventory.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 56 Regional Haze SIP for Class I Areas April 4, 2008 slope of emissions reductions (the glide-path) leading to the final (second) control phase to commence in 2015. The EPA determined the first phase based on th e feasibility of installing the necessary emission control re trofits, as described in section IV.C. Although EPA's primary cost-effectiveness determination is for the 2015 emissions reductions levels, the Agency also evaluated the cost effectiveness of the first phase control levels to ensure that they were al so highly cost effe ctive. Throughout this preamble section, EPA reports both the 2015 and 2010 (and 2009 for NOX) cost effectiveness results, although the first phase levels we re determined based on feasibility rather than cost effectiveness. The 2015 emissions reductions include the 2010 (and 2009 for NOX) emissions reductions as a subset of the more stringent requirements that EPA is imposing in the second phase.

TDEC-APC intends to re-evaluate the IPM predic tions of SO2 reductions for CAIR at the time of the next periodic report in 2012 to ensure that the reductions currently predicted by IPM for CAIR are in fact taking place. Based on the ev aluation of additional control measures and predictions by IPM under CAIR, TD EC-APC has concluded that at this time the CAIR program constitutes reasonable measur es for Tennessee EGUs during this first assessment period (between baseline and 2018).

Step 4: Determine which emission units would be evaluated based on impact.

TDEC-APC calculated the fractional contribution fr om all emission units within the SO2 AoI for a given Class I area and identified those emission units with a contribution of 1% or more.

Step 5: Evaluate the four factors.

Each emission unit identified in Step 4 above was evaluated using the statutory and regulatory factors of 1) cost of compliance, 2) time 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. TDEC-APC believes that the cost of comp liance is the typically th e dominant factor in whether a source will be required to install controls. Therefor e, much emphasis was placed on cost of control as part of this reasonable progr ess assessment, as compared to the other three statutory factors. In addition, TDEC-APC believes that the fi fth factor, visibility improvement, is considered by focusing the evaluation on those units that contribute at l east 1% to visibility impairment at a given Class I area.

For the limited purpose of evaluating the cost for the reasonable progress a ssessment in this first regional haze SIP, TDEC-APC 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 $2000 was used as a determiner of effectiveness.

Based on the AoI analysis, TDEC-APC focused th e reasonable progress assessments on specific units at the following non-EGU facilities in the State based on the 1% criteria discussed earlier in this document:Reasonable Progress Evaluation/Long Term Strategy Appendix H - 57 Regional Haze SIP for Class I Areas April 4, 2008 Table 6-3. Tennessee Sources Impact ing Class I Areas within 300 km

SIGNIFICANT SOURCE IMPACTED CLASS I AREA DETERMINATION A.E. STALEY MANUFACTURING COMPANY (NOW TATE & LYLE) COHU, JOKI, GRSM INCORRECT DATA APAC-TN, INC./HARRISON CONSTRUCTION DIVI GRSM INCORRECT DATA
BOWATER NEWSPRINT & DIRECTORY - CALHOUN COHU, JOKI, GRSM 4-FACTOR ANALYSISE. I. DU PONT DE NEMOURS AND COMPANY (NOW INVISTAHIXSON/CHATTANOOGA) COHU 4-FACTOR ANALYSIS

INTERTRADE HOLDINGS, INC. COHU, JOKI REMOVED FROM SERVICE U.S. DEPARTMENT OF ENERGY, Y-12 PLANT JOKI, GRSM FUEL SWITCH TO N.G.
ALUMINUM COMPANY OF AMERICA - SOUTH PLAN JOKI, GRSM BART SOURCE
EASTMAN CHEMICAL COMPANY JOKI, GRSM, LIGO, SHRO BART SOURCE
TVA BULL RUN FOSSIL PLANT COHU. JOKI, GRSM, LIGO, SHRO BART SOURCE
TVA CUMBERLAND FOSSIL PLANT MACA BART SOURCE

