west virginiadepartment of environmental protection



# Appendix H Reasonable Progress Evaluation and Long Term Strategy

Promoting a healthy environment.[This page intentionally left blank.]WV Regional Haze SIP Appendix H - i 

## Table of Contents

PURPOSE . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix H - 1
1.0. BASE G CAA CONTROLS

................................... Appendix H - 2 1.1. Point Source Controls

..................................... Appendix H - 5 1.1.a. Electric Generating Units (EGU)

.......................... Appendix H - 5 1.1.b. Non-EGUs

.......................................... Appendix H - 13 1.2. Area Source Controls

..................................... Appendix H - 14 1.3. On-Road Mobile Sources

.................................. Appendix H - 15 1.4. Non-Road

.............................................. Appendix H - 15 1.5. Conclusion

............................................. Appendix H - 16
2.0. UNIFORM RATE OF PROGRESS

............................ Appendix H - 18
3.0. GEORGIA TECH SENSITIVITIES

............................ Appendix H - 19 3.1. Evaluation for Dolly Sods Wilderness Area, WV

............... Appendix H - 19 3.2. Summary

.............................................. Appendix H - 21
4.0. REASONABLE PROGRESS EVALUATION

.................... Appendix H - 22 4.1. Area of Influence Analyses

................................ Appendix H - 22 4.2. Source Type Analyses

.................................... Appendix H - 23 4.3. Back Trajectory Analyses

................................. Appendix H - 23 4.4. Area of Influence Data and Displays

......................... Appendix H - 27 4.5. Importance of Pollutants Other Than Sulfate

.................. Appendix H - 33 4.6. Summary of Emission Inventories Used in Cost Curve Analysis . . Appendix H - 33 4.7. Process in Preparing Files for the Cost Effectiveness Curve Development

...................................................... Appendix H - 36 4.8. Application of AirControlNET Technologies

.................. Appendix H - 37 4.9. Development of AoI-Based Cost Curves

...................... Appendix H - 38
5.0. REASONABLE FURTHER PROGRESS ASSESSMENT

.......... Appendix H - 39
6.0. FOUR FACTOR ANALYSIS

................................. Appendix H - 42 6.1. The Four Statutory Factors

................................ Appendix H - 42 6.1.a. Cost of Compliance

................................... Appendix H - 42 6.1.b. Time Necessary for Compliance

......................... Appendix H - 42 6.1.c. Energy and Non-Air Quality Environmental Impacts of Compliance

................................................... Appendix H - 43 6.1.d. Remaining Useful Life of the Source

..................... Appendix H - 43 6.2. Evaluating Four Statutory Factors for Specific SO 2 Emissions Sources in Each Area of Influence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix H - 43 6.2.a. Cost of Compliance

................................... Appendix H - 44 6.2.b. Time Necessary for Compliance

......................... Appendix H - 45WV Regional Haze SIP Appendix H - ii 6.2.c. Energy and Non-Air Environmental Impacts

............... Appendix H - 45 6.2.d. Remaining Useful Life

................................. Appendix H - 45 6.3. Process of Applying the Statutory Factors

.................... Appendix H - 45
7.0. BART

.................................................... Appendix H - 53 7.1. Background

............................................ Appendix H - 53 7.2. Approach to Implementation of BART Requirements

........... Appendix H - 54 7.3. Identification of BART-eligible Sources

...................... Appendix H - 55 7.4. Contribution Threshold

................................... Appendix H - 56 7.5. Exemption of Point Source Volatile Organic Compounds for BART Purposes

...................................................... Appendix H - 57 7.5.a. Method

............................................. Appendix H - 57 7.5.b. Conclusions

......................................... Appendix H - 59 7.6. Treatment of Ammonia Emissions for BART Purposes

.......... Appendix H - 59 7.6.a. Method

............................................. Appendix H - 59 7.6.b. Conclusions

......................................... Appendix H - 61 8.0. Explanation of BART Exemption Modeling

...................... Appendix H - 61 8.1. Background

............................................ Appendix H - 61 8.2. West Virginia BART Sources – Exemption Modeling

........... Appendix H - 62 8.3. BART-Eligible Sources in Other States Within 300 km of West Virginia Class I Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Appendix H - 68 8.4. Use of the New IMPROVE Equation

..................... Appendix H - 69 8.5. Conclusion

............................................. Appendix H - 69
9.0. BART DETERMINATIONS

.................................. Appendix H - 70 9.1. BART Subject Sources

................................... Appendix H - 70
10.0. FINAL LONG TERM STRATEGY AND REASONABLE PROGRESS GOALS

......................................................... Appendix H - 71 10.1. Long-Term Strategy

...................................... Appendix H - 71 10.2. What Additional Emissions Controls Were Considered as Part of the Long-Term Strategy for Visibility Improvement by 2018?

................. Appendix H - 72 10.3. Reasonable Progress Goals

................................ Appendix H - 74WV Regional Haze SIP Appendix H - iii 

## List of Attachments Appendix H.1. Cost Effectiveness Curve Design Appendix H.2. Spreadsheets - AoI and Control Costs Appendix H.3. Excerpt from Clean Air Inters tate Rule Preamble - EPA Cost Analysis Appendix H.4. Assessment of Reasonable Progress for Regional Haze in MANE-VU Class I Areas Appendix H.5. WV Rules to Control Particulate MatterWV Regional Haze SIP Appendix H - iv [This page intentionally left blank.]WV Regional Haze SIP Appendix H - 1 

### PURPOSE The purpose of this appendix is to outline West Virginia’s strategy for complying with the requirement to set and meet Reasonable Progress Go als (RPGs) as part of our Regional Haze SIP under 40 CFR 51.308(d)(1), and the requirements for establishing best available retrofit (BART) controls under 40 CFR 51.308(e). In the 1977 amendments to the Clean Air Act (CAA), Congress set a national goal for visibility as “the prevention of any future, and the remedying of any existing, impairment of visibility in mandatory Class I Federal areas which impairment results from manmade pollution”. The regional haze rule (RHR) at 40 CFR 51.308(d) requires states to demonstrate reasonable progress toward meeting the goal of a return to natural visibility conditions by 2064. As a guide for reasonable progress, the RHR directs states to gr aphically show what would be a “uniform rate of progress” toward natural conditions for each Class I area. This is known as the “glidepath. The RHR then requires states to establish RPGs for visibility improvement at each affected Class I area covering each approximately 10-year period until 2064. Therefore, our first set of RPGs will comprise our long term strategy (LTS) covering the period from the present until 2018. This appendix provides an overview of this first LTS. In addition, a specific component of each state’s first LTS is dictated by the specifi c BART requirements in 40 CFR 51.308(e). This appendix will also include a discussion of our strategy for developing those BART requirements. Our long term strategy contains the following components: 1. Inventory of all controls required or expected under all federal and state regulations by 2009 and 2018. We refer to these controls as “on the books” or “on the way” (OTB/OTW). 2. Modeled expected visibility improvement from OTB/OTW (Base G) controls and Comparison of Base G results for 2018 to the uniform rate of progress, or “glidepath” for each Class I area. 3. Discussion of emissions sensitivity model runs to help determine which pollutants and source categories are contributing the most to visibility impairment at Class I areas (runs conducted by Georgia Institute of Technology). 4. Examination of Area of Influence (AoIs) projections for each of the State’s Class I areas, and also for any surrounding states’ Class I areas whose AoI includes any West Virginia counties, to determine which specific sources are most likely to be impairing visibility at specific Class I areas. 5. Application of the four “statutory factors,” listed in 40 CFR 51.308(d)(1)(i)(A) to those sources identified in the previous step. 6. Using the results of the four factor analys es in development of control determinations for specific sources. 7. Identification of BART-eligible sources. 8. BART exemption modeling for BART-eligible sources. 9. BART determinations for sources subject to BART.WV Regional Haze SIP Appendix H - 2 10. Modeling demonstration of visibility improvement after inclusion of BART and reasonable progress control determinations. 11. Determination of RPGs based on the visibility improvement expected by 2018. 

### 1.0. BASE G CAA CONTROLS 2009 and 2018 emissions projections include the following existing state and federal regulations:

• Clean Air Interstate Rule (CAIR) + Clean Air Mercury Rule (CAMR). Utility projections are based on the Integrated Planning Model (IPM) which is also used by EPA in regulatory applications. CAIR will permanently cap emissions of sulfur dioxide (SO 2 ) and nitrogen oxides (NOx) in the eastern United States. CAIR achieves large reductions of and/or NOx emissions across 28 eastern states and the District of Columbia. When fully implemented, CAIR will reduce SO 2 emissions in these states by over 70 percent and NOx emissions by over 60 percent from 2003 levels. The Clean Air Mercury Rule will build on EPA’s Clean Air Interstate Rule (CAIR) to significantly reduce emissions from coal-fired power plants -- the largest remaining sources of mercury emissions in the country. When fully implemented, these rules will reduce utility emissions of mercury from 48 tons a year to 15 tons, a reduction of nearly 70 percent.

• NOx SIP Call. Phase I of the NOx SIP call applies to certain Electric Generating Units (EGUs) and large non-EGUs, including large industrial boilers and turbines, and cement kilns. States in the The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) region affected by the NOx SIP call have developed rules for the control of NOx emissions that have been approved by EPA. We reviewed the available State rules and guidance documents to determine the affected sources and ozone season allowances. We also obtained and reviewed information in the EPA’s CAMD NOx Allowance Tracking System – Allowances Held Report. Since these controls are to be in effect by the year 2007, we capped the emissions for NOx SIP call affected sources at 2007 levels and carried forward the capped levels for the 2009/2018 future year inventories. This rule will result in a 68 percent reduction in NOx emissions from the State’s large stationary combustion sources by 2006.

• NC Clean Smokestacks Act. Under the act, enacted in 2002, coal-fired power plants in North Carolina must achieve a 77-percent cut in nitrogen oxide (NOx) emissions by 2009 and a 73-percent cut in sulfur dioxide (SO 2 ) emissions by 2013.

• Consent Agreements (Santee Cooper, TECO, VEPCO, Gulf Power, EKPC, Dupont, and Stone Container). • Santee Cooper: A 2004 consent agreement calls for Santee Cooper to install and commence operation of continuous emission control equipment for PM/SO 2/NO x emissions; comply with system-wide annual PM/SO 2/NO x emissions limits; agree not to buy, sell or trade SO 2/NO x allowances allocated to Santee Cooper System as a result of said agreement; and to comply with emission unit limits of said agreement.WV Regional Haze SIP Appendix H - 3 • TECO: 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 NO x , SO 2 and PM.
• VEPCO: Virginia Electric and Power Co. agreed to spend $1.2 billion between by 2013 to eliminate 237,000 tons of SO 2 and NO x emissions each year from eight coal-fired electricity generating plants in Virginia and West Virginia.
• Gulf Power 7: A 2002 agreement calls for Gulf Power to upgrade its operation to cut NO x emission rates by 61 percent at its Crist 7 generating plant by 2007 with major reductions beginning in early 2005. The Crist plant is a significant source of nitrogen oxide emissions in the Pensacola area.
• EKPC: A July 2, 2007 consent agreement between the EPA and East Kentucky Power Cooperative requires the utility to reduce its emissions of SO 2 by 54,000 tons per year and its emissions of NO x by 8,000 tons per year, by installing and operating selective catalytic reduction (SCR) technology; lo w-NOx burners, and PM and mercury Continuous Emissions Monitors at the utility’s Spurlock, Dale and Cooper Plants. According to the EPA, total emissions from the plants will decrease between 50 and 75 percent from 2005 levels. As with all federal consent decrees, EKPC is precluded from using reductions required under other programs, such as CAIR, to meet the reduction requirements of the consent decree. EKPC is expected to spend $654 million to install pollution controls. • Dupont : A 2007 agreement calls for E. I. Dupont Nemours & Company’s James River plant to install dual absorption pollution control equipment by September 1, 2009, resulting in emission reductions of approximately 1,000 tons SO 2 annually.
• Stone Container : A 2004 agreement calls for the West Point Paper Mill owned by Smurfit/Stone Container to control with a wet scrubber the SO 2 emissions of the #8 Power Boiler. This control device should result in reductions of over 3,500 tons of SO 2 in 2018.
• AEP : American Electric Power agreed to spend $4.6 billion dollars to eliminate 72,000 tons of NO x emissions each year by 2016 and 174,000 tons of SO 2 emissions each year by 2018 from sixteen plants located in Indiana, Kentucky, Ohio, Virginia and West Virginia.

• 1-hr ozone SIPs (Atlanta / Birmingham / Northern Kentucky). The purpose of a state implementation plan (SIP) is to demonstrate attainment or maintenance of the 1-hour ozone National Ambient Air Quality Standard (NAAQS). States must determine which Clean Air Act requirements are applicable to their area and submit plans to EPA for public comment and approval.WV Regional Haze SIP Appendix H - 4 • Heavy Duty Diesel (2007) Engine Standard. A PM emissions standard for new heavy-duty engines of 0.01 grams per brake-horsepower-hour (b /bhp-hr), to take full effect for diesels in the 2007 model year. Also includes standards for NOx and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/bhp-hr, resp ectively. These NOx and NMHC standards will be phased in together between 2007 and 2010. Sulfur in diesel fuel must be lowered to enable modern pollution-control technology to be effective on these trucks and buses. EPA required a 97 percent reduction in the sulfur content of highway diesel fuel from its current level of 500 parts per million (low-sulfur diesel or LSD) to 15 parts per million (ultra-low sulfur diesel or ULSD).

• Tier 2 Tailpipe. Tier 2 is a fleet averaging program, modeled after the California LEV II standards. Manufacturers can produce vehicles with emissions ranging from relatively dirty to zero, but the mix of vehicles a manufacturer sells each year must have average NOx emissions below a specified value.

• Large Spark Ignition and Recreational Vehicle Rule. Sets emission standards for these categories of nonroad engines and vehicles.

• Nonroad Diesel Rule. Implements a low sulfur fuel requirement that affects future CMV and locomotive emissions.

