Regional Haze State Implementation Plan 

For 

Kentucky’s Class I Area 

Prepared by 

Kentucky Energy and Environment Cabinet 

Kentucky Division for Air Quality 

Final 

June 2008

Kentucky Regional Haze SIP 
Preface: This document contains summaries of the technical analyses that will be used by the 

Kentucky Division for Air Quality (KYDAQ) to support the regional haze State Implementation 

Plan (SIP) pursuant to §§107(d)(3)(D) and (E) of the Clean Air Act, as amended. KRS 224.10-

100(5) provides the Kentucky Energy and Environment Cabinet (formerly the Environmental 

and Public Protection Cabinet) with the statutory authority to adopt and implement its regional 

haze SIP. A link to KRS 224.10-100 is as follows: 

http://www.lrc.ky.gov/KRS/224-10/100.PDF. 

Kentucky Regional Haze SIP 

 

ii
EXECUTIVE SUMMARY 

Introduction 

Regional haze is pollution that impairs visibility over a large region, including national parks, 

forests, and wilderness areas (many termed “Class I” areas). Regional haze is caused by sources 

and activities emitting fine particles and their precursors, often transported over large regions. 

Particles affect visibility through the scattering and absorption of light. Reducing fine particles 

in the atmosphere is an effective method of improving visibility. In the southeast, the most 

important sources of haze-forming emissions are coal-fired power plants, industrial boilers and 

other combustion sources, but also include mobile source emissions, area sources, fires, and 

wind blown dust. 

An easily understood measure of visibility to most people is visual range. Visual range is the 

greatest distance, in kilometers or miles, at which a dark object can be viewed against the sky. 

However, the most useful measure of visibility impairment is light extinction, which affects the 

clarity and color of objects being viewed. The measure used by the regional haze rule is the 

deciview (dv), calculated directly from light extinction using a logarithmic scale. 

The regional haze rule requires states to demonstrate reasonable progress toward meeting the 

national goal of a return to natural visibility conditions by 2064. The rule directs states to 

graphically show what would be a “uniform rate of progress,” also known as the “glide path,” 

toward natural conditions for each Class I area within the State and certain ones outside the 

State. 

Kentucky’s Class I Area 

Kentucky has one Class I area within its borders: Mammoth Cave National Park. The figure 

below illustrates the location of Mammoth Cave in Kentucky. 

Mammoth Cave 

National Park 

Kentucky Regional Haze SIP 

 

iii
Visibility on the worst days at Mammoth Cave is an estimated 31dv. Natural background 

visibility on the worst days is an estimated 11 dv. 

State Implementation Plan Requirements 

States are required to submit state implementation plans (SIPs) to the United States 

Environmental Protection Agency that set out each state’s plan for meeting the national goal of a 

return to natural visibility conditions by 2064. The plan includes the states’ reasonable progress 

goals, expressed in deciviews, for visibility improvement at each affected Class I area for each 

10-year period until 2064. 

SIPs must include determinations of the baseline visibility conditions (expressed in deciviews) 

for the most impaired and least impaired days. In addition, states must include a monitoring 

strategy for measuring, characterizing, and reporting of regional haze visibility impairment. The 

long-term strategy includes enforceable emissions limitations, compliance schedules, and other 

measures as necessary to achieve the reasonable progress goals. States must also consider 

ongoing control programs, measures to mitigate construction activities, source retirement and 

replacement schedules, smoke management programs for agriculture and forestry, and 

enforceability of specific measures. 

The SIPs for the first review period are due December 17, 2007. These plans will cover longterm strategies for visibility improvement between baseline conditions in 2000-2004 and 2018. 

States are required to evaluate progress toward reasonable progress goals every 5 years to ensure 

that installed emissions controls are on track with emission reduction forecasts in each SIP. 

Federal and State Control Requirements 

There are significant control programs being implemented between the baseline period and 2018. 

These programs will all reduce the particulate emissions that affect visibility in the Class I areas, 

and include: the Clean Air Interstate Rule (CAIR), the NOx SIP Call or state equivalent, one-hour 

ozone SIPs submitted by Atlanta, Birmingham, and Northern Kentucky, NOx RACT in 8-hour 

nonattainment area SIPs, heavy duty diesel (2007) engine standard (for on-road trucks and 

buses), Tier 2 tailpipe standards for on-road vehicles, large spark ignition and recreational 

vehicle rule, nonroad diesel rule, and various Federal Maximum Achievable Control Technology 

regulations and consent agreements with Tampa Electric, Virginia Electric and Power Company, 

Gulf Power, East Kentucky Power Cooperative, American Electric Power and the PM2.5 

attainment demonstrations due in April 2008. 

The regional haze rule also requires states to determine best available retrofit technology 

(BART) for certain facilities. Twenty-one of Kentucky’s twenty-six BART-eligible sources were 

able to demonstrate that they did not cause or contribute to visibility impairment. Further BART 

determination analysis of five Kentucky Electric Generating Units (EGUs) provided for the 

installation of controls to reduce visibility impairing emissions. 

Kentucky Regional Haze SIP 

 

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Conclusion 

For Kentucky’s Class I area, Mammoth Cave National Park, visibility improvements on the 

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. Additionally, the visibility is 

expected to improve for the best days at Mammoth Cave. The table below displays the 2018 

reasonable progress goals for Kentucky’s Class I area. 

Class I Area 

Baseline 

Visibility for 

Worst Days 

(dv) 

Uniform Rate 

of Progress 

for Worst 

Days 

(dv) 

Reasonable 

Progress Goal 

Modeled for 

Worst Days 

(dv) 

Baseline 

Visibility for 

Best Days 

(dv) 

Uniform Rate 

of Progress 

for Best Days 

(dv) 

Reasonable 

Progress Goal 

Modeled for 

Best Days 

(dv) 

Mammoth 

Cave 

National 

Park, KY 

31.37 26.64 25.56 16.51 16.51 15.57 

Kentucky Regional Haze SIP 

 

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TABLE OF CONTENTS 

1.0 Introduction............................................................................................................................... 1

1.1 What is regional haze? .............................................................................................................. 1

1.2 What are the requirements under the Clean Air Act for addressing regional haze?................. 1 

1.3 General overview of regional haze SIP requirements............................................................... 2 

1.4 Class I area in Kentucky ........................................................................................................... 4 

1.5 State and Federal Land Manager (FLM) coordination ............................................................. 5 

2.0 ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND ESTIMATE OF 

NATURAL BACKGROUND CONDITIONS IN CLASS I AREAS ................................... 7 

2.1 Estimating Natural Conditions for Kentucky’s Class I Area.................................................... 8 

2.2 Estimating Baseline Conditions for Kentucky’s Class I Area.................................................. 9 

2.3 Summary of Natural Background and Baseline Conditions for Kentucky’s Class I Area ..... 10 

2.4 Pollutant Contributions to Visibility Impairment (2000-2004 Baseline Data)....................... 10 

3.0 GLIDEPATHS TO NATURAL CONDITIONS IN 2064...................................................... 14 

3.1 Glidepaths for the Class I Area in Kentucky .......................................................................... 14 

4.0 NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILITY IMPAIRMENT IN 

KENTUCKY’S CLASS I AREA......................................................................................... 16 

4.1 Baseline Emissions Inventory................................................................................................. 16 

4.1.1 Stationary Point Sources ............................................................................................ 17 

4.1.2 Stationary Area Sources............................................................................................. 18 

4.1.3 Off-Road Mobile Sources .......................................................................................... 19 

4.1.4 Highway Mobile Sources........................................................................................... 19 

4.1.5 Biogenic Emission Sources........................................................................................ 19 

4.1.6 Summary 2002 Baseline Emissions Inventory for Kentucky .................................... 20 

4.1.7 Model Performance Improvements through Emissions Inventory Improvements .... 20 

4.2 Assessment of Relative Contributions from Specific Pollutants and Sources Categories...... 21 

5.0 REGIONAL HAZE MODELING METHODS AND INPUTS ............................................. 22 

5.1 Analysis Method ..................................................................................................................... 22 

5.2 Model Selection ...................................................................................................................... 23 

5.2.1 Selection of Photochemical Grid Model .................................................................... 23 

5.2.2 Selection of Meteorological Model............................................................................ 24 

5.2.3 Selection of Emissions Processing System................................................................ 25 

5.3 Selection of the Modeling Year .............................................................................................. 27 

5.4 Modeling Domains.................................................................................................................. 28 

5.4.1 Horizontal Modeling Domain .................................................................................... 28 

5.4.2 Vertical Modeling Domain......................................................................................... 31 

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6.0 MODEL PERFORMANCE EVALUATION......................................................................... 31 

6.1 Modeling Performance Goals, and Criteria ............................................................................ 32 

6.2 VISTAS Domain-Wide Performance ..................................................................................... 33 

6.3 Kentucky’s Class I Area Performance.................................................................................... 37 

7.0 LONG-TERM STRATEGY FOR KENTUCKY’S CLASS I AREA .................................... 39 

7.1 Overview of the Long-Term Strategy Development Process................................................. 39 

7.2 Expected Visibility Results in 2018 for Kentucky’s Class I Area under existing and planned 

emissions controls......................................................................................................................... 40 

7.2.1 Federal and State Control Requirements.................................................................... 40 

7.2.2 Additional State programs to reduce emissions......................................................... 43 

7.2.3 Projected 2009 and 2018 Emissions Inventories........................................................ 43 

7.2.4 Model Results for the 2018 Inventory Compared to the Uniform Rate of Progress 

Glidepaths for Kentucky’s Class I Area........................................................................... 45 

7.3 Relative Contribution from International Emissions to Visibility Impairment in 2018 at 

VISTAS Class I areas ................................................................................................................... 50 

7.4 Relative Contributions to Visibility Impairment: Pollutants, Source Categories, and 

Geographic Areas.......................................................................................................................... 54 

7.5 What Control Determinations Represent Best Available Retrofit Technology for Individual 

Sources? ........................................................................................................................................ 56 

7.5.1 Kentucky BART-Eligible Sources........................................................................... 57 

7.5.2 Determination of Sources Subject to BART in Kentucky ......................................... 58 

7.5.3 Determination of BART Requirements for Subject-to-BART Sources..................... 62 

7.6 Relative Contributions to Visibility Impairment: Geographic Areas of Influence for 

Kentucky’s Class I Area ............................................................................................................... 65 

7.6.1 Back Trajectory Analyses .......................................................................................... 67 

7.6.2 Residence Time Plots................................................................................................. 68 

7.6.3 SO2 Areas of Influence .............................................................................................. 69 

7.6.4 Emissions Sources within SO2 Areas of Influence.................................................. 70 

7.6.5 Specific Source Types in the Area of Influence for Kentucky’s Class I Area........... 73 

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

Influence ....................................................................................................................................... 77 

7.8 Which Control Measures Represent Reasonable Progress for Individual Sources?............... 79

7.9 What Additional Emissions Controls Were Considered as part of the Long-Term Strategy for 

Visibility Improvement by 2018? ................................................................................................. 82

8.0 REASONABLE PROGRESS GOALS................................................................................... 84 

9.0 MONITORING STRATEGY................................................................................................. 85 

10.0 INTERSTATE CONSULTATION ...................................................................................... 88 

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11.0 COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN REVISIONS ................... 89 

12.0 DETERMINATION OF ADEQUACY OF THE EXISTING PLAN.................................. 91 

LIST OF APPENDICES 

Appendix A: VISTAS Memorandum of Understanding and Bylaws 

Appendix B: Conceptual Description 

Appendix C: Modeling Analysis Protocol and Quality Assurance Project Plan 

Appendix D: Emissions Preparation and Results 

Appendix E: Air Quality and Meteorological Preparations and Results 

Appendix F: Model Performance Evaluation 

Appendix G: Modeling Results and Supplemental Analysis 

Appendix H: Reasonable Progress Evaluation and Long Term Strategy 

Appendix I: Data Access 

Appendix J: Consultation Process 

Appendix K: Recommended Improvements 

Appendix L: Best Available Retrofit Technology (BART) Related Documentation 

Appendix M: VISTAS Modeling Reports 

Appendix N: Public Hearing Notice and Summary of Comments Received and Cabinet 

Responses 

Kentucky Regional Haze SIP 

 

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1.0 INTRODUCTION 

1.1 What is regional haze? 

Regional haze is pollution from disparate sources that impairs visibility over a large region, 

including national parks, forests, and wilderness areas (156 of which are termed mandatory 

Federal “Class I” areas). Regional haze is caused by sources and activities emitting fine particles 

and their precursors. Those emissions are often transported over large regions. 

Particles affect visibility through the scattering and absorption of light, and fine particles – 

particles similar in size to the wavelength of light – are most efficient, per unit of mass, at 

reducing visibility. Fine particles may either be emitted directly or formed from emissions of 

precursors, the most important of which are sulfur dioxides (SO2) and nitrogen oxides (NOx). 

Reducing fine particles in the atmosphere is generally considered to be an effective method of 

reducing regional haze, and thus improving visibility. Fine particles also adversely impact 

human health, especially respiratory and cardiovascular systems. The United States 

Environmental Protection Agency (USEPA) has set national ambient air quality standards for 

daily and annual levels of fine particles with diameter smaller than 2.5 μm (PM2.5). In the 

southeast, the most important sources of PM2.5 and its precursors are coal-fired power plants, 

industrial boilers and other combustion sources. Other significant contributors to PM2.5 and 

visibility impairment include mobile source emissions, area sources, fires, and wind blown dust. 

1.2 What are the requirements under the Clean Air Act for addressing regional haze? 

In Section 169A of the 1977 Amendments to the Clean Air Act (CAA), Congress set forth a 

program, for protecting visibility in Class I areas, which calls for 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 air pollution.” Congress adopted the visibility 

provisions to protect visibility in these 156 national parks, forests and wilderness areas. On 

December 2, 1980, the USEPA promulgated regulations to address visibility impairment 

(45 FR 80084). The 1980 regulations were developed to address visibility impairment that is 

“reasonably attributable” to a single source or small group of sources. These regulations 

represented the first phase in addressing visibility impairment and deferred action on regional 

haze that emanates from a variety of sources until monitoring, modeling and scientific 

knowledge about the relationships between pollutants and visibility impairment improved. 

In the 1990 Amendments to the CAA, Congress added section 169B and called on the USEPA to 

issue regional haze rules. The regional haze rule that the USEPA promulgated on July 1, 1999 

(64 FR 35713), revised the existing visibility regulations in order to integrate provisions 

addressing regional haze impairment and establish a comprehensive visibility protection program 

for Class I Federal areas. States are required to submit state implementation plans (SIPs) to the 

USEPA that set out each states’ plan for complying with the regional haze rule, including 

consultation and coordination with other states and with Federal Land Managers (FLMs). The 

timing of SIP submittal is tied to the USEPA’s promulgation of designations for the National 

Ambient Air Quality Standard (NAAQS) for fine particulate matter. States must submit a 

Kentucky Regional Haze SIP 

 

1
regional haze implementation plan to the USEPA within three years after the date of designation. 

Because the USEPA promulgated designation dates on December 17, 2004, regional haze SIPs 

must be submitted by December 17, 2007. 

The regional haze rule addressed the combined visibility effects of various pollution sources over 

a wide geographic region. This wide reaching pollution net meant that many states – even those 

without Class I areas – would be required to participate in haze reduction efforts. The USEPA 

designated five Regional Planning Organizations (RPOs) to assist with the coordination and 

cooperation needed to address the visibility issue. The RPO that makes up the southeastern 

portion of the contiguous United States is known as VISTAS (Visibility Improvement – State 

and Tribal Association of the Southeast), and includes the eastern band of the Cherokee Indians 

in addition to the following states: Alabama, Florida, Georgia, Kentucky, Mississippi, North 

Carolina, South Carolina, Tennessee, Virginia, and West Virginia. 

Figure 1.2-1. Geographical Areas of Regional Planning Organizations 

1.3 General overview of regional haze SIP requirements 

The regional haze rule at 40 CFR 51.308(d) requires states to demonstrate reasonable progress 

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

for reasonable progress, the regional haze rule directs states to graphically show what would be a 

“uniform rate of progress” toward natural conditions for each mandatory Class I Federal area 

within the State and/or for each mandatory Class I Federal area located outside the State, which 

may be affected by emissions from sources within the State. States are to establish baseline 

visibility conditions for 2000-2004, natural background visibility conditions in 2064, and the rate 

Kentucky Regional Haze SIP 

 

2
of uniform progress between baseline and background conditions. The uniform rate of progress 

is also known as the “glidepath.” 

The regional haze rule then 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. The goals must provide for reasonable progress 

towards achieving natural visibility conditions, provide for improvement in visibility for the 

most impaired days over the period of the implementation plan, and ensure no degradation in 

visibility for the least impaired days over the same period (see 40 CFR 51.308(d)(1)). 

In order to ensure that visibility goals are properly met and set, state plans must include 

determinations, for each Class I area, of the baseline visibility conditions (expressed in 

deciviews) for the most impaired and least impaired days. SIPs must also contain supporting 

documentation for all required analyses used to calculate the degree of visibility impairment 

under natural visibility conditions for the most impaired and least impaired days (see 40 CFR 

51.308(d)(2)). In addition, states must include a monitoring strategy for measuring, 

characterizing, and reporting of regional haze visibility impairment that is representative of all 

mandatory Class I Federal areas within the state (see 40 CFR 51.308(d)(4)).

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 present until 2018. The long-term strategy 

includes enforceable emissions limitations, compliance schedules, and other measures as 

necessary to achieve the reasonable progress goals, including all controls required or expected 

under all federal and state regulations by 2009 and by 2018. During development of the longterm strategy, states are also required to consider specific factors such as the above mentioned 

ongoing control programs, measures to mitigate construction activities, source retirement and 

replacement schedules, smoke management programs for agriculture and forestry, and 

enforceability of specific measures (see 40 CFR 51.308(d)(3)). 

In addition, a specific component of each state’s first long-term strategy is dictated by the 

specific best available retrofit technology (BART) requirements in 40 CFR 51.308(e) of the 

regional haze rule. The regional haze rule at 40 CFR 51.308(e) requires states to include a 

determination of BART for each BART-eligible source in the State that emits any air pollutant, 

which may reasonably be anticipated to cause or contribute to any impairment of visibility in any 

mandatory Class I Federal area. The Clean Air Act section 169A(b) defines BART-eligible 

sources as sources in 26 specific source categories, in operation within a 15-year period prior to 

enactment of the 1977 Clean Air Act Amendments and having total potential emissions of 250 

tons per year or more for any visibility-impairing pollutant for all emission units. States must 

determine BART according to five factors set out in section 169A(g)(7) of the Clean Air Act. 

Emission limitations representing BART and schedules for compliance with BART for each 

source subject to BART must be included in the long-term strategy. 

The SIPs for the first review period are due December 17, 2007. These plans will cover longterm strategies for visibility improvement between baseline conditions in 2000-2004 and 2018. 

States are required to evaluate progress toward reasonable progress goals every 5 years to ensure 

that installed emissions controls are on track with emissions reduction forecasts in each SIP. The 

Kentucky Regional Haze SIP 

 

3
first interim review will be due to the USEPA in December 2012. If emissions controls are not 

on track to meet SIP forecasts, then states would need to take action to ensure emissions controls 

by 2018 will be consistent with the SIP or to revise the SIP to be consistent with the revised 

emissions forecast. 

The USEPA provided several guidance documents listed below to assist the states in 

implementation of the regional haze rule requirements. KYDAQ followed these guidance 

documents in developing the technical analyses reported in this plan. 

• Guidance for Tracking Progress Under the Regional Haze Rule (EPA-454/B-03-004, 

September 2003). 

• Guidance for Estimating Natural Visibility Conditions Under the Regional Haze Rule 

(EPA-454/B-03-005, September 2003). 

• Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air 

Quality Goals for Ozone, PM2.5 and Regional Haze (EPA, 2007). 

• Guidance for Setting Reasonable Progress Goals Under the Regional Haze Program 

(EPA, June 2007). 

1.4 Class I area in Kentucky 

Kentucky has one Class I area within its borders: Mammoth Cave National Park. The Kentucky 

Energy and Environment Cabinet’s Division for Air Quality (KYDAQ) is responsible for 

developing the Kentucky’s Regional Haze SIP. This SIP establishes reasonable progress goals 

for visibility improvement at its Class I area, and a long-term strategy that will achieve those 

reasonable progress goals within the first regional haze planning period. 

Mammoth Cave 

National Park 

Figure 1.4-1. Kentucky Class I area 

Kentucky Regional Haze SIP 

 

4
In developing this SIP, the KYDAQ has also considered that emission sources outside of 

Kentucky may affect visibility at Kentucky’s Class I area, and that emission sources within 

Kentucky may affect visibility at Class I areas in neighboring states. Through VISTAS, the 

southeastern states have worked together to assess state-by-state contributions to visibility 

impairment in specific Class I areas, including Mammoth Cave in Kentucky and those affected 

by emissions from Kentucky. This technical work is discussed further in Sections 5, 6, and 7. 

Consultations to date between Kentucky and other states are summarized in Section 10; 

consultations are ongoing. 

Prior to VISTAS, the southern states cooperated in a voluntary regional partnership to identify 

and recommend reasonable measures to remedy existing and prevent future adverse effects from 

human-induced air pollution on the air quality related values of the Southern Appalachian 

Mountains. States cooperated with the FLMs, the USEPA, industry, environmental 

organizations and academia to complete a technical assessment of the impacts of acid deposition, 

ozone, and fine particles on sensitive resources in the Southern Appalachians. The (Southern 

Appalachian Mountain Initiative) SAMI Final Report was delivered in August 2002. The SAMI 

Assessment concluded that ammonium sulfate is the major contributor to visibility impairment in 

the Southern Appalachian Mountains and to improve visibility, it is most important to reduce 

SO2 emissions. SAMI also concluded that reducing ammonia emissions would be helpful to 

reduce ammonium nitrate contributions to visibility impairment. Emissions controls for organic 

carbon, elemental carbon, and soil were expected to be less important for improving visibility. 