A.E. STALEY MANUFACTURING COMPANY (NOW TATE & LYLE)
Tate & Lyle (formerly A. E. Staley) in Loudon County significantly reduc ed its sulfur dioxide emissions and that reduction was not recognized in the inventorie s used to perform the VISTAS modeling. The company was issued a construc tion permit on March 9, 2007, that reduced SO2 emissions from the boilers by approximately 62 percent. The lower SO2 emissions, (1145 tons) are not reflected in the VIST AS inventory for 2018. For a pr ojected 2018 SO2 emission of 1136 tons (1145 tons times a factor of 0.9923 - simila r to the AoI 2018 emissi on projection procedure in Appendix H-1 at roughly 0.8% reduction), the source contribution at GRSM and JOKI will be 0.024 (significant) and 0.0041 at COHU (insignifican t). The source contributions were lowered from 6% at GRSM and JOKI to roughly 2% at each, and from initially 1% at COHU to 0.4% insignificant impact contribution. Due to the unce rtainty in the 2018 emission projections for this emission unit, TDEC-APC elected to defer assess ment of this facility until the next review period in 2018.

APAC-TN, INC./HARRISON CONSTRUCTION DIVI

This facility (emission unit #2) was erroneously modeled as a Ready Mix Concrete plant with actual SO2 emissions of 153 tons per year (2002 ) and projected actual 2018 SO2 emissions of 200 tons per year, leading to a significant cont ribution at GRSM of 3.87%. Such source would have minimal SO2 emissions if any. The real SO 2 source that should have been modeled is a Drum Mix Asphalt plant (emission unit #1) with an SO2 allowable emissions of 20.3 tons per year and subject to NSPS (See Appendix H-7, page 8). VISTAS AoI modeling at twice this level of emissions for a 2018 projection of 40.0 tons per year will lead to an AoI insignificant contribution of 0.0077 (or 0.8%) at GRSM [Appe ndix H-1, based on a distance of 3.97 km to GRSM, Q/d value of 10.08, RTMax value of 83.87, total contribution of 109,160.06 (Q/d * RTMax) from all sources at GRSM]. TDEC-APC determined that this source is insignificant with regard to its contribution to GR SM and no further analysis is required.

U.S. DEPARTMENT OF ENERGY, Y-12 PLANTReasonable Progress Evaluation/Long Term Strategy Appendix H - 58 Regional Haze SIP for Class I Areas April 4, 2008 United States Department of Energy Y-12 Plant is in the process of repoweri ng its coal-fired boilers. Construction Permit # 960947F has been issued to the USDOE’s Y-12 Plant to replace the coal-fired boilers with natural gas fired boilers. A copy of this permit wi th the timing of the repowering appears in Appendix H-7. Compared to coal-fir ed emissions, the reduction in sulfur dioxide emissions is very significant, as natural gas has essentially no sulf ur. For this reason, no further attempts were made to evaluate the facility under the four-factor analysis.

INTERTRADE HOLDINGS, INC.
This source is removed from service. Current facility permit is listed in Appendix L-12.

TDEC-APC determined that two non-EGU sour ces, Bowater Newsprint in Calhoun, Tennessee and E.I. DuPont de Nemours (now INVISTA) in Hixson, Tennessee should be subjected to the four-factor analysis because those facilities contributed 1% or more to visibility impairment in a Class I area. Each facility was requested to pe rform an analysis and submit that to TDEC-APC for review (Attachment H-5)

BOWATER NEWSPRINT & DIRECTORY - CALHOUN

The following is a summary of the assessment fo r this Kraft Paper Mi ll (non-EGU) facility:

Date of Bowater 4-factor analysis: October 31, 2007

Unit on an AoI list with a FGD control option cost of $4517.00 /ton SO2 removed

Unit Description: Three Coal-fir ed Boilers, using low sulfur eas tern bituminous coal since 1984 of slightly less than 1.1% sulfur c ontent with the following specifications:

Table 6-4. BOWATER Coal-Fired Boilers

BOILER NO. FUEL TYPE MAX FIRING RATE (MMBtu/hr) EXISTING CONTROLS 10 Bituminous Coal 214 ESP 11 Bituminous Coal 460 ESP, LNB 12 Bituminous Coal 460 ESP, LNB