• Industrial Boiler / Process Heater / RICE MACT. EPA issued final rules to substantially reduce emissions of toxic air pollutants from industrial, commercial and institutional boilers, process heaters and from stationary reciproca ting 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. These rules also reduce emissions of sulfur dioxide and particulate matter in conjunctions with the toxic air pollutant reductions. The applied Maximum Achievable Control Technology (MACT) control efficiencies were 4% for SO 2 and 40% for PM10 and PM2.5. (EPA’s industrial boiler MACT rules were vacated on June 8, 2007. The VISTAS “best and final” modeling run will make adjustments to the control assumptions due to this MACT rule based on the input from each state. West Virginia has determined that the control assumptions should remain, since case-by-case MACT under CAA Section 112j is triggered and the state does not expect the final controls to be any less stringent than previously required by the vacated rule.) • 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 EPA estimates to be small compared to the overall inventory. • VOC 2-, 4-, 7-, and 10-year MACT Standard s. The point source MACTs and associated emission reductions were designed from Federal Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD) sta ff. We did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States.WV Regional Haze SIP Appendix H - 5 The following are source category specific contro ls used to project future year emissions inventories:
1.1. Point Source Controls Different approaches were used for the Electric Generating Unit (EGU) and the non-EGU sectors of the point source inventory: • For the EGUs, the State relied primarily on the Integrated Planning Model ® (IPM ® ) to project future generation as well as to calculate the impact of future emission control programs, to include CAIR and CAMR. The IPM results were adjusted based on State and local (S/L) agency knowledge of planned emission controls at specific EGUs. • For non-EGUs, we used recently updated growth and control data consistent with the data used in EPA’s CAIR analyses, and supplemented these data with available S/L agency input and updated fuel use forecast data for the U.S. Department of Energy. For both sectors, we generated 2009 and 2018 inventories for a combined on-the-books (OTB)and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounts for post2002 emission reductions from promulgated and propos ed federal, state, local, and site-specific control programs as of July 1, 2004. 1.1.a. Electric Generating Units (EGU) S/L agencies specified a number of changes to the IPM results to better reflect current information on when and where future controls would occur. These changes to the IPM results primarily involved S/L agency addition or subtr action of future emission controls based on the best available data from state rules, enforcement agreements, compliance plans, permits, and discussions/commitments from individual companies. Duke Energy and Progress Energy updated their plans for complying with North Carolina’s Clean Smokestack’s Act. These plans vary substantially from the IPM results both in terms of current and future controls and timing of these controls. As a result, NC DENR replaced the IPM emission projections for 2009 with projections from the 2006 Duke Energy and Progress Energy compliance plan. NC DENR elected to use the IPM results for 2018. However, the IPM results for 2018 proclaim a scrubber at Duke Lee 3, which will not exist. A re-run of the Base G emissions (Base G2) included this correction. Table 1.1 lists adjustments to IPM control determinations specified by S/L agencies for the Base G 2009/2018 EGU inventories. Table 1-2 lists othe r adjustments to IPM results specified by S/L agencies for Base G 2009/2018 inventories.WV Regional Haze SIP Appendix H - 6 Table 1.1 Adjustments to IPM Control Determinations Specified by S/L Agencies to the Base G 2009/2018 EGU Inventories

State Plant Name & ID Unit NOx Emissions Controls SO 2 Emission Controls 2009 2018 2009 2018 IPM State IPM State IPM State IPM State
AL James H. Miller ORISID=6002 1 & 2 SCR during
ozone season SCR probable year round due to CAIR SCR during
ozone season SCR probable year round due to CAIR None None None None

3 & 4 SCR during
ozone season SCR year round from Consent Decree SCR during
ozone season SCR year round from Consent Decree None Scrubber None Scrubber

Barry ORISID=3 1, 2, 3 None SNCR SCR SNCR None None None None
4 None SNCR SCR SNCR None None Scrubber None
5 None None SCR SCR None None Scrubber None
E C Gaston ORISID=26 1 - 4 SCR None SCR None None None Scrubber None
5 SCR SCR SCR SCR Scrubber None Scrubber None Gorgas ORISID=8 6 & 7 None None None N one None None None None
8 & 9 None None None None N one Scrubber None Scrubber
10 SCR SCR SCR SCR None Scrubber Scrubber Scrubber
Charles R. Lowman ORISID=56 1 None None None None None Scrubber None Scrubber
2 & 3 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber
GA Bowen ORISID=703 1BLR SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions None Scrubber Scrubber
2BLR SCR SCR SCR SCR None Scrubber Scrubber
3BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber
4BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber Wansley ORISID=6052 1 SCR SCR SCR SCR IPM had retrofit scrubbers but little emission reductions Scrubber Scrubber Scrubber

2 SCR SCR SCR SCR None Scrubber Scrubber

Kraft ORISID=733 1, 2 None None None N one None None None None
3 None None SCR None None None None None
McIntosh ORISID=6124 1 None None SCR None None None None NoneTable 1.1 Adjustments to IPM Control Determinations Specified by S/L Agencies to the Base G 2009/2018 EGU Inventories

State Plant Name & ID Unit NOx Emissions Controls SO 2 Emission Controls 2009 2018 2009 2018 IPM State IPM State IPM State IPM State

WV Regional Haze SIP Appendix H - 7 Yates ORISID=728 1 None None None None Scrubbe r Scrubber Scrubber Scrubber 2, 3 None None None N one None None None None
4 - 7 None None SCR None None None Scrubber None
Hammond ORISID=708 1 None None SCR SCR None Scrubber Scrubber Scrubber
2 None None SCR SCR None Scrubber Scrubber Scrubber
3 None None SCR SCR None Scrubber Scrubber Scrubber
4 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber
KY Ghent ORISID=1356 1 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber
2 None None SCR SCR None Scrubber Scrubber Scrubber 3, 4 None SCR SCR SCR None Scrubber Scrubber Scrubber
Coleman ORISID=1381 C1 None None SCR SCR None Scrubber Scrubber Scrubber
C2 None None SCR SCR None Scrubber Scrubber Scrubber
C3 None None SCR SCR None Scrubber Scrubber Scrubber
HMP&L Station 2 H1 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber
H2 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber
E W Brown ORISID=1355 1 None None None None None Scrubber None Scrubber
2 None None SCR SCR None Scrubber Scrubber Scrubber
3 None None SCR SCR None Scrubber Scrubber Scrubber
SC Jeffries ORISID=3319 3 SCR None SCR None None None None None
4 None None None None None None None None
Wateree ORISID=3297 WAT1 SCR SCR SCR SCR None Scrubber None Scrubber
WAT2 SCR SCR SCR SCR None Scrubber Scrubber Scrubber Canadys ORISID=3280 CAN1 None None None N one None None None None
CAN2 None None None N one None None None None
CAN3 None None None None N one Scrubber None Scrubber Rainey ORISID=7834 CT1A None SCR None SCR None None None None
CT1B None SCR None SCR None None None None TN Kingston ORISID=3407 1 - 8 SCR SCR SCR SCR None None Scrubber Scrubber
9 None SCR SCR SCR None None Scrubber ScrubberTable 1.1 Adjustments to IPM Control Determinations Specified by S/L Agencies to the Base G 2009/2018 EGU Inventories

State Plant Name & ID Unit NOx Emissions Controls SO 2 Emission Controls 2009 2018 2009 2018 IPM State IPM State IPM State IPM State

WV Regional Haze SIP Appendix H - 8 Johnsonville ORISID=3406 1 - 10 SCR None SCR SCR None None None None

WV Willow Island ORISID=3946 2 SCR None SCR SCR Scrubber None Scrubber Scrubber

Kammer ORISID=3947 1 - 3 SCR None SCR SCR Scrubber None Scrubber Scrubber

Table 1.2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. State Plant Name & ID Unit Nature of Update/Correction
FL Central Power and Lime ORISID=10333 GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. This is point 18 in Florida Crushed Stone (12- 053-0530021). Removed IPM emissions for Central Power and Lime. Cedar Bay Generating ORISID=10672 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Cedar Bay is connected to Stone Container (12-031- 0310067). Replaced IPM emissions with 2002 emissions for Cedar Bay (12-031-0310337) times the growth factors for Stone Container. Indiantown Cogeneration ORISID=50976 GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this facility and the cogeneration facility should not grow faster than the underlying industry. Indiantown is connected to Louis Dreyfus Citrus (12- 085-0850002). Replaced IPM emissions with 2002 emissions for Indiantown (12-085-0850102) times the growth factors for Louis Drefus Citrus.
GA Bowen ORISID=703 1BLR 2BLR 3BLR 4BLR IPM indicated retrofit scrubbers on all 4 units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect scrubbers on 1BLR and 2BLR by 2009. Wansley ORISID=6052 1, 2 IPM indicated retrofit scrubbers on both units in 2009, but the IPM emissions showed little reductions from 2002 levels. Changed emissions to reflect one scrubber on Unit 1 by 2009.Table 1.2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. State Plant Name & ID Unit Nature of Update/Correction

WV Regional Haze SIP Appendix H - 9 Riverside ORISID=734 4 All of plant Riverside was retired from service June 1, 2005; emissions set to zero in 2009 and 2018. McIntosh ORISID=727 CT10A CT10B CT11A CT11B The McIntosh Combined Cycle facility became commercial June 1, 2005. Added 346 tons of NO x and 121 tons of SO 2 per unit to the 2009 and 2018 inventories. Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power Development, Inc. GA specified that the emissions from this proposed plant be included in the 2018 projections. Boilers 1 and 2 added 1,882 tons of NO x and 3,227 tons of SO 2 per unit to the 2018 inventory.
MS R D Morrow ORISID=6061 1, 2 Revised the 2018 emissions to reflect controls not indicated by IPM. The SO 2 emissions are much lower than IPM, but their expected NO x emissions are actually higher than IPM. The controls will be coming online 2009 or 2010, so the 2009 inventory did not change. Jack Watson (2049) Victor J Daniel (6073) Chevron Oil (2047) All MS DEQ specified that the emission projections provided by the Southern Company for their units in Mississippi were to be used instead of the IPM results. NC G G Allen (2718) Belews (80421) Buck (2720) Cliffside (2721) Dan River (2723) Marshall (2727) Riverbend (2732) All Replaced all IPM 2009 results with emission projections from Duke Power’s NC Clean Air Compliance Plan for 2006. Used IPM results for 2018

Asheville (2706) Cape Fear (2708) Lee (2709) Mayo (6250) Roxboro (2712) Sutton (2713) Weatherspoon (2716) All Replaced all IPM 2009 results with emission projections from Progress Energy’s NC Clean Smokestacks Act Calendar Year 2005 Progress Report. Used IPM results for 2018

Dwayne Collier Battle Cogeneration Facility ORISID=10384 GEN1 GEN2 Dwayne Collier Battle is a duplicate entry. This is Cogentrix of Rocky Mount (37-065-3706500146, stacks G-26 and G-27). Duplicate entries were removed both the 2009 and 2018 inventories. Kannapolis Energy Partners ORISID=10626 GEN2 GEN3 Kannapolis Energy emissions are being used as credits for another facility. IPM emissions from this facility (37-025-ORIS10626) were removed from the EGU inventory for 2009 and 2018. Emissions from Kannapolis Energy (37-025-3702500113) were carried forward in the 2009/2018.Table 1.2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. State Plant Name & ID Unit Nature of Update/Correction

WV Regional Haze SIP Appendix H - 10

SC Cross ORISID=130 1, 2 Unit 1: upgrade scrubber from 82 percent to 95 percent removal efficiency by June 30, 2006. Recalculate emissions based on upgrade in control efficiency. Unit 2: upgrade scrubber from 70 percent to 87 percent removal efficiency by June 30, 2006. Recalculate emissions based on upgrade in control efficiency. Winyah ORISID=6249 1 - 4 Unit 1: Install scrubber that meets 95 percent removal efficiency by Dec. 31, 2008; Upgrade ESP from 0.38 to 0.03 lb/mmBTU by Dec. 31, 2008 Unit 2: Replace scrubber with one that meets 95 percent removal efficiency from 45 percent by Dec. 31, 2008; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2008 Unit 3: Upgrade scrubber from 70 percent to 90 percent removal efficiency by Dec. 31, 2012; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2012 Unit 4: Upgrade scrubber from 70 percent to 90 percent removal efficiency by Dec. 31, 2007; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 2007 Recalculated SO 2 and PM emissions based on upgrade in control efficiencies. Dolphus Grainger ORISID=3317 1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate Unit 2: Install low NO x burners that meet 0.46 lb/mmBTU from 0.9 by May 1, 2004. Recalculated NO x emissions using 0.46/lbs/mmBtu and IPM heat input Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 95 percent based on change in allowable emission rate Jeffries ORISID=3319 3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 94.44 percent based on change in allowable emission rate Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. Reduced PM 10 and PM25 emissions in 2018 by 94.44 percent based on change in allowable emission rate
W S Lee ORISID=3264 1, 2 IPM does not indicate that these units are installing SOFA NO x control technology by April 30, 2006 to meet 0.27 lb/mmBTU, down from 0.45 lb/mmBtu. Calculated NO x emissions using IPM heat input and 0.27 lbs/mmBtuTable 1.2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. State Plant Name & ID Unit Nature of Update/Correction

WV Regional Haze SIP Appendix H - 11 Generic Unit ORISID=900545 All All predictions for generic units appear reasonable with the exception of Plant ID ORIS900545 Point ID GSC45 which was modeled in Georgetown County. It will be very difficult to add new generation this close to the Cape Romain Class I area. Santee Cooper has no plans for future generation in Georgetown County, but does have plans for new future generation in Florence County. This unit was moved to coordinates specified in Florence County. VA AEP Clinch River ORISID=3775 1, 2, 3 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. AEP Glen Lynn ORISID=3776 51, 52, 6 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Dominion Clover ORISID=7213 1, 2 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Dominion Bremo ORISID=3796 3, 4 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Dominion Chesterfield ORISID=3797 3, 4, 5, 6 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Dominion Yorktown ORISID=3809 1, 2, 3 Units 1, 2: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Unit 3: IPM predicts zero heat input for this 880 MW #6 oil fired unit. IPM does not predict a retirement, just that the heat input is zero. Dominion plans to continue to operate Unit 3. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Dominion Chesapeake ORISID=3803 1 - 4 Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Dominion Possum Point ORISID=3804 3 & 4 5 6 Unit 3&4: IPM had 137 tons of NO x for these units in 2009 and 111 tons in 2018. VA DEQ specified that the permitted emission rates should be used, which equates to 3,066 tons in 2009 and 2018. Unit 5: IPM had zero heat input for this unit. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates.Table 1.2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 2009/2018 EGU Inventories. State Plant Name & ID Unit Nature of Update/Correction