The SAMI modeling found that on the haziest days, much of the benefit of emissions reductions 

would occur in the state where emissions reductions were made. Emissions in surrounding 

SAMI states and states outside the SAMI region also contribute to air quality in the SAMI Class 

I areas. The SAMI states supported strong national multi-pollutant legislation to accomplish its 

mission. Emissions reductions to meet national health standards for ozone and fine particles 

were expected to also improve air quality in the Southern Appalachian Mountains. The SAMI 

states committed to consider air quality benefits in the Southern Appalachians as they developed 

SIPs for the health standards. 

Congress considered several legislative bills to reduce SO2 and NOx from electric generating 

utilities. In 2004, the USEPA promulgated the Clean Air Interstate Rule (CAIR) to require 

emissions reductions for SO2 and NOx from electric generating utilities in 26 eastern states. The 

CAIR rule allows for interstate trading of emissions to find cost-effective reductions. These 

reductions will improve visibility in the Class I area in Kentucky. 

1.5 State and Federal Land Manager (FLM) coordination 

As required by 40 CFR §51.308(i), the regional haze SIP must include procedures for continuing 

consultation between the States and FLMs on the implementation of the visibility protection 

program, including development and review of implementation plan revisions and 5-year 

progress reports, and on the implementation of other programs having the potential to contribute 

to impairment of visibility in any mandatory Class I Federal area within the State. The three 

FLMs are the United States Department of Interior’s (USDI’s) Fish and Wildlife Service (FWS) 

Kentucky Regional Haze SIP 

 

5
and National Park Service (NPS) and the United States Department of Agriculture’s (USDA’s) 

Forest Service (FS). 

Successful implementation of a regional haze program will involve long-term regional 

coordination among states. VISTAS was formed in 2001 to address regional haze and visibility 

problems in the southeastern United States. Jurisdictions represented by VISTAS members 

include the Eastern Band of Cherokee Indians; the States of Alabama, Florida, Georgia, 

Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia; 

and the local air pollution control programs located in these States. A copy of the VISTAS 

Memorandum of Agreement and Bylaws is enclosed as Appendix A. 

The objectives of the VISTAS project are to establish natural background visibility conditions 

across the mandatory Class I Federal areas, identify current visibility impairment levels, analyze 

emission control levels that will achieve interim visibility goals, and provide adequate 

documentation to member agencies so that they can develop their regional haze State/Tribal 

Implementation Plans (SIP/TIP). Figure 1.5-1 shows the 18 mandatory Class I Federal areas in 

the VISTAS Region, where visibility is an important value. Table 1.5-1 lists these Class I areas 

and the reported acreage associated with the Class I areas. 

Figure 1.5-1. Class I Areas in the VISTAS Region 

Kentucky Regional Haze SIP 

 

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Table 1.5-1 Mandatory Class I Federal Areas in the VISTAS Region 

State Area Name Acreage Federal Land 

Manager 

Alabama Sipsey Wilderness 24,922 USDA-FS 

Chassahowitzka Wilderness 23,579 USDI-FWS 

Florida Everglades National Park 1,397,429 USDI-NPS 

St. Marks Wilderness 17,350 USDI-FWS 

Cohutta Wilderness 36,977 USDA-FS 

Georgia Okefenokee Wilderness 353,981 USDI-FWS 

Wolf Island Wilderness 5,126 USDI-FWS 

Kentucky Mammoth Cave National Park 51,303 USDI-NPS 

Great Smoky Mountains National Park 273,551 USDI-NPS 

Joyce Kilmer-Slickrock Wilderness 13,562 USDA-FS 

Linville Gorge Wilderness 11,786 USDA-FS 

Shining Rock Wilderness 18,483 USDA-FS 

North Carolina 

Swanquarter Wilderness 8,785 USDI-FWS 

South Carolina Cape Romain Wilderness 29,000 USDI-FWS 

Great Smoky Mountains National Park 241,207 USDI-NPS Tennessee 

Joyce Kilmer-Slickrock Wilderness 3,832 USDA-FS 

James River Face Wilderness 8,886 USDA-FS Virginia Shenandoah National Park 190,535 USDI-NPS 

Dolly Sods Wilderness 10,215 USDA-FS West Virginia Otter Creek Wilderness 20,000 USDA-FS 

2.0 ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND 

ESTIMATE OF NATURAL BACKGROUND CONDITIONS IN CLASS I 

AREAS 

The goal of the Regional Haze Rule is to restore natural visibility conditions to the 156 Class I 

areas identified in the 1977 Clean Air Act Amendments. 40 CFR 51.301(q) defines natural 

conditions: “Natural conditions include naturally occurring phenomena that reduce visibility as 

measured in terms of light extinction, visual range, contrast, or coloration.” The Regional Haze 

SIPs must contain measures that make “reasonable progress” toward this goal by reducing 

anthropogenic emissions that cause haze. 

An easily understood measure of visibility to most people is visual range. Visual range is the 

greatest distance, in kilometers or miles, at which a dark object can be viewed against the sky. 

Kentucky Regional Haze SIP 

 

7
For evaluating the relative contributions of pollutants to visibility impairment, however, the most 

useful measure of visibility impairment is light extinction, which is usually expressed in units of 

inverse megameters (Mm-1). Light extinction affects the clarity and color of objects being 

viewed. 

The measure used by the regional haze rule is the deciview (dv). Deciviews are calculated 

directly from light extinction using a logarithmic scale. The deciview is a useful measure for 

tracking progress in improving visibility, because each deciview change is an equal incremental 

change in visibility perceived by the human eye. Most people can detect a change in visibility at 

one deciview. 

For each Class I area, there are three metrics of visibility that are part of the determination of 

reasonable progress: 

1) natural conditions, 

2) baseline conditions, and 

3) current conditions. 

Each of the three metrics includes the concentration data of the visibility pollutants as different 

terms in the light extinction algorithm, with respective extinction coefficients and relative 

humidity factors. Total light extinction when converted to deciviews (dv) is calculated for the 

average of the 20 percent best and 20 percent worst visibility days. 

“Natural” visibility is determined by estimating the natural concentrations of visibility pollutants 

and then calculating total light extinction. “Baseline” visibility is the starting point for the 

improvement of visibility conditions. It is the average of the Interagency Monitoring of 

Protected Visual Environments (IMPROVE) monitoring data for 2000 through 2004 and is 

equivalent to “current” visibility conditions for this initial review period. The comparison of 

initial baseline conditions to natural visibility conditions indicates the amount of improvement 

necessary to attain natural visibility by 2064. Each state must estimate natural visibility levels 

for Class I areas within its borders in consultation with Federal Land Managers and other states 

(40 CFR 51.308(d)(2)). “Current conditions” are assessed every five years as part of the SIP 

review where actual progress in reducing visibility impairment is compared to the reductions 

committed to in the SIP. 

2.1 Estimating Natural Conditions for Kentucky’s Class I Area 

Natural background visibility, as defined in Guidance for Estimating Natural Visibility 

Conditions Under the Regional Haze Program, EPA-454/B-03-005, September 2003, is based on 

annual average concentrations of fine particle components. The same annual average natural 

background visibility is assumed for all Class I areas in the eastern United States (separate values 

are estimated for the western United States). Natural background visibility for the 20 percent 

worst days is estimated by assuming that fine particle concentrations for natural background are 

normally distributed and the 90th percentile of the annual distribution represents natural 

background visibility on the 20 percent worst days. 

Kentucky Regional Haze SIP 

 

8
In the 2003 guidance, USEPA also provided that states may use a “refined approach” to estimate 

the values that characterize the natural visibility conditions of the Class I areas. The purpose of 

such a refinement would be to provide more accurate estimates with changes to the extinction 

algorithm that may include the concentration values, factors to calculate extinction from a 

measured particular species and particle size, the extinction coefficients for certain compounds, 

geographical variation (by altitude) of a fixed value, and the addition of visibility pollutants. 

In 2005 the IMPROVE Steering Committee made recommendations for a refined equation that 

modifies the terms of the original equation to account for the most recent data. The choice 

between use of the old or the new equation for calculating the visibility metrics for each Class I 

area is made by the state in which the Class I area is located. 

The new IMPROVE equation accounts for the effect of particle size distribution on light 

extinction efficiency of sulfate, nitrate, and organic carbon. The mass multiplier for organic 

carbon (particulate organic matter) is increased from 1.4 to 1.8. New terms are added to the 

equation to account for light extinction by sea salt and light absorption by gaseous nitrogen 

dioxide. Site-specific values are used for Rayleigh scattering to account for the site-specific 

effects of elevation and temperature. Separate relative humidity enhancement factors are used 

for small and large size distributions of ammonium sulfate and ammonium nitrate and for sea 

salt. The elemental carbon (light-absorbing carbon), fine soil, and coarse mass terms do not 

change between the original and new IMPROVE equation. 

Natural background conditions using the new IMPROVE equation are calculated separately for 

each Class I area. The calculation starts with the annual average values for natural background 

for each component of PM2.5 mass from the EPA 2003 guidance (default values). The annual 

frequency distribution of values of each PM2.5 component for current conditions (2000-2004) is 

then defined. This species-specific frequency distribution is applied to the default annual average 

values for that PM2.5 component to calculate natural conditions on the 20% worst days. The 

current variability in each component is retained while also retaining the same annual average 

background condition for that component as defined in the 2003 guidance. The new calculation 

of natural background allows Rayleigh scattering to vary with elevation. Current sea salt values 

are used for natural background levels of sea salt. 

The VISTAS states chose to use the new IMPROVE equation as the basis for the conceptual 

description because it takes into account the most recent review of the science and because it is 

recommended by the IMPROVE Steering Committee. For more detailed discussion of the two 

IMPROVE equations, see Appendix B. 

2.2 Estimating Baseline Conditions for Kentucky’s Class I Area 

Baseline visibility conditions at Kentucky’s Class I area is estimated using sampling data 

collected at the IMPROVE monitoring site at Mammoth Cave National Park. A five year average 

(2000 to 2004) was calculated for each of the 20 percent worst and 20 percent best visibility days 

in accordance with 40 CFR 51.308(d)(2) and Guidance for Tracking Progress Under the 

Regional Haze Rule, EPA-454-03-004, September 2003. IMPROVE data records for Mammoth 

Kentucky Regional Haze SIP 

 

9
Cave for the period 2000 to 2004 meet USEPA requirements for data completeness (75 percent 

for the year and 50 percent for each quarter). The light extinction and deciview visibility values 

for the 20 percent worst and 20 percent best visibility days at Mammoth Cave are based on data 

and calculations included in Appendix B of this SIP. 

2.3 Summary of Natural Background and Baseline Conditions for Kentucky’s Class I Area 

Table 2.3-1 presents estimated natural background and baseline visibility metrics for Kentucky’s 

Class I area. Note that Kentucky is not considering international emissions to be a component of 

natural background. Baseline visibility on the 20 percent worst days at the Mammoth Cave 

monitoring site is predicted to be 31 dv. Natural background visibility at the Mammoth Cave 

monitoring site is predicted to be 11 dv. A list of the 20 percent worst and 20 percent best days 

used in the technical analyses for Kentucky’s Class I area are available on page 7 of Appendix 

F.2.

Table 2.3-1 Natural Background and Baseline Conditions for Kentucky’s Class I Area

Natural Background Conditions 

Class I area Average for 

20 percent 

Worst Days

(deciviews) 

Average for 

20 percent 

Best Days 

(deciviews) 

Average for 

20 percent 

Worst Days 

Bext (Mm-1) 

Average for 

20 percent 

Best Days 

Bext (Mm-1) 

Mammoth Cave 11.1 5.0 30.7 16.5 

Baseline Visibility Conditions 2000-2004 

Class I area Average for 

20 percent 

Worst Days

(deciviews) 

Average for 

20 percent 

Best Days 

(deciviews)

Bext (Mm-1) 

Average for 

20 percent 

Worst Days

Bext (Mm-1) 

Average for 

20 percent 

Best Days

Mammoth Cave 31.4 16.5 241.4 53.0 

2.4 Pollutant Contributions to Visibility Impairment (2000-2004 Baseline Data) 

The 20 percent worst visibility days at Kentucky’s Mammoth Cave generally occur in the period 

March through September. The peak hazy days occur in the summer under stagnant weather 

conditions with high relative humidity, high temperatures, and low wind speeds. The 20 percent 

best visibility days at Mammoth Cave generally can occur at any time of year. Figures 2.4-1 and 

2.4-2 display the average light extinction for the 20% haziest days and 20% clearest days, 

respectively. 

Kentucky Regional Haze SIP 

 

10
VISTAS coastal VISTAS inland Neighboring non-VISTAS

0

50

100

150

200

250

300

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Extinction (Mm -1)

Sea Salt

Coarse

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

0

50

100

150

200

250

300

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Extinction (Mm -1)

Sea Salt

Coarse

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

Figure 2.4-1. Average light extinction for the 20 percent Haziest Days in 2000-2004 at 

VISTAS and neighboring Class I areas using New IMPROVE equation 

0

10

20

30

40

50

60

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

0

10

20

30

40

50

60

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Figure 2.4-2. Average light extinction for the 20 percent Clearest Days in 2000-2004 at 

VISTAS and neighboring Class I areas using New IMPROVE equation 

Kentucky Regional Haze SIP 

 

11
Ammonium sulfate, (NH4)2SO4, is the most important contributor to visibility impairment and 

fine particle mass on the 20 percent worst (haziest) and 20 percent best (clearest) visibility days 

at Mammoth Cave. Sulfate levels on the 20 percent worst days account for 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 (Figure 2.4-1). On the 20 percent clearest days, sulfate 

levels are more uniform across the region (Figure 2.4-2). 

Sulfate particles are formed in the atmosphere from SO2 emissions. Sulfate particles occur as 

hydrogen sulfate, H2(SO4), ammonium bisulfate HNH4SO4, and ammonium sulfate, (NH4)2SO4, 

depending on the availability of ammonia, NH3, in the atmosphere. 

Particulate Organic Matter (POM) is the second most important contributor to fine particle mass 

and light extinction on the 20 percent haziest days at the Kentucky’s Class I area. Elevated 

levels of POM and Elemental Carbon, EC, indicate impact from wildfires or prescribed fire. 

Typically, in state significant fire impacts are infrequent at Kentucky’s Class I area. VISTAS 

collected additional samples of carbon at five sites, including Mammoth Cave, KY; Great Smoky 

Mountains, NC; Millbrook (Raleigh, NC); Cape Romain, SC; and Shenandoah, VA, to better 

understand sources contributing to carbon in rural and urban areas. Samples were analyzed to 

define the amount of carbon-14 isotope as an indicator of the amount of carbon from modern 

sources (vegetative emissions, fires) and the amount of carbon from fossil sources (gasoline, 

diesel, oil). For most samples, the ratio of modern carbon to fossil carbon was greater than 0.60 

throughout the year. In the fall, winter, and spring, more of the modern carbon is attributable to 

wood burning while in the summer months more of the modern carbon mass is attributable to 

biogenic emissions from vegetation. On some days, greater than 90% of the carbon at Great 

Smoky Mountains is attributable to modern sources of carbon. Biogenic carbon emissions at 

Cape Romain, SC, a coastal site similar to Swanquarter, were lower than emissions at the 

forested mountain sites. Carbon from gasoline and diesel engines is a relatively small 

contribution at the rural sites. At Millbrook, carbon from fossil fuel combustion is a larger 

percentage contribution than at the rural sites, but still less than 50 percent of total carbon 

measured. These results suggest that controlling anthropogenic sources of carbon will have little 

benefit in improving visibility in Class I areas since the majority of the POM comes from 

natural, i.e., biogenic, sources. Controlling anthropogenic sources of carbon will likely be more 

effective to reduce levels of PM2.5 in urban areas. 

Ammonium nitrate, NH4NO3, is the second most important contributor to fine particle mass and 

light extinction on the 20 percent clearest days at Kentucky’s Class I area. NH4NO3 is formed in 

the atmosphere by reaction of NH3 and NOx. In the VISTAS region, nitrate formation is limited 

by availability of NH3 and by temperature. Ammonia preferentially reacts with SO2 and sulfate 

before reacting with NOx. Particle nitrate is formed at lower temperatures; at elevated 

temperatures nitric acid remains in gaseous form. For this reason, particle nitrate levels are very 

low in the summer and a minor contributor to visibility impairment. Particle nitrate 

concentrations are higher on winter days and are more important for the coastal sites where 20 

percent worst days can occur on winter days. Nitrogen oxides are emitted by fossil fuel 

combustion by point, area, on-road, and off-road mobile sources. Modeling data (see Section 7) 

indicate that in the VISTAS region ammonium nitrate formation is limited by NH3 

Kentucky Regional Haze SIP 

 

12
concentrations and suggest that for winter days, controls of NH3 sources would be more 

effective in reducing ammonium nitrate levels than controls of NOx. 

Elemental Carbon, EC, is a comparatively minor contributor to visibility impairment. Sources 

include agricultural and wildland (wildfire, wildland fire use and prescribed fire) burning, and 

incomplete combustion of fossil fuels. EC levels are higher at urban monitors than at the Class I 

areas and suggest controls of fossil fuel combustion sources would be more effective to reduce 

PM2.5 in urban areas than to improve visibility in Class I areas. 

Soil fine particles are minor contributors to visibility impairment at most southeastern sites on 

most days. Occasional episodes of elevated fine soil can be attributed to Saharan dust episodes, 

particularly at Everglades, Florida, but rarely are seen at the Kentucky’s Class I area. No control 

strategies are indicated for fine soil. 

Sea salt, NaCl, is observed at the coastal sites. Sea salt contributions to visibility impairment are 

most important on the 20 percent clearest days when sulfate and POM levels are low. Sea salt 

levels do not contribute significantly to visibility on the 20 percent worst visibility days. The 

new IMPROVE equation uses Chloride ion, Cl-

, from routine IMPROVE measurements to 

calculate sea salt levels. VISTAS used Cl- to calculate sea salt contributions to visibility 

following IMPROVE guidance. 

Coarse particle mass (particles with diameters between 2.5 and 10 microns) has a relatively 

small contribution to visibility impairment because the light extinction efficiency of coarse mass 

is very low compared to the extinction efficiency for sulfate, nitrate, and carbon. 

An unidentified component is reported by IMPROVE as the difference between the total PM2.5 

mass measured on the filter and the sum of the measured components. This unidentified mass 

may be positive or negative and is attributable to water and/or the factors used to calculate 

molecular weights of the other components. 

 

The New IMPROVE equation generally results in higher calculated light extinction on days with 

higher mass and lower light extinction on days with lower mass. This tends to increase 

calculated light extinction for current conditions and to decrease calculated light extinction for 

natural visibility conditions. Adding sea salt to the new IMPROVE equation increases light 

extinction for both current and natural visibility conditions. Increasing the mass multiplier for 

POM in the new IMPROVE equation increases light extinction for current conditions more than 

for natural conditions. The new algorithm does not change the conclusion that in the VISTAS 

region, and in Kentucky, the most effective means to improve visibility is to reduce sulfate 

concentrations. 

PM2.5 trends in urban and Class I areas: IMPROVE data were compared to monitoring data 

from the Speciated Trends Network (STN) in nearby urban areas to understand the similarities 

and differences in composition of fine particle mass. Several PM2.5 nonattainment areas are in 

close proximity to the Class I areas in the southeastern United States, including Atlanta, GA; 

Birmingham, AL; Charleston, WV; Chattanooga, TN; Knoxville, TN; and Louisville, KY. 

Ammonium sulfate concentrations are comparable between urban and nearby Class I areas, 

Kentucky Regional Haze SIP 

 

13
while organic carbon, elemental carbon, and nitrate concentration are generally higher in urban 

areas than the Class I areas. These results suggest that sulfate is widely distributed regionally 

while urban areas see an additional incremental pollutant loading from local emissions sources. 

Role of meteorology in determining visibility conditions: Classification and Regression Tree 

(CART) Analyses were used to characterize the relationship between meteorological conditions 

and visibility conditions at the Class I areas. Days were assigned to one of five visibility classes 

ranging from poor to good visibility. Days were then assigned to bins based on meteorological 

conditions. For the Kentucky’s Class I area, poor visibility days were most likely to occur on 

days with high temperatures, high relative humidity, low wind speeds, and elevated PM2.5 mass 

at upwind urban areas. Precipitation was not a good predictor of visibility condition. Weights 

were assigned to days based on frequency of occurrence of days with similar meteorological 

conditions. 

The above analyses are further discussed in Appendix B. 

 

3.0 GLIDEPATHS TO NATURAL CONDITIONS IN 2064 

As stated in Section 1.3, the regional haze rule directs states to graphically show what would be a 

“uniform rate of progress” toward natural conditions for each mandatory Class I Federal area 

within the State as well as for each mandatory Class I Federal area located outside the State, 

which may be affected by emissions from sources within the State. The uniform rate of progress 

is also known as the “glidepath.” The glidepath is simply a straight graphical line drawn from 

the baseline level of visibility impairment for 2000-2004 to the level representing no manmade 

impairment in 2064. 

Each state must set goals for each Class I area that provide for reasonable progress towards 

achieving natural visibility conditions by 2064. Section 51.308(d)(1) of the regional haze rule 

requires that reasonable progress goals must both: 

(1) provide for improvement in visibility for the most impaired days over the period of the 

implementation plan; and 

(2) ensure no degradation in visibility for the least impaired days over the same period. 

Uniform rate of progress graphs (glidepaths), were developed for each Class I area in the 

VISTAS region. The glidepaths were developed in accordance with the USEPA’s guidance for 

tracking progress and used data collected from the IMPROVE monitoring sites as described in 

Section 2 of this document. The glidepath is one of the indicators used in setting reasonable 

progress goals. 

3.1 Glidepaths for the Class I Area in Kentucky 

The following is the glidepath for the 20 percent most impaired days for Mammoth Cave 

National Park assuming uniform rate of progress toward regional haze goals. Natural 

background visibility for the most impaired days at Mammoth Cave is predicted to be 11 dv. 

Kentucky Regional Haze SIP 

 

14
Uniform Rate of Progress Glidepath

Mammoth Cave - 20% Worst Data Days

New IMPROVE Equation

31.37

29.68

26.64

23.26

19.87

16.49

13.11

11.08

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

Figure 3.1-1. Uniform Rate of Progress Glidepath for 20 percent worst days at Mammoth Cave 

National Park. 

