Appendix H Kentucky Regional Haze SIP 

### Kentucky Energy and Environment Cabinet Kentucky Division for Air Quality



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Appendix H Reasonable Progress Evaluation and Long Term StrategyAppendix H Kentucky Regional Haze SIP ii 

### APPENDIX H
TABLE OF CONTENTS

PURPOSE........................................................................................................................

............... 4

1.0 EMISSIONS CONTROLS MODELED................................................................................... 5
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 .................................................................................................................

......... 16

2.0 UNIFORM RATE OF PROGRESS ....................................................................................... 19

3.0 GEORGIA TECH SENSITIVITIES....................................................................................... 20 3.1 Evaluation for Mammoth Cave National Park (MACA), Kentucky .................................. 21 3.2 Summary....................................................................................................................

......... 23

4.0 REASONABLE PROGRESS EVALUATION...................................................................... 24 4.1 Area of Influence Analyses................................................................................................. 24 4.2 Source Type Analyses .......................................................................................................

. 25 4.3 Back Trajectory Analyses................................................................................................... 26 4.4 Area of Influence Data and Displays.................................................................................. 29 4.5 Importance of Pollutants Other Than Sulfate ..................................................................... 34 4.6 Summary of Emission Inventories Used in Cost Curve Analysis ...................................... 35 4.7 Process in Preparing Files for Cost Effectiveness Curve Development............................. 37 4.8 Application of AirControlNET Technologies .................................................................... 38 4.9 Development of AOI-Based Cost Curves........................................................................... 39

5.0 REASONABLE PROGR ESS ASSESSMENT ...................................................................... 40

6.0 FOUR FACTOR ANALYSIS ................................................................................................ 43 6.1 The Four Statutory Factors ................................................................................................. 43 6.1-1 Cost of Compliance ..................................................................................................... 43 6.1-2 Time Necessary for Compliance ................................................................................. 43 6.1-3 Energy and Non-Air Quality Envi ronmental Impacts of Compliance ........................ 44 6.1-4 Remaining Useful Life of the Source.......................................................................... 44 6.2 Evaluating Four Statutory Factors for Speci fic SO2 Emissions Sources in Each Area of Influence ......................................................................................................................

....... 44 6.2-1 Cost of Compliance ..................................................................................................... 45 6.2-2 Time Necessary for Compliance ................................................................................. 46 6.2-3 Energy and Non-Air Environmental Impacts.............................................................. 46 6.2-4 Remaining Useful Life ................................................................................................ 46 6.3 Process of Applying Statutory Factors ............................................................................... 46Appendix H Kentucky Regional Haze SIP iii 7.0 Best Available Retrofit Technology ....................................................................................... 50 7.1 Background.................................................................................................................

........ 50 7.2 Summary of BART Determinations ................................................................................... 51

8.0 FINAL LONG TERM STRATEGY A ND REASONABLE PROGRESS GOALS............. 52 8.1 Long-Term Strategy.........................................................................................................

... 52 8.2 What Additional Emissions Controls Were C onsidered as Part of the Long-Term Strategy for Visibility Improvement by 2018? ................................................................................. 53 8.3 Reasonable Progress Goals................................................................................................. 54

REFERENCES: ....................................................................................................................

........ 56

Appendix H.1 - Cost Effectiveness Curve Design

Appendix H.2 – AOI Contri bution Spreadsheets

Appendix H.3 - Source Letters

Appendix H.4 – Kentucky Electri c Generating Units (EGUs) Exis ting and Expected Emission Controls

Appendix H.5 – Excerpts for Clean Air Intersta te Rule Preamble – EPA Cost Analysis

Appendix H.6 – VISTAS SO2 Control Cost Information for Century Aluminum

Appendix H.7 – Kentucky CAIR RegulationsAppendix H Kentucky Regional Haze SIP 4 

### PURPOSE

The purpose of this appendix is to outline the stat e’s strategy for complyi ng with the requirement to set and meet Reasonable Progress Goals (RPG s) as part of our Regional Haze SIP under 40 CFR 51.308(d)(1), and the requirements for esta blishing best availa ble 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, impairme nt 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 reas onable progress toward meeting the goal of a return to natural visibility conditions by 2064. As a guide for reasonable progress, the RHR directs states to graphically show what would be a “uniform rate of progress” toward natural conditions for each Class I area. This is known as the “glidepath. The RHR then requires states to establish RPGs for visibility improvement at each affected Class I area covering each approximately 10-year period until 2064. Therefore, our first set of RPGs will comprise our long term strate gy (LTS) covering the period from the present until 2018. This appendix provides an overview of this first LT S. In addition, a specific component of each state’s first LTS is dictated by the specific BART requirements in 40 CFR 51.308(e). This appendix will also include a discussion of our st rategy for developing those BART requirements.

Our long term strategy contai ns the following components:

I. Inventory of all controls required or expected under all federal and state regulations by 2009 and 2018. II. Modeled expected visibility improvement and Comparison of modeling results for 2018 to the uniform rate of progress, or “glidepath” for Kent ucky’s Class I area. III. Discussion of emissions sensi tivity model runs to help determine which pollutants and source categories are contributing the most to visibility impairment at Kentucky’s Class I area (runs conducted by Georgia Institute of Technology). IV. Examination of SO2 Area of Influence (AOIs) projections for each of the State’s Class I areas, and also for any surrounding states ’ Class I areas whose AOI includes any Kentucky counties, to determine which specific sources are most likely to be impairing visibility at specific Class I areas. V. Application of the four “sta tutory factors,” listed in 40 CFR 51.308(d)(1)(i)(A) to those sources identified in the previous step VI. Using the results of the four factor analyses , identification of control determinations for specific sources. VII. Identification of BART-eligible sources. VIII. BART exemption modeling fo r BART-eligible sources.

IX. BART determinations for sources subject to BART. X. Modeling demonstration of visibility improvement after inclusion of BART and reasonable progress control determinations. XI. Determination of RPGs based on the vi sibility improvement expected by 2018.Appendix H Kentucky Regional Haze SIP 5 

### 1.0 EMISSIONS CONTROLS MODELED

2009 and 2018 emission projections include the follo wing 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 n itrogen 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 percen t and NOx emissions by over 60 percent from 2003 levels. The Clean Air Mercury Rule will 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 or state equivalent. Phase I of the NO x SIP call applies to certain Electric Generating Units (EGUs) and large non-EGUs, including large industrial boilers and turbines, and cement kilns. States in the 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. We reviewed the available state rules and guida nce documents to determine the affected sources and ozone season allowances. EPA es timated that CAIR would result in a 66 percent reduction in NOx emissions in Kentucky with the bulk of the reduction occurring for the Electric Generating Units (EGUs) sources by 2006.

• Consent Agreements (Tampa Electric Compa ny, Virginia Electric Power Company, Gulf Power Crist 7).

• The settlement requires Tampa Electri c Company (TECO) to pay a $3.5 million civil penalty. Under the agreement, TECO will install permanent emissionscontrol equipment to meet stringent polluti on limits; implement a series of interim pollution-reduction measures to reduce em issions while the permanent controls are designed and installed; and retire pollution emission allowances that TECO or others could use, or sell to others, to emit additional pollution into the environment. The settlement also require s the company to spend between $10 and $11 million on environmentally beneficial projects in the region designed to mitigate the impact of emissions from the company's plants.

• Virginia Electric and Power Co. (VEPCO ) agreed to spend $1.2 billion between now and 2013 to eliminate 237,000 tons of sulfur dioxide (SO2) and nitrogen oxides (NOx) emissions each year from ei ght coal-fired electricity generating plants in Virginia and West Virginia.

• The 2002 agreement calls for Gulf Power to upgrade its operation to cut nitrogen oxide emission rates by 61 percent at its Crist generating plant by 2007 with major reductions beginning in early 2005. Th e Crist plant is a significant source of nitrogen oxide emissions in the Pensacola area.Appendix H Kentucky Regional Haze SIP 6 • 1-hr ozone SIPs Atlanta (Federal Regist er: June 15, 2005 (Volume 70, Number 114)) / Birmingham (March 12, 2004 (V olume 69, Number 49))/ Nort hern Kentucky (Federal Register: September 16, 2004 (Volume 69, Nu mber 179)). The purpose of a state implementation plan (SIP) is to demonstrat e attainment or main tenance 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 re quire a 97 percent reduction in the sulfur content of highway diesel fuel from its curr ent 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 produce vehicles with emissions ranging from relatively dirty to zer o, 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 and stationary RICE. These rules reduce emissions of a number of toxic air polluta nts, including hydrogen chloride, manganese, lead, arsenic and mercury by 2009. This rule also reduces emissions of sulfur dioxide and particulate matter in conjunction with th e toxic air pollutant 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 MA CT rules were vacated on June 8, 2007. However, the EPA is required under the Clean Air Act to i ssue revised boiler MACT 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 required for industrial boilers. Therefore, the VISTAS States decided to include control assumptions for industrial boilers due to MACT.Appendix H Kentucky Regional Haze SIP 7 • Combustion Turbine MACT standard. The pr ojection inventories do not include the NOx co-benefit effects of the MACT regulations for Gas Turbines or stationary RICE, which EPA estimates to be small compared to the overall inventory.

• 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 Divisi on (ESD) staff. We did not apply reductions for MACT standards w ith an initial compliance date of 2001 or earlier, assuming that the eff ects of these controls are al ready accounted for in the 2002 inventories supplied by the States.

The following are source category specific contro ls used to project future year emissions inventories:

1.1 Point Source Controls

Different approaches were used for the EGU and the non-EGU sectors of the point source inventory:

• For the EGUs, the State relied primar ily on the Integrated Planning Model ® (IPM ® ) to project future generation as well as to calculate the impact of future emission control programs, to include CAIR and CAMR. The IPM results were adjusted based on state and local 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 invent ories for a control scenario which accounts for post-2002 emission reductions from promulgated a nd proposed federal, state, local, and sitespecific control programs as of July 1, 2004.

1.1.1 Electric Generating Units

State and local agencies specified a number of ch anges to the IPM results to better reflect current information on when and where future controls would occur. These changes to the IPM results primarily involved state and local agency additi on or subtraction of future emission controls based on the best available data from state ru les, enforcement agreements, compliance plans, permits, and discussions/commitments from individual companies.

