Appendix H 

 Kentucky Regional Haze SIP 

Kentucky Energy and Environment Cabinet 

Kentucky Division for Air Quality 

------------------------------------------- 

Appendix H 

Reasonable Progress Evaluation 

and Long Term Strategy
 Appendix 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 PROGRESS 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 Environmental Impacts of Compliance ........................ 44 

6.1-4 Remaining Useful Life of the Source.......................................................................... 44 

6.2 Evaluating Four Statutory Factors for Specific 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 ............................................................................... 46 
 Appendix 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 AND REASONABLE PROGRESS GOALS............. 52

8.1 Long-Term Strategy............................................................................................................ 52 

8.2 What Additional Emissions Controls Were Considered 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 Contribution Spreadsheets 

Appendix H.3 - Source Letters 

Appendix H.4 – Kentucky Electric Generating Units (EGUs) Existing and Expected Emission 

Controls 

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

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

Appendix H.7 – Kentucky CAIR Regulations 
 Appendix H 

 Kentucky Regional Haze SIP 

4

PURPOSE 

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

to set and meet Reasonable Progress Goals (RPGs) as part of our Regional Haze SIP under 40 

CFR 51.308(d)(1), and the requirements for establishing best available retrofit technology 

(BART) controls under 40 CFR 51.308(e). 

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

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

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

regional haze rule (RHR) at 51.308(d) requires states to demonstrate reasonable progress toward 

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

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

toward natural conditions for each Class I area. This is known as the “glidepath. The RHR then 

requires states to establish RPGs for visibility improvement at each affected Class I area 

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

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

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

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

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

Our long term strategy contains 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 Kentucky’s Class I area. 

III. Discussion of emissions sensitivity 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 “statutory factors,” listed in 40 CFR 51.308(d)(1)(i)(A) to those 

sources identified in the previous step 

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

specific sources. 

VII. Identification of BART-eligible sources. 

VIII. BART exemption modeling for BART-eligible sources. 

IX. BART determinations for sources subject to BART. 

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

reasonable progress control determinations. 

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

 Kentucky Regional Haze SIP 

5

1.0 EMISSIONS CONTROLS MODELED 

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

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

projections are based on Integrated Planning Model® (IPM®). CAIR will permanently 

cap emissions of sulfur dioxide (SO2) and nitrogen oxides (NOx) in the eastern United 

States. CAIR achieves large reductions of SO2 and/or NOx emissions across 28 eastern 

states and the District of Columbia. When fully implemented, CAIR will reduce SO2 

emissions in these states by over 70 percent 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 NOx SIP call applies to certain Electric 

Generating Units (EGUs) and large non-EGUs, including large industrial boilers and 

turbines, and cement kilns. States in the Visibility Improvement – State and Tribal 

Association of the Southeast (VISTAS) region affected by the NOx SIP call have 

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

reviewed the available state rules and guidance documents to determine the affected 

sources and ozone season allowances. EPA estimated 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 Company, Virginia Electric Power Company, Gulf 

Power Crist 7). 

• The settlement requires Tampa Electric Company (TECO) to pay a $3.5 million 

civil penalty. Under the agreement, TECO will install permanent emissionscontrol equipment to meet stringent pollution limits; implement a series of interim 

pollution-reduction measures to reduce emissions while the permanent controls 

are designed and installed; and retire pollution emission allowances that TECO or 

others could use, or sell to others, to emit additional pollution into the 

environment. The settlement also requires 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 eight 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. The 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 Register: June 15, 2005 (Volume 70, Number 114)) / 

Birmingham (March 12, 2004 (Volume 69, Number 49))/ Northern Kentucky (Federal 

Register: September 16, 2004 (Volume 69, Number 179)). The purpose of a state 

implementation plan (SIP) is to demonstrate attainment or maintenance of the 1-hour 

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

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

public comment and approval. 

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

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

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

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

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

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

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

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

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

Emissions Vehicle Program (LEV II) standards. Manufacturers can produce vehicles with 

emissions ranging from relatively dirty to zero, but the mix of vehicles a manufacturer 

sells each year must have average NOx emissions below a specified value.

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

categories of nonroad engines and vehicles. 

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

commercial marine vessels (CMV) and locomotive emissions. 

• Industrial Boiler / Process Heater / Reciprocating Internal Combustion Engines (RICE) 

Maximum Achievable Control Technology (MACT) standards. The EPA issued final 

rules to substantially reduce emissions of toxic air pollutants from industrial, commercial 

and institutional boilers, process heaters and stationary RICE. These rules reduce 

emissions of a number of toxic air pollutants, including hydrogen chloride, manganese, 

lead, arsenic and mercury by 2009. This rule also reduces emissions of sulfur dioxide 

and particulate matter in conjunction with the toxic air pollutant reductions. The applied 

MACT control efficiencies were 4 percent for SO2 and 40 percent for PM10 and PM2.5. 

The EPA’s industrial boiler MACT rules were vacated on June 8, 2007. However, the 

EPA is required under the Clean Air Act to issue 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 these 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 projection 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 reductions were designed from Federal Register 

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

did not apply reductions for MACT standards with an initial compliance date of 2001 or 

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

inventories supplied by the States. 

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

inventories: 

1.1 Point Source Controls 

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

inventory: 

• For the EGUs, the State relied primarily 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 supplemented 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 inventories for a control scenario which accounts 

for post-2002 emission reductions from promulgated and 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 changes to the IPM results to better reflect current 

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

primarily involved state and local agency addition or subtraction of future emission controls 

based on the best available data from state rules, enforcement agreements, compliance plans, 

permits, and discussions/commitments from individual companies. 

Table 1-1 lists adjustments to IPM control determinations specified by state and local agencies 

for the EGU modeling inventories. Table 1-2 lists other 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 Determinations Specified by State and Local 

Agencies for the EGU Modeling Inventories. 

NOx Emission Controls SO2 Emission Controls 

State Plant Name and ID Unit 2009 2018 2009 2018 

IPM State IPM State IPM State IPM State 

AL James H. Miller 

ORISID=6002 

1 & 2 SCR 

during 

ozone 

season 

SCR 

probable 

yr round 

due to 

CAIR 

SCR 

during 

ozone 

season 

SCR 

probable 

yr round 

due to 

CAIR 

None None None None 

 3 & 4 SCR 

during 

ozone 

season 

SCR yr 

round 

from 

Consent 

Decree 

SCR 

during 

ozone 

season 

SCR yr 

round 

from 

Consent 

Decree 

None Scrubber None Scrubber 

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

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

 5 None None SCR SCR None None Scrubber None 

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

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

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

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

 10 SCR SCR SCR SCR None Scrubber Scrubber Scrubber 

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

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

GA Bowen 1BLR SCR SCR SCR SCR None Scrubber Scrubber 

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

 3BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber 

 4BLR SCR SCR SCR SCR 

IPM had 

retrofit 

scrubbers 

but little 

emission 

reductions 

Scrubber Scrubber Scrubber 

 Wansley 1 SCR SCR SCR SCR Scrubber Scrubber Scrubber 

 ORISID=6052 2 SCR SCR SCR SCR 

IPM had 

retrofit 

scrubbers 

but little 

emission 

reductions 

None Scrubber Scrubber 

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

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

 McIntosh 

ORISID=6124 

1 None None SCR None None None None None 

 Yates 1 None None None None Scrubber Scrubber Scrubber Scrubber 

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

 4 – 7 None None SCR None None None Scrubber None 
 Appendix H 

 Kentucky Regional Haze SIP 

9

Table 1-1 (continued). Adjustments to IPM Control Determinations Specified by State and 

Local Agencies for the EGU Modeling Inventories. 