Kentucky Regional Haze SIP 

 

15
4.0 NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILITY 

IMPAIRMENT IN KENTUCKY’S CLASS I AREA

4.1 Baseline Emissions Inventory 

The Regional Haze Rule at 51.308(d) (4) (v) requires a statewide emissions inventory of 

pollutants that are reasonably anticipated to cause or contribute to visibility impairment in any 

mandatory Class I area. An inventory was developed for the baseline year 2002 and projected 

to 2009 and 2018. The pollutants inventoried include volatile organic compounds, nitrogen 

oxides, fine particulate (PM2.5), coarse particulate (PM10), ammonia and sulfur dioxide. The 

baseline emissions inventory for 2002 was developed for Kentucky following the methods 

described in Appendix D. 

There are five different emission inventory source classifications: stationary point and area 

sources, off-road and on-road mobile sources, and biogenic sources. Stationary point sources are 

those sources that emit greater than a specified tonnage per year, with data provided at the 

facility level. Electric generating utilities and industrial sources are the major categories for 

stationary point sources. Stationary area sources are those sources whose individual emissions 

are relatively small, but due to the large number of these sources, the collective emissions from 

the source category could be significant (i.e., dry cleaners, service stations, agricultural sources, 

fire emissions, etc.). These types of emissions are estimated on a countywide level. Non-road 

(or off-road) mobile sources are equipment that can move but do not use the roadways, i.e., lawn 

mowers, construction equipment, railroad locomotives, aircraft, etc. The emissions from these 

sources, like stationary area sources, are estimated on a countywide level. On-road mobile 

sources are automobiles, trucks, and motorcycles that use the roadway system. The emissions 

from these sources are estimated by vehicle type and road type and are summed to the 

countywide level. Biogenic sources are the natural sources like trees, crops, grasses and natural 

decay of plants. The emissions from these sources are estimated on a countywide level. 

In addition to the various source classifications, there are also various types of emission 

inventories. The first is the actual base year inventory. This inventory is the base year emissions 

that correspond to the meteorological data used, which for this modeling effort is data from 

2002. These emissions are used for evaluating the air quality model performance. 

The second type of inventory is the typical base year inventory. This inventory is similar to the 

actual base year inventory, except that for sources whose emissions change significantly from 

year to year, a more typical emission value is used. In this modeling effort, typical emissions 

were developed for the electric generating units (EGUs) and the wildland fire emissions. The air 

quality modeling runs using the typical base year inventory provide results which are then used 

to calculate relative reduction factors for future years. These relative reduction factors for future 

years are then used to demonstrate reasonable progress toward visibility goals. 

Below is an overview of the inventories used for each source classification. More detailed 

discussion of the emissions inventory development is contained in Appendix D. 

Kentucky Regional Haze SIP 

 

16
4.1.1 Stationary Point Sources 

Point source emissions are emissions from individual sources that are in a fixed location. 

Generally, these sources must have permits in order to construct and/or operate and their 

emissions are inventoried on an annual basis. All sources emitting VOC are inventoried in 

Kentucky’s ozone nonattainment and maintenance areas on an annual basis. Large NOx sources 

having minimum capacity to emit 100 tons per year (tpy) of a criteria pollutant, 10 tpy of a single 

hazardous air pollutant (HAP), or 25 tpy total of multiple HAPs are inventoried annually. 

Smaller sources have been inventoried less frequently. For the purposes of this modeling point 

source emissions data can be grouped into EGU sources and other non-EGU sources. 

Electric Generating Units

The actual base year inventory for the EGU sources used 2002 continuous emissions monitoring 

(CEM) data reported to the USEPA’s Acid Rain program or 2002 hourly emissions data 

provided by stakeholders. These data provide hourly emissions profiles for SO2 and NOx that 

can be used in air quality modeling. Emissions profiles are used to estimate emissions of other 

pollutants (volatile organic compounds, carbon monoxide, ammonia, fine particles, soil) based 

on measured emissions of SO2 and NOx. 

Emissions from EGUs vary daily and seasonally as a function of variability in energy demand 

and utilization and outage schedules. To avoid anomalies in future year emissions created by 

relying on 2002 operations to represent future operations, a typical base year emissions inventory 

was developed for EGUs. This approach is consistent with the USEPA’s modeling guidance. 

To develop a typical year 2002 emissions inventory for EGU sources, each unit’s average CEM 

heat input for 2000 through 2004 was divided by the 2002 actual heat input to generate a unit 

specific normalizing factor. This normalizing factor was then multiplied by the 2002 actual 

emissions. The heat inputs for the period 2000 through 2004 were used because the modeling of 

current conditions use monitored data from this same 5-year period. If a unit was shut down for 

an entire year during the 2000 through 2004 period, the average of the years the unit was 

operational was used. If a unit was shut down in 2002, but not permanently shutdown, the 

emissions and heat inputs from 2001 (or 2000) were used in the normalizing calculations. 

As part of the VISTAS air quality modeling, VISTAS, in cooperation with the other eastern 

RPOs, contracted with ICF Resources, L.L.C., to generate future year emission inventories for 

the electric generating sector of the contiguous United States using the Integrated Planning 

Model (IPM) version 2.1.9 updated with state-specific information. IPM is a dynamic linear 

optimization model that can be used to examine air pollution control policies for various 

pollutants throughout the contiguous United States for the entire electric power system. The 

dynamic nature of IPM enables projection of the behavior of the power system over a specified 

future period. Optimization logic in IPM determines the least-cost means of meeting electric 

generation and capacity requirements while complying with specified constraints including air 

pollution regulations, transmission bottlenecks, and plant-specific operational constraints. The 

versatility of IPM allows users to specify which constraints to exercise, and to populate IPM with 

their own datasets. 

Kentucky Regional Haze SIP 

 

17
The IPM modeling runs took into consideration the USEPA’s Clean Air Interstate Rule (CAIR) 

implementation and North Carolina’s CSA requirements. 

Other Industrial Point Sources

For the non-EGU sources, the same inventory is used for both the actual and typical base year 

emissions inventories. The non-EGU category uses annual emissions as reported under the 

Consolidated Emissions Reporting Rule (CERR) for the year 2002. These emissions are 

temporally allocated to month, day, and hour using source category code (SCC)-based allocation 

factors. 

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

control data consistent with USEPA’s CAIR analyses. This data was supplemented with statespecific growth factors and stakeholder input on growth assumptions. 

4.1.2 Stationary Area Sources 

Stationary area sources are sources whose individual emissions are relatively small, but due to 

the large number of these sources, the collective emissions could be significant (i.e., combustion 

of fuels for heating, structure fires, service stations, etc.). Emissions are estimated by 

multiplying an emission factor by some known indicator of collective activity, such as fuel 

usage, number of households, or population. Stationary area source emissions are estimated at 

the countywide level. 

A small portion of the 2002 area source base year inventory for ozone precursors in eleven 

Kentucky ozone areas was developed by the KYDAQ and provided to the VISTAS contractor. 

The VISTAS contractor calculated the remaining portion of the area source inventory. The 

sources estimated by the contractor include emissions from animal husbandry, wildland fires, 

and particulate matter from paved and unpaved roads. For the other states within the modeling 

domain, either state-supplied data or data reported under CERR for 2002 was used. 

The actual base year inventory will serve as the typical base year inventory for all area source 

categories except for wildland fires. For wildland fires, a typical year inventory was used to 

avoid anomalies in wildfire activity in 2002 compared to longer term averages. Development of 

a typical year fire inventory provided the capability of using a comparable data set for both the 

base year and future years. The VISTAS Fire Special Interest Work Group used State records to 

ratio the number of acres burned over a longer term period (three or more years, as available 

from state records) to 2002. Based on these ratios, the 2002 acreage was then scaled up or down 

to develop a typical year inventory. 

The VISTAS contractor generated future year emissions inventories for 2009 and 2018 for the 

regional haze modeling. Growth factors, supplied either by states or taken from the CAIR 

emission projections, were applied to project the controlled emissions to 2018. If no growth 

factor was available from either a state or the CAIR growth factor files, then the USEPA’s 

Economic Growth and Analysis System Version 5 growth factors were used. 

Kentucky Regional Haze SIP 

 

18
4.1.3 Off-Road Mobile Sources 

Off-road (or non-road) mobile sources are equipment that can move but do not use the roadways, 

such as construction equipment, aircraft, railroad locomotives, lawn and garden equipment, etc. 

For the majority of the non-road mobile sources, the emissions for 2002 were estimated using the 

USEPA’s NONROAD2005c model. For the three source categories not included in the 

NONROAD model, i.e., aircraft engines, railroad locomotives and commercial marine, more 

traditional methods of estimating the emissions were used. The same inventory is used for both 

the actual and typical base year emissions inventories. 

For the source categories estimated using the USEPA’s NONROAD model, the model growth 

assumptions were used to create the 2009 and 2018 future year inventories. The NONROAD 

model takes into consideration regulations affecting emissions from these source categories. For 

the Northern Kentucky Greater Cincinnati International Airport, KYDAQ confirmed to the 

VISTAS contractor the number of landings and takeoffs for 2002. For the commercial marine, 

railroad locomotives and the remaining airport emissions, the VISTAS contractor calculated the 

future growth in emissions using detailed inventory data (both before and after controls) for 1996 

and 2010, obtained from the CAIR Technical Support Document. When available, state-specific 

growth factors were used. 

4.1.4 Highway Mobile Sources 

For onroad vehicles, the newest version of the MOBILE model, MOBILE6.2, was used. Key 

inputs for MOBILE include information on the age of vehicles on the roads, the average speeds 

on the roads, the mix of vehicles on the roads, any programs in place in an area to reduce 

emissions for motor vehicles (e.g., emissions inspection programs), and temperature. 

The MOBILE model takes into consideration regulations that affect emissions from this source 

sector. The same MOBILE run is used to represent the actual and typical year emissions for 

onroad vehicles using input data reflective of 2002. The MOBILE model then is run for 2018 

inventory using input data reflective of that year. KYDAQ provided 2002 and 2018 VMT and 

speed information to the VISTAS contractor for a small number of Kentucky counties. For 

several urban areas in Kentucky that run travel demand models (TDMs), VMT and speed data 

from TDMs was obtained by KYDAQ and provided to the VISTAS contractor. 

4.1.5 Biogenic Emission Sources 

Biogenic emissions were prepared with the SMOKE-BEIS3 (Biogenic Emission Inventory 

System 3 version 0.9) preprocessor. SMOKE-BEIS3 is a modified version of the Urban Airshed 

Model (UAM)-BEIS3 model. Modifications include use of MM5 data, gridded land use data, 

and improved emissions characterization. The emission factors that are used in SMOKE-BEIS3 

are the same as the emission factors as in UAM-BEIS3. The basis for the gridded land use data 

used by BEIS3 is the county land use data in the Biogenic Emissions Landcover Database 

version 3 (BELD3) provided by the USEPA. A separate land classification scheme, based upon 

satellite (AVHRR, 1 km spatial resolution) and census information, aided in defining the forest, 

agriculture and urban portions of each county. 

Kentucky Regional Haze SIP 

 

19
4.1.6 Summary 2002 Baseline Emissions Inventory for Kentucky 

Table 4.1.6-1 is a summary of the 2002 baseline emission inventory for Kentucky. The complete 

inventory and discussion of the methodology is contained in Appendix D. The emissions 

summaries for other VISTAS states can also be found in Appendix D. 

Table 4.1.6-1 2002 Emissions Inventory Summary for Kentucky (tons per year). 

VOC NOx PM2.5 PM10 NH3 SO2 

Point 46,315 240,362 14,219 21,421 995 529,182 

Area 98,713 40,966 51,763 240,226 51,246 41,941 

On-Road Mobile 103,503 156,417 2,697 3,723 5,055 6,308 

Non-Road Mobile 44,805 104,571 6,046 6,425 31 14,043 

Biogenics 630,506 21,090 0 0 0 0 

TOTAL 923,842 563,406 74,725 271,795 57,327 591,474 

4.1.7 Model Performance Improvements through Emissions Inventory Improvements 

Since the initial model performance evaluation, VISTAS has made several improvements to the 

emissions inventory, which in turn improved model performance. These inventory 

improvements are detailed in the VISTAS emissions inventory report and Appendix D, and are 

summarized here: 

• For electric generating utilities, the Integrated Planning Model (IPM) was used to provide 

estimates of future year utility production and emissions. Continuous Emissions 

Monitoring data was used to define seasonal variability in production and emissions. The 

states updated IPM model projections with control data provided by utility companies in 

late 2006 through early 2007. 

• For on-road vehicle emissions, states and local agencies provided updated MOBILE 

model input and vehicle-miles-traveled data. 

• For ammonia emissions from agricultural sources, the Carnegie Mellon University 

ammonia model was used to improve annual and monthly estimates. 

• For fires, the VISTAS states provided fire activity data for 2002 for wildfires, prescribed 

fire, land clearing and agricultural burning to develop a 2002 fire inventory. Where data 

allowed, large fire events were modeled as point sources. In 2006, the United States 

Forest Service and Fish and Wildlife Service provided projections of increased prescribed 

burning in 2009 and 2018; these data were incorporated in the inventory for all states 

except Florida. Because current prescribed fire activity already reflects the use of fire as 

a forest management technique, Florida believed that there is too much uncertainty to 

project how future total fire activity (prescribed plus wildfire) will change. In Florida, 

prescribed fire in the future years is the same as 2002 typical for prescribed fire. 

• For non-road engines, the updated USEPA NONROAD2005 emissions model was used. 

• For commercial marine emissions in shipping lanes in the Gulf of Mexico and Atlantic 

Oceans, gridded emissions for the VISTAS modeling domain was created using 

inventory data newly developed for the USEPA by Corbett at University of Delaware. 

These emissions were incorporated in the modeling. 

• Updated inventories from the neighboring RPOs, Mexico, and Canada were incorporated 

as available. 

Kentucky Regional Haze SIP 

 

20
4.2 Assessment of Relative Contributions from Specific Pollutants and Sources Categories 

Ammonium sulfate is the largest contributor to visibility impairment at Kentucky’s Class I area 

and reduction of SO2 emissions would be the most effective means of reducing ammonium 

sulfate. As illustrated in Figure 4.2-1, 96 percent of SO2 emissions in the VISTAS states are 

attributable to electric generating facilities and industrial point sources. Similarly, in Kentucky 

the stationary point sources, consisting of electric generating facilities and industrial point 

sources, contribute 90 percent of the SO2 emissions as illustrated in Figure 4.2-2. 

VISTAS States SO2 Emissions - 2002 

Utilities

Industrial

On road

Non road

Other

Industrial: 20% Utilities: 76%

4.8 Million tons

VISTAS States SO2 Emissions - 2002 

Utilities

Industrial

On road

Non road

Other

Industrial: 20% Utilities: 76%

4.8 Million tons

Figure 4.2-1. SO2 emissions in 2002 in the VISTAS States. 

KY SO2 Emissions 2002

591,474 tons

Utilities

84%

Industrial

6%

Utilities

Industrial

On road

Non road

Other

Area

Figure 4.2-1. SO2 emissions in 2002 in Kentucky. 

Kentucky Regional Haze SIP 

 

21
Since the largest source of SO2 emissions comes from the stationary point sources, the focus of 

potential controls and the impacts for those controls was on this source sector. In Kentucky, the 

types of sources emitting SO2, and thus contributing to the visibility impairment of its Class I 

area, were predominately coal fired utility and industrial boilers. 

5.0 REGIONAL HAZE MODELING METHODS AND INPUTS 

Modeling for regional haze was performed by VISTAS for the ten southeastern states, including 

Kentucky. The sections below outline the methods and inputs used by VISTAS for the regional 

modeling. Additional details are provided in Appendices C, D and M. 

5.1 Analysis Method 

The modeling analysis is a complex technical evaluation that begins by selection of the modeling 

system. VISTAS decided to use the following modeling system: 

• Meteorological Model: The Pennsylvania State University/National Center for 

Atmospheric Research (PSU/NCAR) Mesoscale Meteorological Model (MM5) is a 

nonhydrostatic, prognostic meteorological model routinely used for urban- and regionalscale photochemical, fine particulate matter, and regional haze regulatory modeling 

studies. 

• Emissions Model: The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling 

system is an emissions modeling system that generates hourly gridded speciated emission 

inputs of mobile, nonroad mobile, area, point, fire and biogenic emission sources for 

photochemical grid models. 

• Air Quality Model: The USEPA’s Models-3/ Community Multiscale Air Quality 

(CMAQ) modeling system is an ‘One-Atmosphere’ photochemical grid model capable of 

addressing ozone, particulate matter (PM), visibility and acid deposition at regional scale. 

The USEPA’s 2007 modeling guidance recommends modeling an entire year or at a minimum 

several days in each quarter of a year to adequately represent the range of meteorological 

conditions that contribute to elevated levels of fine particulate matter. The year 2002 was 

selected by VISTAS as the modeling year for this demonstration. Meteorological inputs were 

developed for 2002 using the meteorological model. Emission inventories were also developed 

for 2002 and processed through the emissions model. These inputs were used in the air quality 

model to predict fine particle mass and visibility. The model results for 2002 were compared 

with observed meteorological and air quality data to evaluate model performance. Several 

configurations of the meteorological and air quality model were evaluated to select a 

configuration that gave the best overall performance for the VISTAS region. 

Once model performance was deemed adequate, the current and future year emissions were 

processed through the emissions model. The air quality modeling results are used to determine a 

relative reduction in future visibility impairment, which is used to determine reasonable progress. 

Kentucky Regional Haze SIP 

 

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The complete modeling protocol used for this analysis can be found in Appendix C. 

5.2 Model Selection 

To ensure that a modeling study is defensible, care must be taken in the selection of the models 

to be used. The models selected must be scientifically appropriate for the intended application 

and be freely accessible to all stakeholders. “Scientifically appropriate” means that the models 

address important physical and chemical phenomena in sufficient detail, using peer-reviewed 

methods. “Freely accessible” means that model formulations and coding are freely available for 

review and that the models are available to stakeholders, and their consultants, for execution and 

verification at no or low cost. 

The following sections outline the criteria for selecting a modeling system that is both defensible 

and capable of meeting the study's goals. These criteria were used in selecting the modeling 

system used for this modeling demonstration. 

5.2.1 Selection of Photochemical Grid Model 

Criteria

For a photochemical grid model to qualify as a candidate for use in a regional haze SIP, a State 

needs to show that it meets the same several general criteria as a model for an attainment 

demonstration for a NAAQS: 

• The model has received a scientific peer review 

• The model can be demonstrated applicable to the problem on a theoretical basis 

• Data bases needed to perform the analysis are available and adequate 

• Available past appropriate performance evaluations have shown the model is not biased 

toward underestimates or overestimates 

• A protocol on methods and procedures to be followed has been established 

• The developer of the model must be willing to make the source code available to users 

for free or for a reasonable cost, and the model cannot otherwise be proprietary. 

Overview of CMAQ

The photochemical model selected for this study was CMAQ version 4.5, with (SOAmods), 

secondary organic aerosol (SOA) modifications that were developed by the VISTAS contractor 

in order to improve organic carbon under prediction performance in the VISTAS modeling (See 

Appendix C for published article regarding the SOA modifications). For more than a decade, the 

USEPA has been developing the Models-3 CMAQ modeling system with the overarching aim of 

producing a ‘One-Atmosphere’ air quality modeling system capable of addressing ozone, fine 

particulate matter, visibility and acid deposition within a common platform. The original 

justification for the Models-3 development emerged from the challenges posed by the 1990 

Kentucky Regional Haze SIP 

 

23
CAAA and the USEPA’s desire to develop an advanced modeling framework for ‘holistic’ 

environmental modeling utilizing state-of-science representations of atmospheric processes in a 

high performance computing environment. The USEPA completed the initial stage of 

development with Models-3 and released the CMAQ model in mid-1999 as the initial operating 

science model under the Models-3 framework. The most recent rendition is CMAQ version 4.5, 

which was released in September 2005. Please note that VISTAS used a previous version of the 

CMAQ model (CMAQv4.4_SOAmods) in earlier VISTAS sensitivity work. 

An advantage of choosing CMAQ as the atmospheric model is the ability to do one-atmospheric 

modeling. The same model configuration is being applied for the ozone and PM2.5 attainment 

demonstrations SIPs, as well as the regional haze SIP. A number of features in CMAQ’s 

theoretical formulation and technical implementation make the model well suited for annual PM 

modeling. 

The configuration used for this modeling demonstration, as well as a more detailed description of 

the CMAQ model, can be found in the Modeling Protocol (Appendix C). 

5.2.2 Selection of Meteorological Model 

Criteria

Meteorological models, either through objective, diagnostic, or prognostic analysis, extend 

available information about the state of the atmosphere to the grid upon which photochemical 

grid modeling is to be carried out. The criteria for selecting a meteorological model are based on 

both the models ability to accurately replicate important meteorological phenomena in the region 

of study, and the model's ability to interface with the rest of the modeling systems -- particularly 

the photochemical grid model. With these issues in mind, the following criteria were established 

for the meteorological model to be used in this study: 

• Non-Hydrostatic Formulation 

• Reasonably current, peer reviewed formulation 

• Simulates Cloud Physics 

• Publicly available at no or low cost 

• Output available in I/O API format 

• Supports Four Dimensional Data Assimilation (FDDA) 

• Enhanced treatment of Planetary Boundary Layer heights for AQ modeling 

Overview of MM5

The non-hydrostatic MM5 model is a three-dimensional, limited-area, primitive equation, 

prognostic model that has been used widely in regional air quality model applications. The basic 

model has been under continuous development, improvement, testing and open peer-review for 

Kentucky Regional Haze SIP 

 

24
more than 20 years and has been used worldwide by hundreds of scientists for a variety of 

mesoscale studies. 

MM5 uses a terrain-following non-dimensionalized pressure, or "sigma", vertical coordinate 

similar to that used in many operational and research models. In the non-hydrostatic MM5, the 

sigma levels are defined according to the initial hydrostatically-balanced reference state so that 

the sigma levels are also time-invariant. The gridded meteorological fields produced by MM5 

are directly compatible with the input requirements of ‘one atmosphere’ air-quality models using 

this coordinate. MM5 fields can be easily used in other regional air quality models with different 

coordinate systems by performing a vertical interpolation, followed by a mass-conservation readjustment. 