WV Regional Haze SIP Appendix H - 12 Potomac River ORISID=3788 1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at this time to retire any units. Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. Units 3, 4, 5: Replaced all 2009/2018 IPM results using VADEQ’s growth and control estimates. WV Albright ORISID=3942 1, 2 IPM predicted early retirement for these units. Allegheny indicated there are no plans for early retirement. For 2009, used 2002 emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement. Rivesville ORISID=3945 7, 8 IPM predicted early retirement for these units. Allegheny indicated there are no plans for early retirement. For 2009, used 2002 emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement. Willow Island ORISID=3946 1, 2 Unit 1: IPM predicted early retirement for these units. Allegheny indicated there are no plans for early retirement. For 2009, used 2002 emissions as these units are not likely to retire by 2009. For 2018, used IPM prediction of retirement. Unit 2: IPM predicted SCR and scrubber for 2009. These controls will not be in place by 2009. North Branch Power Station ORISID=7537 1A, 1B SO 2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO 2 Permit Rate of 0.678 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018
Mt. Storm ORISID=3954 1, 2, 3 SO 2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. Used SO 2 Permit Rate of 0.15 lb/MMBtu and IPM predicted total fuel used to calculate SO 2 emissions in 2009 and 2018WV Regional Haze SIP Appendix H - 13 1.1.b. Non-EGUs The general approach for assembling future year data was to use recently updated growth and control data consistent with the data used in EPA’s Clean Air Interstate Rule analyses, supplement these data with available stakeholder input, and provide the results for stakeholder review to ensure credibility.MACTEC (MACTEC, 2006) used the same control programs for both the 2009 and 2018 nonEGU point inventory. Two control scenarios were developed: on-the-books (OTB) controls and on-the-way (OTW) controls. The OTB control scenario accounts for post-2002 emission reductions from recently promulgated federal, state, local, and site-specific control programs. The OTW control scenario accounts for proposed (but not final) control programs that are reasonably anticipated to result in post-2002 emission reductions. Maximum achievable control technology (MACT) requirements were also applied, as documented in the report entitled Control Packet Development and Data Sources, dated July 14, 2004. The point source MACTs and associated emi ssion reductions were designed from Federal Register (FR) notices and discussions with EP A’s Emission Standards Division (ESD) staff. We did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States. Emission reductions were applied only for MACT standards with an initial compliance date of 2002 or greater.
The final Phase II NO x SIP call rule was finalized on April 21, 2004. States had until April 21, 2005, to submit SIPs meeting the Phase II NO x budget requirements. The Phase II rule applies to large IC engines, which are primarily used in pipeline transmission service at compressor stations. We identified affected units using the same methodology as was used by EPA in the proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than 1 ton per day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC engines and 90 percent for diesel or dual fuel categories. Several S/L agencies provided more specific information on the anticipated controls at the compressor stations. This information was used instead of the default approach used by EPA in the proposed Phase II rule. A summary of Non-EGU point source control programs included in 2009/2018 projection inventories include: • Atlanta / Northern Kentucky / Birmingham 1-hr SIPs • Industrial Boiler/Process Heater/RICE MACT. The applied MACT control efficiencies were 4 percent for SO 2 and 40 for percent for PM10 and PM2.5 to account for the cobenefit from installation of acid gas scrubbers and other control equipment to reduce HAPs.WV Regional Haze SIP Appendix H - 14 • NO x RACT in 8-hr NAA SIPs. NCDENR applied NOx RACT to two facilities located in the Charlotte nonattainment area. NCDENR provided 2009 & 2018 emissions for Philip Morris USA (37-025-3702500048) and Norandal USA (37-159-3715900057).
• NO x SIP Call (Phase I- except where States have adopted II already e.g. NC) Phase I of the NOx SIP call applies to certain large non-EGUs, including large industrial boilers and turbines, and cement kilns. States in the VISTAS region affected by the NOx SIP call have developed rules for the control of NOx emissions that have been approved by EPA. We reviewed the available State rules and guidance documents to determine the affected sources and ozone season allowances. • Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV). This initiative addresses the most significant Clean Air Act compliance concerns affecting the petroleum refinery industry. Since December 2000, 17 global refinery settlements have been reached with refiners representing nearly 77 percent of domestic refining capacity. Three refineries in the VISTAS region ar e affected by two October 2003 Clean Air Act settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the Chevron refinery in Pascagoula, MS; (2) the Ergon refinery in Vicksburg, MS; and (3) the Ergon refinery in Newell, WV. • Reasonable Further Progress 3 percent plans were in place for one hour plans (Metropolitan Washington, DC, and Atlanta, GA). • VOC 2-, 4-, 7-, and 10-year MACT Standards. The point source MACTs and associated emission reductions were designed from Fede ral Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD ) staff. We did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States.• Combustion Turbine MACT. The projection inventories do not include the NOx cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating Internal Combustion Engines, which EPA estimates to be small compared to the overall inventory. • NOx SIP Call (Phase II – remaining States & IC engines). For more information on the development of point source inventories, see Appendix E.
1.2. Area Source Controls Controls (including control efficiency, rule eff ectiveness and rule penetration) provided by the States or originally developed for use in es timating projected emissions for EPA’s Heavy Duty Diesel (HDD) rulemaking emission projections and used in the Clean Air Interstate Rule (CAIR) projections were used to calculate controlled emissions.WV Regional Haze SIP Appendix H - 15 The controls obtained by MACTEC (MACTEC, 2006) for the HDD rulemaking were controls for the years 2007, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, control values for intermediate years were prepared using a straight-line interpolation of control level between 2007 and 2020. State submitted controls had precedence over the EPA developed controls. Open burning is treated as a means of waste disposal in some rural areas. Materials burned generally include household trash, agricultural refuse, landscaping refuse, or scrap wood. The open burning emissions inventory incl udes SCC 2610030000, residential open burning of household waste and SCC 2610000100, open burning of yard trimmings. Since it is generally impermissible to burn within corporate limits, the rural population in each county is used to estimate emissions. For more information on the development of area source inventories, see Appendix E.
1.3. On-Road Mobile Sources By their nature, the assumptions used for the 2002 initial base year inventory vary across the VISTAS region, but our presumption is that these data accurately reflected each State’s situation as it existed in 2002. If a State had no plans to change program requirements between 2002 and 2018, we proposed to maintain the 2002 program descriptions without change. However, if a State planned changes, we requested information on those plans. For more information on the development of mobile source inventories, see Appendix D.
1.4. Non-Road Using the 2002 base year emissions inventory for aircraft, locomotives, and commercial marine vessels (CMV) prepared as described earlier in this document, corresponding emission projections for 2009 and 2018 were developed. Deta iled inventory data (both before and after controls) for these same emission sources for 1996, 2010, 2015, and 2020 were obtained from the EPA's Clean Air Interstate Rule (CAIR) Technical Support Document. Using these data, combined growth and control factors for the period 2002-2009 and 2002-2018 were estimated using straight-line interpolation betw een 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This is done at the State-county-SCC-pollutant level of detail. According to EPA documentation, the CAIR baseline emissions include the impacts of the Tier 4 (T4) non-road diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV and locomotive emissions. The large majority of non-road emissions were projected using EPA’s NONROAD2005c model. Future year estimates were made using default model growth assumptions. For more information on the development of non-road source inventories, see Appendix D.WV Regional Haze SIP Appendix H - 16 0 20 40 60 80 100 120 140 160 180 200

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2002 Typical 2009 2018 OTW

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a We s t VirginiaAnnual NH3 (Thousand Tons) Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2002 Typical 2009 OTW 2018 OTW 1.5. Conclusion In conclusion of this discussion on source sector controls, Figures 1.5-1 thru 1.5-4 depict pollutant totals for NH 3 , PM 2.5 , NO x , and SO 2 for the various sectors by state for 2002, 2009, and 2018 Base G2 modeling

Figure 1.5-1. Annual NH 3 emissions – Base G2.

Figure 1.5-2.Annual PM 2.5 emissions – Base G2.WV Regional Haze SIP Appendix H - 17 0 100 200 300 400 500 600 700

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2018 OTW Figure 1.5-3.Annual NOx emissions – Base G2.

Figure 1.5-4.Annual SO 2 emissions – Base G2. 0 100 200 300 400 500 600 700 800 900 1,000

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2018 OTWWV Regional Haze SIP Appendix H - 18 2.0. UNIFORM RATE OF PROGRESS The linear rate of improvement sufficient to attain natural conditions by 2064 is referred to as the “uniform rate of progress” or “glidepath”. The baseline represents the starting point from which reasonable progress will be measured. There are two baseline values for each Class I area. Using 2000 - 2004 Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring data, the deciview values for the 20 percent best days in each year are averaged together, producing a single average deciview value for the best days. Similarly, the deciview values for the 20 percent worst days in each year are averaged together, producing a single average deciview value for the worst days. Extinction from individual PM components is calculated from the IMPROVE equation (EPA, 2003; Hand a nd Malm, 2006). EPA defined target natural conditions in 2064 for each Class I area (EPA, 2003). For each VISTAS Class I area a baseline visibility using 2000-2004 IMPROVE data and uniform rate of progress was established, using EPA default assumptions for calculating visibility and natural background. [Dolly Sods and Otter Creek, though separate and distinct Class I areas, are treated as one due to their close proximity]. Most recently, the scientific community has reviewed the assumptions used to calculate current and natural background visibility and has agreed to revised methods (Hand and Malm, 2006, Pitchford, 2006). VISTAS intends to present both the original and revised methods to calculate visibility and visibility improvement. Figure 2.1 illustrates the average 20% worst visibility days in the 2000-2004 baseline period for Dolly Sods (DOSO) , the target natural condition in 2064 for the 20% worst days, and the incremental deciview changes assuming a uniform rate of progress between current and natural conditions in 2064, using the new IMPROVE equation for calculating visibility. This is known as the “glide path”.

Figure 2.1. CMAQ 2018 Base G2a results vs. Uniform Rate of Progress at Dolly Sods and Otter Creek. Uniform Rate of Reasonable Progress Glide Path Base G2 inventory, new IMPROVE Algorithm Dolly Sods & Otter Creek - Worst 20% Days

29.0 27.5 24.7 21.6 18.5 15.3 12.2 10.4 24.8 21.6

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction Uniform Rate of Progress = 4.3 dv by 2018WV Regional Haze SIP Appendix H - 19 3.0. GEORGIA TECH SENSITIVITIES Georgia Tech performed emission sensitivities to examine the impact of emission reductions on regional haze, annual PM2.5, and 8-hour ozone concentrations using CMAQv4.4_SOAmods on the VISTAS 12 km modeling domain, using the 2009 OTW (on the way) BaseD emissions. Once the key pollutants contributing to visibility impairment at each Class I area were identified, the sources or source categories responsible for emitting these pollutants or pollutant precursors were determined. Emissions sensitivity analyses were conducted using CMAQ with 2009 Base D inventory and considering 30% reductions frommajor pollutants and source categories. The sensitivity runs were initially designed to consider pollutant contributions in 2009 to PM2.5 in urban areas; results were also considered for Class I areas even though the full benefit of controls anticipated by 2018 are not included in these sensitivity analyses. Results are qualitatively similar to previous sensitivity results using an earlier (Base A) 2018 inventory. While the 2009 sensitivity analyses cannot be used to judge absolute contributions from each state or source sector, the results do indicate relative level of response among pollutants, sectors, and geographic areas. 3.1. Evaluation for Dolly Sods Wilderness Area, WV Figure 3.1-1 shows the results of emissions sensitivity run for Dolly Sods for summer (since summer is when the 20% worst days occur). CMAQ was run using 30% reductions from the 2009 Base D inventory assumptions for implem enting existing state and federal regulations (listed on page 2) for major source categories of SO 2 , NOx, VOC, and PM. The results identify geographic origins for visibility impairing pollutants, and serve as a good starting point when considering potential air quality benefits from additional controls for specific source sectors in VISTAS states or neighboring RPOs. The greates t benefits at Dolly Sods in 2009 are projected to come from further reducing SO 2 from electric generating utilities (EGUs). Additional, smaller benefits are projected from additional SO 2 emission reductions from non-utility, industrial point sources. Reductions of nitrogen oxide emissi ons from point sources (EGU and non-EGU) or ground level sources (on road vehicles, off road engines, and area sources) and reductions of primary carbon from point or ground level sources are projected to be significantly less beneficial than reductions in SO 2 emissions. Reductions in anthropogenic VOC emissions show no response in visibility, while a 30 percent reduction in biogenic VOC emissions result in a measurable improvement. However, controlli ng the VOCs from vegetation is not possible or appropriate. For this sensitivity run, further reducing SO 2 emissions from electricity generating utilities in West Virginia, Kentucky, Tennessee and the Midwest RPO would have the greatest benefit for Dolly Sods; reductions from electric generating utilities in other VISTAS states and MANE-VU would have additional but smaller benef its at Dolly Sods. Approximately 40% of the benefit at Dolly Sods from further SO 2 emission reductions would come from outside the VISTAS region.WV Regional Haze SIP Appendix H - 20 Figure 3.1-1. Sources of various visibility-reducing pollutants - Dolly Sods summer using 2009 Base D emissions. Similar sensitivity analyses were performed for wintertime using the 2009 Base D inventory. These results suggest that in wintertime, reductions in ammonia emissions could be more beneficial for reducing ammonium nitrate contributions to visibility impairment than further reducing nitrogen oxide emissions from eith er ground or point sources. Reducing ammonia emissions could also be more effective in improving visibility in wintertime than further reductions in SO 2 emissions, The largest sources of ammonia emissions in this region are agricultural. 

## Dolly Sods, WV (20% Worst Days)

-16.00 -14.00 -12.00 -10.00

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_Fi r esΔBext(Mm-1) Bio. Antro. BCs MRPO M-VU CEN VISTAS WV VA TN SC NC MS KY GA FL AL Emissions sensitivities for Otter Creek are the same as for Dolly SodsWV Regional Haze SIP Appendix H - 21 Figure 3.1-2. Wintertime sensitivity results for 2009 Base D emissions – Dolly Sods, WV.

3.2. Summary Emissions sensitivity analyses show the relative benefits of reducing different pollutants from different source categories and geographic areas. The 2009 sensitivity analyses indicate that further reductions in SO 2 emissions from electric generating utilities would be most beneficial for visibility at VISTAS Class I areas, followed by SO 2 reductions from industrial point sources. Controlling NOx or primary carbon emissions from either point or ground level sources would have little benefit to visibility. Controlling anthropogenic sources of VOC would not be effective in improving visibility in winter. In wintertime, controlling ammonia emissions would be more effective in reducing ammonium nitrate than controlling nitrogen oxide emissions. 

# Dolly_Sods, WV (Winter)

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PC_ Poi n t PC _ Fires°Bext(Mm-1) Bio. Antro. BCs MRPO M-VU CEN VISTAS WV VA TN SC NC MS KY GA FL ALWV Regional Haze SIP Appendix H - 22 Average Extinction for 20% Worst Days New IMPROVE Algorithm (nia) 2000-2004

0 50 100 150 200 250 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (Mm-1) Sea Salt CM Soil EC POM Amm NO3 Amm SO4 Rayleigh 4.0. REASONABLE PROGRESS EVALUATION 4.1. Area of Influence Analyses The objective of the VISTAS Area of Influence analysis is to identify the geographic source regions that are contributing to visibility impairment at the Class I areas on the 20% worst visibility days. This information will be used by the State as part of the evaluation and demonstration of reasonable progress toward visibility improvement in Class I areas. VISTAS’ contribution assessment based on IMPROVE monitoring data (Brewer and Adlhoch, 2005) demonstrated that ammonium sulfate is the major contributor to PM2.5 mass and visibility impairment at Class I areas in the VISTAS and neighboring states. As illustrated in Figure 4-1, on the 20% worst visibility days in 2000-2004, ammonium sulfate accounted for greater than 70% of the calculated light extinction at Class I areas in the Southern Appalachians and greater than 60% of the calculated light extinction for coastal sites in the VISTAS states (excepting Everglades). In contrast, ammonium nitrate contributed less than 5% of the calculated light extinction at VISTAS Class I areas on the 20% worst visibility days. (Nitrate has a somewhat larger contribution on 20% worst days at Cla ss I areas in neighboring states to the VISTAS region.) Particulate organic matter (organic carbon) accounted for 10-20% of light extinction on 20% worst visibility days (except Everglades where organic carbon accounted for 40%).