NOx Emission Controls SO2 Emission Controls 

State Plant Name and ID Unit 2009 2018 2009 2018 

IPM State IPM State IPM State IPM State 

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 Scrubber Scrubber 

KY Ghent 1 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

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

 3, 4 None SCR SCR SCR None Scrubber Scrubber Scrubber 

 Coleman C1 None None SCR SCR None Scrubber Scrubber Scrubber 

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

 C3 None None SCR SCR None Scrubber Scrubber Scrubber 

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

 H2 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber 

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

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

 3 None None SCR SCR None Scrubber Scrubber Scrubber 

SC Jeffries 3 SCR None SCR None None None None None 

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

 Wateree WAT1 SCR SCR SCR SCR None Scrubber None Scrubber 

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

 Canadys CAN1 None None None None None None None None 

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

 CAN3 None None None None None Scrubber None Scrubber 

 Rainey CT1A None SCR None SCR None None None None 

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

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

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

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

 ORISID=3406 

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

 ORISID=3946 

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

 ORISID=3947 
 Appendix 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 (ORIS10333) is a duplicate entry. 

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

Removed IPM emissions for Central Power and Lime. 

 Cedar Bay Generating 

ORISID=10672 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. Cedar 

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

Replaced IPM emissions with 2002 emissions for Cedar Bay 

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

Container. 

 Indiantown Cogeneration 

ORISID=50976 

GEN1 FLDEP disagrees with IPM projections - no knowledge of 

expansion of this facility and the cogeneration facility 

should not grow faster than the underlying industry. 

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

0850002). Replaced IPM emissions with 2002 emissions for 

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

Louis Drefus Citrus. 

GA Bowen 

ORISID=703 

1BLR 

2BLR 

3BLR 

4BLR 

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

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect scrubbers on 1BLR and 

2BLR by 2009. 

 Wansley 

ORISID=6052 

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

the IPM emissions showed little reductions from 2002 

levels. Changed emissions to reflect one scrubber on Unit 1 

by 2009. 

 Riverside 

ORISID=734 

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

emissions set to zero in 2009 and 2018. 

 McIntosh 

ORISID=727 

CT10A 

CT10B 

CT11A 

CT11B 

The McIntosh Combined Cycle facility became commercial 

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

per unit to the 2009 and 2018 inventories. 

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

Development, Inc. GA specified that the emissions from this 

proposed plant be included in the 2018 projections. Boilers 1 

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

unit to the 2018 inventory. 

MS R D Morrow 

ORISID=6061 

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

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

their expected NOx emissions are actually higher than IPM. 

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

2009 inventory did not change. 

 Jack Watson (2049) 

Victor J Daniel (6073) 

Chevron Oil (2047) 

All MS DEQ specified that the emission projections provided by 

the Southern Company for their units in Mississippi were to 

be used instead of the IPM results. 
 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 results 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 results 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 Cogentrix 

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

inventories. 

 Kannapolis Energy 

Partners 

ORISID=10626 

GEN2 

GEN3 

Kannapolis Energy emissions are being used as credits for 

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

ORIS10626) were removed from the EGU inventory for 

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

3702500113) were carried forward in the 2009/2018. 

SC Cross 

ORISID=130 

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

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

Unit 2: upgrade scrubber from 70 percent to 87 percent 

removal efficiency by June 30, 2006. Recalculate emissions 

based on upgrade in control efficiency. 

 Winyah 

ORISID=6249 

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

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

lb/mmBTU by Dec. 31, 2008 

Unit 2: Replace scrubber with one that meets 95 percent 

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

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

2008 

Unit 3: Upgrade scrubber from 70 percent to 90 percent 

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

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

Unit 4: Upgrade scrubber from 70 percent to 90 percent 

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

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

Recalculated SO2 and PM emissions based on upgrade in 

control efficiencies. 
 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 PM10 and PM25 emissions in 2018 by 95 

percent based on change in allowable emission rate 

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

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

0.46/lbs/mmBtu and IPM heat input 

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

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

percent based on change in allowable emission rate 

SC Jeffries 

ORISID=3319 

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

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

94.44 percent based on change in allowable emission rate 

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

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

94.44 percent based on change in allowable emission rate 

 W S Lee 

ORISID=3264 

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

NOx control technology by April 30, 2006 to meet 0.27 

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

emissions using IPM heat input and 0.27 lbs/mmBtu 

 Generic Unit 

ORISID=900545 

All All predictions for generic units appear reasonable with the 

exception of Plant ID ORIS900545 Point ID GSC45 which 

was modeled in Georgetown County. It will be very difficult 

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

area. Santee Cooper has no plans for future generation in 

Georgetown County, but does have plans for new future 

generation in Florence County. This unit was moved to 

coordinates specified in Florence County. 

VA AEP Clinch River 

ORISID=3775 

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

and control estimates. 

 AEP Glen Lyn 

ORISID=3776 

51, 52, 

6 

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

and control estimates. 

 Dominion Clover 

ORISID=7213 

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

and control estimates. 

 Dominion Bremo 

ORISID=3796 

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

and control estimates. 

 Dominion Chesterfield 

ORISID=3797 

3, 4, 

5, 6 

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

and control estimates. 

 Dominion Yorktown 

ORISID=3809 

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

VADEQ’s growth and control estimates. 

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

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

heat input is zero. Dominion plans to continue to operate 

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

growth and control estimates. 
 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 IPM results using VADEQ’s growth 

and control estimates. 

 Dominion Possum Point 

ORISID=3804 

3 & 4 

5 

6 

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

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

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

in 2009 and 2018. 

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

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

estimates. 

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

growth and control estimates. 

 Potomac River 

ORISID=3788 

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

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

results using VADEQ’s growth and control estimates. 

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

VADEQ’s growth and control estimates. 

WV Albright 

ORISID=3942 

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

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

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

For 2018, used IPM prediction of retirement. 

 Rivesville 

ORISID=3945 

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

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

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

For 2018, used IPM prediction of retirement. 

 Willow Island 

ORISID=3946 

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

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

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

For 2018, used IPM prediction of retirement. 

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

controls will not be in place by 2009. 

 North Branch Power 

Station 

ORISID=7537 

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

Used SO2 Permit Rate of 0.678 lb/MMBtu and IPM 

predicted total fuel used to calculate SO2 emissions in 2009 

and 2018 

 Mt. Storm 

ORISID=3954 

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

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

total fuel used to calculate SO2 emissions in 2009 and 2018 

1.1.2 Non-EGUs 

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

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

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

 Kentucky Regional Haze SIP 

14

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

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

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

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

reasonably anticipated to result in post-2002 emission reductions. 