The following control technology op tions were considered for th e abovementioned Fuel Burning Installation unit (si ngle common stack):

Low sulfur Coals Wet Scrubbers

Bowater evaluated switching to a lower sulfur (0.6%) west ern sub-bituminous coal and determined that is not a viable option due to the different physical properties (ash fusionReasonable Progress Evaluation/Long Term Strategy Appendix H - 59 Regional Haze SIP for Class I Areas April 4, 2008 temperature, etc.) of western sub-bituminous coal . The physical properties of the coal are very important as Bowater’s boilers were designed to burn Eastern bituminous coal, not Western coals. Thus, switching to lower sulfur western coal is not so much a cost factor as it is a technologically infeasible factor.

Bowater also evaluated installing SO2 wet sc rubbers which is tec hnically possible, but determined that is an expensive option for the ol der existing boilers at a projected cost exceeding $5,000 per ton of SO2 removed. Bowater also states that controls can further increase the $/ton of SO2 removed as the facility will be compounded with the increase in manufacturing costs due to the forecasted decline of 30% by 2018 in Nort h American newsprint demand, and that will further reduce operations and thus actual SO2 em issions. They also contends that the VISTAS growth factors for 2009 and 2018 (6.7% and 16.9%, re spectively) are not representative of their future operations due to the proj ected newsprint decline in the fu ture. Bowater also discusses in their analysis the seasonal variability of th eir emissions as not be ing equally distributed throughout the year. Their months of highest coal firing correspond to the months with the best 20% visibility (November through March), and the months of lo west coal firing correspond to the months with the worst 20% visi bility (June thr ough September).

Bowater states that the remaini ng useful life of the power boilers exceeds the useful life of any potential SO2 control equipment . However, the rema ining useful life of the facility’s five paper machines supported by the power boilers may be considerably shorter than the life of any potential SO2 controls. Three of the five paper m achines at the facility were built in the 1950’s, while the remaining two were built in the 1980’s. Based upon market forecasts for newsprint in North America, Bowater believes that the older 1950 vintage machines may be permanently shut down in the future. These less efficient machines require more hot water from the boilers to be produced. If they are shut down, less coal will be burned and less visibility impairing emissions will be produced. This does not mean that the bo ilers will be shut down; it merely means that they will not be operated at a higher capacity

. Other environmental factors impacting the application of wet scrubbers are the water scarcity in the local area due to seasonal droughts and wastewater/sludge trea tment and disposal.

Bowater further states that the VISTAS 2002 emission inventory and modeling utilized an erroneous emission rate (177,579 to ns) based on 1.5% sulfur in the coal as opposed to 1.1% sulfur currently using and 140,000 tons per year cu rrent emissions. This translates into 42% or 2,135 tons of SO2 reductions per year. Additiona lly, the kraft mill non-condensible TRS gases are no longer burned in the power boilers, thus reducing SO2 emissions by another 170 tons per
year.

E. I. DU PONT DE NE MOURS AND COMPANY (NOW INVISTA-HIXSON/ CHATTANOOGA)

The following is a summary of the assessment for this non-EGU facility:

Unit on an AoI list with a FGD contro l option cost of $8162 /ton SO2 removed

Three Coal-fired Boilers, Emission unit EU -002, with the following specifications:Reasonable Progress Evaluation/Long Term Strategy Appendix H - 60 Regional Haze SIP for Class I Areas April 4, 2008 Table 6-5. INVISTA Coal-Fired Boilers

BOILER NO. FUEL TYPE MAX FIRING RATE (MMBtu/hr) EXISTING CONTROLS 3 Bituminous Coal 65 Baghouse 4 Bituminous Coal 150 Baghouse 5 Bituminous Coal 150 Baghouse

The following control technology options were c onsidered for the above mentioned emission points:

Low sulfur Coals Wet FGD (Wet Scrubbers) Spray Dryer Absorber (SDA) System Fluidized Bed Combustion (FBC) with Limestone Dry Sorbent Injection (DSI) System

The current SO2 emissions averaged at 944 t ons/yr over three years (2004, 2005, and 2006) from these boilers. Current Title V permit limits coal sulfur content to 1.25%, ho wever, actual sulfur content has averaged nearly 1.0% over the last three years.