Figure 4-1. Average Extinction for 20% Worst Visibility Days in 2000 - 2004 using the New IMPROVE Equation (data from VIEWS Sept 2006).WV Regional Haze SIP Appendix H - 23 VISTAS emissions sensitivity analyses using the CMAQ regional air quality model show that reductions in SO 2 emissions from Electric Generating Utilities (EGU) and non-EGU industrial point sources will result in the greatest improvements in visibility at VISTAS Class I areas. EGU and non-EGU industrial point sources comprise 95+% of the SO 2 emissions inventory in the VISTAS states. The emissions sensitivity analyses also indicate that improvements in visibility from reductions in NOx or primary carbon emissi ons from ground-level sources or point sources would be small. Based on these analyses, VISTAS states chose to focus their reasonable progress evaluation for the first regional haze SIP on potential controls of SO 2 emissions from EGU and non-EGU point sources. To select the sp ecific point sources that would be considered for each Class I area, states first identified the geographic areas that most likely influence visibility in each Class I area and then identified the major SO 2 point sources in that geographic area. 4.2. Source Type Analyses

Table 4.2-1. Source types 2018 Base G2 modeling Dolly Sods – Percentage.

4.3. Back Trajectory Analyses The WVDAQ defined AoIs to identify source regions for which additional controls might be considered and that are likely to have the greatest impact on each Class I area. Initial focus on AoIs is on SO 2 emissions because SO4 contributes greater than 60% of the calculated light extinction on the haziest days. In fact, figure 4-1 shows that for Dolly Sods (DOSO), SO4 contributes roughly 80% to the calculated light extinction on the haziest days. To better 

## Annual 2018 BaseG2 Emissions (%) Within Area of Influence Dolly Sods, WV

Tier V OC NOX C O SO2 PM-10 PM-2.5 NH 3 Fuel Comb. Elec. Util. 1% 25% 1% 53% 15% 26% 1% Fuel Comb. Industrial 1% 17% 1% 27% 4% 5% 0% Fuel Comb. Other 6% 8% 4% 6% 7% 14% 1% Chemical & Allied Product Mfg 2% 0% 1% 2% 1% 1% 1% Metals Processing 1% 2% 5% 4% 3% 6% 0% Petroleum & Related Industries 0% 0% 0% 2% 0% 0% 0% Other Industrial Processes 4% 6% 0% 5% 9% 11% 1% Solvent Utilization 41% 1% 0% 0% 0% 1% 0% Storag e & Trans port 6% 0% 1% 0% 1% 1% 0% Waste Dis posal & Rec y clin g 4% 2% 3% 0% 4% 9% 0% Hi g hwa y Vehicles 19% 21% 47% 0% 2% 2% 13% Off-hi g hwa y 14% 17% 36% 0% 2% 5% 0% Miscellaneous 1% 0% 2% 0% 52% 20% 81%
Total 100% 100% 100% 100% 100% 100% 100%WV Regional Haze SIP Appendix H - 24 understand the sources that should be considered in a four factor analysis for reasonable progress, VISTAS contracted ENVIRON to partne r with VISTAS’s Data Analysis contractor, Air Resource Specialists (ARS), to provide SO 2 Areas of Influence for each VISTAS and six neighboring Class I areas. ARS generated meteor ological back trajectories for IMPROVE sites in VISTAS and neighboring states. Back traj ectory analyses use interpolated measured or modeled meteorological fields to estimate the most likely central path of air masses that arrive at a receptor at a given time. The method essentially follows a parcel of air backward in hourly steps for a specified length of time. Back trajectories account for the impact of wind direction and wind speed on delivery of emissions to the receptor, but do not account for chemical transformation and dispersion of emissions. Trajectories were generated using the Hybrid-Si ngle Particle Lagrangian Integrated Trajectory (HYSPLIT) model developed by the National Oceanic and Atmospheric Administration’s (NOAA) Air Resources Laboratory (ARL). HYSPLIT uses archived 3-dimensional meteorological fields generated from observati ons and short-term forecasts. HYSPLIT can be run to generate forward or backward trajectories using several available meteorological data archives. The data archives used in this analysis were the National Weather Service's National Centers for Environmental Prediction Eta Data Assimilation Sy stem (EDAS). The EDAS fields are archived by the ARL across the continental U.S., including a buffer zone, at a horizontal resolution of 80 km before 2004, and at a horizontal resolution of 40 km starting in 2004. Detailed information regarding the trajectory model and these data sets can be found on NOAA’s Web site ( http://www.arl.noaa.gov/ready/hysplit4.html ). The major model parameters selected for this analysis include those listed in Table 4.3-1.
Table 4.3.-1 Back Trajectory Model Parameters Selected for VISTAS AoI Analysis Model Parameter Value Trajectory duration 72 hours backward in time Top of model domain 14,000 meters Vertical motion option used model data Meteorological Field EDAS End Times 0600, 1200, 1800 and 2400 EST End Heights 100 and 500 m The choice of these parameters affects the trajectories generated and the final attribution analyses. In particular, trajectories tend to become increasingly uncertain the further back in time they are used. Vertical motion in the model is sometimes best represented by followingWV Regional Haze SIP Appendix H - 25 actual vertical motion measurements (represented by model data), surfaces of constant entropy, or surfaces of constant pressure, depending on th e meteorological conditions at a given location and time. The impact of receptor height (or end height) on an individual trajectory is also important. Low-ending trajectories represent ai r parcels nearer to ground level and high-ending trajectories may represent more accurate boundary layer flow above the local terrain. For the years 2000 – 2004, back trajectories were computed for the following IMPROVE sampling sites in and around the VISTAS region: 1. Breton, LA (BRET1) 2. Brigantine NWR, NJ (BRIG1) 3. Cadiz, KY (CADI1) 4. Caney Creek, AR (CACR1) 5. Cape Romain NWR, SC (ROMA1) 6. Chassahowitzka NWR, FL (CHAS1) 7. Cohutta, GA (COHU1) 8. Dolly Sods Wilderness, WV (DOSO1) 9. Everglades NP, FL (EVER1) 10. Great Smoky Mountains NP, TN (GRSM1) 11. Hercules-Glades, MO (HEGL1) 12. James River Face Wilderness, VA (JARI1) 13. Linville Gorge, NC (LIGO1) 14. Mammoth Cave NP, KY (MACA1) 15. Mingo, MO (MING1) 16. Okefenokee NWR, GA (OKEF1) 17. Shenandoah NP, VA (SHEN1) 18. Shining Rock Wilderness, NC (SHRO1) 19. Sipsy Wilderness, AL (SIPS1) 20. St. Marks, FL (SAMA1) 21. Swanquarter, NC (SWAN1) 22. Upper Buffalo Wilderness, AR (UPBU1)

Figure 4.3-1. shows the 72-hour back trajectory analysis performed for the Dolly Sods Wilderness Area.WV Regional Haze SIP Appendix H - 26 Figure 4.3-1. Example 72-hour back trajectories for 20% worst visibility days in 2002 for Dolly Sods Wilderness Area.

Based on the five years of individual back tr ajectories, ARS generated extinction-weighted residence time data for each IMPROVE site. Each hourly trajectory point was tagged with its associated sample (or end) date. Back trajectories with end dates corresponding to the 20% worst visibility days were weighted with calculated extinction values and summed into 1-degree horizontal grid cells of latitude and longitude. Extinction data is based on the IMPROVE Regional Haze Rule dataset, as available from the VIEWS website ( http://vista.cira.colostate.edu/views/Web/IMPROVE/SummaryData.aspx ) in November 2005 and is calculated based on the original IMPROVE algorithm. For sites with less than three complete years of data, ARS developed and applied a data substitution protocol to fill missing data. Organic carbon and elemental carbon values were filled based on correlations to hydrogen and sulfate values for the same site. Other components were filled based on data from nearby sites. Trajectory data were weighted by total extinction, and by extinction components including ammonium sulfate (AmmSO4), ammonium nitrate (AmmNO3), particulate organic material (POM), Light Absorbing Carbon (LAC), Soil, a nd Coarse Mass (CM). Weighting trajectories for the 20% worst days by sulfate extinction gave greater importance to days influenced by SO 2 emissions and lesser importance to days influenced by organic carbon emissions. This allowed aWV Regional Haze SIP Appendix H - 27 geographic area of influence to be identified based on sulfate contributions and not skewed by contributions from fire. These data files were provided to ENVIR ON. ENVIRON was charged with developing residence time plots to define the geographic area with highest probability of influencing the receptor on the 20% worst days dominated by sulfate. Residence time over an area is indicative of general flow patterns, but since it does not account for emissions and removal processes, it does not necessarily imply specific areas contributed significantly to haze compounds at a receptor site. 4.4. Area of Influence Data and Displays The primary objective of the Area of Influence (AoI) displays and data sets are to assist the State in focusing its reasonable progress analysis on those geographic regions and source categories which most impact a particular Class I Area. The sources of data used in these analyses include back-trajectory residence time data, provide d by ARS and described above, and the VISTAS 2002 and 2018 36-km gridded emissions data (Base G, Aug 2006 inventory version). Extinction weighted back-trajectory residence time plots were provided by ARS for all Class I Areas in the VISTAS region as well as for the surrounding neighboring states. These trajectories were processed on an un-projected (i.e., ge odetic lat/long 1 degree-by-1 degree) grid and transferred to ENVIRON for further GIS processing and analysis. Back-trajectories were run for 100-meter and 500-meter start heights. Because the back-trajectories were to be combined with gridded emissions data, the first step in the an alysis and GIS processing involved re-projecting these data to the Inter-RPO Unified Lambert C onformal Projection domain. Once the data werere-projected, the data were mapped to the 36-km grid cells in the RPO projection using an areaweighted mapping routine. The re-projected ex tinction weighted back-trajectory residence times were then plotted on the VISTAS 12-km modeling domain. As sulfate is the primary visibility impairing component of the total extinction in the Southeast, the SO4-weighted residence time trajectories were chosen as the basic data set for display. For clarity, these data are scaled by the maximum value of the total extinction-weighted residence time within the modeling domain. The 100-km and 200-km distances from the Class I area were labeled. Using the trajectories with the 100-m start height, the State has defined the SO 2 Areas of Influence as the area with grid cells showing 10% (area shaded in yellow in following plots) or greater residence time (the frequency that winds pass over that area on the way to the Class I area on the 20% worst days dominated by sulfate) for the period 2000-2004. Residence time over an area is indicative of general flow patterns, but since it does not account for emissions and removal processes, it does not necessarily imply specific areas contributed significantly to haze compounds at a receptor site. The following figures, 4.4-1 through 4.4-4, are extinction weighted residence time plots for Dolly Sods, Linville Gorge, James River Face, and Shenandoah for 100-m and 500-m trajectory start heights.WV Regional Haze SIP Appendix H - 28 Figure 4.4-1 Dolly Sods extinction-weighted residence time plots for the period 2000 - 2004.

Figure 4.4-2. Linville Gorge SO4 extinction-weighted residence time plots for the period 2000 -2004.WV Regional Haze SIP Appendix H - 29 

## SO2 Area of Influence for James River Face, VA

Green circles indicate 100-km and 200-km radii from Class I area. Red line perimeter indicate Area of Influence with Residence Time > 10% (weighted by sulfate extinction and normalized by total extinction). Orange line perimeter indicate Area of Influence with Residence Time > 5%.



## SO2 Area of Influence for Shenandoah, VA

Green circles indicate 100-km and 200-km radii from Class I area. Red line perimeter indicate Area of Influence with Residence Time > 10% (weighted by sulfate extinction and normalized by total extinction). Orange line perimeter indicate Area of Influence with Residence Time > 5%. Figure 4.4-3. James River Face SO4 extinction-weighted residence time plots for the period 2000 - 2004.

Figure 4.4-4. Shenandoah SO 4 extinction-weighted residence time plots for the period 2000 - 2004.WV Regional Haze SIP Appendix H - 30 As an aid to the analysis, all regions with scaled residence time values greater than 5% and greater than 10% were noted on the display. Fi nally, county boundaries were overlaid to identify those counties and 36-km modeling grid cells for which the extinction-weighted residence time back-trajectories exceeded 5% and 10%. These data were then exported as comma-delimited ASCII data files for further analyses. These residence time displays are used primarily to determine the regions (counties and/or grid cells) impacting each Class I Area. The next step in the analysis is to determine the potential impact from emission sources within the regions identified from the extinction-weighted back-trajectory residence time displays and analyses. Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory analyses have indicated that SO4 is the largest contributor to haze on the 20% worst visibility days and that electric generating utilities and industrial point sources are the largest contributors to SO4 levels at the Class I areas. These two source categories make up 95% of the VISTAS SO 2 inventory. Therefore these two source categorie s were identified as the highest priority for evaluation of reasonable progress in 2018 at the Class I areas. The potential impacts of SO 2 point source emissions for each Class I Area are determined by combining gridded emissions data and weighted back-trajectory residence times for the 36-km grid cells. The analysis was carried out with both the 2002 and 2018 base year emission inventories. Figures 4.4-5 and 4.4-6 display the gridded point source SO 2 emissions from the VISTAS modeling databases, for 2002 and 2018, respectively. These data were processed by summing all vertical layers for each grid column and then summing across all days to obtain annual emission totals for each grid cell.