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

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

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

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

did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, 

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

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

initial compliance date of 2002 or greater. 

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

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

large internal combustion (IC) engines, which are primarily used in pipeline transmission service 

at compressor stations. We identified affected units using the same methodology as was used by 

EPA in the proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more 

than 1 ton per day during 2002). The final rule reflects a control level of 82 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 used instead of the default approach used by EPA in the proposed 

Phase II rule. 

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

projection inventories include: 

• Atlanta / Northern Kentucky / Birmingham 1-hr SIPs 

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

were 4 percent for SO2 and 40 for percent for PM10 and PM2.5 to account for the cobenefit from installation of acid gas scrubbers and other control equipment to reduce 

HAPs.

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

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

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

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

We reviewed the available State rules and guidance documents to determine the affected 

sources and ozone season allowances. 
 Appendix H 

 Kentucky Regional Haze SIP 

15

• Petroleum Refinery Initiative (October 1, 2003 notice; Mississippi & 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 settlements under the EPA Petroleum Refinery 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 plans where in place for one hour plans 

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

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

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

with EPA’s ESD staff. We did not apply reductions for MACT standards with an initial 

compliance date of 2001 or earlier, assuming that the effects of these controls are already 

accounted for in the 2002 inventories supplied by the States. 

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

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

inventory. 

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

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

1.2 Area Source Controls 

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

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

Duty Diesel (HDD) rulemaking emission projections and used in the CAIR projections were 

used to calculate controlled emissions. 

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

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

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

level between 2007 and 2020. 

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

measures submitted by KYDAQ include Stage I controls 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 inspection 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 the VISTAS region, but our presumption is that 

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

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

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

information on those plans. In the final implementation of the inventory, Stage II controls were 

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

refueling estimates are different between MOBILE6 and the NONROAD models. 

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

1.4 Non-Road 

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

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

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

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

the EPA's CAIR Technical Support Document. Using these data, combined growth and control 

factors for the period 2002-2009 and 2002-2018 were estimated using straight-line interpolation 

between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the 

State-county-SCC-pollutant level of detail. According to EPA documentation, the CAIR 

baseline emissions include the impacts of the Tier 4 (T4) non-road diesel rulemaking, which 

implements a low sulfur fuel requirement that affects both future CMV and locomotive 

emissions. 

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

1.5 Conclusion 

In conclusion of this discussion on source sector controls, Figures 1-1 through 1-4 depict 

pollutant totals for NH3, PM2.5, NOx, and SO2 for 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

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NH3 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW

0

20

40

60

80

100

120

140

160

180

200

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual PM-2.5 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 

2018 OTW
 Appendix 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

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU 2002 Typical

2009 OTW

2018 OTW

0

100

200

300

400

500

600

700

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW
 Appendix H 

 Kentucky Regional Haze SIP 

19

2.0 UNIFORM RATE OF PROGRESS 

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

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

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

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

monitoring data, the deciview values for the 20 percent best days in each year are averaged 

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

values for the 20 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 conditions 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, using 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 revised methods (Hand and Malm, 2006, Pitchford, 

2006). For more detailed discussion and comparison 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 uniform rate of progress (red line) to the predicted 

visibility from 2004 to 2018 due to modeled emission reductions expected by federal and state 

control programs during the first long-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

Year

Haziness Index (Deciviews)

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

Figure 2-1. CMAQ 2018 modeling results compared 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 impairment at each Class I area were identified, the 

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

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

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

Emissions sensitivities were initially conducted using 30% reductions 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 linearly responsive to changes in primary carbon 

and SO2, respectively, but nitrate and ozone chemistry 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 full benefit of controls anticipated by 2018 are not included in 

these sensitivity analyses. While the 2009 sensitivity analyses cannot be used to judge absolute 

contributions from each state or source sector, the results do indicate relative level of response 

among pollutants, sectors, and geographic areas. 
 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 run 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 implementing existing state and federal regulations 

(listed on page 2) for major source categories of SO2, NOx, and PM. The results identify 

geographic origins for visibility impairing pollutants, and serve as a good starting point when 

considering potential air quality benefits from additional controls for specific source sectors in 

VISTAS states or neighboring RPOs. The greatest benefits at Mammoth Cave in 2009 are 

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

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

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

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

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

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

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

vegetation is not possible or appropriate. 

Mammoth_Cave, KY (Summer)

-18.00

-16.00

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_

Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

Δ

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 3-1. Summertime sensitivity results for 2009 emissions– Mammoth Cave, Kentucky. 

Several states contribute to modeled reductions in SO4 at Mammoth Cave on the 20% worst 

days modeled in these two episodes in response to further reductions in 2009 SO2 emissions 

from EGUs (Figure 3-2). For this sensitivity run, further reducing SO2 emissions from 
 Appendix 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 Cave. In addition, benefits are projected from 

SO2 reductions from EGUs in several VISTAS states. Approximately, one third of the benefit at 

Mammoth Cave would come from further SO2 emission reductions from outside VISTAS. 

AL

FL

GA

KY

MS

NC

SC

TN

VA

WV

CEN

M-VU

MRPO

BCs

Utility Contributions, by State and Region, to SO4 at Mammoth Cave, KY,

Using 2009 Emissions and CMAQ model run for June 2002 

9%

1%

7%

23%

2%

2%

13% 3%

1%

3%

9%

1%

16%

10% AL

FL

GA

KY

MS

NC

TN SC

VA

WV

CENRAP

MANE-VU

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 ammonia emissions could be more 

beneficial for reducing ammonium nitrate contributions to visibility impairment than further 

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

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

reductions in SO2 emissions. 
 Appendix H 

 Kentucky Regional Haze SIP 

23

Mammoth_Cave, KY (Winter)

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_

Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

Δ

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

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

3.2 Summary 

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

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

further reductions in SO2 emissions from electric generating utilities would be most beneficial 

for visibility at VISTAS Class I areas, followed by SO2 reductions from industrial point sources. 

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

have little benefit to visibility. Controlling anthropogenic sources of VOC would not be 

effective in improving visibility in winter. In wintertime controlling ammonia emissions would 

be more effective in reducing ammonium nitrate than controlling nitrogen oxide emissions. 
 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 identify the geographic source 

regions that are contributing to visibility impairment at the Class I areas on the 20 percent worst 

visibility days. This information will be used by the State as part of the evaluation and 

demonstration of reasonable progress toward visibility improvement in Class I areas. 

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

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

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

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

than 70% of the calculated light extinction at Class I areas in the inland sites and greater than 

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

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

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

somewhat larger contribution on 20 percent worst days at Class I areas in neighboring states to 

the VISTAS region.) Particulate organic matter (organic 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 percent Worst Visibility Days in 2000-2004 using 

New IMPROVE Equation (data from VIEWS Sep 2006). 