Table 1-1 lists adjustments to IPM control determ inations specified by state and local agencies for the EGU modeling inventories. Table 1-2 lists othe r adjustments to IPM results specified by state and local agencies for modeling inventories.Appendix H Kentucky Regional Haze SIP 8 Table 1-1. Adjustments to IPM Control Dete rminations Specified by State and Local Agencies for the 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 Scru bber Scrubber Scrubber Scrubber

GA Bowen 1BLR SCR SCR SCR SCR None Scrubber Scrubber

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

3BLR SCR SCR SCR SCR Sc rubber Scrubber Scrubber

4BLR SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions Scrubber Scrubb er Scrubber

Wansley 1 SCR SCR SCR SCR Sc rubber Scrubber Scrubber

ORISID=6052 2 SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions None Scrubber Scrubber

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

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

McIntosh
ORISID=6124 1 None None SCR None None None None None

Yates 1 None None None None Scrubber Scrubber Scrubber Scrubber
ORISID=728 2, 3 None None None None None None None None
4 – 7 None None SCR None None None Scrubber NoneAppendix H Kentucky Regional Haze SIP 9 Table 1-1 (continued). Adjustments to IPM Co ntrol Determinations Sp ecified by State and Local Agencies for the 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

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 Scrubber Scrubber

4 SCR SCR SCR SCR Scrubber Scrubber Scrubb er Scrubber

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

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

Coleman C1 None None SCR SCR None Scrubber Scrubber Scrubber

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

C3 None None SCR SCR None Scrubber Scrubber Scrubber

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

H2 None SCR SCR SCR Scrubber Scrubber Scru bber 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 Scrubber Scrubber

SC Jeffries 3 SCR None SCR None None None None None

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

Wateree WAT1 SCR SCR SCR SCR None Scrubber None Scrubber

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

ORISID=3280 CAN2 None None No ne None None None None None

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

ORISID=7834 CT1B None SCR None SCR None None None None TN Kingston 1 – 8 SCR SCR SCR S CR 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=3947Appendix H Kentucky Regional Haze SIP 10 Table 1-2. Other Adjustments to IPM Results Specified by State and Local Agencies for 2009/2018 EGU Inventories.

State Plant Name and ID Unit Nature of Update/Correction

FL Central Power and Lime ORISID= 10333 GEN1 Central Power and Lime (ORI S10333) is a duplicate entry. This is point 18 in Florida Crushed Stone (12-053-0530021). Removed IPM emissions for Central Power and Lime.
Cedar Bay Generating ORISID=10672 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Cedar Bay is connected to Stone Container (12-031-0310067). Replaced IPM emissions with 2002 emissions for Cedar Bay (12-031-0310337) times the growth factors for Stone Container.
Indiantown Cogeneration ORISID=50976 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Indiantown is connected to Louis Dreyfus Citrus (12-085- 0850002). Replaced IPM emissions with 2002 emissions for Indiantown (12-085-0850102) times the growth factors for Louis Drefus Citrus.

GA Bowen
ORISID=703 1BLR 2BLR 3BLR 4BLR IPM indicated retrofit scrubbers on all 4 units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect scrubbers on 1BLR and 2BLR by 2009.
Wansley
ORISID=6052 1, 2 IPM indicated retrofit scrubbers on both units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect one scrubber on Unit 1 by 2009.

Riverside
ORISID=734 4 All of plant Riverside was retired from service June 1, 2005; emissions set to zero in 2009 and 2018.

McIntosh
ORISID=727 CT10A CT10B CT11A CT11B The McIntosh Combined Cycl e facility became commercial June 1, 2005. Added 346 tons of NO x and 121 tons of SO 2 per unit to the 2009 and 2018 inventories.

Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power Development, Inc. GA specified that the emissions from this proposed plant be included in the 2018 projections. Boilers 1 and 2 added 1,882 tons of NO x and 3,227 tons of SO 2 per unit to the 2018 inventory.

MS R D Morrow
ORISID=6061 1, 2 Revised the 2018 emissions to reflect controls not indicated by IPM. The SO 2 emissions are much lower than IPM, but their expected NO x emissions are actually higher than IPM. The controls will be coming online 2009 or 2010, so the 2009 inventory did not change.
Jack Watson (2049) Victor J Daniel (6073) Chevron Oil (2047) All MS DEQ specified that the em ission projections provided by the Southern Company for their units in Mississippi were to be used instead of the IPM results.Appendix H Kentucky Regional Haze SIP 11 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.Appendix H Kentucky Regional Haze SIP 12 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.Appendix H Kentucky Regional Haze SIP 13 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 th e data used in EPA’s CAIR analyses, supplement these data with available stakeholder input, and provide the results for stakeholder review to ensure credibility.Appendix H Kentucky Regional Haze SIP 14 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, st ate, local, and site-specific control programs. The OTW control scenario accounts for proposed (but not final) control programs that are reasonably anticipated to result in post-2002 emission reductions.

Maximum achievable control technology (MACT) requirements were also applied, as documented in the report entitled Control Packet Development and Data Sources, dated July 14, 2004. The point source MACTs and associated emi ssion reductions were designed from Federal Register (FR) notices and discussions with EPA’ s Emission Standards Di vision (ESD) staff. We did not apply reductions for MACT standards with an in itial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States. Emission reductions were applied only for MACT standards with an initial compliance date of 2002 or greater.

The final Phase II NO x SIP call rule was finalized on April 21, 2004. States had until April 21, 2005, to submit SIPs meeting the Phase II NO x budget requirements. The Ph ase II rule applies to large internal combustion (IC) engines, which are primarily used in pipeline transmission service at compressor stations. We id entified affected units using th e same methodology as was used by EPA in the proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per day during 2002). The final rule re flects a control level of 82 percent for natural gas-fired IC engines and 90 percent for diesel or dual fuel categories. Several state and local agencies provided more specific information on the anticipated controls at the compressor stations. This information was us ed instead of the default appro ach used by EPA in the proposed Phase II rule.

A summary of Non-EGU point source control programs in cluded 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 percent for SO 2 and 40 for percent for PM 10 and PM2.5 to account for the cobenefit from installation of acid gas scrubbe rs and other control equipment to reduce HAPs.

• NO x SIP Call (Phase I- except wher e States have adopted Phase II already) Phase I of the NO x SIP call applies to certain large non-EGUs, including large indu strial 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. We reviewed the available State rules and gui dance documents to determine the affected sources and ozone season allowances.Appendix H Kentucky Regional Haze SIP 15 • Petroleum Refinery Initiative (October 1, 2003 notice; Mississ ippi & West Virginia). This initiative addresses the most significant Clean Air Act compliance concerns affecting the petroleum refinery industry. Since December 2000, 17 global refinery settlements have been reached with refiners representing nearly 77 percent of domestic refining capacity. Three refineries in the VISTAS region are affected by two October 2003 Clean Air Act settlement s under the EPA Petroleum Re finery Initiative. The refineries are: (1) the Chevron refinery in Pascagoula, Mississippi; (2) the Ergon refinery in Vicksburg, Mississippi; and (3) the Ergon refinery in Newell, West Virginia.

• Reasonable Further Progress 3 percent pl ans 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. We did not apply redu ctions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States.

• Combustion Turbine MACT. The projecti on inventories do not include the NO x cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which EPA estima tes 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 emission projecti ons and used in the CAIR projections were used to calculate cont rolled emissions.

The controls obtained by MACTEC (MACTEC, 2006) for the HDD rulemaking were controls for the years 2007, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for intermediate years were prepared using a straight-line interpolation of control level between 2007 and 2020.

State submitted controls had precedence over the U.S. EPA developed controls. Control measures submitted by KYDAQ include Stage I contro ls for gasoline dispensing facilities, and open burning controls.

For more information on the development of area source inventories, see Appendix D.Appendix H Kentucky Regional Haze SIP 16 1.3 Mobile Sources

Local controls included vehicle emissions insp ection and maintenance (I/M) programs, Stage II vapor recovery programs, anti-tampering programs, etc. By nature, the assumptions used for the 2002 initial base year inventory vary across th e VISTAS region, but our presumption is that these data accurately re flected each State’s situation as it ex isted 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 ch ange. However, if a State pl anned changes, we requested information on those plans. In the final implementa tion of the inventory, St age II controls were exercised in the area source component of the in ventory, 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 for aircraft, locomotives, and commercial marine vessels (CMV) prepared as described earlie r in this document, 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. Using these data, combined growth and control factors for the period 2002-2009 an d 2002-2018 were estimated using straight-line interpolation between 1996 and 2010 (for 200 9) and 2015 and 2020 (for 2018) . This is done at the State-county-SCC-pollutant level of detail. According to EPA documentation, the CAIR baseline emissions include the impacts of the Tier 4 (T4) non-road diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV and locomotive emissions.

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

1.5 Conclusion

In conclusion of this discussion on source sect or controls, Figures 1-1 through 1-4 depict pollutant totals for NH3, PM2.5, NOx, and SO2 fo r the various sectors by state for 2002, 2009, and 2018 modeling.Appendix H Kentucky Regional Haze SIP 17 Figure 1-1. Annual NH3 emissions.

Figure 1-2. Annual PM2.5 emissions. 0 20 40 60 80 100 120 140 160 180 200

A l abama Florida Georgia Ke nt

u ck

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2002 Typical 2009 2018 OTWAppendix H Kentucky Regional Haze SIP 18 Figure 1-3. Annual NOx emissions.

Figure 1-4. Annual SO2 emissions. 0 100 200 300 400 500 600 700 800 900 1,000

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2009 OTW

2018 OTWAppendix H Kentucky Regional Haze SIP 19 

### 2.0 UNIFORM RATE OF PROGRESS

The linear rate of improvement su fficient to attain natural conditi ons by 2064 is referr ed to as the “uniform rate of progress” or “glide path”. The baseline represents the starting point from which reasonable progress will be measured. There ar e 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 percent best days in each year are averaged together, producing a single averag e deciview value for the best days. Similarly, the deciview values for the 20 percent worst days in each year are averaged together, producing a single average deciview value for the worst days. Extinction from individual PM components is calculated from the IMPROVE equation (EPA, 2003; Hand and Malm, 2006).