Distinct planetary boundary layer parameterizations are available for air-quality applications, 

both of which represent sub-grid-scale turbulent fluxes of heat, moisture and momentum. One 

scheme uses a first-order eddy diffusivity formulation for stable and neutral environments and a 

modified first-order scheme for unstable regimes. The other scheme uses a prognostic equation 

for the second-order turbulent kinetic energy, while diagnosing the other key boundary layer 

terms. 

Initial and lateral boundary conditions are specified for real-data cases from mesoscale threedimensional analyses performed at 12-hour intervals on the outermost grid mesh selected by the 

user. Surface fields are analyzed at three-hour intervals. A Cressman-based technique is used to 

analyze standard surface and radiosonde observations, using the National Meteorological 

Center's spectral analysis, as a first guess. The lateral boundary data are introduced using a 

relaxation technique applied in the outermost five rows and columns of the coarsest grid domain. 

The MM5 modeling system in regulatory air quality application studies has been widely reported 

in the literature (e.g., Emery et al., 1999; Tesche et al., 2000, 2003) and many have involved 

comparisons with other prognostic models such as the Regional Atmospheric Modeling System 

(RAMS) and the Systems Application International Mesoscale Model. The MM5 enjoys a far 

richer application history in regulatory modeling studies compared with RAMS or other models. 

Furthermore, in evaluations of these models in over 60 recent regional scale air quality 

application studies since 1995, it has generally been found that the MM5 model tends to produce 

somewhat better photochemical model inputs than alternative models. 

The configuration used for this modeling demonstration, as well as a more detailed description of 

the MM5 model, can be found in the meteorological modeling protocol (Appendix E). 

5.2.3 Selection of Emissions Processing System 

Criteria

The principal criterion for an emissions processing system is that it accurately prepares 

emissions files in a format suitable for the photochemical grid model being used. The following 

list includes clarification of this criterion and additional desirable criteria for effective use of the 

system. 

Kentucky Regional Haze SIP 

 

25
• File System Compatibility with the I/O API 

• File Portability 

• Ability to grid emissions on a Lambert Conformal projection 

• Report Capability 

• Graphical Analysis Capability 

• MOBILE6 Mobile Source Emissions 

• Biogenic Emissions Inventory System version 3 (BEIS-3) 

• Ability to process emissions for the proposed domain in a reasonable amount of time. 

• Ability to process control strategies 

• No or low cost for acquisition and maintenance 

• Expandable to support other species and mechanisms 

Overview of SMOKE

The SMOKE Emissions Processing System Prototype was originally developed at the Microcomputing Center of North Carolina. As with most ‘emissions models’, SMOKE is principally 

an emission processing system and not a true emissions modeling system in which emissions 

estimates are simulated from ‘first principles’. This means that, with the exception of mobile 

and biogenic sources, its purpose is to provide an efficient, modern tool for converting emissions 

inventory data into the formatted emission files required by an air quality simulation model. For 

mobile sources, SMOKE actually estimates emissions based on input mobile-source activity 

data, emission factors and outputs from transportation travel-demand models. 

 

SMOKE was originally designed to allow emissions data processing methods to utilize emergent 

high-performance-computing as applied to sparse-matrix algorithms. Indeed, SMOKE is the 

fastest emissions processing tool currently available to the air quality modeling community. The 

sparse matrix approach utilized throughout SMOKE permits both rapid and flexible processing 

of emissions data. The processing is rapid because SMOKE utilizes a series of matrix 

calculations instead of less efficient algorithms used in previous systems. The processing is 

flexible because the processing steps of temporal projection, controls, chemical speciation, 

temporal allocation, and spatial allocation have been separated into independent operations 

wherever possible. The results from these steps are merged together at a final stage of 

processing. 

 

SMOKE contains a number of major features that make it an attractive component of the 

modeling system. The model supports a variety of input formats from other emissions 

processing systems and models. It supports both gridded and county total land use scheme for 

biogenic emissions modeling. SMOKE can accommodate emissions files from up to 10 

countries and any pollutant can be processed by the system. For additional information about the 

SMOKE model please refer to Modeling Protocol (Appendix C). 

Kentucky Regional Haze SIP 

 

26
5.3 Selection of the Modeling Year 

A crucial step to SIP modeling is the selection of the period of time to model to represent current 

air quality conditions and to project changes in air quality in response to changes in emissions. 

The year 2002 was selected as the base year for several reasons. 

The USEPA’s April 2007 Guidance on the use of Models and Other Analyses for Demonstrating 

Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze identifies specific goals 

to consider when selecting one or more episodes for use in demonstrating reasonable progress in 

attaining the regional haze air quality goals. The USEPA recommends that episode selection 

derive from three principal criteria: 

• Simulate a variety of meteorological conditions; 

• Model time periods in which observed concentrations are close to the appropriate 

baseline design value or visibility impairment; 

• Model periods for which extensive air quality/meteorological data bases exist; and 

• Model a sufficient number of days so that the modeled attainment test applied at each 

monitor violating the NAAQS is based on multiple days. 

For regional haze modeling, the guidance goes further by suggesting that the preferred approach 

is to model a full, representative year. Moreover, the required relative reduction factor values 

should be based on model results averaged over the 20% worst and 20% best visibility days 

determined for each Class I area based on monitoring data from the 2000 – 2004 baseline 

period. 

The USEPA also lists several other considerations to bear in mind when choosing potential 

regional haze episodes including: (a) choose periods which have already been modeled, (b) 

choose periods which are drawn from the years upon which the current design values are based, 

(c) include weekend days among those chosen, and (d) choose modeling periods that meet as 

many episode selection criteria as possible in the maximum number of nonattainment or Class I 

areas as possible. Finally, the USEPA explicitly recommended in its 2007 modeling guidance to 

use 2002 as the baseline inventory year. 

VISTAS adopted a logical, stepwise approach in implementing the USEPA’s 2007 modeling 

guidance in order to identify the most preferable, representative year for regional haze modeling. 

These steps include the following: 

Representativeness of Meteorological Conditions: The VISTAS meteorological 

contractor (BAMS) identified important meteorological characteristics and data sets in 

the VISTAS region directly relevant to the evaluation of candidate annual modeling 

episodes. 

Initial Episode Typing: At the time of selection in 2003, meteorological and air quality 

data were available for 2002 for model inputs and model performance evaluation. 

VISTAS used CART analyses to evaluate visibility conditions for 2000, 2001, and 2002, 

Kentucky Regional Haze SIP 

 

27
the candidate modeling years. The year 2002 was found to be representative of 

conditions in the other two years. Subsequently, these analyses were repeated with the 

meteorological and air quality monitoring data for 2000 to 2004 to evaluate how well the 

2002 modeling year represented the full 2000-2004 baseline period. This analysis 

confirmed that visibility and PM2.5 mass in 2002 were representative of the five-year 

baseline period for the VISTAS Class I areas. This analysis is discussed in more detail in 

the project report in Appendix B. 

Data Availability: In parallel with the CART analyses, episode characterization analyses, 

collaborative investigations by VISTAS states (e.g., NCDAQ, Georgia Department of 

Natural Resources, Florida Department of Environmental Protection) intensively studied 

the availability of PM2.5, meteorological, and emissions data and representativeness of 

alternative baseline modeling periods from a regulatory standpoint. Additionally, 2002 

was the year that the USEPA was requiring states to provide emissions inventory data for 

the Comprehensive Emissions Reporting Rule, it made sense to use 2002 as the modeling 

year to take advantage of the 2002 inventory. 

Years to be used by other RPOs: VISTAS also considered what years other RPO would 

be modeling, and several had already chosen calendar year 2002 as the modeling year. 

After a lengthy process of integrated studies, the episode selection process culminated in the 

selection of calendar year 2002 (1 January through 31 December) as the most current, 

representative, and pragmatic choice for VISTAS regional haze modeling. All of the USEPA 

criteria for regional haze episode selection were directly considered in this process together with 

many other considerations (e.g., timing of new emissions or aerometric data deliveries by the 

USEPA or the states to the modeling teams). 

5.4 Modeling Domains 

5.4.1 Horizontal Modeling Domain 

The USEPA’s 2007 modeling guidance recommends a 12-km modeling grid resolution for 

PM2.5 modeling while a 36-km grid is considered acceptable for regional haze. For the VISTAS 

modeling, a coarse 36-km grid resolution was used for modeling the entire United States and a 

finer 12-km grid was used to model the eastern United States. 

The CMAQ model was run in one-way nested grid mode. This allowed the larger outer domains 

to feed concentration data to the inner nested domain. Two-way nesting was not considered due 

to numerical and computational uncertainty associated with the technique. 

The horizontal coarse grid modeling domain boundaries were determined through a national 

effort to develop a common grid projection and boundary. A smaller 12-km grid, modeling 

domain was selected in an attempt to balance location of areas of interest, such as ozone and fine 

particulate matter nonattainment areas, as well as Class 1 areas for regional haze. Processing 

time was also a factor in choosing a smaller 12-km grid, modeling domain. 

Kentucky Regional Haze SIP 

 

28
The coarse 36-km horizontal grid domain covers the continental United States. This domain was 

used as the outer grid domain for MM5 modeling with the CMAQ domain nested within the 

MM5 domain. Figure 5.4.1-1 shows the MM5 horizontal domain as the outer most, blue grid 

with the CMAQ 36-km domain nested in the MM5 domain. 

Kentucky Regional Haze SIP 

 

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Figure 5.4.1-1. The MM5 horizontal domain is the outer most, blue grid, with the CMAQ 

36-km domain nested in the MM5 domain. 

To achieve finer spatial resolution in the VISTAS states, a one-way nested high resolution 

(12-km grid resolution) was used. Figure 5.4.1-2 shows the 12-km grid, modeling domain for 

the VISTAS region. The modeling results from this modeling domain are the results on which 

the reasonable progress goals will be assessed. 

Figure 5.4.1-2. A more detailed view of the 12-km grid over the VISTAS region. 

Kentucky Regional Haze SIP 

 

30
5.4.2 Vertical Modeling Domain 

The CMAQ vertical structure is primarily defined by the vertical grid used in the MM5 

modeling. The MM5 model employed a terrain following coordinate system defined by 

pressure, using 34 layers that extend from the surface to the 100 mb. A layer-averaging scheme 

was used to generate 19 vertical layers for CMAQ to reduce the computational cost of the 

CMAQ simulations. The effects of layer averaging were evaluated in conjunction with the 

VISTAS modeling effort and was found to have a relatively minor effect on the model 

performance metrics when both the 34 layer and a 19 layer CMAQ models were compared to 

ambient monitoring data. 

 

6.0 MODEL PERFORMANCE EVALUATION 

The initial modeling effort focused on evaluating previous regional air quality modeling 

applications and testing candidate model configurations for the SMOKE emissions and CMAQ 

model for the VISTAS 36-km and 12-km modeling domains. This effort resulted in a report 

recommending the model configuration for the annual emissions and air quality modeling, which 

is included as part of the VISTAS Emissions and Air Quality Modeling Protocol. The evaluation 

of the meteorological modeling configuration can be found in Appendix F.1, with a summary of 

the final meteorological and air quality modeling configuration in the modeling protocol 

contained in Appendix E and Appendix C, respectively. 

Air quality model performance for the 2002 modeling year was initially tested in 2004 using an 

early version of the VISTAS emissions inventory. In keeping with the one-atmosphere objective 

of the CMAQ modeling platform, model performance was evaluated based on measured ozone, 

fine particles, and acid deposition in the Air Quality System (AQS), IMPROVE, Speciated 

Trends Network (STN), Southeastern Aerosol Research and Characterization (SEARCH), 

National Acid Deposition Program (NADP) and Clean Air Status and Trends Network 

(CASTNet) monitoring networks (Figure 6.0-1). A detailed examination of the results was 

published in 2005 in the Journal of Air and Waste Management (see Appendix B.3) as well as 

being summarized in Appendix B.1. 

Kentucky Regional Haze SIP 

 

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Figure 6.0-1: Monitoring Networks used for VISTAS 2002 model performance evaluation, 

and their location within the VISTAS 12km domain. 

6.1 Modeling Performance Goals, and Criteria 

In 2004, VISTAS established model performance goals and criteria for components of fine 

particle mass (Table 6.1-1) based on previous model performance for ozone and fine particles. 

The USEPA’s 2007 modeling guidance for fine particulate matter at the time noted that PM 

models might not be able to achieve the same level of performance as ozone models. VISTAS’s 

evaluation considered several statistical performance measures and displays. Fractional bias and 

mean fractional error were selected as the most appropriate metrics to summarize model 

performance; other metrics were also calculated and are included for IMPROVE monitors in the 

full model performance evaluation (Appendix F.2). 

Kentucky Regional Haze SIP 

 

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Table 6.1-1: Established model performance goals and criteria for the component species of 

fine particle mass. 

Fractional Bias Mean Fractional 

Error 

Comment 

<15 percent <35 percent Goal for PM model performance based on ozone 

model performance, considered excellent performance 

<30 percent <50 percent Goal for PM model performance, considered good 

performance 

<60 percent <75 percent Criteria for PM model performance, considered 

average performance. Exceeding this level of 

performance indicates fundamental concerns with the 

modeling system and triggers diagnostic evaluation. 

Several graphic displays of model performance were prepared including: 

1. Scatter plots of predicted and observed concentrations and deposition by species, 

monitoring network, and month 

2. Time series plots of predicted and observed concentrations and deposition by species, 

monitoring site, and month 

3. Spatially average time series plots 

4. Time series plots of monthly fractional bias and error for a species, region, and network 

5. Performance goal plots (“soccer plots”) that summarize model performance by species, 

region, season 

6. Concentration performance plots (“bugle plots”) that display fractional bias or error as a 

function of concentration by species, region, monitoring network, and month 

The “soccer plots” and “bugle plots” are relatively new tools in model performance evaluations, 

and have recently been included as model performance evaluation displays in the USEPA’s 2007 

modeling guidance for ozone, PM2.5, and regional haze. Both “soccer plots” and “bugle plots” 

allow for convenient way to examine model performance with respect to set goals and criteria. 

The bugle plots have the added benefit of adjusting the goals and criteria to consider the 

concentration of the species. Analysis of “bugle plots” generally suggests that greater emphasis 

should be placed on performance of those components with the greatest contribution to PM mass 

and visibility impairment (e.g. sulfate and organic carbon) and that greater bias and error could 

be accepted for components with smaller contributions to total PM mass (e.g. elemental carbon, 

nitrate, and soil). 

6.2 VISTAS Domain-Wide Performance 

Further discussion of model performance in this document will focus on the comparison of 

observational data from the IMPROVE monitors and model output data from the VISTAS 2002 

actual annual air quality modeling. Focus is limited to the IMPROVE monitoring network as 

these sites are the locations used in projecting visibility improvement goals in the Class I areas. 

The evaluation will primarily focus on the air quality model’s performance with respect to 

individual components of PM2.5, as good model performance of the component species will 

Kentucky Regional Haze SIP 

 

33
dictate good model performance of total or reconstituted PM2.5. Model performance of the total 

PM2.5 and the resulting total light extinction will also be provided as a means to discuss the 

overall model performance for this SIP. 

In the analyses, mean fractional bias (error) is used in lieu of mean bias (error), to prevent low 

observations and model predictions from skewing the metrics. A full list of model performance 

statistics is found in Appendix F.2. The soccer and bugle plots for the all of the VISTAS 

IMPROVE monitors are included here for summary purposes. The goal and criteria levels used 

for regional haze model performance were 30% and 60%, respectively, for mean fractional bias 

and 50% and 75%, respectively, for mean fractional error. Plots have been developed for the 

average monthly concentrations and the performance statistics for all of the most significant light 

scattering component species (Sulfate, Nitrate, and Organic Carbon) for the 20% best days and 

20% worst days. Plots for individual IMPROVE monitors associated with Kentucky’s Class I 

area are included in Appendix F.2. 

The soccer plots of monthly concentrations (Figures. 6.2-1 and 6.2-2) show that values for nitrate 

generally fall outside of criteria performance thresholds (red box). Sulfates and organic carbon 

generally fall within goal thresholds (green box), with a couple of months falling just outside the 

goal thresholds but well within the criteria thresholds. In these figures, each point represents a 

month. Figure 6.2-3 contains separate soccer plots for each season. The seasonal plots 

emphasize poorer nitrate performance in the summer, when observed nitrate is quite low and 

predicted nitrate is even lower. When concentration is factored into performance criteria, nitrate 

performance improves with respect to mean fractional bias and mean fractional error 

(Figures 6.2-4 and 6.2-5). 

All Sites CMAQ 12km - 2002 Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

Figure 6.2-1: Soccer plot depicting both the mean fractional error and fractional bias for 

component concentration for all VISTAS sites. 

Kentucky Regional Haze SIP 

 

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All Sites CMAQ 12km - 2002 Monthly

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

-75.0 -25.0 25.0 75.0

Fractional Bias

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

Figure 6.2-2: A zoomed view of the soccer plot depicting both the mean fractional error 

and fractional bias for component concentration for all VISTAS sites. 

All Sites CMAQ 12km - 2002 Spring Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error

Sulfate

Nitrate

Ammon.

Organics

EC

Soils

PM2.5

PM10

CM

Criteria

Goal

All Sites CMAQ 12km - 2002 Summer Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error

Sulfate

Nitrate

Ammon.

Organics

EC

Soils

PM2.5

PM10

CM

Criteria

Goal

All Sites CMAQ 12km - 2002 Fall Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error

Sulfate

Nitrate

Ammon.

Organics

EC

Soils

PM2.5

PM10

CM

Criteria

Goal

All Sites CMAQ 12km - 2002 Winter Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error

Sulfate

Nitrate

Ammon.

Organics

EC

Soils

PM2.5

PM10

CM

Criteria

Goal

Figure 6.2-3: Seasonal soccer plots for all VISTAS IMPROVE monitors. 

Kentucky Regional Haze SIP 

 

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All Sites CMAQ 12km - 2002 Monthly

0.0

50.0

100.0

150.0

200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Average Concentration (μg/m3)

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

Figure 6.2-4: Bugle plot of the mean fraction bias for particulate matter and its component 

concentrations for all VISTAS sites. 

igure 6.2-5: Bugle plot of mean fraction error for particulate matter and its component 

dditionally, performance assessed at the “one atmosphere” level was also deemed acceptable 

All Sites CMAQ 12km - 2002 Monthly

-200.0

-150.0

-100.0

-50.0

0.0

50.0

100.0

150.0

200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Average Concentration (μg/m3)

Mean Fractional Bias 

Sulfate

Nitrate

Organics

(+) Criteria

(+) Goal

(-) Goal

(-) Criteria

F

species for all VISTAS sites. 

A

for ozone and particulate matter at various monitoring sites (STN, FRM, CASTNet, etc.). 

Overall, VISTAS found the modeling results to be representative and acceptable for use in 

modeling projection for ozone, particulate matter, and regional haze. 

Kentucky Regional Haze SIP 

 

36
6.3 Kentucky’s Class I Area Performance 

The following section provides stack bar charts comparing observed PM2.5 composition and 

modeled PM2.5 composition. The charts have been split into two charts, with the first displaying 

the 20% best days followed by the chart for the 20% worst days. Stacked bar charts have been 

developed for the IMPROVE monitoring site relevant to Kentucky: Mammoth Cave National 

Park (for the location of this area see Figure 1.4-1). 

The stacked bar chart allows a side by side comparison of the each day’s observed and modeled 

compositional and total light extinction. Within each bar the color codes are: 

• Yellow = light extinction due to sulfates (bextSO4) 

• Red = light extinction due to nitrates (bextNO3) 

• Green = light extinction due to organic carbon (bextOC) 

• Black = light extinction due to elemental (bextEC) 

• Brown = light extinction due to soil (bextSoil) 

• Grey = light extinction due to coarse mass (bextCM) 

The components are presented in the same order for both the observed (left hand bar) and 

modeled bar (right hand bar), so it easy to identify days when the prediction light extinction for 

the component differs from the observed. The total height of the bar provides the total 

reconstructed particulate matter light extinction value. 

Kentucky Regional Haze SIP 

 

37
Best 20% Obs (left) vs 2002gt2a (right) at MACA1

0

20

40

60

80

100

120

140

160

14 23 32 35 44 62 68 83 89 113 116 227 266 269 278 281 287 302 308 323 338 347 356 _ _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at MACA1

0

100

200

300

400

500

600

700

800

86 149 152 155 170 173 185 191 197 203 206 212 215 218 224 233 236 239 245 251 254 260 263 341 _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-1: Stacked bar chart for Mammoth Cave on the 20% best days (top) and 20% 

worst days (bottom). Observed composition is presented in the left hand bar, with modeled 

composition represented by the right hand bar. 

Kentucky Regional Haze SIP 

 

38
A cursory view of the stacked bars charts reiterates that sulfates are a large contributor to light 

extinction in the Kentucky Class I area on both 20% best days and 20% worst days. The bar 

charts also suggest that organic carbon and nitrates are important on the 20% best days at the 

IMPROVE site at Mammoth Cave for Kentucky. The bar charts for the 20% best days indicate 

an over prediction of the nitrate and a slight under prediction of the sulfate on many of the 20% 

best days. 

Comparing the 20% best day charts to the 20% worst days charts, one notices that the various 

components of particle pollution play a more prominent role in the 20% best days than with the 

20% worst days. Also, the species make up on the 20% best days varies more widely compared 

to the 20% worst days. This suggests accurately modeling each species is especially important 

on the 20% best days. 

With the bar chart for the 20% worst days, you can see model performance does improve across 

the sites. Light extinction due to sulfate prediction is better, but still falls short on some days. 

Light extinction due to organic carbon also becomes more important to total light extinction. 

Much like the sulfate component, the organic carbon component accuracy has improved 

performance over the 20% best day series, thought some days are still under predicted. Overall, 

the KYDAQ found model performance to fall within acceptable limits for model performance. 

The KYDAQ further asserts the one atmosphere modeling performed by the VISTAS contractors 

is representative of conditions in the southeastern states and is applicable for use in attainment 

demonstrations. 