Figure 4.4-5. Annual point source SO 2 emissions for the VISTAS region in tons/year. (2002 Base G)WV Regional Haze SIP Appendix H - 31 Figure 4.4-6. Annual point source SO 2 emissions for the VISTAS region in tons/year. (2018 Base G) As a way of incorporating the effects of tran sport, deposition, and chemical transformation of point source emissions along the path of the traject ories, these data were weighted by 1/d, where d was calculated as the distance between grid cell centers, in kilometers. For the grid cell containing the Class I Area monitor, a weighti ng of 1/9 was applied. The distance-weighted point source SO 2 emissions are then combined with the gridded extinction-weighted backtrajectory residence times at a spatial resolution of 36-km. The final step in the development of the displays and data sets involves the combination of the residence times and gridded emission data. The distance weighted (1/d) gridded point source SO 2 emissions are multiplied by the total extinction-weighted back-trajectory residence times (SO 2 * Bext-weighted RT * (1/d)) on a grid cell by grid cell basis. These results are then normalized by the domain-wide total and displayed as a percentage. The analysis is carried out for both the 2002 and 2018 base year inventories. Figure 4.4-7 displays the result of this final analysis step. Note that the outlined regions (in red and light orange) represent the extent of the >10% and >5% sulfate extinction-weighted residence times, determined from the first step in the analysis (see Figures 4.4-1 through 4.4-4). As with the residence time analysis, the results of the combined distance-weighted SO 2 emissions and extinction-weighted residence times are overlayed with county boundaries and exported to comma-delimited ASCII data files for further analyses of emissions and control options for specific sources. The following sets of plots show the comparison of 2002 versus 2018 SO 2 emissions multiplied by the SO4 extinction weighted residence time plots.WV Regional Haze SIP Appendix H - 32 Figure 4.4-7. Dolly Sods 2002 vs. 2018 SO 2 Emissions multiplied by SO4 extinction-weighted residence time plots.

VISTAS states evaluated these plots of reside nce time weighted by sulfate extinction plots of gridded SO 2 emissions and defined the SO 2 Areas of Influence as those areas with residence time greater than 10%, based on trajectories with star t height of 100m and four start times per day. Extinction-weighted residence plots for Class I ar eas indicate that the areas of probable influence for sulfate contribution to visibility impairment are similar to those for nitrate contribution even though the visibility impact of nitrate is an order of magnitude smaller than that of sulfate. From these plots we can initially conclude that it is appropriate to focus on sources that contribute to sulfate concentrations and that sources near a Class I area are more likely to contribute to visibility impairment than more distant sources. Gridded SO 2 emissions for the sulfate extinction-weighted residence time plots indicate that large emissions sources at great distance from the Class I area can contribute to visibility impairment on some 20% worst days. 

## 2002 vs 2018 SO2 Emissions weighted by Residence Time Dolly Sods/Otter Creek, WV

Green circles indicate 100-km and 200-km radii from Class I area. Red line perimeter indicate Area of Influence with Residence Time > 10%. Orange line perimeter indicate Area of Influence with Residence Time > 5%. 2002 SO2 emissions 2018 SO2 emissions

Max Value = 18%WV Regional Haze SIP Appendix H - 33 4.5. Importance of Pollutants Other Than Sulfate For completeness, the following is a brief discussion of the importance of other PM components and contributing source categories. If NOx controls are considered, 72% of NOx is from point sources, 16% is from highway vehicles, 9% is from nonroad engines and 3% from area sources. Elevated organic carbon (OC) and elemental carbon (E C) are indicators of fire. Some states may need to consider emissions from residential wood burning, forest fires (wild and prescribed), land clearing, and agricultural burning. Nitrate (NH4NO3) levels in winter can be significant and are dependent on availability of NH 3 ; nearly 80% of NH 3 is from area sources (e.g. agriculture). However, given that sulfate contributes greater than 87% at Dolly Sods on the 20% worst visibility days, the WVDAQ believes it is appropriate to focus on SO 2 reductions in this first Regional Haze SIP. 4.6. Summary of Emission Inventories Used in Cost Curve Analysis A necessary component of control strategy design is a thorough review of the emission inventories that are used in the modeling of the future year base case. These inventories can shed light on the residual emissions from sources or source categories defined to be within areas of transport which impact a Class I area. We used the most current (BaseG fall 2006) VISTAS future year (2018) base case and 2002 base year emissions to conduct this control cost analysis. For purposes of listing sources within the Area of Influence, data were provided for all sources with emissions over distance (Q/d) greater than 5 and maximum residence time (RTmax) greater than 5. States independently defined the criteria for selecting which sources from this list would be considered for reasonable control measures. The NIF formatted and SMOKE-ready modeling files for both 2002 and 2018 base year and base cases were obtained from VISTAS emissions development and modeling contractors and converted to annual emissions and summed for the geography and domain of interest. Tables 4.6-1 and 4.6-2 present the State breakdown of these emissions for the entire VISTAS domain. Because the SMOKE-ready files were used in this analysis, the particulate matter transport factor (0.90 times inventory values) is included in the PM emission summaries. This factor is applied to account for the removal of a substantial portion of fugitive dust emissions near a source by surrounding vegetation and structures when such emissions are used in regional scale modeling analyses.WV Regional Haze SIP Appendix H - 34 Table 4.6-1. VISTAS 2002 Base Year Annual Emissions Summary Base G Annual Emissions - 2002 Typical (tons) State VOC NO x CO SO 2 PM 10 PM 2.5 NH 3 AL 445,497 459,880 2,534,778 584,665 232,229 105,341 67,970 FL 1,291,562 930,086 7,710,376 589,069 408,902 205,450 61,643 GA 765,063 623,645 5,013,024 653,362 408,736 195,654 100,134 KY 286,752 466,403 1,730,622 580,341 148,290 50,981 57,220 MS 302,374 239,547 1,203,899 103,679 180,816 43,533 63,765 NC 655,950 616,583 4,097,444 546,429 179,242 84,513 172,976 SC 382,836 323,976 2,064,423 286,781 165,699 78,356 35,400 TN 473,244 511,151 2,601,059 442,589 165,095 75,458 42,738 VA 448,205 461,628 3,034,414 416,190 109,848 47,004 55,057 WV 135,819 348,576 802,262 569,373 48,423 27,807 12,341 VISTAS 5,187,303 4,981,474 30,792,301 4, 772,477 2,047,281 914,096 669,243

Table 4.6-2. 2018 Base Case Annual Emissions Summary Base G Annual Emissions - 2018 Base Case (Tons) State VOC NO x CO SO 2 PM 10 PM 2.5 NH 3 AL 327,850 268,067 1,994,607 305,938 258,179 114,681 84,513 FL 990,629 448,443 6,099,425 260,963 483,328 226,529 73,455 GA 585,528 357,169 3,820,095 358,570 472,376 211,406 124,237 KY 236,983 277,271 1,356,496 320,525 166,918 58,559 63,959 MS 247,932 173,893 850,056 62,627 205,761 54,912 76,040 NC 421,965 275,907 2,702,315 164,067 208,015 100,253 196,577 SC 300,291 193,247 1,527,341 163,491 189,358 88,891 42,883 TN 374,093 247,827 1,692,551 228,035 187,066 84,117 46,984 VA 311,835 276,525 2,001,939 294,209 131,708 57,993 64,276 WV 107,675 150,777 576,198 190,683 54,736 31,678 14,400 VISTAS 3,904,780 2,669,125 22,621,023 2, 349,107 2,357,445 1,029,017 787,325WV Regional Haze SIP Appendix H - 35 Our review was conducted in a top-down fashion starting with an analysis of the major source categories in the domain of interest to determine which major categories had the highest residual contribution to the area. Once the highest source types were identified, subcategories within those source types were reviewed. Again, a ranki ng of the highest residual sub source types was performed and additional analyses on these categories were conducted. Using the extinction weighted analysis, these emission reviews and summaries like those presented in Figure 4.6-1, VISTAS made a decision to further review only point source controls in increment beyond the Clean Air Act scenario. In addition to reviewing the residual emission categories in the future year base, it was important to identify reductions that had already occurred within each category, or at specific units. This allowed VISTAS States to determine if certain source categories that had yet to be controlled under the future year base case had the potential for reduction, or if source types already reduced have reached the full cost-effective potential. Finally, once each subcategory was identified, unit level tables of emission comparisons from 2002 to 2018 were developed allowing VISTAS St ates to review existing emission reductions and providing the ability to assign new cost-effective controls to units using the best control for the scenario. These tables presented comparisons of 2002 and 2018 emission levels, for SO 2 , and future year control technology assignment ( by IPM forecasting and State modification) for point sources. Non-EGU unit-specific technology a ssignments were identified using the control efficiency tables provided by the VISTAS emi ssions inventory contractor, MACTEC.Ultimately, the final control strategy decisions will include the application of BART subject source reductions in the future year base case.

Figure 4.6-1. VISTAS Base G2 SO 2 Emissions Contribution by Major Source Sector. Al

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09 201 8WV Regional Haze SIP Appendix H - 36 4.7. Process in Preparing Files for the Cost Effectiveness Curve Development The 2018 IPM file used by VISTAS for EGU sources (RPO 2.1.9) was obtained and matched to the 2018 base case inventory of EGU sources. This step was conducted to ensure that incremental controls assigned to these source types did not duplicate existing base case assumptions. Because IPM does not assign a control efficiency with each control device applied to SO 2 and NO X , we made some assumptions, based on IPM documentation, as to what pollutant specific level of reduction was applied in the future year base case runs. These assumptions, by primary and secondary control device code combinations for SO 2, are presented in Table 4.7-1. Since many of the control technology control cost equations within EPA’s AirControlNET (see section 4.8) require additional unit-level characteristic data, we also made matches of the SMOKE IDA files to VISTAS NIF, EPA NEI, orEPA CAMD CEM data sets to obtain these variables when missing. Unit level boiler capacity (MMBtu/hr) or NETDC (MW) values are required for capital and operating and maintenance cost calculations for many of the SO 2 applied technologies. In cases where these nameplate capacity values could not be identified, emission weighted capacities (based on the final EPA 2002 NEI) were assigned to boilers using a primary (highest emitting) SCC. Table 4.7-2 presents these weighted capacities. Additionally, stack flow, sulfur content, and primary SCC assignment were necessary to cross-reference available incremental control technologies with the base case emissions inventory data. These variables were obtained where matches could be found, in priority order of VISTAS, CAMD, and other EPA datasets, respectively.
Primary Device Code Secondary Device Code Description CE RE 0 0 No Control 0 0 119 0 Dry Scrubber 90 100 141 0 Wet Scrubber 90 100 Table 4.7-1. IPM Post Processing Assigned Device Codes and Applied SO 2 Control EfficienciesWV Regional Haze SIP Appendix H - 37 Table 4.7-2. Emissions Weighted NETDC (MW) Association 4.8. Application of AirControlNET Technologies AirControlNET is a control technology analysis tool developed to support the EPA in its analyses of air pollution policies and regulations (Pechan, 2005). The tool provides data on emission sources, potential pollution control measures and emission reductions, and the costs of implementing those controls. The core of AirControlNET is a relational database system in which control technologies are linked to sources within EPA emissions inventories. The system contains a database of control measure applicability, efficiency, and cost information for reducing the emissions contributing to ambient concentrations of ozone, PM 10 , PM 2.5 , SO 2 , NO X , as well as visibility impairment (regional haze) from point, area, and mobile sources. PM 10 and PM 2.5 as included in AirControlNET represent primary emissions of PM. The control measure data file in AirControlNET includes not only the technology's control efficiency, and calculated emission reductions for that source, but also estimates the costs (annual and capital) for application of the control measure.
Since available versions of AirControlNET cont ain the preprocessed application of control technologies to a predetermined set of EPA emissi on inventories, direct use of the model in this analysis was not possible. However, Alpine received approval from EPA’s Innovative Strategies and Economics Group (ISEG) to modify the AirControlNET version 4.1 source code (Sorrels,

SCC Description NETDC (MW)
10100201 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Wet Bottom (Bituminous Coal) 200
10100202 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Bituminous Coal) 500
10100203 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace (Bituminous Coal) 200
10100212 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Tangential) (Bituminous Coal) 500
10100215 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cell Burner (Bituminous Coal) 1300
10100218 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Atmospheric Fluidized Bed Combustion: Circulating Bed (Bitum. Coal) 200
10100222 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Subbituminous Coal) 400
10100223 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace (Subbituminous Coal) 400
10100226 External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom Tangential (Subbituminous Coal) 500 10100401 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Normal Firing 400 10100404 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Tangential Firing 500 10100501 External Combustion Boilers; Electric Generation; Distillate Oil; Grades 1 and 2 Oil 400
10100601 External Combustion Boilers; Electric Generation; Natural Gas; Boilers > 100 Million Btu/hr except Tangential 400 10100701 External Combustion Boilers; Electric Generation; Process Gas; Boilers > 100 Million Btu/hr 200 10100801 External Combustion Boilers; Electric Generation; Petroleum Coke; All Boiler Sizes 600 10101204 External Combustion Boilers; Electric Generation; Solid Waste; Tire Derived Fuel : Shredded 200 10300811 External Combustion Boilers; Commercial/Institutional; Landfill Gas; Landfill Gas 200 20100101 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine 200 20100109 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine: Exhaust 200 20100201 Internal Combustion Engines; Electric Generation; Natural Gas; Turbine 200