INVISTA evaluated switching to a lower sulf ur (0.75%) western sub-bituminous coal and determined that is a viable option, however, to calculate cost-effectiveness, the change in emissions must be determined. The decrease in SO2 emissions from the baseline was calculated to be approximately 214 tons per year. The cost-e ffectiveness was calculated to be approximately $1,225 per ton of SO2 removed. Low sulfur coal is a commodity that is experiencing increasing market denmand and thus increasing costs.

A Wet FGD is determined to be technically feasible option for control of SO2 emissions from EU-002. The TCI (capital cost) for the Wet FGD is estimated at $11,445,390 with an estimated TAC (operating and maintenance) cost of $3,046,633 ba sed on an interest rate of 8.0% and an economic lifetime of 10 years. At 92% efficien cy and 944 tons baseline, the estimated emitted SO2 emissions would be 76 tons per year. Th e cost-effectiveness was calculated to be approximately $3,508 per ton of SO2 removed. Additional costs associated with installing a separate stack due to problems associated with the presence of a persiste nt , highly opaque steam plume from the scrubbers’stacks making this option even less cost-effective.

An SDA system was determined to be technically feasible as a control option. However, this option could result in an overall ash with properties so different from the current that it will no longer be acceptable for use in cem ent kiln. If that becomes the cas e, the ash and spent reactant mixture would have to be trucked offsite for disposal in a landfill at a substa ntial increase in cost relative to the curr ent disposal. The cost-effectiveness of applying SDA to EU-002 is estimated to be at least $4,000 per ton of SO2 removed.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 61 Regional Haze SIP for Class I Areas April 4, 2008 Table 6-6. INVISTS Extract From EPA Table 1A (EPA-F/452-03-34) for Boilers<2,000 MMBtu/hr

CAPITOL COST

($/MMBtu/hr) O&M COST ($/MMBtu/hr) ANNUAL COST ($/MMBtu/hr) COST OF SO2 REMOVED

($/TON) 30,000 – 150,000 1,000 – 30,000 10,000 – 50,000 500 – 4,000

The DSI system was determined to be technically feasible as a control option. However, this option could result in an overall ash with properties so different from the current that it will no longer be acceptable for use in cem ent kiln. If that becomes the cas e, the ash and spent reactant mixture would have to be trucked offsite for dispos al in a landfill at a subs tantial increase in cost relative to the cu rrent disposal. The TCI for this system is estimated at $4,700,000 with an estimated TAC cost of $1,905,890 based on an intere st rate of 8.0% and an economic lifetime of 10 years. At 50% efficiency and 944 tons baselin e, the estimated removed SO2 emissions would be 472 tons per year. The cost-effectiveness of a pplying DSIO to EU-002 is estimated to be at least $4,037 per ton of SO2 removed.

Table 6-7. INVISTA SUMMARY OF CONTROLS
CONTROL

OPTION COST OF SO2 REMOVED ($/TON) LOW SULFUR COAL 1,225 WET FGD/SCRUBBBER 3,508 SDA SYSTEM 4,000 DSI SYSTEM 4,037

Table 6-8. INVISTA TIME FOR COMPLIANCE
CONTROL

OPTION TIME TO IMPLEMENT

LOW SULFUR COAL 1 YEAR WET FGD/SCRUBBBER 3 YEARS SDA SYSTEM 3 YEARS DSI SYSTEM 3 YEARS

Table 6-9. INVISTA ENERGY & NO N-AIR ENVIRONMENTAL IMPACTS

CONTROL OPTION ENERGY IMPACTS NON-AIR QUALITY ENVIRONMENTAL IMPACTS

LOW SULFUR COAL May have to be shipped from greater Distances, resulting in additional fuel usage. None IdentifiedReasonable Progress Evaluation/Long Term Strategy Appendix H - 62 Regional Haze SIP for Class I Areas April 4, 2008 WET FGD/SCRUBBER Additional fuel usage to transport lime to Facility, increased electricity usage for lime handling, recirculation pumps, and to overcome increased pressure drop across scrubbers. Potential for increased fuel usage if stack reheaters are needed to reduce steam plumes Use of substantial quantities of fresh water. Generation of substantial quantities of industrial wastewater containing suspended and dissolved solids requiring disposal