7.0 LONG-TERM STRATEGY FOR KENTUCKY’S CLASS I AREA 

As stated in Section 1.3, the regional haze rule requires a State to establish reasonable progress 

goals for Class I areas within the State, expressed in deciviews, that provide for reasonable 

progress toward achieving natural visibility by 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 through 2018. States are also to evaluate the effects of emissions from their 

State on Class I areas in other states. This section discusses development of Kentucky’s longterm strategy. 

7.1 Overview of the Long-Term Strategy Development Process 

The process KYDAQ used to develop its long-term strategy was to address the following set of 

questions: 

a. Assuming implementation of existing federal and state air regulatory requirements, 

how much visibility improvement would be expected at Kentucky’s Class I area 

between now and 2018 compared to the area’s uniform rate of progress? 

b. What additional emission controls represent BART in Kentucky? 

Kentucky Regional Haze SIP 

 

39
c. If additional emission reductions were needed, from what pollutants and source 

categories would the greatest visibility benefits be realized between the baseline and 

2018? 

d. Based on the pollutants identified in (c) above, determine what are the geographic 

locations (i.e., area of influence) for the Class I area where these emissions having the 

greatest impact on visibility are found? 

e. What types of emissions sources do we find in those geographic locations (i.e., area 

of influence)? 

f. Which specific individual sources in those geographic locations (i.e., area of 

influence) have the greatest visibility impacts at a Class I area? 

g. What additional emission controls represent reasonable control measures for those 

sources identified in (f) above? 

h. Given the additional emission reductions from BART and reasonable control 

measures identified, how much visibility improvement, compared to the glidepath, is 

expected at the Class I area in Kentucky between the baseline and 2018? 

7.2 Expected Visibility Results in 2018 for Kentucky’s Class I Area under existing and 

planned emissions controls 

There are significant control programs being implemented between the baseline period and 2018. 

These programs are described in more detail below. 

7.2.1 Federal and State Control Requirements 

NOx SIP Call or state equivalent. Phase I of the NOx SIP call applies to certain EGUs and large 

non-EGUs, including large industrial boilers and turbines, and cement kilns. Those states 

affected by the NOx SIP call in the VISTAS region have developed rules for the control of NOx 

emissions that have been approved by the USEPA. The NOx SIP Call has resulted in a 66 

percent reduction in summertime NOx emissions from large stationary combustion sources in 

Kentucky. 

CAIR. CAIR will permanently cap emissions of SO2 and NOx from EGUs in the eastern United 

States by 2015. When fully implemented, CAIR will reduce SO2 emissions from EGUs in these 

states by more than 70 percent, and NOx emissions by more than 60 percent, from 2003 levels. 

One-hour ozone SIPs (Atlanta / Birmingham / Northern Kentucky). New SIPs have been 

submitted to the USEPA to demonstrate attainment of the one-hour ozone NAAQS. These SIPs 

require NOx reductions from specific coal fired power plants and address transportation plans in 

these cities. 

Kentucky Regional Haze SIP 

 

40
Heavy Duty Diesel (2007) Engine Standard (for on-road trucks and buses). The USEPA set a 

PM emissions standard for new heavy-duty engines of 0.01 grams per brake-horsepower-hour 

(g/bhp-hr), to take full effect for diesel engines in the 2007 model year. This rule 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 pollutioncontrol technology to be effective on these trucks and buses. The USEPA requires a 97 percent 

reduction in the sulfur content of highway diesel fuel from its previous 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 (On-road vehicles). The USEPA mobile source rules include the Tier 2 fleet 

averaging program, modeled after the California LEV II standards. Manufacturers can produce 

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

manufacturer sells each year must have average NOx emissions below a specified value. Tier 2 

standards became effective in the 2005 model year. 

Large Spark Ignition and Recreational Vehicle Rule. The USEPA has adopted new standards for 

emissions of NOx, hydrocarbons, and carbon monoxide from several groups of previously 

unregulated nonroad engines. Included in these are large industrial spark-ignition engines and 

recreational vehicles. Nonroad spark-ignition engines are those powered by gasoline, liquid 

propane gas, or compressed natural gas rated over 19 kilowatts (kW) (25 horsepower). These 

engines are used in commercial and industrial applications, including forklifts, electric 

generators, airport baggage transport vehicles, and a variety of farm and construction 

applications. Nonroad recreational vehicles include snowmobiles, off-highway motorcycles, and 

all-terrain-vehicles. These rules were initially effective in 2004 and will be fully phased-in by 

2012. 

Nonroad Diesel Rule. This rule sets standards that will reduce emissions by more than 90 

percent from nonroad diesel equipment, and reduce sulfur levels by 99 percent from current 

levels in nonroad diesel fuel starting in 2007. This step will apply to most nonroad diesel fuel in 

2010 and to fuel used in locomotives and marine vessels in 2012. 

Industrial Boiler/Process Heater/RICE MACTs. The USEPA issued final rules to substantially 

reduce emissions of toxic air pollutants from industrial, commercial and institutional boilers, 

process heaters and from stationary reciprocating internal combustion engines (RICE). These 

rules reduce emissions of a number of toxic air pollutants, including hydrogen chloride, 

manganese, lead, arsenic and mercury by 2009. This rule also reduces emissions of SO2 and PM 

in conjunction with the toxic air pollutant reductions. The applied Maximum Achievable 

Control Technology (MACT) control efficiencies were 4 percent for SO2 and 40 percent for 

PM10 and PM2.5. The USEPA’s industrial boiler MACT rules were vacated on June 8, 2007. 

The VISTAS states decided to leave these controls in the modeling since it is believed that by 

2018 the USEPA will have re-promulgated a boiler MACT rule or states will have addressed the 

issue through state rule making.

Kentucky Regional Haze SIP 

 

41
Combustion Turbine MACT. The projection inventories do not include the NOx co-benefit 

effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal 

Combustion Engines, which the USEPA estimates to be small compared to the overall inventory.

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

emission reductions were implemented. Reductions occurring before 2002 were assumed to be 

accounted for in the 2002 base year inventory. 

Consent Agreements. Under a settlement agreement, by 2008, Tampa Electric will install 

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

interim pollution-reduction measures to reduce emissions while the permanent controls are 

designed and installed; and retire pollution emission allowances that Tampa Electric or others 

could use, or sell to others, to emit additional NOx, SO2, and PM. 

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

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

plants in Virginia and West Virginia. 

A 2002 agreement calls for Gulf Power to upgrade its operation to cut NOx emission rates by 61 

percent at its Crist generating plant by 2007, with major reductions beginning in early 2005. The 

Crist plant is a significant source of NOx emissions in the Pensacola area. 

East Kentucky Power Cooperative (EKPC), a coal-fired electric utility, has agreed to spend 

approximately $650 million on pollution controls and pay a $750,000 penalty to resolve 

violations of the Clean Air Act at its three plants in Kentucky known as Spurlock, Dale, and 

Cooper. The agreement will reduce harmful air pollutants by more than 60,000 tons per year 

according to EPA. The company will install state-of-the-art pollution control equipment to 

reduce emissions of pollutants that cause acid rain and smog. The controls will reduce annual 

emissions of smog-forming nitrogen oxides by approximately 8,000 tons and sulfur dioxide by 

more than 54,000 tons per year from EKPC’s Spurlock, Dale, and Cooper plants when the 

controls are fully implemented. This consent decree will facilitate that SO2 scrubbers are 

installed for EKPC’s Spurlock Units 1 and 2 and Cooper Units 1 and 2 for BART. Per IPM, 

SO2 scrubbers for EKPC Spurlock Units 1 and 2 and Cooper Unit 2 have been included in this 

SIP’s regional haze modeling results for 2018. 

American Electric Power (AEP) has agreed to cut 813,000 tons of air pollutants annually 

(654,000 tons of SO2 and 159,000 tons of NOx) at an estimated cost of more than $4.6 billion, 

pay a $15 million penalty, and spend $60 million on projects to mitigate the adverse effects of its 

past excess emissions. The agreement imposes caps on emissions of pollutants from 16 plants 

located in five states. The facilities are located in Moundsville (2 facilities), St. Albans, Glasgow, 

and New Haven (2 facilities), West Virginia; Louisa, Kentucky; Glen Lyn and Carbo, Virginia; 

Brilliant, Conesville, Cheshire, Lockburne, and Beverly, Ohio; and Rockport and Lawrenceburg, 

Indiana. AEP will install pollution control equipment to reduce and cap sulfur dioxide and 

nitrogen oxide emissions by more than 813,000 tons per year when fully implemented. By 

installing these pollution control measures, the plants will emit 79 percent less sulfur dioxide and 

Kentucky Regional Haze SIP 

 

42
69 percent less nitrogen oxides, as compared to 2006 emissions. This consent decree will 

facilitate that a SO2 scrubber is installed for Kentucky’s AEP Big Sandy Unit 2 for BART. Per 

IPM, a SO2 scrubber for AEP Big Sandy Unit 2 has been included in this SIP’s regional haze 

modeling results. 

7.2.2 Additional State programs to reduce emissions 

In addition to accounting for specific emission reductions due to ongoing air pollution programs 

as required under the regional haze rule section 308 (d)(3)(v)(A), states are also required to 

consider the air quality benefits of measures to mitigate the impacts of construction activities 

[section 308(d)(3)(v)(B)] and agricultural and forestry smoke management 

[section 308(d)(3)(v)(E)]. These state measures are discussed in more detail in Appendix H. 

7.2.3 Projected 2009 and 2018 Emissions Inventories 

The inventories for 2009 and 2018 account for post-2002 emission reductions from promulgated 

and proposed federal, state, local, and site-specific control programs as of July 1, 2004. In 

general, emissions inventories were developed for 2009 and 2018 using current control 

information in Kentucky. 

For EGUs, IPM results were adjusted based on state and local air agencies knowledge of planned 

emission controls at specific EGUs. These updates are documented in the MACTEC emissions 

inventory report “Documentation of the 2002 Base Year and 2009 and 2018 Projection Year 

Emission Inventories for VISTAS” dated February 2007 (Appendix D). 

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

used in the USEPA’s CAIR analyses (Clean Air Interstate Rule Emissions Inventory Technical 

Support Document, March 2005) supplemented by state and local air agencies data and updated 

forecasts from the Department of Energy (DOE). 

Area source controls were estimated using known state level Stage I controls on gasoline 

dispensing facilities and open burning estimates, as well as controls used to project emissions for 

the USEPA’s Heavy Duty Diesel rulemaking and for the CAIR rulemaking. 

Mobile source controls included local controls underlying the 2002 baseline inventory (vehicle 

emission inspection, Stage II vapor recovery, anti-tampering, etc.) with changes based on 

specific State input. The future year inventories were developed by running the MOBILE6.2 

model for each year modeled. The future year emissions for the off-road mobile sources 

included in the USEPA NONROAD model were estimated by running the model for each future 

year. For the other off-road mobile source categories control data and projections for 1996, 

2010, 2015, and 2020 were obtained from the USEPA's CAIR Technical Support Document, and 

straight-line projections were used to estimate 2009 and 2018 levels. 

The following bar charts show expected decreases in emissions of SO2 and NOx across the 

VISTAS states from 2002 through 2018. (Similar charts for other visibility impairing pollutants 

are contained in Appendix H). Note that for SO2 emissions in particular, which are the largest 

Kentucky Regional Haze SIP 

 

43
contributors to haze, emissions from electric generating facilities are expected to decrease 

dramatically (70 percent) between 2002 and 2018. However, even after implementation of 

CAIR, EGU emissions are projected to remain the largest contributor to haze, comprising more 

than half of remaining SO2 emissions in most states. 

West Virginia

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

West Virginia

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

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

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Figure 7.2.3-1. Annual SO2 emissions for 2002, 2009, and 2018 in the VISTAS states 

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

2009

2018

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

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

2002

2009

2018

Figure 7.2.3-2. Annual NOx emissions for 2002, 2009, and 2018 in the VISTAS states 

Kentucky Regional Haze SIP 

 

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Summary of Emission Inventories for 2002, 2009, and 2018

Tables 7.2.3-1, 7.2.3-2, and 7.2.3-3 are summaries of the 2002, 2009, and 2018 emission 

inventory, respectively. The complete inventory and discussion of the methodology is contained 

in Appendix D. 

Table 7.2.3-1. 2002 Emissions Inventory Summary for Kentucky (tons per year). 

VOC NOx PM2.5 PM10 NH3 SO2 

Point 46,315 240,362 14,219 21,421 995 529,182 

Area 98,713 40,966 51,763 240,226 51,246 41,941 

On-Road Mobile 103,503 156,417 2,697 3,723 5,055 6,308 

Non-Road Mobile 44,805 104,571 6,046 6,425 31 14,043 

Biogenics 630,506 21,090 0 0 0 0 

TOTAL 923,842 563,406 74,725 271,795 57,327 591,474 

Table 7.2.3-2. 2009 Emissions Inventory Summary for Kentucky. 

VOC NOx PM2.5 PM10 NH3 SO2 

Point 49,154 129,778 15,966 23,637 1,160 326,611 

Area 97,379 43,548 52,553 248,844 53,115 43,222 

On-Road Mobile 73,942 101,182 1,920 2,976 5,796 759 

Non-Road Mobile 38,558 94,752 5,203 5,544 34 9,180 

Biogenics 630,506 21,090 NA NA NA NA 

TOTAL 889,539 390,350 75,642 281,001 60,105 379,772 

Table 7.2.3-3. 2018 Emissions Inventory Summary for Kentucky. 

VOC NOx PM2.5 PM10 NH3 SO2 

Point 57,287 105,411 18,172 26,848 1,377 266,745 

Area 106,827 45,806 53,955 262,719 55,321 44,322 

On-Road Mobile 47,066 52,263 1,272 2,580 7,811 763 

Non-Road Mobile 30,920 79,392 4,256 4,556 40 8,592 

Biogenics 630,506 21,090 NA NA NA NA 

TOTAL 872,606 303,962 77,655 296,703 64,549 320,422 

7.2.4 Model Results for the 2018 Inventory Compared to the Uniform Rate of Progress 

Glidepaths for Kentucky’s Class I Area 

Using 2000 - 2004 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. The average values represent the 

current visibility conditions. 

Kentucky Regional Haze SIP 

 

45
The predicted visibility improvement is calculated by comparing the 2002 typical year modeling 

results for the 12-km grid to the 2018 12-km modeling results to develop a relative reduction 

factor. This factor is then applied to the current visibility condition values to estimate the future 

visibility. Detailed discussions about how the relative reduction factors are calculated can be 

found in Appendix G. 

For the 20% worst days in Kentucky’s Class I area, Figure 7.2.4-1 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 (purple line) Similarly, for the 20% best days in the area, Figure 7.2.4-2 

graphically compares visibility with no degradation over the first planning period (red line) to the 

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

and state programs (purple line). 

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 7.2.4-1. Reasonable progress assessment compared to Uniform Rate of Progress for 

20% worst days at Mammoth Cave National Park. 

Kentucky Regional Haze SIP 

 

46
Reasonable Progress Assessment 

 Mammoth Cave - 20% Best Days

New IMPROVE Equation, 12 km grid

16.51 16.51 16.51

15.57

4.99

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)

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

Figure 7.2.4-2 Reasonable progress assessment for 20% best days at Mammoth Cave NP. 

Note that for Mammoth Cave, 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 Mammoth Cave, a 4.73 dv improvement in 

visibility would meet uniform rate of progress in 2018; expected emissions reductions by 2018 

are projected to achieve a 5.81 dv improvement. In fact, as illustrated in Figure 7.2.4-3, visibility 

improvements at all the VISTAS mountain Class I areas and most of the coastal Class I areas are 

projected to be better than the uniform rate of progress. In Figure 7.2.4-3 the percentage of the 

target reduction achieved for Kentucky’s Class I area using the new IMPROVE equation is an 

estimated 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. As illustrated in Figure 

7.2.4-4, 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 emission reductions. In Figure 7.2.4-4 the percentage of the 

target achieved for the Kentucky’s Class I area is an 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). 

Kentucky Regional Haze SIP 

 

47
0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

COHU

DOSOGRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVEROKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

COHU

DOSOGRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVEROKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

COHU

DOSOGRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVEROKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

Figure 7.2.4-3. Projected visibility improvement on 20 percent worst visibility days at 

VISTAS and neighboring Class I areas for 2018 (12 km grid) 

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

COHU

DOSO

GRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVER

OKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

COHU

DOSO

GRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVER

OKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

Figure 7.2.4-4. Projected visibility improvement on 20 percent best visibility days at 

VISTAS and neighboring Class I areas for 2018 (12 km grid) 

Kentucky Regional Haze SIP 

 

48
The expected change in visibility at Mammoth Cave between 2000-2004 baseline conditions on the 20 

percent worst days and 2018 projections is illustrated in Figure 7.2.4-5. In contrast, natural background 

visibility conditions for the 20 percent worst days are illustrated at Mammoth Cave in Figure 7.2.4-6. 

These images were generated using WINHAZE, a photographic imaging tool that accounts for the effect 

of concentrations of fine particle components and relative humidity on visibility. These images try to 

illustrate that notable improvements in visibility are expected by 2018 and that significantly greater 

improvements are needed to reach natural background conditions. 

20% Haziest Days at Mammoth Cave 

Figure 7.2.4-5. Visibility improvement on 20 percent haziest days at Mammoth Cave 

National Park between 2000-2004 baseline conditions (left) and 2018 projected visibility 

(right). Image generated using WinHaze. 

Kentucky Regional Haze SIP 

 

49
Natural Background Visibility at Mammoth Cave

Figure 7.2.4-6. Projected visibility on 20 percent haziest days for natural background 

visibility conditions at Mammoth Cave National Park. Image generated using WinHaze. 

7.3 Relative Contribution from International Emissions to Visibility Impairment in 2018 at 

VISTAS Class I areas 

Emissions from Mexico, Canada, Central America, Asia, and Africa contribute to PM2.5 

loadings and visibility impairment at Class I areas in the continental United States. To evaluate 

the relative contribution of international emissions to visibility at Class I areas in the 

southeastern United States, VISTAS used a combination of modeling results from the global 

three-dimensional chemical transport model (GEOS-Chem) and CMAQ. VISTAS used the 

GEOS-Chem global model to generate initial and boundary conditions for the CMAQ modeling 

domain. GEOS-Chem was run for the 2002 modeling year using a 4 x 5 degree horizontal grid 

resolution and a 3-hour temporal resolution. Because emissions were based on monthly 

averages, the model does not capture the episodic variability in emissions. The GEOS-Chem 

outputs were used to calculate initial and boundary conditions for the national CMAQ modeling 

domain. The national CMAQ domain included portions of Canada and Mexico, so emissions for 

these countries were included within the national CMAQ modeling domain or as part of the 

boundary conditions outside the national modeling domain, as appropriate. 

Two complementary methods were used to calculate the impact of international emissions at 

Class I areas. Because the international emissions inventory used in GEOS-CHEM did not 

distinguish between wildfires and anthropogenic fires, all international fire emissions were 

assumed to be wildfire, and the contributions attributable to international anthropogenic fires are 

underestimated in these projections. 

Kentucky Regional Haze SIP 

 

50
1) International emissions are represented by the difference between two GEOS-Chem runs. 

In the first run United States anthropogenic emissions were removed, and in the second 

run both United States and international anthropogenic emissions were removed. The 

difference represents international anthropogenic emissions, in the absence of United 

States anthropogenic emissions (e.g. compared to 2064 levels). Harvard University 

provided GEOS-Chem results to VISTAS for 2002 international contribution on 4 x 5 

degree grid. Concurrently Harvard modeling for the Electric Power Research Institute 

(EPRI) provided GEOS-Chem results for 2001 international contribution on a 1 x 1 

degree grid scale. 

2) International emissions are represented by the difference between two CMAQ 36-km 

simulations, both using 2018 Base F emissions and boundary conditions from GEOSChem. In the first CMAQ run, all global natural and anthropogenic emissions in 2018 

are active. In the second CMAQ run, only global (United States and international) 

natural emissions are active. Here the impacts of international emissions are compared 

against 2018 conditions rather than natural background conditions. 

VISTAS has compared its results to results from other RPOs on the impact of international 

emissions and boundary conditions on visibility at Class I areas in 2002; the results were 

similar. 

As illustrated in Figure 7.3-1 for annual average contributions to sulfate at VISTAS and 

neighboring Class I areas, the estimated international contributions are higher at Class I areas 

near the Canadian and Mexican borders and along the eastern coast. The estimated 

international contribution is higher using CMAQ than in the GEOS-Chem runs because the 

grid scale is finer (more accurate dispersion of emissions) and because the background 

atmosphere includes loadings from current United States anthropogenic emissions (greater 

photochemical activity). Similar charts for nitrate and organic carbon mass, for impacts on 

20 percent worst visibility days, and for impacts of international emissions on calculated light 

extinction are included in Appendix H. 

Kentucky Regional Haze SIP 

 

51
Transboundary Man-Made Impacts

0.0

0.2

0.4

0.6

0.8

1.0

1.2

BRIG

HEGL

CACR

MINGUPBU

BRETEVER

CHAS

SAMA

COHU

OKEF

ROMA

SIPS

SHRO

GRSM

LIGO

MACA

SWAN

JARI

DOSO

SHEN

(NH

4) SO

2

4 Conc. (

g/m

3

)

GEOS_4x5 GEOS_1x1 CMAQ

Figure 7.3-1. Estimated international emissions contributions to sulfate at VISTAS 

and neighboring Class I areas. 

Kentucky Regional Haze SIP 

 

52
In Figure 7.3-2 CMAQ projections of contributions from international emissions to PM mass on 20 

percent worst visibility days in 2002 at Mammoth Cave, Kentucky are compared to United States 

domestic contributions to PM components at the site on those days. 

MACA1

Domestic and International Aerosol Mass by Species

20% Worst Days (2002)

0

5

10

15

20

25

30

35

40

Domestic

International

Domestic

International

Domestic

International

Domestic

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Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

International

Domestic

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Domestic

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Domestic

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Domestic

International

3/27 5/29 6/1 6/4 6/19 6/22 7/4 7/10 7/16 7/22 7/25 7/31 8/3 8/6 8/12 8/21 8/24 8/27 9/2 9/8 9/11 9/17 9/20 12/7

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

Figure 7.3-2. PM component concentrations from US domestic sources on 20 percent worst 

visibility days in 2002 (left bars) and CMAQ-simulated international contributions (right 

bars) at Mammoth Cave, Kentucky. 