The USEPA has defined target natural conditi ons in 2064 for each Class I area (USEPA, 2003). For each southeastern Class I area, a baseline visibility using 2000-2004 IMPROVE data and uniform rate of progress was established, us ing EPA default assumptions for calculating visibility and natural background. 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 revi sed methods (Hand and Malm, 2006, Pitchford, 2006). For more detailed discussion and co mparison of the two IMPROVE equations, see Appendix B.

For the 20% worst days in Kentucky’s Class I area, Figure 2-1 graphically compares the visibility which would result with the area’s unif orm rate of progress (red line) to the predicted visibility from 2004 to 2018 due to modeled emissi on reductions expected by federal and state control programs during the first l ong-term strategy (purple line).Appendix H Kentucky Regional Haze SIP 20 

### Reasonable Progress Assessment Mammoth Cave - 20% Worst Days New IMPROVE Equation, 12 km grid

31.37 29.68

26.64

23.26

19.87

16.49

13.11 11.08 25.56

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064 YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction
Figure 2-1. CMAQ 2018 modeling results compa red to Uniform Rate of Progress at Mammoth Cave National Park.



### 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) emissions. Once the key pollutants contributing to visibility impair ment at each Class I area were identified, the sources or source categories responsible for emitting these pollutants or pollutant precursors were determined. Emissions sensitivity anal yses were conducted using CMAQ with the 2009 inventory and considering 30% reductions from major pollutants and source categories. Emissions sensitivities were in itially conducted using 30% reducti ons 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 changes in primary carbon and SO2, respectively, but nitrate and ozone chemistr y 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 contro ls anticipated by 2018 are not included in these sensitivity analyses. While the 2009 sensitiv ity analyses cannot be us ed to judge absolute contributions from each state or source sector, the results do indicate relative level of response among pollutants, sectors, and geographic areas.Appendix H Kentucky Regional Haze SIP 21 3.1 Evaluation for Mammoth Cave National Park (MACA), Kentucky

Figure 3-1 shows the results of an emissions sensitivity r un for Mammoth Cave for summer (since summer is when 20% worst days occur) . CMAQ was run using 30% reductions from the 2009 Base D inventory assumptions for implemen ting existing state and federal regulations (listed on page 2) for major source categorie s of SO2, NOx, and PM. The results identify geographic origins for visibility impairing pollu tants, and serve as a good starting point when considering potential air quality benefits from a dditional controls for specific source sectors in VISTAS states or neighboring RPOs. The gr eatest benefits at Mammoth Cave in 2009 are projected to come from further reducing SO2 from electric generati ng utilities (EGUs). Additional, smaller benefits are projected fr om additional SO2 emission reductions from nonutility, industrial point sources. Reductions of nitrogen oxide emissions from point sources (EGU and non-EGU) or ground leve l 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 benefi cial than reductions in SO2 emissions. Reduc tions in anthropogenic VOC emissions show no response in visibility, while a 30 percent reduc tion in biogenic VOC emissions results in a measurable improveme nt. However, contro lling the VOCs from vegetation is not possible or appropriate. 

# Mammoth_Cave, KY (Summer)

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### 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 emissions– Mammo th Cave, Kentucky.

Several states contribute to modeled reducti ons in SO4 at Mammoth Cave on the 20% worst days modeled in these two episodes in respons e to further reductions in 2009 SO2 emissions from EGUs (Figure 3-2). For this sensitiv ity run, further reducing SO2 emissions fromAppendix H Kentucky Regional Haze SIP 22 electricity generating utilities from other RPOs and outside the boundary are significant and would provide the greatest benefit to Mammoth Ca ve. In addition, benef its are projected from SO2 reductions from EGUs in several VISTAS stat es. Approximately, one third of the benefit at Mammoth Cave would come from further SO2 emission reductions from outside VISTAS.

AL
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BCs Utility Contributions, by State and Region, to SO4 at Mammoth Cave, KY , Using 2009 Emissions and CMAQ model run for June 2002

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MRPO Boundary Conditions

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

Similar sensitivity analyses were performed for wintertime using the 2009 inventory (Figure 3- 3). These results suggest that in wintertime, reductions in a mmonia emissions could be more beneficial for reducing ammonium nitrate contri butions to visibility impairment than further reducing nitrogen oxide emissions from either ground or point sources. Reducing ammonia emissions could also be more effective in imp roving visibility in wintertime than further reductions in SO2 emissions.Appendix H Kentucky Regional Haze SIP 23 

# Mammoth_Cave, KY (Winter)

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### Bio. Antro. BCs MRPO M-VU CEN VISTAS
WV VA TN SC NC MS
KY GA FL AL

Figure 3-3. Wintertime sensitivity results for 2009 emissions – Mammoth Cave, Kentucky.

3.2 Summary

Emissions sensitivity analyses s how the relative benefits of re ducing different pollutants from different source categories and geographic areas. These 2009 sensitivity analyses indicate that further reductions in SO 2 emissions from electric generating ut ilities would be most beneficial for visibility at VISTAS Class I areas, followed by SO2 reductions from industrial point sources. Controlling NOx or primary carbon emissions from either point or ground level sources would have little benefit to visibili ty. Controlling anthropogenic sources of VOC would not be effective in improving visibility in winter. In wintertime cont rolling ammonia emissions would be more effective in reducing ammonium nitrat e than controlling nitr ogen oxide emissions.Appendix H Kentucky Regional Haze SIP 24 

### 4.0 REASONABLE PROGRESS EVALUATION

4.1 Area of Influence Analyses

The objective of the VISTAS Area of Influence analysis is to identif y the geographic source regions that are contributing to visibility impair ment at the Class I areas on the 20 percent worst visibility days. This information will be us ed 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 i llustrated in Figure 4-1, on the 20 percent worst visibility days in 2000 -2004, ammonium sulfate accounted for greater than 70% of the calculated light extinction at Cl ass I areas in the inland sites and greater than 60% of the calculated light extinction for coas tal sites in the VISTAS states (excepting Everglades). In contrast, amm onium nitrate contribu ted less than 5% of the calculated light extinction at VISTAS Class I areas on the 20 percent worst visibility days. (Nitrate has a somewhat larger contribution on 20 percent worst days at Class I areas in neighbor ing states to the VISTAS region.) Particulate organic matter (o rganic carbon) accounted for 10-20 percent of light extinction on 20 percent worst visibility days (except Everglades where organic carbon accounted for 40%).

Figure 4-1. Average Extinction for 20 percen t Worst Visibility Days in 2000-2004 using New IMPROVE Equation (data from 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 RayleighAppendix H Kentucky Regional Haze SIP 25 VISTAS emissions sensitivity analyses using th e CMAQ regional air 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 sensitivity 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 SIP on potential cont rols of SO2 emissions from EGU and non-EGU point sources. To select the specific point sour ces that would be considered for each Class I area, states fi rst identified the geographic area s 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

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

Table 4-1. Source types 2018 modeling Mammoth Cave – Percentage.
Annual 2018 Emissions (%) Tier VOC NOX CO SO2 PM-10 PM-2.5 NH3 Fuel Comb. Elec. Util. 1% 25% 1% 66% 8% 18% 1% Fuel Comb. Industrial 1% 16% 2% 19% 3% 6% 0% Fuel Comb. Other 4% 7% 3% 5% 3% 8% 0% Chemical & Allied Product Mfg 2% 1% 1% 1% 1% 1% 1% Metals Processing 1% 1% 5% 3% 3% 7% 0% Petroleum & Related Industries 1% 0% 0% 1% 0% 0% 0% Other Industrial Processes 7% 5% 1% 3% 8% 10% 1% Solvent Utilization 45% 0% 0% 0% 0% 0% 0% Storage & Transport 6% 0% 0% 0% 1% 1% 0% Waste Disposal & Recycling 3% 1% 2% 0% 3% 7% 0% Highway Vehicles 17% 20% 48% 0% 1% 2% 9% Off-highway 12% 24% 36% 1% 2% 4% 0% Miscellaneous 1% 0% 3% 0% 69% 35% 87% VISTAS Total 100% 100% 100% 100% 100% 100% 100%Appendix H Kentucky Regional Haze SIP 26 4.3 Back Trajectory Analyses

The KYDAQ defined AOIs to identify source regions for which additional controls might be considered and that are likely to have the great est 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, figur e 4-2 shows that for the inland areas (Mammoth Cave), SO4 contributes 78% to the calculated light extinction on the h aziest days. To better understand the sources that shoul d be considered in a four f actor analysis for reasonable progress, VISTAS contracted ENVIRON to partne r with VISTAS’s Data Analysis contractor, Air Resource Specialists (ARS), to provide SO2 Areas of Infl uence for each VISTAS and six neighboring Class I areas. ARS generated meteorological back tr ajectories for IMPROVE sites in VISTAS and neighboring states. Back trajec tory analyses use interpolated measured or modeled meteorological fields to estimate the most likely central path of air masses that arrive at a receptor at a given time. The method essentiall y follows a parcel of air backward in hourly steps for a specified length of time. Back tr ajectories account for the impact of wind direction and wind speed on delivery of emissions to th e receptor, but do not account for chemical transformation and dispersion of emissions.

Trajectories were generated using the Hybrid-Si ngle Particle Lagrangian 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 backward trajectorie s using several availabl e 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 horizontal resolution of 80 km before 2004, and at a horizont al resolution of 40 km starting in 2004. Detailed information regarding the trajectory model and these data sets can be found on NOAA’s Web site ( http://www.arl.noaa.gov/ready/hysplit4.html ).