SPRAY DRYER ABSORBER (SDA) SYSTEM Additional fuel usage to transport lime to Facility, increased electricity usage for lime handling, recirculation pumps, and to overcome increased pressure drop in absorption chamber and baghouse. Potentially increased fuel and electricit y usage if fly ash must be disposed of at the landfill. Potential for increased fuel usage if stack reheaters are needed to reduce steam plume. Use of substantial quantities of fresh water. Potential for degradation in quality of water discharged from ash pond outfall due to lime and dissolved solids Potentially substantial increase in solid waste generation and disposal if fly ash cannot be recycled.

DRY SORBENT INJECTION (DSI) SYSTEM Additional fuel usage to transport lime to Facility, increased electricity usage for lime injector and due to increased pressure drop in baghouse. Increased fuel and electricity usage due to disposal of fly ash at the landfill. Substantial increase in solid waste generation and disposal associated with flyash and spent reactant.

Results of the fou r-factor analysis:

Bowater Newsprint Bowater Newsprint operates three coal-fired power boilers that constitute the bulk of its facility SO2 emissions. Bowater presented information and data in its four-factor analysis that lead TDEC-APC to conclude that it should not have to install SO2 post combustion controls nor switch to lower sulfur fuels during this first re gional haze SIP review period. The information in their four factor analysis states that the emissions in the VISTAS modeling inventory are overstated and that the growth proj ections for that particular faci lity are in excess of what is likely to occur for a paper mill that age. TD EC-APC is making a formal declaration that additional SO2 reductions at Bowater Newsprint are not needed during this first regional haze SIP review period. This declar ation does not constitute a dete rmination that additional SO2 reductions at Bowater Newsprint will not be required for any subsequent regional haze SIP review period beyond 2018, nor does it constitute su ch a determination for any other regulatory program or requirement.

INVISTAReasonable Progress Evaluation/Long Term Strategy Appendix H - 63 Regional Haze SIP for Class I Areas April 4, 2008 INVISTA operates three coal-fired boilers that constitute the bulk of its SO2 emissions. INVISTA presented an argument that switching to lower sulfur coal at a cost of $1,225 per ton control costs was un-justifiable as the cost es timates were based upon the current cost of low sulfur coal. INVISTA argued, and TDEC-APC ag reed, that with fuel-switching becoming a favored option among a number of sources for a number of air pollution control reasons, the future cost of a coal switch could be potenti ally cost prohibitive. For this reason, TDEC-APC deferred requiring the company to switch during th is review period until future low sulfur fuel costs were more finite in the next review period. TD EC-APC notes that 2018 predicted visibility impairment values for the Class I areas in the vicinity of INVISTAS are well below the uniform rate of progress glide slopes as further justification for deferring fuel switching in this current review period.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 64 Regional Haze SIP for Class I Areas April 4, 2008 

### 7.0 Best Available Retrofit Technology

7.1 Background

As required by the CAA, the EPA included in the final regional haze rule a requirement for Best Available Retrofit Technology (BART) for certain la rge stationary sources that were placed in operation between 1962 and 1977. The BART-eligible sources are those sources which have the potential to emit 250 tons or more of a visibility-impairing air po llutant, were placed in operation between August 7, 1962 and August 7, 1977, and whose operations fall within one or more of 26 specifically listed source categorie s. Under the CAA, BART is required for any BART-eligible source that a State determines ‘‘emits any air po llutant which may reasonably be anticipated to cause or contribute to any impair ment of visibility in any such area.’’ Accordingly, for stationary sources meeting these criteria, States must a ddress the BART requirement when they develop regional haze SIPs. The EPA has set guidance fo r identifying BART-eligible sources in 40 CFR Part 51 Appendix Y.
A BART-eligible source that is re sponsible for a 1.0 deciview (dv) change or more is considered to “cause” visibility impairment. Although th e appropriate threshold may vary, the EPA’s guidance states that the contribu tion threshold used for BART a pplicability should not be higher than 0.5 deciviews. Thus a BART-eligible source that is responsible for a 0.5 dv change or more is considered to “contribute” to visibility im pairment. Any source determined to cause or contribute to visibility impairment in any Class I area is subject to BART.