Although VISTAS assessed impacts from international emissions at the Class I areas, these 

modeling runs were to provide information to the states to understand what the potential impacts 

may be at their Class I areas. The modeling showed that for Kentucky’s Class I area Mammoth 

Cave the impacts from international emissions were 1.27 dv of the projected current conditions. 

Since good projected emissions for areas outside of the continental United States are not readily 

available, there is no real way to assess what the impacts from international emissions would be 

for 2018, other than to assume that it would be approximately same amount as for the baseline 

current conditions. Therefore, the KYDAQ will not be accounting for international emissions in 

setting the 2018 reasonable progress goals for its Class I areas. 

Nevertheless, as the atmosphere becomes closer to natural background conditions in the future, 

the incremental contribution from international emissions will become more important. The 

information is included in this SIP documentation to provide reference for future assessments of 

reasonable progress. 

Kentucky Regional Haze SIP 

 

53
7.4 Relative Contributions to Visibility Impairment: Pollutants, Source Categories, and 

Geographic Areas 

An important step toward identifying potential reasonable control measures is to identify the key 

pollutants contributing to visibility impairment at each Class I area. To understand the relative 

benefit of further reducing emissions from different pollutants, source sectors, and geographic 

areas, VISTAS engaged the Georgia Institute of Technology to perform emission sensitivity 

model runs using CMAQ. Emissions sensitivities were initially performed for three episodes 

representing winter and summer conditions: Jan 2002, July 2001, and July 2002. These runs 

used the initial 2018 projections inventory and considered 30 percent reductions from specific 

pollutants, source categories, and geographic areas. As part of a separate effort, emissions 

sensitivities were repeated using a preliminary 2009 projection inventory and two, month-long 

episodes from 2002: Jun 1 – Jul 10 and Nov 19 – Dec 19. The emissions in 2009 were reduced 

by 30 percent for each pollutant sensitivity run. The pollutant contributions that were evaluated 

were: 

• SO2 from EGU sources in each VISTAS state, other RPOs in the VISTAS 12 km grid, 

and Boundary Conditions from outside the 12 km domain. 

• SO2 from non-EGU point sources in each VISTAS state, other RPOs, and Boundary 

Conditions 

• NOx from ground level sources (on-road plus off-road plus area) in each VISTAS state 

and other RPOs. In the VISTAS states, these reductions were only applied to specific 

counties that were of concern for 8-hour ozone nonattainment. 

• NOx from point (EGU plus non-EGU) sources in each VISTAS state and other RPOs 

• NH3 from all sources in VISTAS and other RPOs 

• Volatile Organic Compounds from anthropogenic and biogenic sources in the 12 km 

modeling domain 

• Primary Carbon from all ground level sources in each VISTAS state and other RPOs. In 

the VISTAS states, these reductions were only applied to specific counties that were of 

concern for PM2.5 nonattainment. 

• Primary Carbon from all point sources in each VISTAS state and other RPOs 

• Primary Carbon from all fires in each VISTAS state and other RPOs 

While the 2009 sensitivity analyses cannot be used to judge the absolute contributions from each 

state or source sector, the results do indicate relative level of response among pollutants, sectors, 

and geographic areas. The KYDAQ decided to use the 2009 sensitivities to assess relative 

contribution to visibility impairment from various source sectors and believes this is an 

appropriate use of this data since the use of the emissions sensitivities is to qualitatively 

understand how reductions in emissions from various source sectors would impact visibility at 

Class I areas. 

Results are shown in Figures 7.4-1 below for the average of the 20 percent worst visibility days 

for Kentucky’s Class I area. Responses for 20 percent worst days were calculated by averaging 

Kentucky Regional Haze SIP 

 

54
the responses of the 20 percent worst days that were modeled in the two episodes. For 

Kentucky’s site, responses on six of the 20 percent worst visibility days were included in these 

graphics. 

Mammoth_Cave, KY (Worst)

-20.00

-15.00

-10.00

-5.00

0.00

5.00

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

Mammoth_Cave, KY (Worst)

-20.00

-15.00

-10.00

-5.00

0.00

5.00

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 7.4-1. CMAQ projections of visibility responses on 20 percent worst days at 

Mammoth Cave to 30 percent reductions from a 2009 inventory for visibility-reducing 

pollutants in different source categories and geographic areas. 

As Figure 7.4-1 illustrates, the greatest visibility benefits on the 20 percent worst days for the 

Kentucky’s Class I area are projected to result from further reducing SO2 from EGUs. At the 

mountain Class I areas, benefits are projected from SO2 reductions from EGUs in several 

VISTAS states including Alabama, Georgia, Kentucky, North Carolina, South Carolina, 

Tennessee, Virginia, and West Virginia. Contributions from other RPOs and SO2 coming from 

outside the boundary are also significant. The greatest benefit would likely be from further 

reductions from other VISTAS states, the MRPO, and outside the boundary. Additional, smaller 

benefits are projected from additional SO2 emission reductions from non-utility, industrial point 

Kentucky Regional Haze SIP 

 

55
sources. The pattern of relative SO2 contributions from non-EGUs among the various VISTAS 

states is similar to the pattern of relative SO2 contributions from EGUs. 

Because ammonium nitrate is a small contributor to PM2.5 mass and visibility impairment on the 

20 percent worst days at the mountain Class I areas, the benefits of reducing NOx and NH3 

emissions at these sites are small. 

VOC emissions do contribute to visibility impairment, but as shown in the charts above, this 

contribution is from biogenic sources such as vegetative emissions. Controlling anthropogenic 

sources of VOC emissions has little if any visibility benefit at the Class I areas. Reducing 

primary carbon from point sources, ground level sources or fires are projected to have small to 

no visibility benefit. This is consistent with the monitoring data that shows that most of 

measured organic carbon is secondary in origin and primary carbon is only a small fraction of the 

total measured carbon (Appendix B). Reducing carbon from fires was not found to be effective 

because there was little fire activity at these sites on the days modeled in the sensitivity analyses. 

Note that these results from the emission sensitivity runs are consistent with the conclusions 

drawn from the 2000-2004 baseline monitoring data (see Section 2.4). The results indicate that 

sulfate is the dominant contributor to visibility impairment on the 20 percent worst days at all 

sites, and that ammonium nitrate may be important for sites where the 20 percent worst days 

occur in the winter. KYDAQ concludes that reducing SO2 emissions from EGUs in the Midwest 

RPO would have the greatest visibility benefit for Mammoth Cave. Contributions from other 

VISTAS states are also significant for this area. These results are consistent with the CMAQ 

model results indicating that contributions from international emissions to visibility impairment 

at VISTAS Class I areas are greater closer to the boundaries of the modeling domain (see 

summary in Section 7.3 and further discussion in Appendix H). 

7.5 What Control Determinations Represent Best Available Retrofit Technology for 

Individual Sources? 

Section 169A of the CAA directs States to assess certain large emission sources for additional 

controls in order to address visibility impacts. States are directed to conduct BART 

determinations for such sources in specific source categories, and which contribute to visibility 

impairment in Class I areas. The 1999 regional haze rule includes the BART requirement, and 

directs States to include BART in their regional haze SIPs. On July 6, 2005, the USEPA 

published a revised final rule, including Appendix Y to 40 CFR Part 51, the Guidelines for BART 

Determinations Under the Regional Haze Rule (hereinafter referred to as the “BART 

Guidelines”) that provides direction to states on determining which of these sources should be 

subject to BART, and how to determine BART for each source. 

A BART-eligible source is one which has the potential to emit 250 tons or more of a visibilityimpairing air pollutant, was put in place 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 

Kentucky Regional Haze SIP 

 

56
which may reasonably be anticipated to cause or contribute to any impairment of visibility in any 

such area.’’ 

For those sources subject to BART, 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. 

7.5.1 Kentucky BART-Eligible Sources 

The following is a list of BART-eligible sources in Kentucky. See Appendix L for detailed 

information regarding each of the BART-eligible sources: 

• American Electric Power Big Sandy Plant 

• AK Steel Corporation. - Coke Mfg Plant 

• AK Steel Corporation - Steel Plant 

• Alcan Primary Products Corporation 

• Arch Chemicals Inc. 

• Calgon Carbon Corporation 

• Century Aluminum 

• Commonwealth Aluminum Lewisport LLC 

• Duke Energy East Bend Station 

• E.ON U.S Brown Station 

• E.ON U.S Cane Run Station 

• E.ON U.S Ghent Station 

• E.ON U.S Mill Creek Station 

• East Kentucky Power Cooperative Cooper Station 

• East Kentucky Power Cooperative Spurlock Station 

• Henderson Power and Light 

• Marathon Petroleum Company Refinery 

• Martin County Coal Corporation 

• NewPage Corporation Wickliffe Paper Company 

• Owensboro Municipal Utilities 

• Pinnacle Processing Inc. 

• TVA Paradise Plant 

• Western Kentucky Energy Coleman Station 

• Western Kentucky Energy Green Station 

• Western Kentucky Energy Reid/Henderson Station 

• Westlake Vinyls Inc. 

The BART-eligible sources were identified using the methodology in the BART Guidelines. 

Kentucky Regional Haze SIP 

 

57
• One or more emissions units at the facility fit within one of the 26 categories listed in the 

BART Guidelines; 

• The emission unit(s) were in existence on August 7, 1977 and began operation at some 

point on or after August 7, 1962; and 

• The potential emissions considering enforceable limits from all emission units identified 

in the previous two bullets emission units were 250 tons or more per year of any of these 

visibility-impairing pollutants: SO2, NOx, and PM10. 

The BART Guidelines recommend addressing these visibility-impairing pollutants: SO2, NOx, 

and particulate matter, and suggest that States use their best judgment in determining whether to 

address VOC or ammonia emissions. The KYDAQ addressed SO2 and NOx, and used 

particulate matter less than 10 microns in diameter (PM10) as an indicator for particulate matter 

to identify BART-eligible units, as the BART Guidelines recommend. As discussed in detail in 

Appendix L, VISTAS modeling demonstrated that VOCs and ammonia from point sources are 

not visibility-impairing pollutants. For this reason, the KYDAQ did not evaluate emissions of 

VOCs and ammonia in BART determinations. Additional BART modeling information and 

BART related information regarding KYDAQ BART-eligible sources is available in Appendix 

L. 

The following five KYDAQ sources were determined not to be BART-eligible based on the 

BART methodology in the BART Guidelines. These sources were discussed with EPA in the 

January 2006. Documentation and correspondence regarding these sources is available in 

Appendix L. 

• Arkema (Formerly Atofina Chemicals) 

• E.I. Dupont Inc. 

• Cc Metals & Alloys Inc. 

• ISP Chemicals Inc. 

• Kingsford Manufacturing Co. 

7.5.2 Determination of Sources Subject to BART in Kentucky 

Under the BART Guidelines, the KYDAQ may consider exempting some sources from BART if 

it is determined that they do not cause or contribute to visibility impairment in a Class I area. In 

accordance with the BART guidelines, the KYDAQ chose to perform source-specific analyses to 

determine which sources cause or contribute to visibility impairment using the CALPUFF 

model. The CALPUFF modeling protocol used for determining which facilities are subject to 

BART is included in Appendix L. In accordance with the Guidelines, a contribution threshold of 

0.5 dv was used for determining which sources were subject to BART. Detailed discussions 

about how a threshold of 0.5 dv meets the USEPA’s BART guidelines can be found in 

Appendix L. 

All of Kentucky’s twenty-six BART-eligible sources had BART exemption-modeling 

demonstrations performed; nine of the sources that had Q/d of less than 10 for actual 2002 SO2 

emissions had exemption modeling performed through VISTAS contractor TRC and 17 sources 

performed the BART exemption modeling with their own contractor. Twenty-one of the twentyKentucky Regional Haze SIP 

 

58
six sources were able to demonstrate exemption from BART (< 0.5 dv) either with 12 km or 4 

km modeling. Results of these demonstrations are summarized in Table 7.5.2-1 as follows. 

Additional details are available in Appendix L. Facilities found to be subject to BART were 

required to complete a BART determination analysis. 

Table 7.5.2-1 represents the facilities that were able to demonstrate exemption from BART based 

on CALPUFF modeling conducted using the VISTAS modeling protocol and either the old 

IMPROVE equation or new IMPROVE equation. The KYDAQ is proposing to exempt the units 

listed in Table 7.5.2-1. For further details about the BART exemption modeling, please refer to 

Appendix L. 

Table 7.5.2-1. Kentucky BART Exemption Modeling Results for Sources Exempted From BART 

Source Class I Area Impact 

(Change 

in DV) 

Modeling 

Duke Energy East Bend Station Mammoth Cave (210 km) 0.242 12 km Max dv value 

Owensboro Municipal Utilities Mammoth Cave (93 km) 0.432 4km 8th Highest dv value 

Mingo (289 km) 0.053 4km 8th Highest dv value 

AK Steel Corporation - Steel Plant Dolly Sods (287 km) 0.346 4km Max dv value 

James River Face (295 km) 0.386 4km Max dv value 

Linville Gorge (293) 0.358 4km Max dv value 

Otter Creek (261) 0.442 4km Max dv value 

Great Smokey Mt. (308 km) 0.190 4km 8th Highest dv value 

AK Steel Corp. - Coke Mfg Plant Dolly Sods (282 km) 0.180 12 km Max dv value 

Great Smokey Mt. 1 (304 km) 0.262 12 km Max dv value 

James River Face (288 km) 0.182 12 km Max dv value 

Linville Gorge (287 km) 0.155 12 km Max dv value 

Otter Creek (257 km) 0.208 12 km Max dv value 

Martin County Coal Corporation Dolly Sods1 (305 km) 0.068 12 km Max dv value 

Great Smokey Mt. (226 km) 0.135 12 km Max dv value 

James River Face (265 km) 0.085 12 km Max dv value 

Joyce Kilmer-Slickrock (285 km) 0.121 12 km Max dv value 

Linville Gorge (207 km) 0.131 12 km Max dv value 

Otter Creek (280 km) 0.077 12 km Max dv value 

Shining Rock (259 km) 0.103 12 km Max dv value 

Pinnacle Processing Inc. Great Smokey Mt. (235 km) 0.108 12 km Max dv value 

James River Face (262) 0.070 12 km Max dv value 

Joyce Kilmer-Slickrock (294 km) 0.053 12 km Max dv value 

Linville Gorge (214 km) 0.077 12 km Max dv value 

Otter Creek (272 km) 0.015 12 km Max dv value 

Shining Rock (268 km) 0.021 12 km Max dv value 

Arch Chemicals Inc. Mammoth Cave (83 km) 0.417 4km 8th Highest dv value 

Commonwealth Aluminum Lewisport LLC Mammoth Cave (94 km) 0.489 12 km Max dv value 

Mingo (304 km) 0.052 12 km Max dv value 

Henderson Power and Light Mammoth Cave (134 km) 0.302 12 km Max dv value 

Mingo (238 km) 0.084 12 km Max dv value 

Kentucky Regional Haze SIP 

 

59
Table 7.5.2-1. Kentucky BART Exemption Modeling Results for Sources Exempted From BART 

Source Class I Area Impact 

(Change 

in DV) 

Modeling 

Calgon Carbon Corporation Dolly Sods (284 km) 0.133 12 km Max dv value 

Great Smokey Mt. (290 km) 0.191 12 km Max dv value 

James River Face (282 km) 0.098 12 km Max dv value 

Linville Gorge (273 km) 0.103 12 km Max dv value 

Otter Creek (259 km) 0.157 12 km Max dv value 

Westlake Vinyls Inc. Mammoth Cave (183 km) 0.150 12 km Max dv value 

Mingo (156 km) 0.167 12 km Max dv value 

Sipsey1 (309 km) 0.084 12 km Max dv value 

Century Aluminum* Mammoth Cave (100 km)* 0.446 4km 8th Highest dv value 

Alcan Primary Products Corporation Mammoth Cave (118 km) 0.467 4km 8th Highest dv value 

Mingo (244 km) 0.184 4km 8th Highest dv value 

NewPage**Corporation Wickliffe PaperCo. Mammoth Cave (250 km)** 0.102 4km 8th Highest dv value 

Mingo (91 km) 0.291 4km 8th Highest dv value 

Sipsey (319 km) 0.060 4km 8th Highest dv value 

Western Kentucky Energy Coleman Station Mammoth Cave (91 km) 0.368 4km 8th Highest dv value 

Western Kentucky Energy Reid/Henderson 

Station*** 

Mammoth Cave (118 km) 0.464*** ***4km 8th Highest dv 

value 

Mingo (244 km) 0.072 4km 8th Highest dv value 

Western Kentucky Energy Green Station Mammoth Cave (118 km) 0.217 4km 8th Highest dv value 

Mingo (244 km) 0.039 4km 8th Highest dv value 

 Marathon Petroleum Company Dolly Sods (287 km) 0.055 12 km Max dv value 

Great Smokey Mt. (293 km) 0.056 12 km Max dv value 

James River Face (287 km) 0.079 12 km Max dv value 

Linville Gorge (276 km) 0.041 12 km Max dv value 

Otter Creek (261 km) 0.086 12 km Max dv value 

E. ON U.S. Brown Station Mammoth Cave (130) km) 0.410 4km 8th Highest dv value 

Great Smokey Mt. (250 km) 0.210 4km 8th Highest dv value 

Joyce Kilmer-Slickrock (265 km) 0.153 4km 8th Highest dv value 

E. ON U.S. Cane Run Station Mammoth Cave (100) km) 0.378 4km 8th Highest dv value 

E. ON U.S. Ghent Station Mammoth Cave (190) km) 0.292 4km 8th Highest dv value 

*Century Aluminum and **NewPage modeled below 0.5 dv with and without the new improve equation. 

***Western Kentucky Energy Reid/Henderson Station BART exemption modeling was based exclusively on the use 

of the new improve equation. A copy of a request to EPA Region 4 requesting approval of the use of the new 

improve equation and a letter from EPA granting its approval of the request for these three sources are available in 

Appendix L.9. The modeled values in the above table for Century Aluminum and NewPage are for the old improve 

equation. The values for Western Kentucky Energy Reid/Henderson are for the new improve equation. 

In Table 7.5.2-2, five of the twenty-six Kentucky BART-eligible sources that were unable to 

demonstrate exemption from BART based on CALPUFF modeling conducted using the VISTAS 

BART Modeling Protocol are provided.. The five sources found subject to BART are EGUs that 

are subject to BART because of their inorganic condensible particulate emissions (SO3, H2SO4). 

These subject BART sources were required to complete BART determination modeling, which 

included a five factor analysis, to determine appropriate BART controls for PM. 

Kentucky Regional Haze SIP 

 

60
Table 7.5.2-2. Kentucky BART Exemption Modeling Results for BART-Subject Sources 

Source Class I Areas Impact 

(Change 

in DV) 

Modeling 

East Kentucky Power (EKPC) 

Cooperative Spurlock Station Mammoth Cave (251 km) 1.834 4km 8th Highest dv value

East Kentucky Power (EKPC) 

Cooperative Cooper Station Mammoth Cave (130 km) 7.376 4km 8th Highest dv value

Great Smoky Mountains National Park 

(162 km) 6.763 4km 8th Highest dv value

Joyce Kilmer-Slickrock Wilderness 

(178 km) 4.974 4km 8th Highest dv value

Cohutta Wilderness Area (221 km) 3.363 4km 8th Highest dv value

Shinning Rock (233 km) 2.022 4km 8th Highest dv value

Linville Gorge Wilderness Area (267 km) 1.885 4km 8th Highest dv value

TVA Paradise Fossil Steam Plant Mammoth Cave (63 km) 3.93 4km 8th Highest dv value

Mingo (283 km) 0.865 4km 8th Highest dv value

American Electric Power (AEP) 

Big Sandy Plant Dolly Sods (291 km) 1.027 4km 8th Highest dv value

James River Face (279 km) 1.052 4km 8th Highest dv value

Linville Gorge (256 km) 0.835 4km 8th Highest dv value

Otter Creek (266 km) 1.285 4km 8th Highest dv value

E. ON U.S. Mill Creek Station Mammoth Cave (90 km) 2.265 4km 8th Highest dv value

Fourteen of Kentucky’s twenty-six BART-eligible sources are EGUs that are subject to CAIR. 

The USEPA has determined that, as a whole, the CAIR cap-and-trade program improves 

visibility more than implementing BART for individual sources in states affected by CAIR. A 

State that opts to participate in the CAIR program under 40 CFR 96.201-.224 (Subpart AAA 

through EEE) need not require affected BART-eligible EGUs to install, operate, and maintain 

BART for SO2 or NOx emissions. Given that most BART-eligible units have existing or are 

installing scrubbers and NOx controls, and since Kentucky is participating in CAIR and accepts 

the USEPA’s overall finding that CAIR “substitutes” for BART for NOx and SO2, Kentucky’s 

EGUs were allowed to submit BART exemption modeling demonstrations for PM emissions 

only. Nine of the fourteen Kentucky EGUs demonstrated that they do not contribute to visibility 

impairment in any Class I area. 

Kentucky Regional Haze SIP 

 

61
In total twenty-one of Kentucky’s twenty-six BART-eligible sources were able to demonstrate 

that they did not cause or contribute to visibility impairment in any Class I area within 300 km of 

the source. 