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

Table 4-2. Back Trajectory Model Parame ters Selected for VISTAS AoI Analysis Model Parameter Value Trajectory duration 72 hours backward in time Top of model domain 14,000 meters Vertical motion option used model data Meteorological Field EDAS End Times 0600, 1200, 1800 and 2400 EST End Heights 100 and 500 m

The choice of these parameters affects the tr ajectories generated a nd the final attribution analyses. In particular, trajectories tend to be come increasingly uncertain the further back inAppendix H Kentucky Regional Haze SIP 27 time they are used. Vertical motion in the model is sometimes best represented by following actual vertical motion measuremen ts (represented by model 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 trajectories 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 analys is performed for Mammoth Cave National Park, Kentucky.Appendix H Kentucky Regional Haze SIP 28 

### Back Trajectories for 20% Worst Days for 2002 Mammoth Cave, KY

Figure 4-2. Example 72-hour back trajectories for 20 percent worst visibility days in 2002 for Mammoth Cave National Park, Kentucky.

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 traject ories with end dates corre sponding to the 20 percent worst visibility days were weighted with calcul ated extinction values and summed into 1-degree horizontal grid cells of latitude and longitude.

Extinction data is based on the IMPROVE Regional 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 orig inal 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 ba sed 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 extinction, and by ex tinction components including ammonium sulfate (AmmSO4), ammonium nitrat e (AmmNO3), particulate organic material (POM), Light Absorbing Carbon (LAC), Soil, a nd Coarse Mass (CM). Weighting trajectories for the 20 percent worst days by sulfate extinction gave greater importance to days influenced by SO2 emissions and lesser importance to days influenced by organic carbon emissions. This allowed a geographic area of influence to be id entified based on sulfate contributions and not skewed by contributions from fire.Appendix H Kentucky Regional Haze SIP 29 These data files were provided to ENVIRON. ENVIRON was charge d with developing residence time plots to define the geographic area w ith highest probability of influencing the receptor on the 20 percent worst days dominated by sulfate. Residence time over an area is indicative of general flow patterns, but sin ce it does not account for emissions and removal processes, it does not necessa rily imply specific areas contributed significantly to haze compounds at a receptor site.

4.4 Area of Influence Data and Displays

The primary objective of the Area of Influence (AOI) displays and data sets are to assist the State in focusing its reasonable progress analysis on those geographic regions and source categories which most impact a particular Class I Area. The sources of data used in these analyses include back-trajectory residence time data, provided by ARS and described above, and the VISTAS 2002 and 2018 36-km gridded emissions data.

Extinction weighted back-trajectory residence ti me plots were provided by ARS for all Class I Areas in the VISTAS region as well as for the surrounding neighboring states . These trajectories were processed on an un-projected (i.e., geod etic lat/lon 1 degree by 1 degree) grid and transferred to ENVIRON for furthe r 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 an alysis 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 extin ction weighted back-trajectory residence times were then plotted on the VISTAS 12-km modeling dom ain. As sulfate is the primary visibility impairing component of the total extinction in the Southeast, the SO4-weighted residence time trajectories were chosen as the basic data set for display. For clarity, these data are scaled by the maximum value of the total extinction-weighted residence time within the modeling domain. The 100-km and 200-km distances from th e Class I area were labeled.

Using the trajectories with the 100-m start he ight, the State has defined the SO2 Areas of Influence as the area with grid cells showing 10% (area shaded in yellow in following plots) or greater residence time (the frequency that winds pass over that area on the way to the Class I area on the 20 percent worst days dominated by su lfate) for the period 2000-2004. Residence time over an area is indicativ e of general flow pattern s, but since it does not account for emissions and removal processes, it does not n ecessarily imply specific areas contributed significantly to haze compounds at a receptor site. The following figure , 4-3, is an extinction weighted residence time plot for Mammoth Cave for 100-m and 500-m trajectory start heights.Appendix H Kentucky Regional Haze SIP 30 

### SO2 Area of Influence for Mammoth Cave, KY

Green circles indicate 100-km and 200-km radii from Class I area. Area in yellow indicates Area of Influence with Residence Time > 10% Area in gray indicates Area of Influence with Residence Time > 5%.

Figure 4-3. Mammoth Cave SO4 extinction-wei ghted residence time plots for the period 2000-2004.

As an aid to the analysis, all regions with s caled residence time values greater than 5% and greater than 10% were noted on the display. Fi nally, county boundaries were overlaid to identify those counties and 36-km modeli ng grid cells for which the extinction-weighted residence time back-trajectories exceeded 5% and 10%. These data were th en exported as comma-delimited ASCII data files for further analyses. These residence time displays are used primarily to determine the regions (counties and/or grid cells) impacting each Class I Area. The next step in the analysis is to determine the potential im pact from emission sources within the regions identified from the extinction-weighted back-traj ectory residence time displays and analyses.

Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory analyses have indicated that SO4 is the largest contributor to haze on the 20 percent worst visibility days and that electric generating utilities and indu strial point sources are the largest contributors to SO4 levels at th e Class I areas. These two source categories make up 95% of the VISTAS SO2 inventory. Therefore these two sour ce categories were identified as the highest priority for evaluation of reasonable progr ess in 2018 at the Class I areas.

The potential impacts of SO2 point source emissi ons 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 w ith both the 2002 and 2018 base year emission inventories. Figures 4-4 and 4-5 display the gri dded point source SO2 emissions from the VISTAS modeling databases, for 2002 and 2018, resp ectively. These data were processed byAppendix H Kentucky Regional Haze SIP 31 summing all vertical layers for each grid column and then summing across all days to obtain annual emission totals for each grid cell.

Figure 4-4. Annual 2002 point source SO2 emissions for the VISTAS region for in tons/year.

Figure 4-5. Annual 2018 point source SO2 emissions for the VISTAS region for in tons/year.Appendix H Kentucky Regional Haze SIP 32 As a way of incorporating the effects of transp ort, deposition, and chemical transformation of point source emissions along the path of the traject ories, 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 monito r, a weighting of 1/9 was appl ied. 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 extinction-weighted back-trajectory residence times (SO2 * Bext-weighted RT * (1/d )) on a grid cell by grid cell ba sis. 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 in ventories. Figure 4-6 displays the result of this final analysis step. Note that the out lined regions (in red and light ora nge) represent the extent of the >10% and >5% sulfate extinction-weighted residence times, determined from the first step in the analysis (see Figure 4-6). As with the reside nce time analysis, the results of the combined distance-weighted SO2 emissions and extinction-weight ed residence times are overlayed with county boundaries and exported to comma-delimited ASCII data files for further analyses of emissions and control options for specific sources.



### 2002 SO2 Emissions weighted by Residence Time Mammoth Cave, KY

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

Figure 4-6. Mammoth Cave 2002 SO2 Emissions * SO4 extinction-weighted residence time plots.Appendix H Kentucky Regional Haze SIP 33 The following plot (Figure 4-7) shows th e 2018 SO2 Emissions multiplied by the SO4 extinction-weighted residence time plots. These were produced the same way as the previous plots, only using 2018 emissions instead of 2002 emissions.



### 2018 SO2 Emissions weighted by Residence Time Mammoth Cave, KY

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%. 2018 SO2 emissions 2018 SO2 emissions

Figure 4-7. Mammoth Cave 2018 SO2 Emissions * SO4 extinction-weighted residence time plots.

To understand how emissions have changed by 2018, the following plot, (Figure 4-8), compares 2002 and 2018 SO2 multiplied by residence time.Appendix H Kentucky Regional Haze SIP 34 

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

### - Mammoth Cave, KY

2018 SO2 emissions 2002 SO2 emissions

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

Figure 4-8. Mammoth Cave 2002 vs. 2018 SO2 em issions multiplied by residence time.

VISTAS states evaluated these plots of reside nce time weighted by sulfate extinction plots of gridded SO2 emissions and define d the SO2 Areas of Influence as those areas with residence time greater than 10%, based on trajectories with start height of 100m and 4 start times per day.

Extinction-weighted residence plots for Class I ar eas indicate that the areas of probable influence for sulfate contribution to visibi lity impairment are similar to those for nitrate contribution even though the visibility impact of nitrat e is an order of magnitude smalle r than that of sulfate. From these plots we can initially conclude that it is appropriate to focus on s ources 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 emi ssions sources at great distance from the Class I area can contribute to visibi lity impairment on some 20 percent worst days.

4.5 Importance of Pollutants Other Than Sulfate

For completion, the following is a brief discussion of the importance of other PM components and contributing source categories. If NOx controls are consider ed, 37% of NOx is from point sources, 23% is from highway ve hicles, and 21% is from nonroa d engines. Elevated organic carbon (OC) and elemental carbon (EC) are indicators of fire. Some states may need to consider emissions from residential wood burning, forest fires (wild and prescrib ed), land clearing, and agricultural burning.Appendix H Kentucky Regional Haze SIP 35 Nitrate (NH4NO3) levels in winter can be signif icant and are dependent on availability of NH3; 83% of NH3 is from area sources (e.g. agriculture) . However, given that sulfate contributes an estimated 78% at Mammoth Cave on the 20 per cent worst visibility days, the KYDAQ believes it is appropriate to focus on SO2 reducti ons in this first Regional Haze SIP.

4.6 Summary of Emission Inventories Used in Cost Curve Analysis

A necessary component of control strategy de sign is a thorough review of the emission inventories that are used in the modeling of the fu ture 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. We used the most current VISTAS future year (2018) base case and 2002 base year emissions to conduct this control cost analysis. For purposes of listing sources within the Area of Influence, data we re provided for all sources with emissions over distance (Q/d) greater than 5 and maximum resi dence time (RTmax) greater than 5. States independently defined the criteria for selecting which sources from this list would be considered for reasonable control measures.

The NIF formatted and SMOKE-ready modeling 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 emi ssions 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 incl uded in the PM emission summaries. This factor is applied to account for the removal of a substantial portion of fugitive dust emissions near a source by surrounding vegetation and structur es when such emissions are used in regional scale modeling analyses.