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

CADI1

BRIG1

BRET1

MING1

HEGL1UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm -1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

CADI1

BRIG1

BRET1

MING1

HEGL1UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm -1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh
 Appendix H 

 Kentucky Regional Haze SIP 

25

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

reductions in SO2 emissions from Electric Generating Utilities (EGU) and non-EGU industrial 

point sources will result in the greatest improvements in visibility at VISTAS Class I areas. EGU 

and non-EGU industrial point sources comprise 95+% of the SO2 emissions inventory in the 

VISTAS states. The emissions sensitivity analyses also indicate that improvements in visibility 

from reductions in NOx or primary carbon emissions from ground- level sources or point sources 

would be small. Based on these analyses, VISTAS states chose to focus their reasonable 

progress evaluation for the first regional haze SIP on potential controls of SO2 emissions from 

EGU and non-EGU point sources. To select the specific point sources that would be considered 

for each Class I area, states first identified the geographic areas that most likely influence 

visibility in each Class I area and then identified the major SO2 point sources in that geographic 

area. 

4.2 Source Type Analyses 

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 remaining 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 greatest impact on each Class I area. Initial focus on 

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

extinction on the haziest days. In fact, figure 4-2 shows that for the inland areas (Mammoth 

Cave), SO4 contributes 78% to the calculated light extinction on the haziest days. To better 

understand the sources that should be considered in a four factor analysis for reasonable 

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

Air Resource Specialists (ARS), to provide SO2 Areas of Influence for each VISTAS and six 

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

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

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

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

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

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

transformation and dispersion of emissions. 

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

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

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

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

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

archives. 

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

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

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

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

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

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

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

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

Model Parameter Value 

Trajectory duration 72 hours backward in time 

Top of model domain 14,000 meters 

Vertical motion option used model data 

Meteorological Field EDAS 

End Times 0600, 1200, 1800 and 2400 EST 

End Heights 100 and 500 m 

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

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

 Kentucky Regional Haze SIP 

27

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

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

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

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

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

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

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

sampling sites in and around the VISTAS region: 

1. Breton, LA (BRET1) 

2. Brigantine NWR, NJ (BRIG1) 

3. Cadiz, KY (CADI1) 

4. Caney Creek, AR (CACR1) 

5. Cape Romain NWR, SC (ROMA1) 

6. Chassahowitzka NWR, FL (CHAS1) 

7. Cohutta, GA (COHU1) 

8. Dolly Sods Wilderness, WV (DOSO1) 

9. Everglades NP, FL (EVER1) 

10. Great Smoky Mountains NP, TN (GRSM1) 

11. Hercules-Glades, MO (HEGL1) 

12. James River Face Wilderness, VA (JARI1) 

13. Linville Gorge, North Carolina (LIGO1) 

14. Mammoth Cave NP, KY (MACA1) 

15. Mingo, MO (MING1) 

16. Okefenokee NWR, GA (OKEF1) 

17. Shenandoah NP, VA (SHEN1) 

18. Shining Rock Wilderness, NC (SHRO1) 

19. Sipsy Wilderness, AL (SIPS1) 

20. St. Marks, FL (SAMA1) 

21. Swanquarter, NC (SWAN1) 

22. Upper Buffalo Wilderness, AR (UPBU1) 

Figure 4-2 shows the 72-hour back trajectory analysis 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 trajectories, ARS generated extinction-weighted 

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

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

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

horizontal grid cells of latitude and longitude. 

Extinction data is based on the IMPROVE Regional Haze Rule 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 original IMPROVE algorithm. For sites with less 

than three complete years of data, ARS developed and applied a data substitution protocol to fill 

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

hydrogen and sulfate values for the same site. Other components were filled based on data from 

nearby sites. 

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

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

(POM), Light Absorbing Carbon (LAC), Soil, and Coarse Mass (CM). 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 identified 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 charged with developing 

residence time plots to define the geographic area with 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 since it does not account for emissions and removal 

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

compounds at a receptor site. 

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 time plots were provided by ARS for all Class I 

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

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

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

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

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

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

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

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

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

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

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

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

Using the trajectories with the 100-m start height, the State has defined the SO2 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 sulfate) for the period 2000-2004. Residence time 

over an area is indicative of general flow patterns, but since it does not account for emissions and 

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

compounds at a receptor site. 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-weighted residence time plots for the period 

2000-2004. 

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

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

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

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

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

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

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

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

Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory 

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

visibility days and that electric generating utilities and industrial point sources are the largest 

contributors to SO4 levels at the Class I areas. These two source categories make up 95% of the 

VISTAS SO2 inventory. Therefore these two source categories were identified as the highest 

priority for evaluation of reasonable progress in 2018 at the Class I areas. 

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

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

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

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

VISTAS modeling databases, for 2002 and 2018, respectively. These data were processed by 
 Appendix 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 transport, deposition, and chemical transformation of 

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

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

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

point source SO2 emissions are then combined with the gridded extinction-weighted backtrajectory residence times at a spatial resolution of 36-km. 

The final step in the development of the displays 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 basis. These results are then 

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

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

analysis step. Note that the outlined regions (in red and light orange) represent the extent of the 

>10% and >5% sulfate extinction-weighted residence times, determined from the first step in the 

analysis (see Figure 4-6). As with the residence time analysis, the results of the combined 

distance-weighted SO2 emissions and extinction-weighted residence times are overlayed with 

county boundaries and exported to comma-delimited ASCII data files for further analyses of 

emissions 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 the 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 

2002 SO2 emissions 2018 SO2 emissions

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

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

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

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

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

gridded SO2 emissions and defined 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 areas indicate that the areas of probable influence 

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

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

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

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

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

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

from the Class I area can contribute to visibility impairment on some 20 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 considered, 37% of NOx is from point 

sources, 23% is from highway vehicles, and 21% is from nonroad engines. Elevated organic 

carbon (OC) and elemental carbon (EC) are indicators of fire. Some states may need to consider 

emissions from residential wood burning, forest fires (wild and prescribed), land clearing, and 

agricultural burning. 
 Appendix H 

 Kentucky Regional Haze SIP 

35

Nitrate (NH4NO3) levels in winter can be significant 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 percent worst visibility days, the KYDAQ believes 

it is appropriate to focus on SO2 reductions in this first Regional Haze SIP. 

4.6 Summary of Emission Inventories Used in Cost Curve Analysis 

A necessary component of control strategy design is a thorough review of the emission 

inventories that are used in the modeling of the future year base case. These inventories can shed 

light on the residual emissions from sources or source categories defined to be within areas of 

transport or impact of a Class I area. 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 were provided for all sources with emissions over 

distance (Q/d) greater than 5 and maximum residence time (RTmax) greater than 5. States 

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

for reasonable control measures. 

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

cases were obtained from VISTAS emissions development and modeling contractors and 

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

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

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

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

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

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

scale modeling analyses. 

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

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

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

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

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

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

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

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

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

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

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

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

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

BaseG Annual Emissions - 2002 Typical (Tons)
 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 starting with an analysis of the major source 

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

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

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

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

extinction weighted analysis, these emission reviews and summaries like those presented in 

Figure 4-9, VISTAS made a decision to further review only point source controls in increment to 

the Clean Air Act scenario. 