The guidelines direct that Stat es should include SO2, NOx, and direct particulate matter (PM) emissions, including both PM10 and PM2.5, in dete rmining whether sources cause or contribute to visibility impairment. States may use th eir best judgment to determine whether VOC or ammonia emissions are likely to have an impact on visibility in an area.

Sources that are subject to BA RT must undergo a BART determin ation. 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 resu lt from the use of such technology.

See Appendix L for a full discussion of the BART process used for the Regional Haze SIP.

7.2 Summary of BART Determinations

In Tennessee, there were twelve facilities identified with BART -eligible sources. Of these twelve sources, eight were exempt from BART through modeling. For a list of BART-eligible facilities please refer to Appendix L. The four remaining sources were unable to demonstrate less than a 0.5 dv impact on one or more Class I areas. Alcoa , Inc .- Tennessee Operations, located in Alcoa, Tennessee was determined to impact Great Smoky Mountains National Park and Joyce Kilmer – Slickrock Wilderness Area. E. I.duPont de Nemours and Company (DuPont) located in Old Hickory, Tennessee was determin ed to impact Mammoth Cave National ParkReasonable Progress Evaluation/Long Term Strategy Appendix H - 65 Regional Haze SIP for Class I Areas April 4, 2008 Eastman Chemical located in Kingsport, Tennessee was determined to impact Great Smoky Mountains National Park, Linvill e Gorge National Wilderness Area, Joyce Kilmer – Slickrock Wilderness Area, James River Face Wilderness Area, Shining Rock Wilderness Area, and Cohutta Wilderness Area. TVA-Cumberland locat ed in Cumberland, Tennessee was determined to impact Mammoth Cave National Park and Sipsey National Wilderness Area.

These four facilities were subject to the Te nnessee BART rule and were required to submit a permit application proposing BART for their sour ces. The proposed BART determinations were shared with the EPA and the FLMs for their review and comment.

The TDEC-APC reviewed the proposed BART dete rminations and has conc luded that BART for Alcoa is limiting the sulfur in the calcined petroleum coke used to manufacture anodes to 3%.

TDEC-APC concluded that BART for Eastman Chem ical is the applicati on of SDA/FF-dry fluegas desulfurization using a Spray Dryer Absorber (SDA) followed by a fabric filter for the five Coal-fired Boilers #25-#29 (B-253).

TDEC-APC concluded that BART for TVA-Cu mberland is no additional controls.

TDEC-APC concluded that BART for DuPont-Old Hickory is limiting the total combined daily emissions for Boilers 20 and 24 based upon the fo llowing operating limits stated in Table 7.2 below.

Table 7.2 DuPont-Old Hickory BART Contro l Determination–Emission Limitations Operating Limits SO2 (lb/day) NOx (lb/day) Summer Months (May-September) 32260 6120 NON-Summer Months (O ctober -April) 38570 6770

For a full discussion of the BART subject sources please refer to Appendix L.



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

As stated in section 2.0 above, the Regional H aze Rule (RHR) requires States to establish Reasonable Progress Goals (RPGs), expressed in deciviews (dv), fo r visibility improvement at each affected Class I area covering each (appr oximately) 10-year period until 2064. This first set of RPGs must be met through measures containe d in the state’s LTS covering the period from the baseline until 2018. This section disc usses development of Tennessee’s LTS.