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

State V OC NOx CO SO2 PM-10 PM-2.5 NH3 AL 445,497 459,880 2,534,778 584,665 232,229 105,341 67,970 FL 1,291,562 930,086 7,710,376 589,069 408,902 205,450 61,643 GA 765,063 623,645 5,013,024 653,362 408,736 195,654 100,134 KY 286,752 466,403 1,730,622 580,341 148,290 50,981 57,220 MS 302,374 239,547 1,203,899 103,679 180,816 43,533 63,765 NC 655,950 616,583 4,097,444 546,429 179,242 84,513 172,976 SC 382,836 323,976 2,064,423 286,781 165,699 78,356 35,400 TN 473,244 511,151 2,601,059 442,589 165,095 75,458 42,738 VA 448,205 461,628 3,034,414 416,190 109,848 47,004 55,057 WV 135,819 348,576 802,262 569,373 48,423 27,807 12,341

V ISTA S 5,187,303 4,981,474 30,792,301 4,772,477 2,047,281 914,096 669,243 BaseG Annual Emissions - 2002 Typical (Tons)Appendix H Kentucky Regional Haze SIP 36 Table 4-4. 2018 Base Case Annual Emissions Summary.

Our 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 high est source types were identified, subcategories within those source types were reviewed. Again, a ranking of the highest residual sub source types was performed and additi onal analyses on these categor ies were conducted. Using the extinction weighted analysis, these emission re views and summaries like those presented in Figure 4-9, VISTAS made a decision to further review only point s ource controls in increment to the Clean Air Act scenario.

In addition to reviewing the resi dual emission categories in the futu re year base, it was important to identify reductions that had already occurred within each category or at specific units. This allowed VISTAS States to determine if certain s ource categories that had yet to be controlled under the future year base case had the potential for reduction or if source types already reduced have reached the full cost-effective (did states take advantage of this step of the analysis) potential.

Finally, once each subcategory was identified, unit level tables of emission comparisons from 2002 to 2018 were developed allowing VISTAS Stat es to review existing emission reductions and providing the ability to assign new cost-effective controls to un its using the best control for the scenario. These tables presented comp arisons of 2002 and 2018 emission levels, for SO2, and future year control technology assignment ( by IPM forecasting and State modification) for point sources. Non-EGU unit-spec ific technology assignments were identified using the control efficiency tables provided by the VISTAS emissions inventory contractor, MACTEC.

Ultimately, the final control strategy decisions will include the application of BART subject source reductions in the future year base case. 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)Appendix H Kentucky Regional Haze SIP 37 Figure 4-9. VISTAS SO2 Emissions Co ntribution 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 wa s conducted to ensure that incremental controls assigned to these source types did not duplicat e existing base case assumptions. Because IPM does not assign a contro l efficiency with each control device applied to SO 2 and NO X , we made some assumptions, based on IP M documentation, as to what pollutant specific level of reduction was applied in the futu re year base case runs. These assumptions, by primary and secondary control de vice code combinations for SO 2, are presented in Table 4-5.

Since many of the control technology control cost equations within AirControlNET require additional unit-level characteristic data, we al so made matches 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 NETDC (MW) values are required for capital and operating and maintenance cost calc ulations for many of the SO2 a pplied 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) 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 emissions inventor y data. These variables were obtained where matches could be found, in priority order of VISTAS, CAMD, and other EPA datasets, respectively. A

l a b

a m

a F l o r i d

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a r o l i n a

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

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A

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a r o l i n a

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

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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 8Appendix H Kentucky Regional Haze SIP 38 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 policies and regulatio ns (Pechan, 2005). The tool provides data on emission sources, potential pollutio n control measures and emissi on reductions, and the costs of implementing those controls.

The core of AirControlNET is a relational databa se system in which control technologies are linked to sources within EPA emi ssions inventories. The system 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

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 100Appendix H Kentucky Regional Haze SIP 39 AirControlNET represent primary emissions of PM. 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.

Since available versions of AirControlNET contain the prepro cessed application of control technologies to a predetermined se t of EPA emission inventories, di rect 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 Ai rControlNET 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, efficiency, and cost information from the unmodified version of the source co de, 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 abov e, every available SO2 control strategy in AirControlNET was run against the EGU and non- EGU point source inventories to develop a master list of available, incrementalcontrol strategies for the en tire VISTAS 36 km domain necessary for VISTAS states to design command- and-control or cost-eff ectiveness 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 associat ed 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 applica tion of all available control measures to all applicable point sources within the AOI. The curv es will allow VISTAS States to determine if, based on the generic application of SO2 control t echnologies from the associations originally developed in AirControlNET and improved upon w ith stakeholder input will help attain reasonable further progress emission reduction objectives while presumably minimizing the number and type of controlled sources in each AOI.

Using a geocoded county list from these AOIs, we parsed the master list of incremental control measures from all point sources located within th e 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 em ission reduction targets for SO2 within each AOI. Each individual source had its own co st effectiveness curve generated.

In aggregate, the results of these applications are SO2 emission 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 considered in this an alysis. An illustrative example of the steps involved with the cost effectiveness curve de sign can be found in the Appendix H.1 of this document.Appendix H Kentucky Regional Haze SIP 40 With each AOI’s cost curve, additional metrics calculated for the distance from the emission release point to the Class I area IMPROVE monitor (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 fo r incremental review and consideration. The KYDAQ used these values to further determin e control strategy deve lopment for individual Class I areas.



### 5.0 REASONABLE PROGRESS ASSESSMENT

The state concluded that SO2 emissions from EGU and non-EGU point sources in geographic Areas of Influence (AOIs) are sources to consid er for further controls. VISTAS developed source matrices for 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 cal culation is based on a si ngle stack at a unit (when more than one are represente d in the inventory) and is calcula ted 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 w ould focus on those sources where RT max was equal to or grea ter than 10%. A second matrix for sources in the SO2 AOI was developed for sources with a 2018 Q/d > 5 when d was greater than 100 km, Q/d 2 > 0.03 when d was less than 20 km, and Q/d > 5 or Q/d 2 > 0.03 when d was 20-100 km (these values were chosen arbitrarily to limit the number of source s on the list and focus on those that are most influential).

Next, the KYDAQ elected to focus on those units th at contributed at least one percent to sulfate visibility impairment at a given Class I area for several reasons. First, the units with the larger contribution toward visibility impairment woul d likely show an environmental benefit under a control evaluation, and KYDAQ would be able to use that environmental benefit to requireAppendix H Kentucky Regional Haze SIP 41 controls on a given unit. S econd, there are several regulato ry programs that use a higher threshold than one percent for evaluation thresholds.

1. The BART rule specifies that a maximum impact of 0.5 dv is an acceptable threshold for establishing significance. This threshold equates to roughly a 5 percent change in visible perception. This same significance level is used in the Prevention of Significant Deterioration/ New Source Review program for the visi bility air quality related value.

2. The NOx SIP Call laid out a significance level for Section 126 pe titions of 4 parts per million (ppm), that being the level to which a State's contribution to another state's ozone problem was considered significant. Four ppm represents approximately 3.75 percent of the 1- hour ozone standard, which was in place at the time EPA promulgated the NOx SIP Call.

3. For the CAIR rule, a PM contribution of 0.2 ug/m3 was used to demonstrate a significant impact, which is 1.3% of the annual PM2.5 standard of 15 ug/m3.

4. Lastly, when human health standards ar e proposed (NAAQS) significant impact levels are assigned which allow sources to determine their significance on air quality in the area around their facilities. Sources that demonstrate that their "contribution" from the new or modified sources is less than these significance levels do not have to complete any further modeling. The SILS represent a percentage of the NAAQS.

After looking at all averaging pe riods for the criteria pollutant s, KYDAQ determined that the one percent threshold we were proposin g for reasonable further progres s was as protective or more protective than the significant impact levels. Th e most restrictive threshold identified was for NOx, which has a NAAQS of 100 ug/m3 and a signifi cance level of 1 ug/m3, which represents one percent of the total.

Finally, KYDAQ considered available resources to evaluate the sources in each Class I area’s sulfate AoI. KYDAQ recognized that there was ne ither sufficient time or resources available to evaluate all units within a given AoI. Theref ore, a threshold needed to be established to determine which units would be evaluated. Ta ble 5-1 shows that a one percent contribution threshold captures greater than 50 percent of the total point source SO2 contribution at Mammoth Cave, while requiring an evaluation of 19 units. In order to capture a significant percentage of the total contribution, the next increment would involve an evaluation of many more units. For example, at Mammoth Cave National Park, one-hundred and forty-six units represent an additional 42 percent of the tota l SO2 emissions contri buting to visibility impairment at the Class I area. KYDAQ believes th e one percent threshold is appropriate, given the contribution to the total visibility impairment at the Class I area, and the limited resources available to conduct the unit-by-unit evaluation for reasonable progress.Appendix H Kentucky Regional Haze SIP 42 Table 5-1. Numbers and percentage of 2018 SO 2 emission units that contribute to Kentucky’s Class I area.
Kentucky’s Class I Area MACA # Units Contributing >= 1% 19 Percentage of total contribution 53%

# Units Contributing >= 0.1%, but < 1% 146

Percentage of total contribution 42%

# Units Contributing < 0.1% 96 Percentage of total contribution 5%

The following Table, 5-2, shows the analysis for the Mammoth Cave AOI for sources that were found to have one percent or more contribution for Mammoth Cave. The one percent and full spreadsheet for Mammoth Cave and one per cent contribution spreadsheets for VISTAS, CENRAP and other Class I areas ar e available in Appendix H.2.

Table 5-2. Mammoth Cave Q/d, Q/d^2, RTMax, and fractional cont ribution analysis.