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

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

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

under the future year base case had the potential for reduction 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 States to review existing emission reductions 

and providing the ability to assign new cost-effective controls to units using the best control for 

the scenario. These tables presented comparisons 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-specific 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 VOC NOx CO SO2 PM-10 PM-2.5 NH3

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

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

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

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

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

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

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

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

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

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

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

BaseG Annual Emissions - 2018 Base Case (Tons)
 Appendix H 

 Kentucky Regional Haze SIP 

37

Figure 4-9. VISTAS SO2 Emissions Contribution by Major Source Sector. 

4.7 Process in Preparing Files for Cost Effectiveness Curve Development 

The 2018 IPM file used by VISTAS for EGU sources (RPO 2.1.9) was obtained and matched to 

the 2018 base case inventory of EGU sources. This step was conducted to ensure that 

incremental controls assigned to these source types did not duplicate existing base case 

assumptions. Because IPM does not assign a control efficiency with each control device applied 

to SO2 and NOX, we made some assumptions, based on IPM documentation, as to what pollutant 

specific level of reduction was applied in the future year base case runs. These assumptions, by 

primary and secondary control device code combinations for SO2, are presented in Table 4-5. 

Since many of the control technology control cost equations within AirControlNET require 

additional unit-level characteristic data, we also 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 calculations for many of the SO2 applied technologies. In cases 

where these nameplate capacity values could not 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 cross-reference available incremental control 

technologies to the base case emissions inventory data. These variables were obtained where 

matches could be found, in priority order of VISTAS, CAMD, and other EPA datasets, 

respectively. 

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

West Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

West Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018
 Appendix H 

 Kentucky Regional Haze SIP 

38

Table 4-5. IPM Post Processing Assigned Device Codes and Applied SO2 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 tool developed to support the U.S. EPA in its 

analyses of air pollution policies and regulations (Pechan, 2005). The tool provides data on 

emission sources, potential pollution control measures and emission reductions, and the costs of 

implementing those controls. 

The core of AirControlNET 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 applicability, efficiency, and cost information for reducing the emissions contributing to 

ambient concentrations of ozone, PM10, PM2.5, SO2, NOX, as well as visibility impairment 

(regional haze) from point, area, and mobile sources. PM10 and PM2.5 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 100
 Appendix 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 preprocessed application of control 

technologies to a predetermined set of EPA emission inventories, direct use of the model in this 

analysis was not possible. However, Alpine received approval from EPA’s Innovative Strategies 

and Economics Group (ISEG) to modify the AirControlNET version 4.1 source code (Sorrels, 

2006) and data tables in order to make it useful to this study. The 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 code, but were applied to the VISTAS modeling 

inventories with updated price index scalars to reflect control costs in 2005-dollars. 

Using the modified inventories identified above, 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, incremental control strategies for the entire VISTAS 36 km domain 

necessary for VISTAS states to design command-and-control or cost-effectiveness based control 

strategies by source or domain. 

4.9 Development of AOI-Based Cost Curves 

Each Class I area in the VISTAS modeling domain had an associated AOI as identified earlier in 

this document. In order to best determine where emission reduction has the greatest benefit, this 

geography was designed to limit the available source type list from including all sources within 

the entire domain. 

These marginal cost curves include the application of all available control measures to all 

applicable point sources within the AOI. The curves will allow VISTAS States to determine if, 

based on the generic application of SO2 control technologies from the associations originally 

developed in AirControlNET and improved upon with 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 the boundaries of the AOIs. This parsed list was 

then sorted by incremental cost-effectiveness (marginal cost) basis to determine the most cost 

effective control suite available to attain emission reduction targets for SO2 within each AOI. 

Each individual source had its own cost 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 analysis. An illustrative example of the steps 

involved with the cost effectiveness curve design 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 distance (Q/d^2), and the normalized 2018 SO2 point source emissions 

times distance-weighted residence time (RTMax) values for the county in which the emission 

release point was located were calculated for incremental review and consideration. The 

KYDAQ used these values to further determine control strategy development 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 consider for further controls. VISTAS developed source 

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

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

Spreadsheets were developed for each Class I area with: 

• Plant name 

• Point ID 

• Tons SO2 projected for 2018 

• Q (tons) 

• Current control efficiency, CE (%) 

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

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

• 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/d2

 is more representative when d is less 

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

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

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

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

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

RT max was equal to or greater 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/d2

 > 0.03 when d 

was less than 20 km, and Q/d > 5 or Q/d2 > 0.03 when d was 20-100 km (these values were 

chosen arbitrarily to limit the number of sources on the list and focus on those that are most 

influential). 

Next, the KYDAQ elected to focus on those units that 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 would likely show an environmental benefit under a 

control evaluation, and KYDAQ would be able to use that environmental benefit to require 
 Appendix H 

 Kentucky Regional Haze SIP 

41

controls on a given unit. Second, there are several regulatory 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 visibility air quality related value. 

2. The NOx SIP Call laid out a significance level for Section 126 petitions 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 are 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 periods for the criteria pollutants, KYDAQ determined that the one 

percent threshold we were proposing for reasonable further progress was as protective or more 

protective than the significant impact levels. The most restrictive threshold identified was for 

NOx, which has a NAAQS of 100 ug/m3 and a significance 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 neither sufficient time or resources available to 

evaluate all units within a given AoI. Therefore, a threshold needed to be established to 

determine which units would be evaluated. Table 5-1 shows that a 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 total SO2 emissions contributing to visibility 

impairment at the Class I area. KYDAQ believes the 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 SO2 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 percent contribution spreadsheets for VISTAS, 

CENRAP and other Class I areas are available in Appendix H.2. 

Table 5-2. Mammoth Cave Q/d, Q/d^2, RTMax, and fractional contribution 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 002 7,941 90 75.45 105.25 1.39 35.87 0.039

Kentucky TVA PARADISE STEAM PLANT 001 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 RIVER 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 RIVER 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 004 5,383 0 128.51 41.89 0.33 25.48 0.011

Indiana PSI ENERGY - GALLAGHER 001 5,383 0 129.50 41.57 0.32 25.48 0.011

Indiana PSI ENERGY - GALLAGHER 003 5,309 0 128.51 41.31 0.32 25.48 0.011

Indiana PSI ENERGY - GALLAGHER 002 5,285 0 129.50 40.81 0.32 25.48 0.011

Spreadsheets were developed for each Class I area source with Q/d > 5 or Q/d2

 > 0.03, indicating 

the plant name, industry description, emissions projections for 2018, current control efficiency 

(CE%), distance from Class I area, Q/d, Q/d2

, RT average, RT maximum, Q/d*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 which facilities are already controlled by what 

percent and which may be controlled further. 

Next, an analysis of control options, generic costs of controls, and "Cost/ton" for various units 

contributing greater than one percent to any Class I area was developed. Spreadsheets 
 Appendix 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 cost (in 2005 dollars), and cost per ton reduced 

for application of specific control measures. 