7.5.3 Determination of BART Requirements for Subject-to-BART Sources 

Table 7.5.3-1 presents BART determination modeling results for the five Kentucky EGU sources 

that were unable to demonstrate a contribution of less than 0.5 dv at all Class I areas within 300 

km from their source location. These five sources are considered to be “subject to BART” and 

were required to submit BART determination modeling containing their evaluation of potential 

BART control options and proposed BART determinations. Each of these sources has agreed to 

install emission controls to address inorganic condensible particulate emissions (SO3/H2SO4), 

which is causing the sources to be subject to BART. The BART determination resulting controls 

are provided in the Table 7.5.3-1 that follows and they were taken to public hearing concurrent 

with the public hearing on Kentucky’s Regional Haze SIP. Table 7.5.3-2 that follows, in 

addition to the emission controls, provides the source’s BART emission limits and timeframes 

for compliance. Applicable BART controls and emission limits will be incorporated into the 

sources’ Title V permit as appropriate or upon renewal. In addition, since TVA had previously 

indicated to the KYDAQ its plans to install hydrated lime injection controls on TVA Paradise 

Units 1-3 to mitigate opacity due to SO3 emissions and that additional controls are not costeffective at this time, the KYDAQ has determined BART to be no control for TVA Paradise 

Units 1-3. However, as related by TVA, the hydrated lime injection controls for TVA Paradise 

Units 1-3 will be in place well before the BART controls are required; will achieve the reduction 

in visibility impacts listed in the Draft Implementation Plan (Kentucky Regional Haze SIP); and 

will be included in TVA Paradise’s Title V permit. Specifically, regarding the installation of 

hydrated lime injection controls for TVA Paradise Units 1-3, TVA has communicated to 

KYDAQ its proposed plan that provides for permitting activities to proceed in July 2008; for 

construction to begin in mid-2009 on Unit 3 with construction for Unit 1 and 2 to follow; and for 

controls to be operating on all three TVA Paradise units possibly by the fall of 2010. Also, as 

indicated in the E.ON U.S. Mill Creek BART determination submittal, the average cost for 

installing sorbent controls on all four Mill Creek units is about the same (an estimated 5.1 

million $/dv). However, sorbent injection at all four units would mean an additional total capital 

investment of $8.8 million as compared to controls only on the larger Units 3 and 4. Therefore, 

E.ON U.S. concluded that BART should be the installation of sorbent injection controls on the 

larger Mill Creek Units 3 and 4 since they can achieve an estimated 70 percent of the total dv 

improvement achieved by controlling all four units. Given the extra cost for the lesser additional 

dv improvement for Units 1 and 2, the Cabinet agreed that BART for Mill Creek is the 

installation of sorbent injection controls on the larger Units 3 and 4. For further details about the 

BART determination modeling for the five BART-Subject sources, please refer to Appendix L. 

Kentucky Regional Haze SIP 

 

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Table 7.5.3-1 Kentucky BART Determination Modeling Results for BART-Subject Sources 

Source Class I Areas BART Controls to 

Be Installed* 98th 

Percentile 

Impact 

Before 

BART 

Controls 

(Change in 

dv) 

98th

Percentile 

Impact with 

BART 

Controls 

(Change in 

dv) 

BART 

Determination 

Control 

Visibility 

Improvement 

From 98th

Percentile 

value 

(Change in dv)

East Kentucky 

Power Cooperative 

(EKPC) Spurlock 

Station 

Mammoth Cave (251 km) 

EKPC per a consent 

decree and for BART 

will install a wet FGD 

and wet ESP at EKPC 

Spurlock Units 1 and 

2 that will address 

condensible 

particulate emissions 

and other visibility 

impairing pollutants.

1.834 0.213 1.621 

East Kentucky 

Power Cooperative 

(EKPC) Cooper 

Station 

Mammoth Cave (130) km 7.376 0.252 7.124 

Great Smoky Mountains National Park 

(162 km) 6.763 0.219 6.544 

Joyce Kilmer-Slickrock Wilderness 

(178 km) 4.974 0.122 4.852 

Cohutta Wilderness Area (221 km) 3.363 0.087 3.276 

Shinning Rock (233 km) 2.022 0.049 1.973 

Linville Gorge Wilderness Area 

 (267 km) 

EKPC per a consent 

decree and for BART 

will install a wet FGD 

and wet ESP at EKPC 

Cooper Units 1 and 2 

that will address 

condensible 

particulate emissions 

and other visibility 

impairing pollutants.

1.885 0.046 1.839 

TVA Paradise 

Fossil Steam Plant* Mammoth Cave (63 km) 

U1- 1.285 

U2- 1.285 

U3- 1.842

 4.412 

3.930 

0.606 

0.606 

0.836

2.048 

2.048 

0.679 

0.679 

1.006

2.364 

1.882 

Mingo (283 km) 

*Although not for 

BART, TVA 

previously indicated 

to KYDAQ its 

plans to install 

hydrated lime 

injection controls 

on TVA Paradise 

Units 1-3 to 

mitigate opacity due 

to SO3 emissions.

U1- 0.251 

U2- 0.251 

U3- 0.381

 0.883 

0.865 

0.116 

0.116 

0.166

0.398 

0.398 

0.135 

0.135 

0.215

0.485 

0.467 

Kentucky Regional Haze SIP 

 

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Table 7.5.3-1 Kentucky BART Determination Modeling Results for BART-Subject Sources 

Source Class I Areas BART Controls to 

Be Installed* 98th 

Percentile 

Impact 

Before 

BART 

Controls 

(Change in 

dv) 

98th

Percentile 

Impact with 

BART 

Controls 

(Change in 

dv) 

BART 

Determination 

Control 

Visibility 

Improvement 

From 98th

Percentile 

value 

(Change in dv)

American Electric 

Power Big Sandy 

Plant (AEP) 

Dolly Sods (291 km) 1.027 0.496 0.531 

James River Face (279 km) 1.052 0.457 0.595 

Linville Gorge (256 km) 0.835 

 

0.364 0.471 

Otter Creek (266 km) 

Per a consent decree 

and BART, AEP will 

install ammonia 

injection on Unit 1 

and a FGD scrubber 

on Unit 2 to address 

condensible 

particulate emissions 

and other visibility 

impairing pollutants.

1.285 0.558 0.697 

E.ON U.S Mill** 

Creek Station Mammoth Cave (90 km) 

**E.ON U.S. for 

BART will install 

sorbent injection 

controls on the larger 

Units 3-4 to mitigate 

condensable 

particulate emissions.

2.265 1.440 0.825 

*Since TVA had previously indicated to the KYDAQ its plans to install hydrated lime injection controls on TVA Paradise Units 

1-3 to mitigate opacity due to SO3 emissions and that additional controls are not cost-effective at this time, the KYDAQ has 

determined BART to be no control for TVA Paradise Units 1-3. **Given the extra cost for the lesser additional dv improvement 

for Units 1 and 2, the Cabinet agreed that BART for Mill Creek is the installation of sorbent injection controls on the larger Units 

3 and 4. 

Kentucky Regional Haze SIP 

 

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Table 7.5.3-2 Kentucky BART Controls, Emission Limits, and Compliance Timeframes for BARTSubject Sources 

Kentucky BART 

Subject Source 

BART Controls To 

Be Installed 

BART Emission 

Limits 

Inclusion in 

Title V 

Permit 

Timeframe for 

Compliance with 

BART Emission 

Limits\Controls 

East Kentucky 

Power Cooperative 

(EKPC) 

Spurlock Units 1 

and 2 and Cooper 

Units 1 and 2 

Install wet FGD and 

wet ESP on Spurlock 

Units 1 and 2 and 

Cooper Units 1 and 2.

A 07/02/07 EKPC 

consent decree 

provides a filterable 

PM emission rate of 

0.030 lb/MMBTU, 

which was utilized to 

demonstrate modeled 

visibility 

improvement. 

Emission 

limits and 

controls will 

be included in 

the source’s 

Title V Permit 

as appropriate 

or on renewal. 

Expeditiously as 

practicable, but 

no later than 5 

years after EPA 

approves 

Kentucky’s 

Regional Haze 

SIP. 

AEP Big Sandy 

Unit 1 

Unit 2 

Install ammonia 

injection controls on 

Unit 1 and a FGD on 

Unit 2. 

Inorganic 

Condensible 

Particulate Limits 

(modeled as sulfates): 

101.0 lb/hr (H2SO4) 

127.0 lb/hr (H2SO4) 

Emission 

limits and 

controls will 

be included in 

the source’s 

Title V Permit 

as appropriate 

or on renewal. 

Expeditiously as 

practicable, but 

no later than 5 

years after EPA 

approves 

Kentucky’s 

Regional Haze 

SIP. 

KYDAQ will 

work with AEP to 

install the FGD 

scrubber on AEP 

Big Sandy Unit 2 

as expeditiously 

as practicable. 

TVA Paradise* 

Unit 1 

Unit 2 

Unit 3 

*Although not for 

BART, TVA 

previously indicated 

to KYDAQ its plans 

to install hydrated 

lime injection 

controls on TVA 

Paradise Units 1-3 to 

mitigate opacity due 

to SO3 emissions. 

*NA *Although not 

for BART, 

TVA has 

indicated that 

its planned 

SO3 controls 

for Paradise 

Units 1-3 will 

be included in 

its Title V 

Permit as 

appropriate or 

on renewal. 

*Although not for 

BART, TVA in 

its BART 

Determination 

has indicated the 

SO3 controls will 

be in place on 

Paradise Units 1-

3 well before 

BART controls 

are required. 

Specifically, TVA 

has related to 

Kentucky Regional Haze SIP 

 

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Table 7.5.3-2 Kentucky BART Controls, Emission Limits, and Compliance Timeframes for BARTSubject Sources 

Kentucky BART 

Subject Source 

BART Controls To 

Be Installed 

BART Emission 

Limits 

Inclusion in 

Title V 

Permit 

Timeframe for 

Compliance with 

BART Emission 

Limits\Controls 

KYDAQ its 

proposed plan to 

have hydrated 

lime injection 

controls operating 

on all three TVA 

Paradise units 

possibly by the 

fall of 2010. 

E.ON U.S.** 

Mill Creek 

Unit 3 

Unit 4 

**Install sorbent 

injection controls on 

larger Units 3 and 4 

to control SO3 

emissions and 

continue to utilize 

existing ESPs to 

control PM emissions 

for Units 1 through 4. 

SO3 Limit: 

0.015 lb/MMBTU 

0.015 lb/MMBTU 

**Emission 

limits and 

controls will 

be included in 

the source’s 

Title V Permit 

as appropriate 

or on renewal. 

**Expeditiously 

as practicable, but 

no later than 5 

years after EPA 

approves 

Kentucky’s 

Regional Haze 

SIP. 

*Since TVA had previously indicated to the KYDAQ its plans to install hydrated lime injection controls on TVA Paradise Units 

1-3 to mitigate opacity due to SO3 emissions and that additional controls are not cost-effective at this time, the KYDAQ has 

determined BART to be no control for TVA Paradise Units 1-3. **Given the extra cost for the lesser additional dv improvement 

for Units 1 and 2, the Cabinet agreed that BART for Mill Creek is the installation of sorbent injection controls on the larger Units 

3 and 4. 

7.6 Relative Contributions to Visibility Impairment: Geographic Areas of Influence for 

Kentucky’s Class I Area 

Once it was determined that SO2 emission reductions from EGU and non-EGU point sources in 

the VISTAS states would be the most effective sources to control to improve visibility at 

Kentucky’s Class I area, the next step was to identify the specific geographic areas that most 

likely influence visibility in each Class I area, and then to identify the major SO2 point sources 

located in those geographic areas. An SO2 Area of Influence was defined for each Class I area 

to represent the geographic area containing sources that would likely have the greatest impact on 

visibility at that Class I area. All SO2 point sources within these Areas of Influence were 

identified and ranked by their 2018 emissions. The following sections contain a broad overview 

of the steps in the Area of Influence analyses. See Appendix H for a more detailed discussion of 

these analyses and plots for Kentucky’s Class I area. The plots that follow are only for 

Kentucky’s Class I area since KYDAQ’s Q/d times RTMax area of influence analysis identified 

no Kentucky sources that contributed one percent or more to visibility impairment for any other 

Class I area examined by VISTAS. 

Kentucky Regional Haze SIP 

 

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7.6.1 Back Trajectory Analyses 

The first step was to generate meteorological back trajectories for IMPROVE monitoring sites in 

Kentucky and neighboring Class I areas for the 2000-2004 20 percent worst days baseline 

period. 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. 

Figure 7.6.1-1 is an example back trajectory analysis for Mammoth Cave National Park for the 

20 percent worst days in 2002. 

Back Trajectories for 20% Worst Days for 2002

Mammoth Cave, KY

Figure 7.6.1-1. Example back trajectories for 20 percent worst visibility days in 2002 for 

Mammoth Cave National Park. 

Kentucky Regional Haze SIP 

 

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Trajectories were started at 100 meters and 500 meters above the surface and run backward from 

the site for 72-hours. These individual back trajectories for 20 percent worst days in 2002 were 

also useful in evaluating model performance for individual days at the Class I areas. 

7.6.2 Residence Time Plots 

The next step was to plot residence time for each Class I area using five years of back trajectories 

for the 20 percent worst visibility days in 2000-2004. Residence time is the frequency that winds 

pass over a specific geographic area on the path to a Class I area. Separate residence time plots 

were generated using trajectories with 100m and 500m start heights. As illustrated in 

Figure 7.6.2-1, winds influencing Mammoth Cave on the 20 percent worst days come from all 

directions and there is no single predominant wind direction influencing the 20 percent worst 

visibility days. 

Residence Time for 20% Worst Days in 2000-2004 

Mammoth Cave, KY

Figure 7.6.2-1 Example residence time plot for 20 percent worst visibility days in 

2000-2004 for Mammoth Cave National Park. Based on trajectories with 100m 

start height. 

Kentucky Regional Haze SIP 

 

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7.6.3 SO2 Areas of Influence 

As discussed earlier, the KYDAQ has determined that reductions in SO2 emissions would have 

the greatest visibility impact. Therefore, sulfate extinction-weighted residence time plots were 

developed to define the geographic area with highest probability of influencing the receptor on 

the 20% worst days in the 2000-2004 baseline period that were dominated by sulfate. Each back 

trajectory was weighted by sulfate extinction for that day. This allows the focus to be on the 20 

percent worst days that are influenced by sulfate and places less importance on days influenced 

by organic carbon from fires. Sulfate-weighted back trajectories for the 20 percent worst days 

were combined for 5 years of data. The resulting sulfate extinction-weighted residence time 

plots were used to define the geographic Area of Influence for sources of SO2 emissions. In 

Figure 7.6.3-1 the area representing 10 percent or greater residence time is outlined in red and 

the area representing 5 percent or greater residence time is outlined in gray. 

The VISTAS states discussed various options as to what percentage of sulfate extinctionweighted area of influence should be assessed. It was determined that for this planning period 

that the area of influence defined by 5% or greater sulfate extinction-weighted residence time 

provided a reasonable universe of sources that may cause visibility impairment at a Class I area. 

The VISTAS states recognized that this did not represent 100% of the sources contributing to 

visibility impairment at Class I areas, but rather a reasonable universe of sources to consider 

during the first planning period. 

SO2 Area of Influence for 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%.

Kentucky Regional Haze SIP 

 

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Figure 7.6.3-1 Example SO2 Area of Influence plot for sulfate extinction weighted 

residence time for 20 percent worst visibility days in 2000-2004 for Mammoth Cave 

National Park based on trajectories with 100m start height. 

7.6.4 Emissions Sources within SO2 Areas of Influence 

Residence time plots were then combined with geographically-gridded emission data based on 

the 2002 baseline and 2018 emissions inventories. Plots were generated for the Areas of 

Influence defined by trajectories with 100m and 500 m start heights. 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, in kilometers, between the center of the grid cell in which a source is located and the 

center of the grid cell in which the IMPROVE monitor is located. The distance-weighted point 

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

residence times at a spatial resolution of 36-km. 

The final step was to combine the residence times and gridded emissions data in plots and data 

sets. The distance weighted (1/d) gridded point source SO2 emissions were multiplied by the 

total extinction-weighted back-trajectory residence times on a grid cell by grid cell basis. These 

results were then normalized by the domain-wide total and displayed as a percentage. The 

analysis was done using both the 2002 and 2018 emissions inventories. 

Figure 7.6.4-1 illustrates the 2002 and 2018 distance weighted gridded emissions multiplied by 

sulfate extinction weighted residence time for Mammoth Cave National Park. These maps help 

visualize where the emissions reductions will be occurring between 2002 and 2018. The change 

in SO2 emissions between 2002 and 2018 can be seen by comparing emissions source strengths 

in the two plots. Note the emissions from each source are normalized by the total emissions in 

the domain. Sources that reduce SO2 emissions by 2018 will show a lower contribution to 

emissions in the domain. On the 2018, map the grid cells with these sources will show a lighter 

color gradient than on the 2002 map. For example, SO2 reductions from EGUs from west to east 

in Kentucky for CAIR can be seen by comparing the 2002 and 2018 maps. Because the total 

emissions in the domain are smaller in 2018, a source that does not change emissions between 

2002 and 2018 may actually appear to increase in importance in 2018 compared to 2002. 

Although the sulfate extinction-weighted residence times were developed using the 2002 

emissions, the 2018 emissions weighted by residence time plots still provides useful information. 

The KYDAQ does not believe that the area of influence would have changed significantly if 

sulfate extinction-weighted residence times were developed using the 2018 emissions. However, 

if the area of influence would have been smaller using 2018 emissions due to reductions 

expected in the EGU source sector, then the area developed to identify potential sources would 

be considered conservative. 

Kentucky Regional Haze SIP 

 

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2002 vs 2018 SO2 Emissions weighted by Residence Time

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%.

Max Value = 19%

Figure 7.6.4-1. Mammoth Cave National Park 2002 (left) and 2018 (right) SO2 distance 

weighted emissions times SO4 extinction-weighted residence time plots. 

Figure 7.6.4-2 illustrates similar plots for 2018 for Mammoth Cave National Park. These plots 

illustrate the relative importance of Kentucky sources of SO2 compared to sources in 

neighboring states. Additional analyses, including 2002 and 2018 distance weighted emissions 

times residence-time plots for the Class I area in Kentucky and neighboring states are contained 

in Appendix H. These analyses are serving as the basis for consultation among the VISTAS 

states. 

Kentucky Regional Haze SIP 

 

71
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 weighted by Residence Time

Mammoth Cave, KY

Figure 7.6.4-2. Mammoth Cave 2018 SO2 distance weighted emissions times SO4 

extinction-weighted residence time plot. 

Finally, Table 7.6.4-1 shows, in tabular form, the relative contributions of point source SO2 

emissions from nearby states to Kentucky’s Class I area. These percentages were estimated by 

multiplying the maximum residence time to the emissions over distance. 

Table 7.6.4-1 2018 Point Source SO2 Contribution to Kentucky’s Class I Area by State 

State 

Kentucky Class I Area 

 Mammoth Cave 

Alabama 4.33% 

Arkansas 

Delaware 

Florida 

Georgia 1.79% 

Illinois 0.53% 

Indiana 21.22% 

Iowa 

Kansas 

Kentucky Regional Haze SIP 

 

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State 

Kentucky Class I Area 

 Mammoth Cave 

Kentucky 53.60 

Louisiana 

Maryland 

Michigan 

Minnesota 

Mississippi 

Missouri 0.53 

Nebraska 

New Jersey 

New York 

North Carolina 

Ohio 3.95% 

Pennsylvania 

South Carolina 

Tennessee 13.46% 

Virginia 

West Virginia 0.54 

Wisconsin 

Total 100.00% 

7.6.5 Specific Source Types in the Areas of Influence for Kentucky’s Class I Area 

The next step in the analysis was to review the emissions inventories to determine the source 

categories, as well as specific sources, found to have the greatest impact on visibility in 

Kentucky’s Class I area. Lists of SO2 point sources within the Areas of Influence for each Class 

I areas were developed using the VISTAS 2002 base year and 2018 future year emissions. For 

this purpose, the Area of Influence was defined as the counties with maximum sulfate extinction 

weighted residence time greater than five. For SO2 sources within each Area of Influence, the 

following attributes were defined for each individual unit: 

• State, county, and source (plant), and industry identification codes 

• SO2 emissions for 2002 and 2018 

• 2018 control efficiency 

• Distance to Class I areas (defined by distance to the monitor at the Class I area) 

• Emissions divided by distance (Q/d), a metric that accounts for the dispersion of 

emissions over distance 

• Maximum sulfate extinction weighted residence time (RTmax) 

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

categories in each SO2 Area of Influence to determine which major categories had the highest 

residual contribution to the area in 2018. It was also important to identify reductions that are 

projected to occur between 2002 and 2018 within each category or at specific units. This 

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

Kentucky Regional Haze SIP 

 

73
controlled under the future year base case had the potential for reduction. Once the highest 

source types were identified, subcategories within those source types were reviewed. The 

contributions from major source categories to the 2018 inventory for the SO2 Areas of Influence 

for the Kentucky Class I areas are listed in Table 7.6.5-1. In these tables, the source categories 

are broken out by the USEPA’s Tier 1 report categories and are defined below: 

• Fuel Comb Elec Utility Emissions from all fuel combustions at utility boilers 

• Fuel Comb Industrial Emissions from all fuel combustions at industrial boilers 

• Fuel Comb Other Emissions from all fuel combustions from 

commercial/institutional and residential sources (i.e., 

fireplaces, natural gas stoves, oil heaters, etc.) 

• Chemical & Allied Product Mfg Emissions from chemical manufacturing processes 

• Metal Processing Emissions from metal processing operations 

• Petroleum & Related Industries Emissions from petroleum refineries & related industries

• Other Industrial Processes All other industrial processing not previously mentioned 

• Solvent Utilization Emissions from solvent utilization such as degreasing 

operations, surface coating operations, etc. 

• Storage & Transport Emissions from storage and transport of petroleum, 

organic and inorganic products 

• Waste Disposal & Recycling Emissions from open burning, incineration, landfills, 

publicly owned treatment works, treatment storage 

and/or disposal facilities, wastewater treatment facilities 

• Highway Vehicles Emissions from on-road mobile sources 

• Off-highway Emissions from off-road mobile sources 

• Miscellaneous (Ag, Fires) Emissions from agricultural operations, wildland fires, 

and other emissions sources not previously mentioned 

Kentucky Regional Haze SIP 

 

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Table 7.6.5-1. 2018 SO2 Emissions Contributions from Major Source Categories in the 

Area of Influence for Mammoth Cave National Park, Kentucky. 