State Plant Point ID 2018 Q (tons) CE (%) d (km) Q/d Q/d^2 RTMax Fraction Kentucky TVA PARADISE STEAM PLANT 003 22,539 90 75.45 298.73 3.96 35.87 0.111 Kentucky WESTERN KY ENERGY CORP WILSON STATION 001 11,115 90.9 89.81 123.76 1.38 48.07 0.062 Kentucky TVA PARADISE STEAM PLANT 0 02 7,941 90 75.45 105.25 1.39 35.87 0.039 Kentucky TVA PARADISE STEAM PLANT 0 01 7,823 90 75.45 103.69 1.37 35.87 0.038 Indiana INDIANA MICHIGAN POWER-ROCKPORT 002 32,660 0 117.79 277.29 2.35 12.31 0.035 Indiana INDIANA MICHIGAN POWER-ROCKPORT 001 32,350 0 117.79 274.65 2.33 12.31 0.035 Kentucky LOU GAS & ELEC, MILL CREEK 04 12,823 91.7 104.63 122.56 1.17 25.68 0.033 Kentucky LOU GAS & ELEC, MILL CREEK 03 10,316 91.7 104.63 98.60 0.94 25.68 0.026 Kentucky KENTUCKY UTILITIES CO GREEN RIVE R STATIO 004 4,234 0 90.11 46.98 0.52 35.87 0.017 Tennessee TVA CUMBERLAND FOSSIL PLANT 001 12,073 95 157.50 76.65 0.49 21.87 0.017 Tennessee TVA CUMBERLAND FOSSIL PLANT 002 11,936 95 157.56 75.76 0.48 21.87 0.017 Kentucky LOU GAS & ELEC, MILL CREEK 02 6,014 91.8 106.63 56.40 0.53 25.68 0.015 Kentucky CENTURY ALUMINUM OF KY LLC 024 6,366 0 106.54 59.75 0.56 21.08 0.013 Kentucky KENTUCKY UTILITIES CO GREEN RIVE R STATIO 003 2,944 0 90.11 32.67 0.36 35.87 0.012 Kentucky GENERIC UNIT GSC21 5,927 0 108.62 54.57 0.50 21.08 0.012 Indiana PSI ENERGY - GALLAGHER 0 04 5,383 0 128.51 41.89 0.33 25.48 0.011 Indiana PSI ENERGY - GALLAGHER 0 01 5,383 0 129.50 41.57 0.32 25.48 0.011 Indiana PSI ENERGY - GALLAGHER 0 03 5,309 0 128.51 41.31 0.32 25.48 0.011 Indiana PSI ENERGY - GALLAGHER 0 02 5,285 0 129.50 40.81 0.32 25.48 0.011

Spreadsheets were developed for each Cl ass I area source w ith Q/d > 5 or Q/d 2 > 0.03, indicating the plant name, industry description, emissions projections for 2018, current control efficiency (CE%), distance from Class I area, Q/d, Q/d 2 , RT average, RT maximum, Q/d*RT, the fraction a single source contributes to the total Q/d*RT for a Class I area.

CE% is important because it gives a sense of wh ich facilities are alrea dy controlled by what percent and which may be controlled further.

Next, an analysis of control options, generic co sts of controls, and "Cost/ton" for various units contributing greater than one percent to an y Class I area was developed. SpreadsheetsAppendix H Kentucky Regional Haze SIP 43 containing unit-level emissions and other associated data for the Class I areas was matched with data from AirControlNET (Pechan, 2005) to give SO2 control efficiency, annual SO2 emissions reduction from 2018 Base Case, total annualized co st (in 2005 dollars), and cost per ton reduced for application of specific control measures.

KYDAQ reviewed the sources, emissions, control opt ions, and costs 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 com bustion from industrial s ources, with little contribution from other sources. Therefore, KYDAQ eliminated other source categories from the Four Factor Analysis. KYDAQ next looked at source-specific cost s, existing controls, remaining useful life, envi ronmental and energy impacts.



### 6.0 FOUR FACTOR ANALYSIS

Section 169A(g)(1) of the Clean Air Act (C AA) 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 goal for any mandatory Class I area with in a State: cost of compliance, time necessary for compliance, energy and non-air quality enviro nmental impacts of compliance, and remaining useful life of any existing source subject to such requirements. These statutory factors would be specific to the sources being considered for additional controls. Kentucky sent December 22, 2005, letters to several Kentucky sources pr oviding them with EPA’s November 28, 2005,

“ Draft Guidance for Setting Reasonable Progre ss Goals Under the Regional Haze Program. ” Copies of these source letters are available in Appendix H.3. Many other source BART letters and correspondence are avai lable in Appendix L.2.

6.1 The Four Statutory Factors

6.1-1 Cost of Compliance

The “cost of compliance” is a factor used to determine whether complian ce costs for sources are reasonable compared to the emission reduction a nd visibility improvement they will achieve. Note that visibility improvement is not only related to tons of pollu tant 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 comparis on, sulfate particulate impairs visibility greater than coarse partic ulate. Costs should be determined fo r one-time capital co sts, 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 reasonable progress goals to reflect the degree of improvement achievable within the long-term st rategy period, as opposed to the improvement expected at full implementati on of a control measure, if the time needed for full compliance exceeds the length of the l ong-term strategy peri od. For instance, if implementation of a control measure could not be completed within the schedule outlined by theAppendix H Kentucky Regional Haze SIP 44 control strategy, the RPG should reflect what visi bility improvement coul d be expected within the strategy period.

For example, if construction labor availability c onstraints preclude the inst allation of controls at all sources of a particul ar category within the LTS period, th e RPG should reflect the visibility improvement anticipated from installation of contro ls at the percentage of sources that could be controlled within the strategy period. (The SIP c ould still include control strategies that extend beyond the 2018 milestone; in the a bove example, the visibility improvement anticipated from installation of controls at the pe rcentage of sources that could not be controlled within the first strategy period would have to be counted in a later SIP).

6.1-3 Energy and Non-Air Quality Envi ronmental Impacts of Compliance

The “energy and non-air quality environmental impacts of compliance” 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 engine s may decrease the overall efficiency and require a significant increase in diesel fu el consumption. The State shoul d 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 “rem aining useful life of the source” is applicable only to those measures, which would require retrofitting of co ntrol devices (or possibly production changes) at existing sources. In such cases, this factor should be treated as one element of the overall cost analysis. For purposes of this analysis, the remaining useful lif e is the difference between the year of the reasonable progress analysis and the da te 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

The next step was to identify emission reductions th at have already occurred within each source category and at specific units. Unit level tabl es of emission comparisons from 2002 to 2018 were developed, allowing VISTAS states to re view existing emission reductions. 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 wa s conducted to ensure that incremental controls assigned to these source types did not duplicat e existing base case assumptions.Appendix H Kentucky Regional Haze SIP 45 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. Using the modified inventories identified above, 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 VISTAS 36 km domain.

For the sources within the AOIs for Kentucky’s Class I area, the master list of incremental control measures was sorted to determine the costs of incremental control measures. These data were combined in a master spreadsheet with th e distance from the emissi on release point to the Class I area IMPROVE monitor (in km), the 2018 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 th e county in which the em ission release point was located. Kentucky evaluated these control measures and costs as part of their review of the statutory factors for reas onable further progress.

The Regional Haze Rule requires that states co nsider the following fact ors and demonstrate how these factors were taken into considerati on in selecting the reasonable 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

As defined in Section 7.5.5, coal-fir ed electric utilities and coal-fir ed industrial boilers were the largest source categories contributing to SO2 in 2018 in the Areas of Influence defined for Kentucky’s Class I area. 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 institutional boilers can be controlled either by switching the fuel source to a lower sulfur fuel content or by installing postcombustion controls. Costs vary by fuel sour ce and boiler type and require source specific analyses for accuracy.

Bituminous coal is commonly bur ned in boilers in the eastern US. Switching to another bituminous coal with lower sulfur content or blending bituminous coals can reduce SO2 emissions with least impact to boiler performance. While sub-bituminous coal has a lower sulfur content than bituminous coal, it also has a lower heat rate and so more coal has to be burned to generate the same energy output. For boilers th at are designed for bituminous coal, only a small fraction of the fuel can be switched to low sulf ur sub-bituminous coal without affecting boilerAppendix H Kentucky Regional Haze SIP 46 operations. Costs of boiler modifications to acc ommodate low sulfur sub-bituminous coal may make switching to sub-bituminous coal impractical. Contract initiation and termination costs, differential fuel prices and heat rates, transportation costs, a nd modification to boiler operations, fuel handling and waste handling systems will have to be considered specific to each source.

Flue-gas desulfurization is the common post-com bustion control for coal-fired boilers. Flue gas is passed through an absorbent for sulfur dioxide (generally limestone or lime) in either a wet scrubber, dry scrubber, or spra y dryer. A calcium sulfate bypr oduct is produced that may be further processed to produce gypsum as a commercial byproduct. Costs of flue-gas desulfurization include initial construction costs and ongoing operational and maintenance costs for the absorber tower, sorbent handling, and 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 co sts, and maintenance costs. Conceptually, post-combustion controls can be used for oil boilers, but th ere is little precedence for such installations.

6.2-2 Time Necessary for Compliance

For fuel switching, the time necessary to termin ate existing fuel contracts and initiate new contracts needs to be considered . Generally two to three years may be required. Instillation of post-combustion controls will require 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- combustion controls may reduce boiler heat rate and energy output. Scrubbers and spray dryers will require additiona l safeguards for fuel handling and waste handling systems to avoid addi tional 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 impact s of increased carbon emissions wi ll 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

The KYDAQ has just completed the Reasonable Pr ogress Assessment for the first regional haze SIP. The following was KYDAQ’ s Process on Reasonable Progress Assessment for the current time period (from the present to 2018):Appendix H Kentucky Regional Haze SIP 47 Step 1: Determine pollutants of concern.

VISTAS evaluated the species contribution on the 20 percent worst visibility days and concluded that sulfate accounted for greater than 70 percen t of the visibility im pairing pollution. The VISTAS States concluded that controlling SO2 em issions was the appropriate step in addressing the reasonable progress assessment for 2018. The VI STAS findings were consistent with the findings of the Southern Appalachian Mountai n Initiative (SAMI). As you may recall, SAMI confirmed that sulfate particles account for the gr eatest portion of the haze affecting Class I areas in the Southern Appalachian region and that these sulfates were produced in large part from SO2 emissions from coal combustion.

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

Since SO2 point source emissions in 2018 are proj ected to represent great er than 95 percent of the total SO2 emissions inventory, the VISTAS States concluded 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.

KYDAQ evaluated the amount of SO2 reduction from the EGU sector resulting from the implementation of CAIR. The EGUs in Kentucky are expected to reduce their SO2 emissions by 54 percent between 2002 (2002 emissions approx imately 495,152 tons per year) and 2018 (2018 emissions approximately 226,062 tons per year). Much of that reducti on is the result of requirements that are predicted by the IPM to m eet CAIR. It should be noted that many of Kentucky’s EGUs had SO2 scrubbers in operation before 2002.