KYDAQ reviewed the sources, emissions, control options, 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 combustion from industrial sources, with little 

contribution from other sources. Therefore, KYDAQ eliminated other source categories from 

the Four Factor Analysis. KYDAQ next looked at source-specific costs, existing controls, 

remaining useful life, environmental and energy impacts. 

6.0 FOUR FACTOR ANALYSIS 

Section 169A(g)(1) of the Clean Air Act (CAA) and 40 CFR 51.308(d)(1)(i)(A) outline four 

statutory factors that have been identified as mandatory for purposes of establishing a reasonable 

progress goal for any mandatory Class I area within a State: cost of compliance, time necessary 

for compliance, energy and non-air quality environmental impacts of compliance, and remaining 

useful life of any existing source subject to such requirements. These statutory factors would be 

specific to the sources being considered for additional controls. Kentucky sent December 22, 

2005, letters to several Kentucky sources providing them with EPA’s November 28, 2005, 

“Draft Guidance for Setting Reasonable Progress 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 available 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 compliance costs for sources are 

reasonable compared to the emission reduction and visibility improvement they will achieve. 

Note that visibility improvement is not only related to tons of pollutant removed, but also 

involves how the pollutant or chemical compound affects the extinction coefficient in each Class 

I area. For example, on a pound to pound comparison, sulfate particulate impairs visibility 

greater than coarse particulate. Costs should be determined for one-time capital costs, as well as, 

ongoing annual operation and maintenance. 

6.1-2 Time Necessary for Compliance

The “time necessary for compliance” factor may be used to adjust the reasonable progress goals 

to reflect the degree of improvement achievable within the long-term strategy period, as opposed 

to the improvement expected at full implementation of a control measure, if the time needed for 

full compliance exceeds the length of the long-term strategy period. For instance, if 

implementation of a control measure could not be completed within the schedule outlined by the 
 Appendix H 

 Kentucky Regional Haze SIP 

44

control strategy, the RPG should reflect what visibility improvement could be expected within 

the strategy period. 

For example, if construction labor availability constraints preclude the installation of controls at 

all sources of a particular category within the LTS period, the RPG should reflect the visibility 

improvement anticipated from installation of controls at the percentage of sources that could be 

controlled within the strategy period. (The SIP could still include control strategies that extend 

beyond the 2018 milestone; in the above example, the visibility improvement anticipated from 

installation of controls at the percentage of sources that could not be controlled within the first 

strategy period would have to be counted in a later SIP). 

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

The “energy and non-air quality environmental impacts of compliance” factor is meant to 

consider whether the energy requirements of the control technology result in energy penalties or 

benefits. For example, controls on diesel engines may decrease the overall efficiency and require 

a significant increase in diesel fuel consumption. The State should also consider any significant 

or unusual non-air environmental impacts, such as a waste stream that may be generated by a 

particular control technology 

6.1-4 Remaining Useful Life of the Source 

The statutory factor of the “remaining useful life of the source” is applicable only to those 

measures, which would require retrofitting of control devices (or possibly production changes) at 

existing sources. In such cases, this factor should be treated as one element of the overall cost 

analysis. For purposes of this analysis, the remaining useful life is the difference between the 

year of the reasonable progress analysis and the date the facility permanently stops operations. 

The remaining useful life of a source affects the annualized costs of retrofit controls. 

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

Influence 

The next step was to identify emission reductions that have already occurred within each source 

category and at specific units. Unit level tables of emission comparisons from 2002 to 2018 

were developed, allowing VISTAS states to review existing emission reductions. These tables 

assigned future year control technology from IPM forecasting and State modification for EGU 

and from control efficiency tables for Non-EGU point sources. 

Once emission control profiles for specific units were defined, the next step is to determine what, 

if any, additional control measures would feasibly be available, and to assign costs to those 

control measures. 

For EGUs, the 2018 IPM file used by VISTAS for EGU sources was obtained and matched to 

the 2018 base case inventory of EGU sources. This step was conducted to ensure that 

incremental controls assigned to these source types did not duplicate existing base case 

assumptions. 
 Appendix H 

 Kentucky Regional Haze SIP 

45

For non-EGUs, VISTAS used EPA’s AirControNET database, modified for the VISTAS 

emission inventories. The core of AirControlNET 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 applicability, 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 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 distance (Q/d^2), and the normalized 2018 SO2 point source emissions times distanceweighted residence time (RTMax) values for the county in which the emission release point was 

located. Kentucky evaluated these control measures and costs as part of their review of the 

statutory factors for reasonable further progress. 

The Regional Haze Rule requires that states consider the following factors and demonstrate how 

these factors were taken into consideration in selecting the reasonable progress goal: 

• the costs of compliance 

• the time necessary for compliance 

• the energy and non-air quality environmental impacts of compliance, and 

• the remaining useful life of any potentially affected sources. 

6.2-1 Cost of Compliance 

As defined in Section 7.5.5, coal-fired electric utilities and coal-fired 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 using oil and commercial and institutional boilers 

using coal or oil had small contributions to SO2 in 2018. 

Sulfur dioxide emissions from utility, industrial, commercial, or institutional boilers can be 

controlled either by switching the fuel source to a lower sulfur fuel content or by installing postcombustion controls. Costs vary by fuel source and boiler type and require source specific 

analyses for accuracy. 

Bituminous coal is commonly burned 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 that are designed for bituminous coal, only a small 

fraction of the fuel can be switched to low sulfur sub-bituminous coal without affecting boiler 
 Appendix H 

 Kentucky Regional Haze SIP 

46

operations. Costs of boiler modifications to accommodate low sulfur sub-bituminous coal may 

make switching to sub-bituminous coal impractical. Contract initiation and termination costs, 

differential fuel prices and heat rates, transportation costs, and modification to boiler operations, 

fuel handling and waste handling systems will have to be considered specific to each source. 

Flue-gas desulfurization is the common post-combustion control for coal-fired boilers. Flue gas 

is passed through an absorbent for sulfur dioxide (generally limestone or lime) in either a wet 

scrubber, dry scrubber, or spray dryer. A calcium sulfate byproduct is produced that may be 

further processed to produce gypsum as a commercial byproduct. Costs of flue-gas 

desulfurization include initial construction costs and ongoing operational and maintenance costs 

for the absorber tower, sorbent handling, and waste product handling facilities. Costs per ton 

vary with boiler size, type, and facility siting considerations. 

For oil-fired boilers, lower sulfur oil may be an option. Costs need to consider differential fuel 

prices and heat rate, boiler modifications, fuel handling costs, and maintenance costs. 

Conceptually, post-combustion controls can be used for oil boilers, but there is little precedence 

for such installations. 

6.2-2 Time Necessary for Compliance 

For fuel switching, the time necessary to terminate existing fuel contracts and initiate new 

contracts needs to be considered. Generally two to three years may be required. Instillation of 

post-combustion controls will require 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 additional safeguards for fuel 

handling and waste handling systems to avoid additional non-air environmental impacts such as 

increased effluents in waste water discharges and storm water runoff. These factors will need to 

be considered specific to individual sources. Carbon dioxide is emitted as a byproduct of flue gas 

desulfurization, therefore impacts of increased carbon emissions will need to be considered, 

particularly if carbon emissions are limited in the future under climate change mitigation 

strategies. 