All other boilers 100WV Regional Haze SIP Appendix H - 38 2006) and data tables in order to make it useful to this study. The results of the application of this modified version of the code still retain the applicability, efficiency, and cost information from the unmodified version of the source code, but were applied to the VISTAS modeling inventories with updated price index scalars to reflect control costs in 2005-dollars. Using the modified inventories identified above, we ran every available SO 2 control strategy in AirControlNET against the EGU and non-EGU point source inventories to develop a master list of available, incrementalcontrol strategies for the entire VISTAS 36 km domain necessary for VISTAS States to design command-and-control or cost-effectiveness based control strategies by source or domain. 4.9. Development of AoI-Based Cost Curves Each Class I area in the VISTAS modeling domain had an associated AoI as identified earlier in this document. In order to best determine where emission reduction has the greatest benefit, this geography was designed to limit the available source type list from including all sources within the entire domain. These marginal cost curves include the application of all available control measures to all applicable point sources within the AoI. The curves will allow VISTAS States to determine if, based on the generic application of SO 2 control technologies from the associations originally developed in AirControlNET and improved upon with stakeholder input will help attain reasonable further progress emission reduction objectives while presumably minimizing the number and type of controlled sources in each AoI. Using a geocoded county list from these AoIs, we parsed the master list of incremental control measures from all point sources located within the boundaries of the AoIs. This parsed list was then sorted by incremental cost-effectiveness (marginal cost) basis to determine the most cost effective control suite available to attain emission reduction targets for SO 2 within each AoI. Each individual source had its own cost effectiveness curve generated. In aggregate, the results of these applications are SO 2 emission cost curves for all EGU and nonEGU point sources within the geographic domain of the AoI. Incremental controls on area and mobile sources were not considered in this analysis. An illustrative example of the steps involved with the cost effectiveness curve desi gn can be found in the Attachment H-1a of this document. With each AoI’s cost curve, additional metrics calculated for the distance from the emission release point to the Class I area IMPROVE monitor (in km), the 2018 residual emissions and distance (Q/d) or squared distance (Q/d^2), and the normalized 2018 SO 2 point source emissions times distance-weighted residence time (RTMax) values for the county in which the emission release point was located were calculated for incremental review and consideration. The WVDAQ used these values to further determine control strategy development for individual Class I areas.WV Regional Haze SIP Appendix H - 39 5.0. REASONABLE FURTHER PROGRESS ASSESSMENT
The State concluded that SO 2 emissions from EGU and non-E GU point sources in geographic Areas of Influence (AoIs) are sources which s hould be considered for further controls. VISTAS developed source matrices for SO 2 AoIs for each Class I area, using data delivered by ENVIRON for 2002 and 2018 SO 2 emissions multiplied by SO 4 extinction weighted residence time plots. Spreadsheets were developed for each Class I area with: • Plant name • Point ID • Tons SO 2 projected for 2018 • Q (tons) • Current control efficiency, CE (%) • Stationary source distance to Class I area, d (km) • Analysis of emissions per distance from source, Q/d • RT Max, the maximum percentage of time that winds pass over that area on the way to the Class I area on the 20 worst days The ranking refers to the source rank by Q/d when sources from all states are included. The distance calculation is based on a single stack at a unit (when more than one are represented in the inventory) and is calculated in distance (km) to the IMPROVE monitor at each Class I area. The residence time for the county where the source is located was reviewed. It was generally agreed that states would focus on those sources where RT max was equal to or greater than 10%. A second matrix for sources in the SO 2 AoI was developed for sources with a year 2018 Q/d > 5 when d was greater than 100 km (these values were chosen to limit the number of sources on the list and focus on those that are most influential). Next, for several reasons, the WVDAQ elected to fo cus on those units that contributed at least one percent to sulfate visibility impairment at a given Class I area. First, the units with the larger contribution toward visibility impairment would likely show an environmental benefit under a control evaluation, and WVDAQ would be able to use that environmental benefit to require controls on a given unit. Second, there are several regulatory programs that use a higher threshold than one percent for evaluation thresholds. 1. EPA in the preamble to the BART rule stated that the threshold used “for determining whether a source contributes to visibility impairment should not be higher than 0.5 deciviews.” [70 FR 39161, 6JUL2005] This threshold equates to roughly a 5 percent change in visible perception. This same significance le vel is used in the Prevention of Significant Deterioration/ New Source Review program for the visibility air quality related value. The Federal Land Managers’ Air Quality Related Workgroup (FLAG) Phase I Report (December 2000) [page 26] states: “The FLMs are concerned about situations where a change in extinction from new source growth is greater than 5% as compared against natural conditions.” 2. The NOx SIP Call laid out a significance level for Section 126 petitions of 4 parts per million (ppm), that being the level to which a State's contribution to another state's ozone problemWV Regional Haze SIP Appendix H - 40 was considered significant. Four ppm represents approximately 3.75 percent of the 1-hour ozone standard, which was in place at the time EPA promulgated the NO x SIP Call. 3. For the CAIR rule, a PM contribution of 0.2 μg/m 3 was used to demonstrate a significant impact, which is 1.3% of the annual PM 2.5 standard of 15 μg/m 3

. 4. Lastly, when human health standards are proposed (NAAQS) significant impact levels (SILS) are assigned which allow sources to determine their significance on air quality in the area around their facilities. Sources that demonstrate that their "contribution" from the new or modified sources is less than these significance levels do not have to complete any further modeling. The SILS represent a percentage of the NAAQS. After reviewing all averaging periods for the criteria pollutants, WVDAQ determined that the one percent threshold we were proposing for r easonable further progress was as protective or more protective than the significant impact levels. The most restrictive threshold identified was for NOx, which has a NAAQS of 100 μg/m 3 and a significance level of 1 μg/m 3 , which represents one percent of the total. Finally, WVDAQ considered available resources to evaluate the sources in each Class I area’s sulfate AoI. WVDAQ recognized that there was neither sufficient time or resources available to evaluate all units within a given AoI. Therefore, a threshold was needed to determine which units would be evaluated. Table 5.0-1 shows that a one percent contribution threshold captures greater than 64% of the total point source SO 2 contribution to Dolly Sods, while requiring an evaluation of only 17 units. The next 27% of cumulative contribution may be attributed to units with individual contribution between 0.1% - 1% and would require analysis of 97 additional units. The WVDAQ believes that the one percent threshold is appropriate, given the contribution to the total visibility impairment at each Class I area, and the limited resources available to conduct the unit-by-unit evaluation for reasonable progress.

Table 5.0-1. Numbers and Percentages of 2018 SO 2 Emission Units that Contribute to Visibility Impairment at Dolly Sods Dolly Sods # Units Contributing > 1% 17 Percentage of total Contribution 64.28%
# Units Contributing > 0.1%, but < 1% 97 Percentage of total Contribution 27.33%
# Units Contributing < 0.1% 209 Percentage of total Contribution 8.38%WV Regional Haze SIP Appendix H - 41 Table 5.0-2 shows the analysis for Dolly Sods for sources that met the above criteria.
Table 5.0-2. Dolly Sods – Q/d, RTmax and Percent Contribution
State Plant Point ID 2018 Q (tons) CE (%) d (km) Q/d RTmax Percent
MD New Page - Luke Mill 1 9,610 0 51.59 186.26 42.35 5.25 MD New Page - Luke Mill 2 8,441 0 51.59 163.60 42.35 4.61 VA MeadWestVaco Packaging 25 9,997 0 153.90 64.96 24.77 1.07

WV Mount Storm 001 3,191 95 17.36 183.81 74.90 9.16 WV Mount Storm 002 3,191 95 17.36 183.81 74.90 9.16 WV Mount Storm 003 2,923 94.98 17.36 168.39 74.90 8.39 WV Mon. Power - Harrison 003 5,998 97.98 82.67 72.56 86.63 4.18 WV Mon. Power - Harrison 002 5,954 97.98 82.67 72.02 86.63 4.15 WV Mon. Power - Harrison 001 5,908 97.98 82.67 71.47 86.63 4.12 WV North Branch Power Station 002 1,018 94.98 18.73 54.33 74.90 2.71

WV North Branch Power Station 001 1,004 95 18.73 53.63 74.90 2.67

WV Mon. Power - Pleasants 001 6,334 90 149.65 42.33 61.20 1.72 WV Mon. Power - Pleasants 002 6,165 90 149.65 41.20 61.20 1.68 WV Mon. Power - Ft. Martin 001 4,922 90 78.30 62.86 36.51 1.53

WV Mon. Power - Ft. Martin 002 4,890 90 78.30 62.45 36.51 1.52

WV APCO - Amos Power Sta. 003 10,821 90 219.63 49.27 39.08 1.28

WV APCO - Mountaineer 001 11,433 90 217.38 52.60 30.89 1.08 Spreadsheets were developed for each Class I area source with Q/d > 5, indicating the plant name, industry description, emissions projecti ons for 2018, current control efficiency (CE%), distance from Class I area, Q/d, RT maximu m, Q/d*RT max, the fraction a single source contributes to the total Q/d*RT for a Class I area. CE% is important because it gives a sense of which facilities are already controlled by what percent and which may be controlled further.WV Regional Haze SIP Appendix H - 42 Next, an analysis of control options, generic costs of controls, and "Cost/ton" for various units contributing greater than one percent to any Class I area was developed. Spreadsheets containing unit-level emissions and other associated data for the Class I areas were matched with data from AirControlNET (Pechan, 2005) to give SO 2 control efficiency, annual SO 2 emissions reduction from 2018 Base Case, total annualized cost (in 2005 dollars), and cost per ton reduced for application of specific control measures. The WVDAQ reviewed the sources, emissions, control options, and costs from the SO 2 AoI matrices and defined sources for which the Four Factor Analysis was to be conducted. The same few categories of point sources, fuel combus tion from electric utilities and from industrial sources, contribute to the majority of SO 2 emissions, with little contribution from other sources. Therefore, the WVDAQ eliminated other source cate gories from the Four Factor Analysis. The WVDAQ next looked at source-specific costs, existing controls, remaining useful life, environmental and energy impacts.
6.0. FOUR FACTOR ANALYSIS Section 169A(g)(1) of the Clean Air Act (CAA) and 40 CFR 51.308(d)(1)(i)(A) outline four statutory factors that have been identified as mandatory for purposes of establishing a reasonable progress goal for any Class I area within a State: cost of compliance, time necessary for compliance, energy and non-air quality environmental impacts of compliance, and remaining useful life of any existing source subject to such requirements. These statutory factors would be specific to the sources being considered for additional controls. 6.1. The Four Statutory Factors
6.1.a. Cost of Compliance The “cost of compliance” is a factor used to determine whether compliance costs for sources are reasonable compared to the emission reduction and visibility improvement they will achieve. Note that visibility improvement is not only related to tons of pollutant removed, but also involves how the pollutant or chemical compound affects the light extinction coefficient in each Class I area. For example, on a pound to pound basis, sulfate particulate impairs visibility greater than coarse particulate. Costs should be determined for one-time capital costs as well as ongoing annual operation and maintenance.
6.1.b. Time Necessary for Compliance The “time necessary for compliance” factor may be used to adjust the reasonable progress goals to reflect the degree of improvement achievable within the long-term strategy period, as opposed to the improvement expected at full implementation of a control measure, if the time needed for full compliance exceeds the length of the long-term strategy period. For instance, if implementation of a control measure could not be fully completed within the schedule outlined by the control strategy, the RPG should reflect what visibility improvement could be expected within the strategy period. For example, if construction labor availability constraints preclude the installation of controls at some sources of a particular category within the LTS period, the RPG should reflect the visibilityWV Regional Haze SIP Appendix H - 43 improvement anticipated from installation of controls at the percentage of sources that could be controlled within the strategy period. (The SIP could still include control strategies that extend beyond the 2018 milestone; in the above example, the visibility improvement anticipated from installation of controls at the percentage of sources that could not be controlled within the first strategy period would have to be counted in a later SIP).
6.1.c. Energy and Non-Air Quality Environmental Impacts of Compliance The “energy and non-air quality environmental impacts of compliance” factor is meant to consider whether the energy requirements of the control technology result in energy penalties or benefits. For example, controls on diesel engines may decrease the overall efficiency and require a significant increase in diesel fuel c onsumption. The State should also consider any significant or unusual non-air environmental impacts, such as a waste stream that may be generated by a particular control technology.
6.1.d. Remaining Useful Life of the Source The statutory factor of the “remaining useful lif e of the source” is applicable only to those measures, which would require retrofitting of c ontrol devices (or possibly production changes) at existing sources. In such cases, this factor should be treated as one element of the overall cost analysis. For purposes of this analysis, the re maining useful life is the difference between the year of the reasonable progress analysis and the date the facility permanently stops operations. The remaining useful life of a source may aff ect the annualized costs of retrofit controls. 6.2. Evaluating Four Statutory Factors for Specific SO 2 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 re view existing emission reductions. These tables assigned future year control technology from IPM forecasting; from State modification for EGUs; and from control efficiency tables for Non-EGU point sources. Once emission control profiles for specific units were defined, the next step was to determine what, if any, additional control measures would feasibly be available, and to assign costs to those control measures. For EGUs, the 2018 IPM file used by VISTAS for EGU sources was obtained and matched to the 2018 base case inventory of EGU sources. This step was conducted to ensure that incremental controls assigned to these source types did not duplicate existing base case assumptions. For non-EGUs, VISTAS used EPA’s AirContro NET database, modified for the VISTAS emission inventories. The core of AirControlNET is a relational database system in which control technologies are linked to sources within EPA emissions inventories. The system contains a database of control measure applicability, efficiency, and cost information for reducing emissions. The control measure data file in AirControlNET includes not only theWV Regional Haze SIP Appendix H - 44 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 SO 2 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 AoI for Dolly Sods, 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); and the normalized 2018 SO 2 point source emissions times distance-weighted residence time (RTMax) values for the county in which the emission release point was located. WVDAQ evaluated these control measures and costs as part of the review of th e statutory factors for reasonable further progress. The Regional Haze Rule requires that states c onsider the following factors and demonstrate how these factors were taken into consideration in selecting the reasonable progress goal: • the costs of compliance • the time necessary for compliance • the energy and non-air quality environmental impacts of compliance, and • the remaining useful life of any potentially affected sources.
6.2.a. Cost of Compliance Coal-fired electric utilities and coal-fired industrial boilers are the largest source categories contributing to SO 2 in 2018 in the Areas of Influence defined for Dolly Sods. Industrial boilers using oil and commercial and institutional boilers using coal or oil had small contributions to SO 2 in 2018. Sulfur dioxide emissions from utility, industrial, commercial, or institutional boilers can becontrolled 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 often reduce SO 2 emissions with the least impact on 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 withoutaffecting boiler operations. Costs of boiler modifications to accommodate low sulfur subbituminous coal may make switching to sub-bituminous coal impractical. Contract initiation and termination costs, differential fuel prices and h eat rates, transportation costs, and modification to boiler operations, fuel handling and waste handling systems must be considered specific to each source. Flue-gas desulfurization is a common post-combustion control for coal-fired boilers. Flue gas is passed through an absorbent for sulfur dioxide (generally limestone or lime) in a wet scrubber,WV Regional Haze SIP Appendix H - 45 dry scrubber, or spray dryer. A calcium su lfate byproduct is produced that may be further processed to produce gypsum as a commercial byproduct. Costs of flue-gas desulfurization include initial construction costs and ongoing operational and maintenance costs for the absorber tower, sorbent handling, and waste product handling facilities. Costs per ton vary with boiler size, type, and facility siting considerations. For oil-fired boilers, lower sulfur oil may be an option. Costs evaluation should consider differential fuel prices and heat rate, boiler m odifications, fuel handling costs, and maintenance costs. Conceptually, post-combustion controls can be used for oil boilers, but there is little precedence for such installations.
6.2.b. 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 may require 3 or more years, depending on market availability of labor and materials and utility system-wide priorities. Time necessary for compliance will need to be refined for specific sources.
6.2.c. 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 often require additional safeguards for fuel handling and waste handling systems to avoid additional non-air environmental impacts such as increased effluents in waste water discharges a nd storm water runoff. These factors should be considered specifically for individual sources. Carbon dioxide is emitted as a byproduct of flue gas desulfurization, therefore impacts of increas ed carbon emissions will need to be considered, particularly if carbon emissions are limited in the future under climate change mitigation strategies.
6.2.d. Remaining Useful Life Remaining useful live is specific to the facility for which controls are considered. 6.3. Process of Applying the Statutory Factors The WVDAQ has just completed the Reasonable Progress Assessment for the first Regional Haze SIP. The following was the WVDAQ’s Process for the Reasonable Progress Assessment for the current time period (from the present to 2018): Step 1: Determine pollutants of concern. VISTAS evaluated the species contribution on the 20 percent worst visibility days and concluded that sulfate accounted for greater than 70 percent of the visibility impairing pollution. The VISTAS States concluded that controlling SO 2 emissions was the most important step in addressing the reasonable progress assessment for 2018. The VISTAS findings were consistent with the findings of the Southern Appalachian Mountain Initiative (SAMI). As you may recall, SAMI confirmed that sulfate particles account for the greatest portion of the haze affecting ClassWV Regional Haze SIP Appendix H - 46 I areas in the Southern Appalachian region and that these sulfates were produced in large part from SO 2 emissions from coal combustion. Step 2: Determine which source sectors should be evaluated for reasonable progress.
Since SO 2 point source emissions in 2018 are projected to represent greater than 95 percent of the total SO 2 emissions inventory, the VISTAS States concluded that the focus should be on electric generating unit (EGU) and non-EGU point sources of SO 2 emissions. Step 3: Determine if CAIR is sufficient for reasonable progress for subject EGU’s. The WVDAQ calculated the fractional contribution from all emission units within the SO 2 AoI for a given Class I area and identified the EGUs with a contribution of one percent (1%) or more to the visibility impairment at that Class I area. [Note: No EGU units were identified with a contribution of $ 1% to visibility impairment within the AoI for Brigantine, NJ.] The West Virginia Division of Air Quality (WVDAQ) evaluated the amount of SO 2 reduction from the EGUs projected due to CAIR. The EGUs in West Virginia are projected to reduce their 2002 SO 2 emissions by 47 percent by 2009 and a total of 78 percent by 2018. The projected SO 2 emission reductions are the result of CAIR which dictates statewide emission caps but allows unchecked trading and the use of banked Title IV allowances by regulated facilities. Therefore, the reductions are not directly enforceable. However, WVDAQ has issued permits for the installation of controls, and confirmed the commen cement of the installation of controls at the three plants (6 units) projected to reduce emissions by 2009, and one of the plants (2 units) projected to control by 2018. In fact, the controls on two of the plants (3 units) were operational by the summer of 2007. Once the controls have been installed, the facilities have a strong financial incentive to operate them continuously. The additional controls projected by IPM on three plants are not as certain due to the rule’s reliance on the banking and trading of allowances. The WVDAQ intends to re-evaluate the IPM predictions of SO 2 reductions for CAIR at the time of our first periodic report in 2012 to ensure that the predicted reductions are, in fact, taking place where they are expected and needed. Based on the confirmed CAIR controls and the CAIR controls predicted by IPM, WVDAQ has concluded that, at this time, CAIR constitutes reasonable measures for West Virginia’s EGUs during this first assessment period (between baseline and 2018).