To further support EGUs subject to CAIR is sufficient for reas onable progress, a discussion in the CAIR rule highlighted below (See Appe ndix H.5 for 70 FR 25197-25198) addresses the reasonable progress factors of cost and time necessary for compliance for these EGUs, and provide the necessary support for a State's four factor reasonabl e progress analysis that must accompany a state’s assertion that CAIR is suffi cient 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 pollution control retrofits that result from a program to achieve highly cost-effective reducti ons are quite signific ant and can not be immediately installed. Such retrofits 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 industry will need to secure large amounts of capital to meet the control requirements wh ile managing an already large debt load, and is facing other large capital requiremen ts to improve the transmission system. Furthermore, allowing pollution control ret rofits to be installed over time enables the industry to take advantage of planned outages at power plants (unplanned outages can lead to lost revenue) and to enable project manage ment to learn from early installationsAppendix H Kentucky Regional Haze SIP 48 how to deal with some of the engineering challenges that will exist, especially for the smaller units that often present space limitations.

Based on these and other considerations, EPA det ermined in the NPR that the earliest reasonable deadline for compliance with the fin al highly cost-effective control levels for reducing emissions was 2015 (taking into cons ideration the existing bank 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 em issions 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 level 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 ph ase commences in 2009 instead of in 2010, as explained in detail in section IV.C). Th e first phase would be the initial step on the 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 the feasibility of installing the necessary emi ssion control retrofits, as described in section IV.C.

Although EPA's primary cost-effectiveness de termination 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 also highly cost effective. Throughout this preamble section, EPA reports both the 2015 and 2010 (and 2009 for NOX) costeffectiveness results, although the first phase l evels were determined based on feasibility rather than cost effectiveness. The 2015 emi ssions 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.

The KYDAQ 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 where they were expected and needed. If KYDAQ’s assessment for the periodic report indicates th at its emissions are likely not to meet 2018 projections then the KYDAQ may re-evaluate the four factors to re-assess the Long-Term Strategy. Based on the controls currently being installed for CAIR, re quired by BART, consent decrees, and predicted by IPM under CAIR, the KYDAQ has concluded that at this time these existing regulatory programs constitute reasonable control measures fo r Kentucky EGUs during this first assessment period (between baseline and 2018). A table listing the existing and expected Kentucky EGU controls is available in Appendix H.4.

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

The KYDAQ calculated the fractiona l contribution from all emission units within the SO2 Area of Influence for a given Class I area and identified those emissi on units with a contribution of one percent or more to the visibility impairment at each Class I area. Sources considered in the reasonable progress evaluation ca n be found in Appendix H.2.Appendix H Kentucky Regional Haze SIP 49 Step 5: Evaluate the four factors.

Each emission unit identified in Step 4 above wa s considered for evaluation using the statutory and regulatory factors of 1) cost of compliance, 2) time necessary for compliance, 3) the energy and non-air quality environmental impacts of complia nce, and 4) the remain ing useful life of the emissions unit. If any control measure for an emission unit was found reasonable after assessing the four factors, modeling would be performed to determine if the contro ls would result in a visibility improvement at any Class I area.

For the limited purpose of evaluating the cost for the reasonable progress assessment in this first regional haze SIP, the KYDAQ believes it is not equ itable to require Non-EGUs to bear a greater economic burden than EGUs for a given contro l strategy. The KYDAQ used EPA’s CAIR EGU cost analysis to establish a cost/ton of SO2 re moved threshold. During the current reasonable progress assessment, no units in Kentucky were identified for additional control since no measures were found to be below the cost thre shold. Below is a summary of the analysis.

Results of four-factor analysis

The KYDAQ used the cost of compliance as a screening tool to determine the universe of sources to perform the full four-f actor evaluation. Therefore, the summary is focused on the cost of control. The dollar per ton of SO2 removed threshold that the KYDAQ used to determine if the cost was reasonable was based on EPA’s CAIR cost analysis for implementing CAIR (See EPA’s CAIR cost analysis in 70 FR 25201-25208 12May2005 available in Appendix H.5). After a review of EPA’s CAIR cost analysis, the KYDAQ determined that the CAIR SO2 control costs vary by year of analysis (2010 vs. 2015) and may range from $400 to $3,400 per ton of SO2 removed. Ultimately, EPA found a consistent marg inal cost for both years at $2000 per ton, which KYDAQ believes establishes an appropriat e threshold against which cost-effectiveness may be evaluated for reasonable progress. During the current r easonable progress assessment, no Non-EGU units in Kentucky were identified for additional control because no measures were found to be cost-effective.

For Non-EGUs, KYDAQ found that emissions fr om the following facility contributed one percent or more to visibility impairment in a Class I area, and therefor e focused the reasonable progress assessments on specific units at this facility:

• Century Aluminum of Kentucky for impacts at Mammoth Cave.

The KYDAQ also looked at what sources in Kentucky may be im pacting Class I areas located outside of the Kentucky, as well as what source s located outside of Kentucky may be impacting Kentucky’s Class I area. KYDAQ, based on its Q/d times RTMax analysis identified eight EGUs, six from Indiana and two from Tennessee, w ith a one percent or more contribution for the Mammoth Cave area of influence. KYDAQ sent le tters to Indiana and Te nnessee indicating that no additional controls are requested at this time since Mammoth Cave is currently exceeding the uniform rate of progress and the EGUs are being a ddressed by CAIR (See copi es of the letters in Appendix J). In addition, ba sed on the KYDAQ Q/d times RT Max analysis, no Kentucky sources were identified with a contribution of one percent or more to the vi sibility impairment atAppendix H Kentucky Regional Haze SIP 50 Class I areas in other states. The list of sources identified by the KYDAQ’s Q/d times RTMax analysis for given Class I areas are available in Appendix H.2.

Cost of Compliance

VISTAS contracted with Alpine Geophysics to evaluate control options and costs for sources within the AoI for the Class I ar eas of concern. Alpine used EPA’s AirControlNet software to evaluate control options and costs for contro ls. The SO2 control suggested by the VISTAS control cost spreadsheet for Century Aluminum is a sulfuric acid pl ant at a cost of $14,207, $23,020, and $43,281 per ton of SO2 removed for potlin es 1-4, potline 5, and the anode baking furnace respectively (See the VISTAS SO2 contro l cost spreadsheet for Century Aluminum in Appendix H.6). Therefore, since the cost of co mpliance for the control option ranges from 7 to 22 times greater than the cost-effectiveness th reshold, the KYDAQ conclude s that there are no cost-effective controls available for these Century Aluminum units at this time within the cost threshold established for this reasonable progress assessment.

Time Necessary for Compliance, Energy and N on-Air Impacts, and Remaining Useful Life

The three remaining statutory factors: 1) tim e necessary for compliance, 2) the energy and nonair quality environmental impacts of compliance, and 3) the remaining useful life of the emissions unit, while required to be considered, were deemed not applicable, since there were no cost-effective controls to evaluate.


### 7.0 Best Available Retrofit Technology

7.1 Background

As required by the CAA, the EPA included in the fi nal regional haze rule a requirement for Best Available Retrofit Technology (BART) for certain large 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 visibili ty-impairing air pollutant, were placed in operation between August 7, 1962 and August 7, 1977, and whose operations fall within one or more of 26 specifically listed source 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 address the BART requirement when they develop regional haze SIPs. The EPA ha s set guidance for identifying BA RT-eligible sources in 40 CFR Part 51 Appendix Y.
A BART-eligible source that is responsible for a 1.0 deciview (dv) change or more is considered to “cause” visibility impairme nt. Although the appropriate th reshold may vary, the EPA’s guidance states that the contribution threshold us ed for BART applicability 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.Appendix H Kentucky Regional Haze SIP 51 The guidelines direct that Stat es should include SO2, NOx, and di rect 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 pollution control technol ogy 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 Kentucky, there were twenty-six facilities id entified with BART-eligible sources. Of these twenty-six BART-eligible facilities, twenty-one were exem pted from BART through modeling. For a list of BART-eligible facilities please refer to Appendix L. Seventeen of twenty-six facilities submitted site-specific modeling protoc ols and subsequent modeling demonstrations based upon the VISTAS modeling protocol. Modeli ng of nine Kentucky BART-eligible sources was conducted by VISTAS contractor using the VISTAS common protoc ol. The site-specific protocols are found in Appendix L.5 and the ex emption modeling demons trations are found in Appendix L.6. The BART modeling protocols were reviewed by KYDAQ staff that worked with and shared the BART protocols with both EPA and the FLMs for their review and comment. Their comments were shared with the faci lities and addressed be fore the modeling was conducted. The individual source BART exem ption modeling demonstrations are being provided to EPA and the FLMs with this Regional Haze SIP.

KYDAQ staff reviewed the exemption demonstrati ons to determine whether the sources have less than 0.5 deicview (dv) imp act on any Class I area within 300 km of the source. Sources demonstrating less than 0.5 dv impa ct are considered exempt. Sour ces contributing 0.5 dv impact or greater are considered subject to BART an d were required to proceed to conduct BART determination modeling to determine what cont rol measures, if any, constitute BART for the

source.

Five EGU sources were found to be subject to BART based on th eir BART exemption modeling. KYDAQ reviewed the proposed BART determinati on modeling results and has concurred with the findings that BART, for the fi ve subject sources, are the cont rols the sources’ recommended in consideration of applicable cons ent decrees. All five facilities wi ll install emission controls to address condensible particulates, except the contro ls installed for TVA Para dise Units 1-3 are not for BART. The five individual source BART determination modeling submittals are being provided to EPA and the FLMs in this Regional H aze SIP. For a full discussion of the BART exempted and subject sources, please refer to Appendix L.Appendix H Kentucky Regional Haze SIP 52 

### 8.0 FINAL LONG TERM STRATE GY AND REASON ABLE PROGRESS GOALS

As stated in section 2.0 above, the regional haze rule requires States to establish reasonable progress goals, expressed in deciviews, for visib ility improvement at each affected Class I area covering each (approximately) 10-year period until 2064. This first set of reasonable progress goals must be met through measures contained in the state’s long-term strategy covering the period from the baseline until 2018. This sect ion discusses development of Kentucky’s longterm strategy.