6.2-4 Remaining Useful Life 

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

6.3 Process of Applying Statutory Factors 

The KYDAQ has just completed the Reasonable Progress 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 percent of the visibility impairing pollution. The 

VISTAS States concluded that controlling SO2 emissions was the appropriate step in addressing 

the reasonable progress assessment for 2018. The VISTAS findings were consistent with the 

findings of the Southern Appalachian Mountain Initiative (SAMI). As you may recall, SAMI 

confirmed that sulfate particles account for the greatest portion of the haze affecting Class I areas 

in the Southern Appalachian region and that these sulfates were produced in large part from SO2 

emissions from coal combustion. 

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

Since SO2 point source emissions in 2018 are projected to represent greater than 95 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 approximately 495,152 tons per year) and 2018 (2018 

emissions approximately 226,062 tons per year). Much of that reduction is the result of 

requirements that are predicted by the IPM to meet 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 reasonable progress, a discussion in 

the CAIR rule highlighted below (See Appendix 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 reasonable progress analysis that must 

accompany a state’s assertion that CAIR is sufficient for reasonable progress for subject EGU’s 

during the first planning period. 

From past experience in examining multi-pollutant 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 reductions are quite significant 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 while managing an already large debt load, and 

is facing other large capital requirements to improve the transmission system. 

Furthermore, allowing pollution control retrofits to be installed over time enables the 

industry to take advantage of planned outages at power plants (unplanned outages can 

lead to lost revenue) and to enable project management to learn from early installations 
 Appendix 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 determined in the NPR that the earliest 

reasonable deadline for compliance with the final highly cost-effective control levels for 

reducing emissions was 2015 (taking into consideration 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 emissions caps for 2015 lead to highly costeffective controls for the CAIR region. 

Once EPA determined the 2015 emissions reductions 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 phase commences in 2009 instead of in 2010, 

as explained in detail in section IV.C). The first phase would be the initial step on the 

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 emission control retrofits, as described in section IV.C. 

Although EPA's primary cost-effectiveness determination is for the 2015 emissions 

reductions levels, the Agency also evaluated the cost effectiveness of the first phase 

control levels to ensure that they were 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 levels were determined based on feasibility 

rather than cost effectiveness. The 2015 emissions reductions include the 2010 (and 2009 

for NOX) emissions reductions as a subset of the more stringent requirements that EPA is 

imposing in the second phase. 

The KYDAQ intends to re-evaluate the IPM predictions of SO2 reductions for CAIR at the time 

of the next periodic report in 2012 to ensure that the reductions currently predicted by IPM for 

CAIR are in fact taking place where they were expected and needed. If KYDAQ’s assessment 

for the periodic report indicates that 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, required 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 for 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 fractional contribution from all emission units within the SO2 Area 

of Influence for a given Class I area and identified those emission 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 can 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 was 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 compliance, and 4) the remaining 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 controls 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 equitable to require Non-EGUs to bear a greater 

economic burden than EGUs for a given control strategy. The KYDAQ used EPA’s CAIR EGU 

cost analysis to establish a cost/ton of SO2 removed 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 threshold. 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-factor 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 marginal cost for both years at $2000 per ton, 

which KYDAQ believes establishes an appropriate threshold against which cost-effectiveness 

may be evaluated for reasonable progress. During the current reasonable 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 from the following facility contributed one 

percent or more to visibility impairment in a Class I area, and therefore 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 impacting Class I areas located 

outside of the Kentucky, as well as what sources 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, with a one percent or more contribution for the 

Mammoth Cave area of influence. KYDAQ sent letters to Indiana and Tennessee 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 addressed by CAIR (See copies of the letters in 

Appendix J). In addition, based on the KYDAQ Q/d times RTMax analysis, no Kentucky 

sources were identified with a contribution of one percent or more to the visibility impairment at 
 Appendix 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 areas of concern. Alpine used EPA’s AirControlNet software to 

evaluate control options and costs for controls. The SO2 control suggested by the VISTAS 

control cost spreadsheet for Century Aluminum is a sulfuric acid plant at a cost of $14,207, 

$23,020, and $43,281 per ton of SO2 removed for potlines 1-4, potline 5, and the anode baking 

furnace respectively (See the VISTAS SO2 control cost spreadsheet for Century Aluminum in 

Appendix H.6). Therefore, since the cost of compliance for the control option ranges from 7 to 

22 times greater than the cost-effectiveness threshold, the KYDAQ concludes 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 Non-Air Impacts, and Remaining Useful Life 

 The three remaining statutory factors: 1) time 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 final 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 visibility-impairing air pollutant, were placed in operation 

between August 7, 1962 and August 7, 1977, and whose operations fall within one or more of 26 

specifically listed source categories. Under the CAA, BART is required for any BART-eligible 

source that a State determines ‘‘emits any air pollutant which may reasonably be anticipated to 

cause or contribute to any impairment of visibility in any such area.’’ Accordingly, for stationary 

sources meeting these criteria, States must address the BART requirement when they develop 

regional haze SIPs. The EPA has set guidance for identifying BART-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 impairment. Although the appropriate threshold may vary, the EPA’s 

guidance states that the contribution threshold used 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 impairment. 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 States should include SO2, NOx, and direct particulate matter (PM) 

emissions, including both PM10 and PM2.5, in determining whether sources cause or contribute 

to visibility impairment. States may use their best judgment to determine whether VOC or 

ammonia emissions are likely to have an impact on visibility in an area.

Sources that are subject to BART must undergo a BART determination. Section 169A(g)(7) of 

the CAA requires that States must consider the following factors in making BART 

determinations: (1) The costs of compliance, (2) The energy and non-air quality environmental 

impacts of compliance, (3) Any existing pollution control technology in use at the source, (4) 

The remaining useful life of the source, and (5) The degree of improvement in visibility which 

may reasonably be anticipated to result from the use of such technology. 

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 identified with BART-eligible sources. Of these 

twenty-six BART-eligible facilities, twenty-one were exempted 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 protocols and subsequent modeling demonstrations 

based upon the VISTAS modeling protocol. Modeling of nine Kentucky BART-eligible sources 

was conducted by VISTAS contractor using the VISTAS common protocol. The site-specific 

protocols are found in Appendix L.5 and the exemption modeling demonstrations 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 facilities and addressed before the modeling was 

conducted. The individual source BART exemption modeling demonstrations are being 

provided to EPA and the FLMs with this Regional Haze SIP. 

KYDAQ staff reviewed the exemption demonstrations to determine whether the sources have 

less than 0.5 deicview (dv) impact on any Class I area within 300 km of the source. Sources 

demonstrating less than 0.5 dv impact are considered exempt. Sources contributing 0.5 dv impact 

or greater are considered subject to BART and were required to proceed to conduct BART 

determination modeling to determine what control measures, if any, constitute BART for the 

source. 

Five EGU sources were found to be subject to BART based on their BART exemption modeling. 