Table 6.3-1. EGU Sources with Contribution $ 1% to any Class I Area Plant ID Plant Point ID Class I areas where Contribution $ 1% 023-0003 Mount Storm Power Station 1 001 Dolly Sods, Shenandoah 023-0003 Mount Storm Power Station 1 002 Dolly Sods, Shenandoah 023-0003 Mount Storm Power Station 1 003 Dolly Sods, Shenandoah 033-0015 Harrison Power Station 1 001 Dolly Sods, Shenandoah 033-0015 Harrison Power Station 1 002 Dolly Sods, ShenandoahTable 6.3-1. EGU Sources with Contribution $ 1% to any Class I Area Plant ID Plant Point ID Class I areas where Contribution $ 1%

WV Regional Haze SIP Appendix H - 47

033-0015 Harrison Power Station 1 003 Dolly Sods, Shenandoah 023-0014 North Branch Power Station 2 001 Dolly Sods 023-0014 North Branch Power Station 2 002 Dolly Sods 073-0005 Pleasants Power Station 1 001 Dolly Sods, Shenandoah 073-0005 Pleasants Power Station 1 002 Dolly Sods, Shenandoah 061-0001 Ft. Martin Power Station 3 001 Dolly Sods 061-0001 Ft. Martin Power Station 3 002 Dolly Sods 079-0006 John Amos Power Station 3 001 Dolly Sods, James River Face 079-0006 John Amos Power Station 3 002 James River Face 079-0006 John Amos Power Station 3 003 James River Face, Shenandoah 053-0009 Mountaineer Power Station 1 001 Dolly Sods, Shenandoah

1 Currently equipped wet scrubbers with SO 2 control efficiency >90% 2 Circulating Fluidized Bed (CFB) boiler with SO 2 control efficiency >90% 3 Construction has commenced on wet scrubbers with SO 2 control efficiency >90%, to be completed 2008-10

Step 4: Determine which emission units would be evaluated based on impact. The WVDAQ calculated the fractional contribution from all emission units within the SO 2 AoI for a given Class I area and identified the non-EGUs with a contribution of one percent (1%) or more to the visibility impairment at that Class I area. [Note: No non-EGU units were identified with a contribution of $ 1% to visibility impairment within the AoI for Brigantine, NJ. In fact, the greatest impact from any single unit in West Virginia was about 0.1% and the entire cumulative impact from the whole state was less than 1%.]
Table 6.3-2. Non-EGU Sources to be Evaluated for Reasonable Further Progress Plant ID Plant Point ID Class I areas where Contribution >1% 003-006 Capitol Cement 010 ShenandoahWV Regional Haze SIP Appendix H - 48 Step 5: Evaluate the four factors. Each emission unit identified in Step 4 above was evaluated using the statutory and regulatory factors of: 1) cost of compliance, 2) time necessary for compliance, 3) the energy and non-air quality environmental impacts of compliance, and 4) the remaining useful life of the emissions unit. While all four (4) factors should be considered, any one of them may provide a compelling reason to exclude a control measure. This is particularly true of control cost. If no cost effective control exists, then it is not reasonable to require controls. For the purpose of evaluating the cost for the reasonable progress assessment in this first regional haze SIP, WV DAQ believes it is not equitable to require non-EGUs to bear a greater economic burden than EGUs for a given control strategy. That is, the agency does not believe it is reasonable to potentially subject non-EGUs to control measures that require a higher cost per ton than that which has been found reasonable for EGUs. In order to determine the cost effectiveness of SO 2 controls for EGUs, the WV DAQ reviewed EPA’s CAIR analysis. [See EPA CAIR analysis at 70 FR 25201-25208, 12MAY2005]. The CAIR analysis is a recent and comprehensiv e review of the cost-effectiveness of EGU SO 2 controls, which is appropriate to consider as a benchmark in determining a reasonable cost effectiveness for SO 2 control for purposes of the reasonable progress assessment. In the CAIR preamble EPA notes that:
The SO 2 annual control costs that were presented in the CAIR NPR [Notice of Proposed Rulemaking] were average costs of $700 per ton and $800 per ton for years 2010 and 2015, respectively, and marginal costs of $700 per ton and $1,000 per ton for years 2010 and 2015. In addition, the NPR included the results of sensitivity analyses that examined costs of the proposed SO 2 controls based on the Energy Information Administration’s projections for electricity growth and natural gas prices. These sensitivity analyses showed marginal SO 2 control costs of $900 per ton and $1,100 per ton for years 21010 and 2015, respectively.” EPA goes on to address the analysis of SO 2 emission reduction requirements for the CAIR final rule. (I) Reference Lists of Cost-Effective SO 2 Controls For today’s action, EPA updated the referen ce list of controls included in the NPR of the average and marginal cots per ton of recent SO 2 control actions. The EPA systematically developed a list of cost information from both recent actions and proposed actions. The EPA compiled cost information for actions taken by the Agency, and examined public comments submitted after the NPR was published, to identify all available control cost information to provide the updated reference list for today’s preamble. The updated referen ce list includes both average and marginal costs of control, to which EPA compares the CAIR control costs, and the list represents what regulatory decision makers and/or the public believes are the control costs.WV Regional Haze SIP Appendix H - 49 Table IV-3 provides average costs of SO 2 controls. This table includes average costs for recent BACT permitting decisions for SO 2 . Under EPA’s New Source Review (NSR) program, if a company is planning to build a new plant or modify an existing plant such that a significant net increase in emissions will occur, the company must obtain a NSR permit that addresses controls for air emissions. BACT is the type of control required by the NSR program for existing sources in attainment areas. The BACT decisions are determined on a case- by-case basis, usually by State and local permitting agencies, and reflect consideration of average and incremental cost effectiveness. These decisions are relevant for EPA’s reference list of average costs of SO 2 controls, because they represent co st-effective controls that have been demonstrated.

TABLE IV-3. – Average Costs per Ton of Annual SO 2 Controls SO 2 control action Average cost per ton Best Available Control Technology (BACT) Determinations 1 $400-$2,100 Nonroad Diesel Engines and Fuel 2 $800 Proposed Best Available Retrofit Technology (BART) for Electric Power Sector 3 $2,600-$3,400

1 These numbers reflect a range of cost-effectiveness data entered into EPA’s RACT/BACT/LAER Clearinghouse (RBLC) for add-on SO 2 controls ( www.epe.gov/ttn/catc/). We identified actions in the data base for larg e, utility scale, coal-fired boiler units for which cost effectiveness data were reported. The rangeof costs shown here is for boilers ranging from 30MW to an estimated 790 MW (we used a conversion factor of 10 mmBtu/hr = 1 MW for units for which size was reported in mmBtu/hr). Emission limits for these actions ranged from 0.1 mmBtu to 0.27 lb/mmBtu. Add-on controls re ported for these units are dry or wet scrubbers (in one case with added alkali and in one case with a baghouse).Where the dollar-year was not reported we assumed 1999 dollars. The cost range presented in the NPR was $500-$2,100- today’s range includes additional BACT costs that were entered into the clearinghouse after the NPR was published.

2 Control of Emissions of Air Pollution from Nonroad Diesel Engines and Fuel; Final Rule (69 FR 39131; June 29, 2004). The value in this table represents the long-term cost per ton of emissions reduced from the total fuel and engine s program (cost per ton of emissions reduced in the year 2030). 1999$ per ton.

3 The EPA IPM modeling 2004, available in the docket. The EPA modeled the Regional Haze Requirements as source specific limits (90 percent SO2 reduction of 0.1 lb/mmBtu rate; except the five state WRAP region for which we did not model SO2 controls beyond what is done for the WRAP cap in the base case modeling). Estim ated average costs based on this modeling are $2,600 per ton in 2015 and $3,400 per ton in 2020. 1999$ per ton. Table IV-4 provides the marginal cost pe r ton of recent State and regional decisions for annual SO 2 controls.WV Regional Haze SIP Appendix H - 50 Table IV-4.– Marginal Costs per Ton of Annual SO 2 Controls SO 2 control action Marginal cost per ton New Hampshire Rule 1 $600 WRAP Regional SO 2 Trading Rule 2 $1,100-$2,200

1 The EPA IPM base case modeling August 2004, available in the docket. (1999$ per ton). We modeled New Hampshire’s State Bill ENV-A2900, which caps SO 2 emissions of all existing fossil steam units.

2 "An Assessment of Critical Mass for the Regional SO 2 Trading Program,” prepared for the Western Regional Air Partnership Market Trad ing Forum by ICF Consulting Group, September 27, 2002, available in the docket. This analysis l ooked at the implications of one or more States choosing to opt-out of the WRAP regional SO 2 trading program. (1999$ per ton). (II) Cost Effectiveness of the CAIR Annual SO 2 Reductions . . .Table IV-5 provides the average and marginal costs of annual SO 2 reductions under the CAIR for 2010 and 2015.(When pres enting estimated CAIR control costs in section IV of this preamble, EPA uses “Main Case” to indicate the primary CAIR IPM analysis, as differentiated from other IPM analyses such as sensitivity runs used to examine the impacts of varying assump tions about natural gas price and electric growth.)
Table IV-5. – Estimated Costs per Tons of SO 2 Controlled Under CAIR, Cap Levels Beginning in 2010 and 2015 1 Type of cost effectiveness 2010 2015 Average Cost – Main Case $500 $700 Marginal Cost – Main Case 700 1,000 Sensitivity Analysis: Marginal Cost Using EIA Growth and Natural Gas Prices 800 1,200

1 The EPA IPM modeling 2004, available in the docket. 1999$ per ton.
These estimated SO 2 control costs under the CAIR reflect annual EGU SO 2 caps of 3.6 million tons in 2010 and 2.5 million tons in 2015 within the CAIR region. . . . (IV) Cost Effectiveness: Marginal Cost Curves for SO 2 Control . . . Figure IV-1 shows that the “knee” in the 2010 marginal cost-effectiveness curve – the point where the cost of controlling a ton of SO2 from EGUs is increasing at a noticeably higher rate – appears to occur at about $2,000 per ton of SO2. Figure IV2 shows that the “knee” in the 2015 marginal cost-effectiveness curve also appears to occur at about $2,000 per ton of SO 2 . . . . ”WV Regional Haze SIP Appendix H - 51WV Regional Haze SIP Appendix H - 52 After review of EPA’s CAIR cost analyses the WV DAQ determined that the CAIR SO 2 control costs vary by year of analysis (2010 vs. 2015) and may range from $400 to $3,400 per ton SO 2 removed. Ultimately, EPA found a consistent marginal cost for both years at $2000 per ton, which WV DAQ believes establishes an appropriate benchmark against which cost effectiveness may be evaluated for reasonable progress. During the current reasonable progress assessment, no non-EGU units in West Virginia were identified for additional control because no measures were found to be cost effective. The only non-EGU identified as contributing greater than 1% to visibility impairment at a Class I area was Capitol Cement, with a 1.27% contribution to visibility impairment at Shenandoah. Capitol Cement Capitol Cement is a portland cement manufacturing facility located in Martinsburg, WV. In 2002, ESSROC acquired Riverton Investment Corporation which operated the facility. Capitol Cement then applied for a permit to modernize operations by replacing certain existing operations and increasing overall plant production capacity. The modernization project included the replacement of two existing long wet process cement kilns (Kilns 8 and 9) and associated clinker coolers with a modern large precalciner kiln system and related equipment. Kiln 7 (point ID 010, identified above), a long wet process kiln, remained at the facility and is used to make a limited amount of clinker, including certain specialty (colored) clinkers. The modernization project at Capitol Cement wa s subject to both minor source and major source permitting requirements, and was required to undergo PSD permitting. Permit R14-026 was issued for the project on June 2, 2005. Under the conditions of permit R14-026 the SO 2 limit for Kiln 7 was reduced to 900 tpy; actual SO 2 emissions in 2002 from Kiln 7 were 1,247 tons and projected SO 2 emissions for 2018 were 1,717 tons. Although, only Kiln 7 was identified as requiring a Reasonable Progress analysis, the WVDAQ determined that the new preheater kiln should also be considered in regard to reasonable progress, since the allowable SO 2 emissions from the new large preheater kiln are 4,426 tpy. The facility underwent PSD permitting for CO and VOC , and BACT was required for CO and VOC. However, the facility was able to net out of PSD for SO 2 , so BACT for SO 2 was not required.