8.1 Long-Term Strategy

Ammonium sulfate is the most important contributor to vi sibility impairment and fine particle mass on the 20 percent worst and 20 percent best visibility days at Mammoth Cave. Sulfate levels on the 20 percent worst days account fo r an estimated 78 percent of the visibility impairment at Mammoth Cave. Across the VIST AS region, sulfate levels are higher at the inland sites than at the coastal sites. On the 20 percent cleares t days, sulfate levels are more uniform across the region. Reduction of SO2 emi ssions would be the most effective means of reducing ammonium sulfate. Ninety percent of SO2 emissions in Kentucky are attributable to electric generating facilities and industrial poin t sources. Thus, the long-term strategy for this first Regional Haze SIP focused on reductions in SO2 emissions.

There are significant control programs in plac e in Kentucky and the region to reduce SO2 emissions between the baseline period and 2018. Mo st notably, CAIR is predicted to result in greater than eighty percent re duction from EGU SO2 emissions in Kentucky. Overall the SO2 emissions in Kentucky are predicted to decreas e from 2002 levels at 495,152 tons per year to 226,062 tons per year in 2018. Such large SO2 reductions are predicte d to result in significant improvements in visibility. Kentucky’s CAIR rule s are available as Appendix H.7. It should be noted that many of Kentucky’s EGUs had SO 2 scrubbers in operation before 2002. The KYDAQ intends to re-evaluate the IPM predictions of SO2 reductions for CAIR at the time of our next periodic report in 2012 to ensure that the reductions currently predicted by IPM for CAIR are in fact taking place where they are expected and needed. However, based on the existing SO2 controls in operation and those that are currently being constructed and others being required by consent decr ee and BART, Kentucky has conclu ded that at this time these existing regulatory programs constitute reasonable measures for Kentucky EGUs during this first assessment period (between baseline and 2018). A table listing the existing and expected Kentucky EGU controls is av ailable in Appendix H.4.

At Kentucky’s Class I area, visibi lity improvements on the 20 percent worst days are expected to be better than the uniform rate of progress g lidepath by 2018 based sole ly on reductions from existing and planned emissions controls. For ex ample, at Mammoth Cave National Park, a 4.7 deciview improvement in visibility would meet uniform rate of prog ress in 2018; expected emissions reductions by 2018 are projected to achieve a 5.8 deci view improvement. In fact, visibility improvements at all VISTAS inland Cla ss I areas and most of the coastal Class I areas are projected to be better than the uniform rate of progress. The percentage of the targetAppendix H Kentucky Regional Haze SIP 53 reduction achieved for the Mammoth Cave is 123 percent. This mean s that the rate of improvement is 23 percent gr eater than the uniform rate of progress by 2018.

In addition to improving visibility on the 20 percent worst visibility days, st ates are also required to protect visibility on the 20 percent best days at the Class I areas. Vi sibility on the 20 percent best days is projected to improve in 2018 at al l VISTAS Class I areas as a result of the 2018 emissions reductions. The percentage of the targ et achieved for the Mammo th Cave is about -6 percent. Zero percent change would mean no change in visibility; -6 percent means that visibility is better than no change, or a 6 pe rcent improvement (values lower than current conditions.)

The KYDAQ completed a reasonable progress a ssessment 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 one percent to visibility impairment at the Class I area in Kentucky or in neighboring St ates. The KYDAQ conclude d that the predicted 54 percent reduction in EGU SO2 emissions from CAIR requirements were reasonable for this long-term strategy.

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 Cl ass I areas and status of state plans to mitigate emissions from construction activities, and the ro le of NH3 and potential 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 wildfire s) is a infrequent cont ributor to visibility impairment at the Class I area in Kentucky. However, KYDAQ has an open burning regulation (401 KAR 63:005) that addresses open burning in Kentucky. The KYDAQ believes that 401 KAR 63:005, which is already incorporated into Kentucky’s SIP, provides additional support to aid the Commonwealth with meeting its reasonable progress goals (RPGs) for this first planning period. A copy of KYDAQ’s open burni ng regulation can be obtained at www.lrc.ky.gov.

Also as discussed in Section 4.1 and demonstrated in Figure 17, fine soils are a relatively minor contributor to visibility impairment at Kentucky’s Class I area. Nevertheless, regarding fugitive dust emissions, KYDAQ has a fugitive emissions regulation (401 KAR 63: 010) that addresses fugitive dust emissions in Kentucky. The KYDAQ believes that 401 KAR 63:010, which is already incorporated into Kentucky’s SIP, provi des additional support to aid the Commonwealth with meeting its RPGs for this first plan ning period. A copy of KYDAQ’s fugitive dust regulation can be obtained at www.lrc.ky.gov.

Through its work with VISTAS, Kentucky has not found that ammonia controls are warranted at this time from Kentucky sources. Based on Geor gia Tech sensitivities, a significant amount of ammonia emissions comes from outside of Kentucky ( See Figure 3-3 ). Kentucky, per its CMAQAppendix H Kentucky Regional Haze SIP 54 regional haze modeling with VISTAS, is focused on obtaining additional SO2 emissions reductions to address CAIR, BART, and consent decrees in Kentucky. The reduction in large amounts of SO2 emissions w ill lessen the formation of Ammonium sulfate , (NH 4 ) 2 SO 4 emissions.

Additional Kentucky EGU controls for CAIR per IPM, consent decrees, and BART that can be quantified have been included by VISTAS in a final modeling run to address the cumulative benefits from the emission controls discussed in Section 7.2.1, any controls resulting from BART determinations within the VISTAS states and any other controls resulting from the states within VISTAS to address reasonable pr ogress that can be quantified. If the final modeling run and analyses are completed within a reasonable period of time prior to the final Regional Haze SIP submittal on December 17, 2007, the KYDAQ would cons ider incorporating these findings in the final SIP, including revising reasonable progre ss goals if needed. If the modeling runs and analyses are not completed in time, the KYDAQ will review the information as it becomes available and determine if a SIP revision is nece ssary. Furthermore, if the addition of some additional controls or changes in a final VISTAS model run doe s not significantly change the current VISTAS regional haze modeling results for Kentucky, as presented in Section 8.3, then it is not likely that KYDAQ will modify its regional haze SIP for this reason.

8.3 Reasonable Progress Goals

The regional haze rule at 40 CFR 51.308(d)(1) requi res a State to establish reasonable progress goals for each Class I area within the state (expre ssed in deciviews) that provide for reasonable progress towards achieving natu ral visibility conditions by 2064. In addition, the USEPA released guidance on June 7, 2007 to use in setti ng reasonable progress goa ls. The goals must provide improvement in visibility for the most impaired days, and ensu re no degradation in visibility for the least impair ed days over the SIP period.

In accordance with the requirements of 40 CFR 51.308( d)(1), this Regional Haze SIP establishes reasonable progress goals for th e Class I area in Kentucky. The KYDAQ compared baseline visibility conditions to natural visibility conditions in the Cl ass I area to determine the uniform rate of visibility improvement (in deciviews) that would need to be maintained during each implementation period in order to attain natural visibility conditions by 2064.

Through the VISTAS modeling, the KYDAQ has estimat ed the expected visibility improvements resulting from existing federal and state regulations . As alluded to earlier, VISTAS in December 2007 and also into 2008 was in the process of m odeling additional control measures found to be reasonable to implement in this review period by the VISTAS states, as well as the results of VISTAS states’ BART determinations. The KYDA Q will not include the results of this final modeling run in its final SIP submittal due to ti ming and since the results provide reasonable progress goals that are very similar and as favora ble to the ones presented in this section. The VISTAS baseline modeling has already demonstr ated that the 2018 base control scenario provides for an improvement in visibility better than the uniform rate of progress for Kentucky’s Class I area for the most impaired days over th e period of the implementation plan and ensures no degradation in visibility for the leas t impaired days over the same period.Appendix H Kentucky Regional Haze SIP 55 Table 8-1 contains the reasonabl e progress goals for this planni ng period for Kentucky’s Class I area. For the 20% worst days, the reasonable progress goal for the Class I area provides for greater visibility improvement by 2018 than the area’s uniform ra te of progress. For the 20% best days, the reasonable progress goal for the Class I area indicates an improvement of visibility by 2018 than current best day conditions. These goals are based on the modeling results discussed in Section 7.2.4. The model performance for the 20% best days is not as good as for the 20% worst days because the model has gr eater difficulty accurately projecting small concentrations. On the 20% best days, the mo del does not meet VISTAS model performance goals or criteria for sulfate, nitr ate, and coarse mass (under predic ted) and soil (over predicted), however, the organic carbon and elemental carb on do meet performance goals on the 20% best days. Given the larger percent errors of the fractional bias on the 20% best days, the KYDAQ has less confidence in the absolute values projected for these reasonable progress goals, however, the KYDAQ does expect that visibility on these days will be better than the current conditions 20% best days.

Table 8-1. Kentucky 2018 Reasonab le Progress Goals (in decviews)

Class I Area Baseline Visibility for 20% Worst Days (dv) Reasonable Progress Goal Modeled for 20% Worst Days (Improvement) (dv) Baseline Visibility for

20% Best

Days (dv) Reasonable Progress Goal Modeled for

20% Best

Days (Improvement) (dv) Deciview Improvement Needed 2018-2064 (20% Worst Days)

Mammoth Cave National Park, KY 31.37 25.56 (5.81) 16.51 15.57 (0.94) 14.48Appendix H Kentucky Regional Haze SIP 56 

### REFERENCES:

1. Boylan Ph.D., James, 2006, VISTAS Joint Tech Analysis-Planning Call. Power Point Presentation: Summary BART_VOC_NH3_PM.ppt. 2. Brewer, P.F.; and Adloch, J.P., 2005, Trends in Speciated Fine Pa rticulate Matter and Visibility across Monitoring Networks in the Southeastern United States . J Air and Waste Management Association , 55, 1663-1674. 3. Federal Register / Vol. 70, No. 128 / 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 (IMPROVE), Colorado State University, Cooperative Institute for Resear ch in the Atmosphere, Fort Collins, CO. 5. MACTEC, 2006, Documentation of the Ba se 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 Tracki ng Progress under the Regional Haze Program; EPA-54/B-03-004, 2003.