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%

These tables indicate that for Kentucky’s Class I area, EGUs and industrial boilers are the two 

major sources categories contributing to 2018 SO2 emissions in the Areas of Influence, even 

after implementation of CAIR. Together these two source categories contribute 85 percent of the 

2018 SO2 emissions for the Areas of Influence for Kentucky’s Class I area. Other fuel 

combustion and other industrial processes comprise another 8 percent of the 2018 SO2 

emissions. 

These tables can also be used to evaluate the major source categories contributing to emissions 

of NOx, NH3, and PM emissions in 2018. For instance, highway vehicles and off road vehicles 

are major sources of NOx emissions, in addition to electric utilities and industrial boilers. The 

source category “miscellaneous” (which includes agricultural sources and fires) is the major 

contributor to NH3 and primary PM. However, based upon the 2000 - 2004 reconstructed 

extinction for the 20% worst visibility days (Appendix B), these pollutants are not significant 

contributors to visibility impairment on most days in the baseline period. Additionally, the 

emissions sensitivities discussed in Section 7.4 indicated very small benefits of controlling NOx, 

NH3, and primary PM emissions at Kentucky’s Class I area, but if these emissions were of 

concern, different source categories would need to be addressed. 

The contributions to SO2 emissions in 2018 from the three highest source categories, electric 

utilities, industrial boilers, and other fuel combustion have been further broken out into 

subcategories. Table 7.6.5-2 indicates subcategories for the Areas of Influence for Kentucky’s 

Class I area. Within electric utilities, all the SO2 emissions are attributable to coal fired power 

plants. Within industrial boilers, most emissions are attributable to coal fired boilers with lesser 

Kentucky Regional Haze SIP 

 

75
contributions from oil and gas boilers. Commercial and institutional coal and oil boilers have 

smaller contributions. 

Table 7.6.5-2. 2018 SO2 Emissions Contributions from Major Source Subcategories in the 

Area of Influence for Mammoth Cave National Park, Kentucky. 

Tier MACA

Fuel Comb. Elec. Util.-Coal 66%

Fuel Comb. Elec. Util.-Oil 0%

Fuel Comb. Elec. Util.-Gas 0%

Fuel Comb. Elec. Util.-Other 0%

Fuel Comb. Elec. Util.-Internal Combustion 0%

Fuel Comb. Industrial-Coal 14%

Fuel Comb. Industrial-Oil 3%

Fuel Comb. Industrial-Gas 2%

Fuel Comb. Industrial-Other 1%

Fuel Comb. Industrial-Internal Combustion 0%

Fuel Comb. OtherCommercial/Institutional Coal 2%

Fuel Comb. OtherCommercial/Institutional Oil 2%

Fuel Comb. Other-Commercial/Institutional Gas 0%

Fuel Comb. Other-Misc. Fuel Comb. (Except 

Residential) 0%

Fuel Comb. Other-Residential Wood 0%

Fuel Comb. Other-Residential Other 1%

From these analyses, the KYDAQ considered what additional control measures for electric 

utilities and industrial boilers are reasonable. The lists of individual sources are also being used 

to determine if individual sources in other sources categories are major contributors to SO2 

emissions in the Areas of Influence. 

Kentucky Regional Haze SIP 

 

76
7.7 Evaluating the 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 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. 

VISTAS used the USEPA’s AirControlNET database, modified for the VISTAS emission 

inventories, for the non-EGUs. The core of AirControlNET is a relational database system in 

which control technologies are linked to sources within the USEPA 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 Area of Influence 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 

distance-weighted 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. 

Kentucky Regional Haze SIP 

 

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Cost of Compliance: 

As defined in Section 7.6.5, 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 

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 by-product 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. 

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. Installation 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. 

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 

Kentucky Regional Haze SIP 

 

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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 by-product 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. 

Remaining Useful Life: 

The useful remaining life is specific to the unit for which controls are considered. 

7.8 Which Control Measures Represent Reasonable Progress for Individual Sources? 

The following summarizes the process for determining reasonable progress for Kentucky 

sources. For a detailed discussion of the reasonable progress assessments for all units with a 

contribution of greater than one percent to visibility impairment at the Class I area in Kentucky 

or in neighboring states, please see Appendix H. 

Step 1: Determine pollutants of concern. 

VISTAS evaluated the species contribution on the 20 percent worst visibility days in the baseline 

period 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 SAMI. As you 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 the pollutant of primary concern was determined to be SO2, the emissions inventory was 

assessed to determine the source categories that contribute the most SO2 emissions. Since 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 is sufficient for reasonable progress for subject 

EGUs. 

The KYDAQ evaluated the amount of SO2 reduction from the EGU sector resulting from the 

implementation of the CAIR. The EGUs in Kentucky are expected to reduce their 2002 SO2 

emissions by an estimated 54 percent by 2018. Much of that reduction is the result of 

requirements that are predicted by the IPM to meet CAIR. 

To further support EGUs subject to CAIR is sufficient for reasonable progress, a discussion in 

the CAIR rule highlighted below (See Appendix H for 70 FR 25197-25198) addresses the 

reasonable progress factors of cost and time necessary for compliance for these EGUs, and 

Kentucky Regional Haze SIP 

 

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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 

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 

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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). 

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 that Class I area. A full description of this 

process and a list of sources considered in the reasonable progress evaluation can be found in 

Appendix H. 

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. The 

detailed analysis is included in Appendix H.

Results of four-factor analysis 

The following is a brief summary of the Non-EGU four-factor analysis. Additional detail is 

included in Appendix H. 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). 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 

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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 

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. 

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 control cost spreadsheet for Century Aluminum in 

Appendix H). 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 costeffective 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. 

7.9 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 

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82
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 2.4 and demonstrated in Figures 2.4-1 and 2.4-2, elemental carbon 

(sources include agriculture, prescribed wildland fires, and wildfires) is a relatively minor 

contributor to visibility impairment at the Class I area in Kentucky. However, KYDAQ has an 

open burning regulation, 401 KAR 63:005, that establishes requirements for the control of 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. The exact benefits from 

the reduction in open burning emissions can not be quantified at this time and will not be 

included in Final VISTAS modeling. 

Also as discussed in Section 2.4 and demonstrated in Figures 2.4-1 and 2.4-2, fine soils are a 

relatively minor contributor to visibility impairment at the Class I areas in Kentucky. 

Nevertheless, in regard to construction activities, KYDAQ has a fugitive emissions regulation, 

401 KAR 63:010. Fugitive emissions, that provides for the control of fugitive 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. 

In regard to agricultural ammonia, Kentucky, per its CMAQ 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, then it 

is not likely that KYDAQ will modify its regional haze SIP for this reason. 

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83
8.0 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. 

 

Table 8.0-1 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. 

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Table 8.0-1. Kentucky 2018 Reasonable Progress Goals (in decviews) 

Class I Area 

Baseline 

Visibility for 

20% Worst 

Days 

(dv) 

Uniform Rate 

of Progress 

for 20% 

Worst Days 

(dv) 

Reasonable 

Progress Goal 

Modeled for 

20% Worst 

Days 

(Improvement)

(dv) 

Baseline 

Visibility for

20% Best 

Days 

(dv) 

Uniform Rate 

of Progress 

for 20% Best 

Days 

(dv) 

Reasonable 

Progress Goal 

Modeled for 

20% Best 

Days 

(Improvement)

(dv) 

Mammoth 

Cave 

National 

Park, KY 

31.37 26.64 

(4.73)

25.56 

(5.81) 16.51 16.51 (0.00) 

15.57 

(0.94) 

9.0 MONITORING STRATEGY 

The State Implementation Plan is to be accompanied by a strategy for monitoring regional haze 

visibility impairment. Specifically, the Regional Haze Rule states at 40 CFR 51.308(d)(4): 

“(4) Monitoring strategy and other implementation plan requirements. The State must 

submit with the implementation plan a monitoring strategy for measuring, characterizing, 

and reporting of regional haze visibility impairment that is representative of all 

mandatory Class I Federal areas within the State. This monitoring strategy must be 

coordinated with the monitoring strategy required in §51.305 for reasonably attributable 

visibility impairment. Compliance with this requirement may be met through 

participation in the IMPROVE network. The implementation plan must also provide for 

the following: 

(i) The establishment of any additional monitoring sites or equipment needed to 

assess whether reasonable progress goals to address regional haze for all 

mandatory Class I Federal areas within the State are being achieved. 

(ii)-(vi) [Other implementation plan requirements that pertain to reporting and use 

of monitoring data and an emission inventory.]” 

Such monitoring is intended to provide the data needed to satisfy four objectives: 

1. Track the expected visibility improvements resulting from emissions reductions 

identified in this SIP. 

2. Better understand the atmospheric processes of importance to haze. 

3. Identify chemical species in the ambient particulate matter and relate them to 

emissions from sources. 

4. Evaluate regional air quality models for haze and construct relative response factors 

(RRFs) for using those models. 

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85
The primary monitoring network for regional haze, both nationwide and in Kentucky, is the 

IMPROVE network. Given that IMPROVE monitoring data from 2000-2004 serve as the 

baseline for the regional haze program, the future regional haze monitoring strategy must 

necessarily be based on, or directly comparable to, IMPROVE. The IMPROVE measurements 

provide the only long-term record available for tracking visibility improvement or degradation 

and therefore Kentucky intends to rely on the IMPROVE network for complying with the 

regional haze monitoring requirement in the Regional Haze Rule. 

There is currently one IMPROVE site in Kentucky’s Mammoth Cave National Park as provided 

in Table 9.0-1. 

Class I Area IMPROVE Site 

Designation 

Mammoth Cave National Park MACA1 (KY) 

Table 9.0-1. Kentucky Class I Area and Representative IMPROVE Monitor. 

In addition to the IMPROVE measurements, some ongoing long-term limited monitoring 

supported by Federal Land Managers provides additional insight into progress toward regional 

haze goals. Kentucky benefits from the data from these measurements, but is not responsible for 

the funding decisions to maintain these measurements into the future. Such measurements 

include: 

• Web cameras operated by the National Park Service in Mammoth Cave National Park 

KYDAQ and the local air agencies in the State operate a comprehensive PM2.5 network of the 

filter based Federal reference method monitors, continuous mass monitors (TEOMs), and filter 

based speciated monitors. A map of the various locations around the State is included in Figure 

9.0-1. These PM2.5 measurements help the KYDAQ characterize air pollution levels in areas 

across the state, and therefore aid in the analysis of visibility improvement in and near the Class I 

areas. 

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86
Figure 9.0-1 PM2.5 Monitoring Network in Kentucky. 

The IMPROVE measurements are central to Kentucky’s regional haze monitoring strategy, and 

it is difficult to visualize how the objectives listed above could be met without the monitoring 

provided by IMPROVE. Any reduction in the scope of the IMPROVE network in Kentucky 

would jeopardize the State’s ability to demonstrate reasonable progress toward visibility 

improvement in some of its Class I areas. In particular, Kentucky’s regional haze strategy relies 

on emission reductions that will result from the CAIR, which occur on different time scales and 

will most likely not be spatially uniform. Monitoring at every Class I area is important to 

document the different air quality responses to the emissions reductions. 

Because each of the current IMPROVE monitor in Mammoth Cave represents a different 

airshed, reduction of the IMPROVE network by shutting down one of these monitoring sites 

impedes tracking progress at reducing haze at the affected Class I area. In the event this occurs, 

Kentucky, in consultation with the USEPA and relevant Federal Land Managers, will develop an 

alternative approach for meeting the tracking goal, perhaps by seeking contingency funding to 

carry out limited monitoring or by relying on data from nearby urban monitoring sites to 

demonstrate trends in speciated PM2.5 mass. 

Data produced by the IMPROVE monitoring network will be used nearly continuously for 

preparing the 5-year progress reports and the 10-year SIP revisions, each of which relies on 

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87
analysis of the preceding five years of data. Consequently, the monitoring data from the 

IMPROVE sites needs to be readily accessible and to be kept up to date. Presumably, IMPROVE 

will continue to process information from its own measurements at about the same pace and with 

the same attention to quality as it has shown in the recent past. The VIEWS web site has been 

maintained by VISTAS and the other Regional Planning Organizations to provide ready access 

to the IMPROVE data and data analysis tools. KYDAQ is encouraging VISTAS and the other 

RPOs to maintain VIEWS or a similar data management system to facilitate analysis of the 

IMPROVE data. 

10.0 INTERSTATE CONSULTATION 

The VISTAS states have jointly developed the technical analyses to define the visibility 

improvement by 2018 under existing federal and state regulations compared to the uniform rate 

of progress, SO2 Areas of Influence for each Class I area, and methods to prioritize contributions 

from individual sources within the Areas of Influence. The states collectively accept the 

conclusions of these analyses. 

In December 2006, the VISTAS State Air Directors held their first formal consultation meeting 

to review the modeling results and the SO2 Areas of Influence analyses. The Air Directors 

agreed to look at reasonable control measures for sources on the lists for the SO2 Areas of 

Influence. Each state would consider sources within their state and would identify sources in 

neighboring states that they would like to have that neighboring state consider. States 

acknowledged that the review process would differ among states since some Class I areas are 

projected to see visibility improvements near the uniform rate of progress while most Class I 

areas are projected to have greater improvements than uniform rate of progress. 

In May 2007, the VISTAS State Air Directors met for their second formal interstate consultation. 

States shared their lists of sources in their state and neighboring states for each Class I area. 

They also shared their criteria for listing sources and their plans for further interstate 

consultation. A summary of this meeting is included in Appendix J. 

The KYDAQ has evaluated the impact of Kentucky sources on Class I areas in neighboring and 

other states and determined that there are no additional reasonable control measures that should 

be implemented to mitigate impacts in Class I areas in neighboring and other states since no 

Kentucky source was found to contribute one percent or more to visibility impairment for other 

states’ Class I areas (See Appendix H for KYDAQ’s Q/d times RTMax analysis that identified 

sources with one percent or more impact for given Class I areas). Analysis of impacts from 

Kentucky sources and their existing and expected controls are provided in Appendix H. As 

discussed in following text, Kentucky received MANE-VU state requests for support in assuring 

reasonable progress pursuant to certain Kentucky sources. Copies of MANE-VU letters to 

KYDAQ are available in Appendix J. KYDAQ’s response to MANE-VU is reflected in its 

regional haze SIP. In addition, a letter from Tennessee which relates that it does not plan to ask 

Kentucky for additional emission reductions for this first cycle of the regional haze SIP process 

is provided in Appendix J. 

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88
The KYDAQ has evaluated the impact of sources in neighboring states and their impact on 

Mammoth Cave and determined that there are no additional reasonable control measures that 

should be implemented to mitigate impacts on Mammoth Cave at this time. The KYDAQ sent 

letters to the Midwest RPO state of Indiana, the Lake Michigan Air Directors Consortium 

(LADCO), and to the VISTAS state of Tennessee regarding sources outside of Kentucky that 

were determined to contribute one percent or higher to Kentucky’s Class I area. Kentucky 

related in its letters that since the units identified are EGUs subject to CAIR and since 

Kentucky’s Class I area is currently exceeding the uniform rate of progress, Kentucky would not 

be requesting additional emission reductions at this time. Copies of the consultation letters can 

be found in Appendix J. 

In addition, KYDAQ did participate in regional haze consultation regarding CENRAP states of 

Missouri and Arkansas regarding their Central Class I areas. Copies of the consultation letters 

with Missouri and Arkansas and conference call minutes are included in Appendix J. 

The MANE-VU states of Maine, New Jersey, New Hampshire, and Vermont sent letters to 

Kentucky in the spring of 2007 stating that based on 2002 emissions Kentucky contributed to 

visibility impairment to Class I areas in those states. MANE-VU states asked KYDAQ to 

participate in further consultation with these states, and a meeting was held in August 2007, in 

Atlanta, Georgia with VISTAS states. 

The MANE-VU states identified 14 EGUs in Kentucky that they would like to see controlled to 

90% efficiency. They also requested a control strategy to provide a 28% reduction in SO2 

emissions from sources other than EGUs (i.e., Non-EGUs) that would be equivalent to their low 

sulfur fuel oil strategy. Of the 14 Kentucky EGUs identified by MANE-VU, 93% of those 

sources have existing SO2 controls or will have SO2 controls by 2015 or sooner. Kentucky 

EGU existing and expected controls are provided in detail in Appendix H. The KYDAQ 

believes that the significant Kentucky existing and expected EGU emission controls more than 

adequately addresses MANE-VU’s EGU and Non-EGU emission control requests. The letters 

from MANE-VU states and the meeting notes are included in Appendix J. 

11.0 COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN 

REVISIONS 

40 CFR section 51.308(f) requires the KYDAQ to revise its regional haze implementation plan 

and submit a plan revision to USEPA by July 31, 2018 and every ten years thereafter. In 

accordance with the requirements listed in Section 51.308(f) of the federal rule for regional haze, 

Kentucky commits to revising and submitting this regional haze implementation plan by July 31, 

2018 and every ten years thereafter. 

In addition, Section 51.308(g) requires periodic reports evaluating progress towards the 

reasonable progress goals established for each mandatory Class I area. In accordance with the 

requirements listed in Section 51.308(g) of the federal rule for regional haze, the KYDAQ 

commits to submitting a report on reasonable progress to USEPA every five years following the 

initial submittal of the SIP. The report will be in the form of a SIP revision. The reasonable 

Kentucky Regional Haze SIP 

 

89
progress report will evaluate the progress made towards the reasonable progress goal for the 

mandatory Class I area located within Kentucky and in each mandatory Class I area located 

outside Kentucky which may be affected by emissions from within Kentucky. 

The requirements listed in 51.308(g) include the following: 

1. Description of the status of implementation; 

2. Summary of emission reductions achieved thus far, including especially the status of 

implementation of the CAIR compliance plans for EGUs compared to the control 

assumed in the modeling; 

3. Assessment of changes in visibility conditions at each Class I area (current vs. baseline), 

expressed as 5-year averages of annual values for 20 percent best and worst days; 

4. Analysis of emission changes over the 5-year period, identified by source or activity; 

5. Analysis of any significant changes in or out of the State which have impeded progress; 

6. Assessment of the sufficiency of the implementation plan to meet Reasonable progress 

goals (RPGs); and 

7. Review and any modifications to our visibility monitoring plan. 

All requirements listed in 51.308(g) shall be addressed in the SIP revision for reasonable 

progress. In particular, the KYDAQ recognizes that the 2018 projections of EGU controls from 

the IPM runs represent one solution to how the CAIR requirements will be met. By the time of 

the first periodic report, the KYDAQ anticipates that the actual compliance strategy for the 

various utility companies will be much more defined. An assessment of those actual compliance 

plans will be done for the first periodic report. 

The KYDAQ believes that its New Source Review (NSR) regulation for nonattainment areas as 

well as its Prevention of Significant Deterioration (PSD) regulation for attainment areas will 

address emissions from new sources that may locate near a Class I area or increased emissions 

from major modifications to existing sources. In addition to the KYDAQ regulations that would 

govern these sources, consultation with the FLMs is also required for sources that are subject to 

KYDAQ’s NSR/PSD regulations. 

KYDAQ also plans for continued consultation with the FLMs throughout the implementation 

process, including discussion of the implementation process and the most recent IMPROVE 

monitoring and VIEWS data. Consultation between KYDAQ and the FLMs will include early 

involvement of FLMs in the periodic review process and FLMs will receive copies of the revised 

regional haze SIP for comment prior to finalization. 

There are several technical improvements that are recommended in the emissions inventory and 

air quality models that are used to support regulatory decisions for regional haze. These 

improvements recommended, as funding is available, to support the next long term strategy. The 

following is an overall summary; Appendix K contains a fuller discussion of possible technical 

improvements. 

First and foremost, continued improvements are needed in the integrated one-atmosphere air 

quality models that are used to project air quality responses to emissions reductions. As our 

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understanding of partitioning between gaseous and aerosol phases improves, this understanding 

needs to be reflected in the models. Improvements can also be made in how the models handle 

individual pollutants. Sulfate performance for the CMAQ regional air quality model is good 

overall. However sulfate deposition is frequently overestimated in the models, particularly in the 

summer months. At the coastal sites, when winds are blowing from the Gulf of Mexico or 

Atlantic Ocean, CMAQ underestimates measured sulfate at the monitors. CMAQ’s processes 

also should be reviewed for sulfate formation over water. Nitrate is overestimated by the model 

in the winter and underestimated in the summer, although summer monitored values of nitrate 

are very low. Additional improvements in seasonal allocation of ammonia emissions would 

improve model estimates of ammonium nitrate formation. Organic carbon is generally 

underestimated in the summer months. Improvements are needed in the characterization of both 

primary carbon emissions and formation of secondary organic carbon. 

Other improvements needed include better tools for organic carbon source apportionment, and 

more consistent measurement techniques between rural and urban monitoring networks. To 

improve our understanding of the contribution of fire from natural forest fires, prescribed 

burning, land clearing, and agricultural burning, states need improved record keeping. 

Additional improvements to international emissions inventory are also needed, to improve our 

understanding of boundary conditions for our modeling domain and of the contributions from 

international emissions to pollutant concentrations at the VISTAS Class I areas. 

12.0 DETERMINATION OF ADEQUACY OF THE EXISTING PLAN 

Depending on the findings of the five-year progress report, KYDAQ commits to taking one of 

the actions listed in 40 CFR section 51.308(h). The findings of the five-year progress report will 

determine which action is appropriate and necessary. 

List of Possible Actions – 40 CFR section 51.308(h) 

1) KYDAQ may determine that the existing SIP requires no further substantive revision in 

order to achieve established goals. KYDAQ would then provide to the Administrator a 

negative declaration that further revision of the SIP is not needed at this time. 

2) KYDAQ may determine that the existing SIP may be inadequate to ensure reasonable 

progress due to emissions from other states which participated in the regional planning 

process. KYDAQ would then provide notification to the Administrator and the states that 

participated in regional planning. KYDAQ collaborates with states through the regional 

planning process to address the SIP’s deficiencies. 

3) KYDAQ may determine that the current SIP may be inadequate to ensure reasonable 

progress due to emissions from another country. KYDAQ would then provides

notification, along with available information, to the Administrator. 

4) KYDAQ may determine that the existing SIP is inadequate to ensure reasonable progress 

due to emissions within the state. KYDAQ would then take action to revise its SIP to 

address the plan’s deficiencies within one year.

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