8.1 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 Great Smokys and Joyce KilmerSlickrock Tennessee Class I areas. Sulfate levels on the 20% worst days acc ount for greater than 70% of the visibility impairment. Across the VI STAS region, sulfate leve ls are higher at the Southern Appalachian sites than at the coastal sites. On the 20% clearest days, sulfate levels areReasonable Progress Evaluation/Long Term Strategy Appendix H - 66 Regional Haze SIP for Class I Areas April 4, 2008 more uniform across the region. Reduction of SO2 emissions would be the most effective means of reducing ammonium sulfate. Greater than 95% of SO2 emissions in Tennessee are attributable to EGUs and industr ial point sources. Thus, the LTS for this first Regional Haze SIP focused on reductions in SO2 emissions.

In Tennessee and across the region there are significant control programs in place to reduce SO2 emissions between the baseline period and 2018. Most notably, CAIR is predicted to result in approximately 75% reduction from E GU SO2 emissions in Tennessee (Table 6-2). Overall the SO 2 emissions in Tennessee are predicted to decrease from 2002 levels at 442,589 tons per year to 228,035 tons per year in 2018 (Table 4-3). Such large SO 2 reductions are predicted to result in significan t improvements in visibility.

At the two Class I areas in Tennessee, Great Smokys and Joyce Kilmer-S lick rock, visibility improvements on the 20% worst days are expected to be better than the uniform rate of progress glidepath by 2018 (Figures 2-2 and 2-3) based so lely on reductions from existing and planned emissions controls. For example, at Great Smoky Mountains, a 4.5 deciview improvement in visibility would meet uniform rate of progr ess in 2018; expected em issions reductions by 2018 Base Best & Final (B&F) are projected to ach ieve a 6.8 deciview improvement. In fact, visibility improvements at all of the VISTAS mountain Class I areas and most of the coastal Class I areas are projected to be better than the uniform rate of progress.

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 Clas s 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 B&F emissions reductions. The percentage of the target achieved for the Great Smokys and Joyce Kilmer-Slickrock Tennessee Class I areas is about –10.8% (Figure 8-1). Zero percent change would mean no change in visibility; -10% means that visibility is better than no change, or a 10% improvement (values lower th an current conditions.)Reasonable Progress Evaluation/Long Term Strategy Appendix H - 67 Regional Haze SIP for Class I Areas April 4, 2008 Figure 8-1. Reasonable progress assessment for 20% best days at Great Smoky Mountains National Park
Visibility Improvement at Joyce Kilmer Wilderness is represented by Great Smoky Mountains.

TDEC-APC completed a reasonable progress as sessment after modeling the Clean Air Act controls discussed above. The assessment did not identify any cost effective control measures for the SO2 non-EGU units that cont ributed greater than 1% to vi sibility impairment at any of the Class I areas in Tennessee or in neighboring States. TDEC-APC concluded that the required reductions from the CAIR requirement s were reasonable for this LTS.

8.2 What Additional Emissions Controls We re 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 activit ies, and the role of NH3 and pot ential benefits if emissions from agricultural sources were mitigated.

As discussed in Section 4.1 and demonstrated in Figure 4-1, elemental carbon (sources include agriculture, prescribed wildland fires, and wildfires) is a relatively minor c ontributor to visibility impairment at the Class I areas in Tennessee. However, TDEC-APC is currently working to develop a smoke management program that addr esses the issues laid out in EPA’s 1998 draft guidance for smoke management plans.

Also as discussed in Section 4.1 and demonstrated in Figure 4-1, fine soils are a relatively minor contributor to visibility impairmen t at the Class I areas in Tenness ee. Nevertheless, in regard to construction activities, the Tennessee Departme nt of Transportation (TDOT) has issued regulations addressing control of erosion, siltation, and pollution from construction activities. Reasonable Progress Assessment Great Smoky Mountains - 20% Best Days New Improve Equation, 12 km grid

13.58 13.58 13.58

13.11 12.11 4.54


### 0 5 10 15 20 25 30 35

200 0 200 4 200 8 201 2 201 6 202 0 202 4 202 8 203 2 203 6 204 0 204 4 204 8 205 2 205 6 206 0 206 4

YearHaziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

Uniform rate of p ro g ress = 2.11 dv b y 2018Reasonable Progress Evaluation/Long Term Strategy Appendix H - 68 Regional Haze SIP for Class I Areas April 4, 2008 In addition, TDEC-APC curren tly having a Fugitive Dust Emissions Control rule, TAPCR Chapter 1200-3-8 (the citation of this rule is offered only for re ference purposes and it is not offered for inclusion into the Tennessee Regiona l Haze SIP.), to control particulates from fugitive dust emission sources generated within plant boundaries from activities such as “unloading and loading areas, proc ess areas, stockpiles, stock p ile working, plant parking lots, and plant roads (including access ro ads and haul roads).” Copy of this rule is included as Attachment H-6.

In regard to agricultural ammoni a, TDEC-APC has no regulations.

8.3 Reasonable Progress Goals (RPGs)

The Regional Haze Rule (RHR) at 40 CFR sec tion 51.308(d)(1) requires States to establish RPGs for each Class I area within the state (exp ressed in deciviews) that provide for reasonable progress towards achieving natural visibility. In addition, EPA pub lished the final “Guidance for Setting Reasonable Progress Goals under the Re gional haze Rule” on June 1, 2007 to use in setting RPGs (Attachment H-4). The goals must provide improvement in visibility for the most impaired days, and ensure no degr adation 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 Great Smokys and Joyce Kilmer-Slickroc k Class I areas in Tennessee. To calculate the rate of pr ogress represented by each RPG, TDEC-APC compared baseline visibility conditions to natural visibility conditio ns in each Tennessee class I area and determined the uniform rate of visibility improvement (in d eciviews) that would need to be maintained during each implementation period in order to at tain natural visibility conditions by 2064. The TDEC-APC has summarized expected visibility improvements under existing federal and state regulations, BART determinations in Tenness ee and neighboring states , and any additional control measures found to be reas onable to implement in this re view period. These controls will be modeled in CMAQ as part of the Long-Term Strategy (LTS). At this time TDEC-APC has determined that the RPGs will be at least as stri ngent as the uniform rate of progress “glidepath”. VISTAS has already demonstrated that the 2018 Base B&F contro l scenario provides for an improvement in visibility bette r than the uniform rate of progress for the Great Smokys and Joyce Kilmer-Slickrock for the most impaired da ys over the period of the implementation plan and ensures no degradation in visibility for the least impaired days over the same period. In addition, it is expected that IMPROVE monitoring results for 2018 will at that time be used to establish a new baseline for the next planning period.

In addition, because Great Smoky Mountain Nationa l Park and Joyce Kilmer-Slickrock are split between Tennessee and North Carolina, the TDEC-A PC and the North Carolina Division of Air Quality (NCDAQ) have agreed to work together in setting RPGs. Note that TDEC-APC and NCDAQ have been working together thr ough VISTAS throughout the regional haze SIP planning process. Table 8- 1 lists Tennessee’s RPGs.Reasonable Progress Evaluation/Long Term Strategy Appendix H - 69 Regional Haze SIP for Class I Areas April 4, 2008 Table 8-1. Reasonable Progress Goals ( RPGs) for Tennessee Class I Areas (2018 Base Best&Final)

Class I Area Baseline Visibility (deciviews) RPG (Deciview Improvement Expected by 2018, 20% Worst Days) RPG (Deciview Improvement Expected by 2018, 20% Best Days) Deciview Improvement Needed 2018- 2064 (20% Worst Days)

Great Smoky Mountains National Park 30.28 6.78 1.47 12.11

Joyce KilmerSlickrock Wilderness 30.28 6.78 1.47 12.11Reasonable Progress Evaluation/Long Term Strategy Appendix H - 70 Regional Haze SIP for Class I Areas April 4, 2008 

### 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 / Wedne sday, 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, North Carolina. 9. U.S. Environmental Protection Agency. (2003). Guidance for Tracking Progress under the Regional Haze Program; EPA-54/B-03-004, 2003.