KYDAQ reviewed the proposed BART determination modeling results and has concurred with 

the findings that BART, for the five subject sources, are the controls the sources’ recommended 

in consideration of applicable consent decrees. All five facilities will install emission controls to 

address condensible particulates, except the controls installed for TVA Paradise 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 Haze 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 STRATEGY AND REASONABLE PROGRESS 

GOALS 

As stated in section 2.0 above, the regional haze rule requires States to establish reasonable 

progress goals, expressed in deciviews, for visibility 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 section discusses development of Kentucky’s longterm strategy. 

8.1 Long-Term Strategy 

Ammonium sulfate is the most important contributor to visibility 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 for an estimated 78 percent of the visibility 

impairment at Mammoth Cave. Across the VISTAS region, sulfate levels are higher at the 

inland sites than at the coastal sites. On the 20 percent clearest days, sulfate levels are more 

uniform across the region. Reduction of SO2 emissions 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 point sources. Thus, the long-term strategy for this 

first Regional Haze SIP focused on reductions in SO2 emissions. 

There are significant control programs in place in Kentucky and the region to reduce SO2 

emissions between the baseline period and 2018. Most notably, CAIR is predicted to result in 

greater than eighty percent reduction from EGU SO2 emissions in Kentucky. Overall the SO2 

emissions in Kentucky are predicted to decrease from 2002 levels at 495,152 tons per year to 

226,062 tons per year in 2018. Such large SO2 reductions are predicted to result in significant 

improvements in visibility. Kentucky’s CAIR rules are available as Appendix H.7. It should be 

noted that many of Kentucky’s EGUs had SO2 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 decree and BART, Kentucky has concluded 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 available in Appendix H.4. 

At Kentucky’s Class I area, visibility improvements on the 20 percent worst days are expected to 

be better than the uniform rate of progress glidepath by 2018 based solely on reductions from 

existing and planned emissions controls. For example, at Mammoth Cave National Park, a 4.7 

deciview improvement in visibility would meet uniform rate of progress in 2018; expected 

emissions reductions by 2018 are projected to achieve a 5.8 deciview improvement. In fact, 

visibility improvements at all VISTAS inland Class I areas and most of the coastal Class I areas 

are projected to be better than the uniform rate of progress. The percentage of the target 
 Appendix H 

 Kentucky Regional Haze SIP 

53

reduction achieved for the Mammoth Cave is 123 percent. This means that the rate of 

improvement is 23 percent greater than the uniform rate of progress by 2018. 

In addition to improving visibility on the 20 percent worst visibility days, states are also required 

to protect visibility on the 20 percent best days at the Class I areas. Visibility on the 20 percent 

best days is projected to improve in 2018 at all VISTAS Class I areas as a result of the 2018 

emissions reductions. The percentage of the target achieved for the Mammoth 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 percent improvement (values lower than current 

conditions.) 

The KYDAQ completed a reasonable progress assessment after modeling the Clean Air Act 

controls discussed above. The assessment did not identify any cost effective control measures 

for the SO2 non-EGU units that contributed greater than one percent to visibility impairment at 

the Class I area in Kentucky or in neighboring States. The KYDAQ concluded 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 Were Considered as Part of the Long-Term 

Strategy for Visibility Improvement by 2018? 

Section 308(d)(3)(v) of the regional haze rule lists several factors that must be addressed in each 

SIP. These factors include the role of fire at Class I areas and status of state planning for smoke 

management, the role of dust and fine soil at Class I areas and status of state plans to mitigate 

emissions from construction activities, and the role of NH3 and potential benefits if emissions 

from agricultural sources were mitigated. 

As discussed in Section 4.1 and demonstrated in Figure 4-1, elemental carbon (sources include 

agriculture, prescribed wildland fires, and wildfires) is a infrequent contributor 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 burning 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, provides additional support to aid the Commonwealth 

with meeting its RPGs for this first planning 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 Georgia Tech sensitivities, a significant amount of 

ammonia emissions comes from outside of Kentucky (See Figure 3-3). Kentucky, per its CMAQ 
 Appendix 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 will lessen the formation of Ammonium sulfate, (NH4)2SO4 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 progress 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 consider incorporating these findings in 

the final SIP, including revising reasonable progress 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 necessary. Furthermore, if the addition of some 

additional controls or changes in a final VISTAS model run does 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) requires a State to establish reasonable progress 

goals for each Class I area within the state (expressed in deciviews) that provide for reasonable 

progress towards achieving natural visibility conditions by 2064. In addition, the USEPA 

released guidance on June 7, 2007 to use in setting reasonable progress goals. The goals must 

provide improvement in visibility for the most impaired days, and ensure no degradation in 

visibility for the least impaired days over the SIP period. 

In accordance with the requirements of 40 CFR 51.308(d)(1), this Regional Haze SIP establishes 

reasonable progress goals for the Class I area in Kentucky. The KYDAQ compared baseline 

visibility conditions to natural visibility conditions in the Class 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 estimated 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 modeling 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 KYDAQ will not include the results of this final 

modeling run in its final SIP submittal due to timing and since the results provide reasonable 

progress goals that are very similar and as favorable to the ones presented in this section. The 

VISTAS baseline modeling has already demonstrated 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 the period of the implementation plan and ensures 

no degradation in visibility for the least impaired days over the same period. 

 
 Appendix H 

 Kentucky Regional Haze SIP 

55

Table 8-1 contains the reasonable progress goals for this planning 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 rate 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 greater difficulty accurately projecting small 

concentrations. On the 20% best days, the model does not meet VISTAS model performance 

goals or criteria for sulfate, nitrate, and coarse mass (under predicted) and soil (over predicted), 

however, the organic carbon and elemental carbon 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 Reasonable 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) 14.48 
 Appendix 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 Particulate Matter and 

Visibility across Monitoring Networks in the Southeastern United States. J Air and Waste 

Management Association, 55, 1663-1674. 

3. Federal Register / Vol. 70, No. 128 / Wednesday, July 6, 2005 / Rules and Regulations. 

4. Hand, J.L.; and Malm, W.C.,2006, Review of the IMPROVE Equation for Estimating 

Ambient Light Extinction Coefficients - Final Report. March 2006. Prepared for 

Interagency Monitoring of Protected Visual Environments (IMPROVE), Colorado State 

University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO. 

5. MACTEC, 2006, Documentation of the Base G 2002 Base Year, 2009 and 2018, 

Emissions Inventory VISTAS. 

6. Pechan, E.H., and Associates, Inc., 2005, AirControlNET User Guide. 

7. Pitchford, Marc., 2006, Natural Haze Levels II: Application of the New IMPROVE 

Alogrithm to Natural Species Concentrations Estimates. Final Report of the Natural 

Haze Levels II Committee to the RPO Monitoring/Data Analysis Workgroup. Sep 2006. 

8. Sorrels, Larry, 2006, AirControlNET 4.1 Software; US EPA, OAQPS, Research Triangle 

Park, North Carolina. 

9. U.S. Environmental Protection Agency. (2003). Guidance for Tracking Progress under 

the Regional Haze Program; EPA-54/B-03-004, 2003.