Cost of Compliance - Wet Kiln 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 to evaluate control options and costs for controls on Kiln 7 at Capitol Cement. The control option identified was flue gas desulfurization (FGD) with a cost effectiveness of $25,266 per ton. Since the cost of compliance for an FGD on Kiln 7 is greater than $2,000 per ton, and the facility has taken permit limits to reduce emissions and limit operations of Kiln 7, the WVDAQ determined that there are no cost effective SO 2 controls available. Cost of Compliance - Precalciner System The Mid-Atlantic/Northeast Visibility Union (M ANE-VU) RPO contracted with MACTEC, Inc. to evaluate control options and the four st atutory factors for assessing Reasonable Progress Goals (RPGs) for regional haze in the MANE-VU region. The project report [ Assessment ofWV Regional Haze SIP Appendix H - 53 Reasonable Progress for Regional Haze In MANE-VU Class I Areas , dated July 9, 2007] summarizes the control measures available for SO 2 emissions from electric utilities, industrial boilers, kilns, residential heating oil and wood combustion. For kilns, the report identifies four control options for SO 2 for cement kilns: • Limiting sulfur content in raw materials and fuel, • Dry Flue Gas Desulfurization - Spray Dryer Absorption (FGD), • Wet Flue Gas Desulfurization, and • Advanced Flue Gas Desulfurization (FGD). As noted by Capitol Cement in their permit application, emissions of SO 2 from cement kilns are primarily determined by the content of sulfur in the raw materials and not from the sulfur content of the fuel. Capitol Cement’s facility is situated on about 800 acres near Martinsburg, WV. Capitol Cement operates an open pit quarry from which the limestone (a raw material) is obtained. Since the limestone is mined on site, an alternative was not considered to be a viable option for SO 2 control. MACTEC, in their report, provided cost estimates for the other three control options identified above.

Table 6.3-3. SO 2 Control Costs for Large Preheater Kilns (2006 Dollars) Capitol Cost (10 6 $) Annual Operating Costs (10 6 $) SO 2 Cost Effectiveness ($/ton SO 2 reduction) Dry FGD $3.6 - $105.2 $0.9 - $21.0 $10,000 - $72,800 Wet FGD $6.2 - $92.5 $0.9 - $18.9 $9,700 - $64,600 Advanced FGD $17.8 - $58.0 $1.2 - $11.8 $13,600 - $38,000 Since the cost of compliance for all three control options is significantly greater than $2,000 per ton, the WVDAQ determined that there are no cost effective SO 2 controls available for the new precalciner system at Capitol Cement. Time Necessary for Compliance, Energy and Non-Air Impacts, and Remaining Useful LifeThe three remaining statutory factors: 1) time necessary for compliance, 2) the energy and nonair quality environmental impacts of compliance, and 3) the remaining useful life of the emissions unit, while required to be considered, were deemed not applicable, since there were no cost effective controls to evaluate.

7.0. BART 7.1. Background As required by the CAA, EPA included in the final regional haze rule a requirement for Best Available Retrofit Technology (BART) for certain large stationary sources that were placed in operation between 1962 and 1977. The BART-eligible sources are those sources which have theWV Regional Haze SIP Appendix H - 54 potential to emit 250 tons or more of a visibility-impairing air pollutant, were placed in operation between August 7, 1962 and August 7, 1977, and whose operations fall within one or more of 26 specifically listed source categories. Under the CAA, BART is required for any BART-eligible source that a State determines ‘‘emits any air pollutant which may reasonably be anticipated to cause or contribute to any impairment of visibility in any such area.’’ Accordingly, for stationary sources meeting these criteria, States must address the BART requirement when they develop regional haze SIPs. EPA has set guidance for identifying BART-eligible sources in 40 CFR Part 51 Appendix Y. A BART-eligible source that is responsible for a 1.0 deciview (dv) change or more is considered to “cause” visibility impairment. Although the appropriate threshold may vary, the guidelines state that the “contribution” threshold used for BART applicability should not be higher than 0.5 deciviews. Thus a BART-eligible source that is responsible for a 0.5 dv change or more is considered to “contribute” to visibility impairment. Any source determined to cause or contribute to visibility impairment in any Class I area is subject to BART. The guidelines direct that States should include SO 2 , NOX, and direct particulate matter (PM) emissions, including both PM10 and PM2.5, in determ ining whether sources cause or contribute to visibility impairment. States may use their best judgment to determine whether VOC or ammonia emissions are likely to have an impact on visibility in an area. To determine which BART-eligible sources are subject to BART, states have several options. A state may consider all BART-eligible sources subject to BART; may perform analysis showing that the full group of BART-eligible sources in a State cumulatively may not be reasonably anticipated to cause or contribute to any visibility impairment in any Class I areas; or may consider the individualized contribution of a BART-eligible source to determine whether a specific BART-eligible source is subject to BART. Sources that are subject to BART must undergo a BART determination. Section 169A(g)(7) of the CAA requires that States must consider the following factors in making BART determinations: (1) The costs of compliance, (2) The energy and non-air quality environmental impacts of compliance, (3) Any existing pollution control technology in use at the source, (4) The remaining useful life of the source, and (5) The degree of improvement in visibility which may reasonably be anticipated to result from the use of such technology. To demonstrate the degree of improvement in visibility from various BART control options, the States may run CALPUFF or another appropriate dispersion model to predict visibility impacts. Scenarios would be run for the pre-controlled and post-controlled emission rates for each of the BART control options under review. The maximum 24-hour emission rates would be modeled for a period of three or five years of meteorological data. States have the flexibility to develop their own methods to evaluate model results. 7.2. Approach to Implementation of BART Requirements In order to meet the SIP submittal deadline, West Virginia has used a multi-layered approach to address the federal regional haze rule BART requirements. The approach consists of source identification efforts; requests to sources for information and modeling; use of a permitting process to establish any resulting BART limits for inclusion in the SIP submittal; participation inWV Regional Haze SIP Appendix H - 55 VISTAS BART subgroup to resolve technical issues spanning states in the VISTAS region; and ongoing consultation with affected sources, EPA and FLMs throughout the BART process. 7.3. Identification of BART-eligible Sources EPA provided guidance for identifying BART-elig ible sources in 40 CFR Part 51 Appendix Y. West Virginia followed this guidance in identifying its BART-eligible sources. The West Virginia 2002 air emissions inventory was reviewed to determine the population of potential BART-eligible sources. The data were initially queried for any sources emitting SO 2 , NOx, PM10, VOC, or ammonia, based upon the StandardIndustrial Classification and the Source Classification Code. The data set was refined based on emissions, whether emission units fit in any of the twenty-six listed source categories for BART, and available date information obtained through review of permit and inspection reports and discussion with permits section and regional office staff familiar with the facilities. An information packet on BART was sent to and additional information was collected from the remaining sources regarding potential emissions and BART eligibility from the standpoint of source category and date criteria. Through this iterative review process, the list of potential BART-eligible sources was pared down to the twenty-two BART-eligible sources listed below.
Table 7.3-1. BART-Eligible Sources in West Virginia Facility Name Facility ID Location Allegheny Energy - Ft. Martin 061-00001 Maidsville Allegheny Energy - Harrison 033-00015 Haywood Allegheny Energy - Pleasants 073-00005 Willow Island AEP - Appalachian Power - John Amos 079-00006 St. Albans AEP - Ohio Power - Mitchell 051-00005 Moundsville AEP - Appalachian Power - Mountaineer 053-00009 New Haven Bayer Material Science 051-00009 New Martinsville Cabot Corp 073-00006 Waverly Capitol Cement Corporation 003-00006 Martinsburg Century Aluminum 035-00002 Ravenswood Clearon Corporation 039-00011 South Charleston Columbian Chemicals 051-00019 Moundsville Dominion - Mt. Storm 023-00003 Mt. Storm Dupont 039-00001 Belle Kepler Processing 109-00013 PinevilleTable 7.3-1. BART-Eligible Sources in West Virginia Facility Name Facility ID Location

WV Regional Haze SIP Appendix H - 56

ERGON Corp - West Virginia, Inc. 029-00008 Newell GE Advanced Materials 107-00010 Washington Mittal Steel USA - Weirton, Inc. (formerly Weirton Steel) 029-00001 Weirton Pinnacle Mining Co. - No. 50 Coal Prep Plant 109-00006 Pineville Pocahontas Coal Co. - East Gulf Prep Plant 081-00012 Rhodell PPG Industries 051-00002 Natrium Mountain State Carbon (formerly Wheeling Pittsburgh Steel) 009-00002 Wheeling

West Virginia’s BART-eligible sources were presumed to be subject to BART, but were provided the opportunity to submit modeling demonstrations showing that they did not contribute to visibility impairment, i.e., had le ss than 0.5 deciviews (dv) impact, on any Class I area within 300 kilometers and thus could be exempt. (See Section 8.0 for more discussion regarding the BART exemption process.)
7.4. Contribution Threshold Determining whether a source causes or contributes to visibility impairment is one step in the BART review process. The Guidelines for BART Determinations Under the Regional Haze Rule state that “A single source that is responsible for a 1.0 deciview change or more should be considered to ‘cause’ visibility impairment.” The guideline document also states that “the appropriate threshold for determining whether a source ‘contributes to visibility impairment’ may reasonably differ across states,” but, “As a general matter, any threshold that you use for determining whether a source ‘contributes’ to visibility impairment should not be higher than 0.5 deciviews.” The rationale for these instructions is provided in the preamble to the BART guidance, in the statement, “If ‘causing’ visibility impairment means causing a humanly perceptible change in visibility in virtually all situations ( i.e. a 1.0 deciview change), then ‘contributing’ to visibility impairment must mean having some lesser impact on the conditions affecting visibility that need not rise to the level of human perception.” The guidance document itself also states that, “States remain free to use a threshold lower than 0.5 deciviews if they conclude that the location of a large number of BART-eligible sources within the State and in proximity to a Class I area justify this approach.” The EPA’s documents strive to set these thresholds in the context of the human perception of visibility change. As noted above, the EPA considers a 1.0-deciview change in visibility to be humanly perceptible “in virtually all situations.” Also, the preamble to the BART guidance cites an analysis in an appendix of a NAPAP (National Acid Precipitation Assessment Program) report, which asserts that “changes in light extinction of 5 percent will evoke just noticeable changes in most landscapes.” (A 5% change is approximately 0.5 dv.) But, as noted above, the preamble also states that perceptibility is not a prerequisite for choosing a contribution threshold.WV Regional Haze SIP Appendix H - 57 Putting all this together, it appears that “causing” visibility impairment means having a humanly perceptible impact (for which EPA considers the practical threshold to be 1.0 dv) while “contributing” to visibility impairment means having a smaller impact (for which EPA considers the threshold to be 0.5 dv or some smaller value) that may or may not be perceptible. The EPA argues that a contribution threshold of less than 0.5 dv impact per source is appropriate when multiple sources contribute, in order to limit the combined effect of these sources. As an example, EPA asserts that if there were 100 sources, each affecting visibility by 0.1 dv (presumably an imperceptible amount), their total impact would be 10 dv (which can be expected to be quite perceptible). The point remains that multiple sources can cause a larger impact than a single one. For BART purposes, visibility impacts are calculated as 24-hr averages of 1-hr plume impacts, so if the plumes from the various sources each impact the point of interest at some time during a 24-hr period (not necessarily all at the same hour) then the 24-hr average will reflect their combined impact. WV DAQ concluded that the EPA suggested contribution threshold of 0.5 dv was appropriate in this situation since there are a limited number of out of state sources that impact the various Class I areas in the state. 7.5. Exemption of Point Source Volatile Organic Compounds for BART Purposes The State of West Virginia determined through modeling that Volatile Organic Compounds (VOC) from point sources are not anticipated to cause or contribute significantly to any impairment of visibility and should be exempt for BART purposes.
7.5.a. Method Modeling was conducted through VISTAS which contracted with Georgia Institute of Technology to perform model sensitivity runs to determine the impact of point source VOCs on visibility in Class I areas. Georgia Tech performed emission sensitivities to examine the impact of emission reductions on regional haze, annual PM2.5, and 8-hour ozone concentrations using CMAQv4.4_SOAmods on the VISTAS 12 km modeling domain, using the 2009 OTW (on the way) BaseD emissions. One such sensitivity run reduced anthropogenic, point source VOCs by 100%. The purpose was to quantify the impact of VOC emissions from VISTAS BART sources on Class I areas. Two episodes were examined: June 1-July 10, 2002 and November 19 – December 19, 2002. The approach included calculating the extinction coefficient in dv (deciviews), then determining the maximum impact of point source VOCs. The chart below shows the impact on the twenty-two Class I areas within the VISTAS domain.WV Regional Haze SIP Appendix H - 58 

# Maximum Point VOC Impact

Maximum VOC Impact

0.0 0.1 0.2 0.3 0.4 0.5 0.6BRETBRIGCACRCHASCOHUDOSOEVERGRSMHEGLJARILIGOMACAMINGOKEFROMASAMASHENSHROSIPSSWANUPBUWOLFΔdV

Figure 7.5-1. Maximum Point VOC Impact BRET = Breton, LA BRIG = Brigantine NWR, NJ CACR = Caney Creek, AR CHAS = Chassahowitzka, FL COHU = Cohutta, GA DOSO = Dolly Sods, WV EVER = Everglades, FL GRSM = Great Smoky Mountains National Park HEGL = Hercules Glade, MO JARI = James River Face, VA LIGO = Linville Gorge, NC MACA = Mammoth Cave, KY MING = Mingo, MO OKEF = Okefenokee, GA ROMA = Cape Romain, SC SAMA = Saint Marks, FL SHEN = Shenandoah, VA SHRO = Shining Rock, NC SIPS = Sipsey Wilderness, AL SWAN = Swanquarter, NC UPBU = Upper Buffalo Wilderness, AR WOLF = Wolf Island, GAWV Regional Haze SIP Appendix H - 59 7.5.b. Conclusions The results show that the maximum impact from eliminating all point source VOC emissions in the VISTAS 12 km domain is less than a 0.5 dv for all Class I areas in the VISTAS domain. Given that the fraction of the total point source VOC emissions that are also BART-eligible in the state of West Virginia is about 29%, the expected impact of controlling VOCs from a BART source would be much less than the 0.5 dv threshold. Indeed, the point source VOC contribution is only about 3% of total VOCs when biogenic sources are included. VISTAS and the State of West Virginia conclude that VOCs from point s ources are not a visibility impairing pollutant for BART purposes and that BART-eligible sources do not need to consider VOC emissions. 7.6. Treatment of Ammonia Emissions for BART Purposes Similar to its treatment of VOCs, EPA guidance a llows States the discretion to decide whether or not ammonia emissions are to be considered for BART purposes based on evaluations of the contributions of the emissions to haze at Class I areas in their areas of influence. One approach a State can use to determine whether applying BART will be needed is to evaluate the haze impacts of all current emissions from all BART-eligible sources in the State. If the impact from all sources in the state is less than the contribution threshold established by the State, 0.5 dv for West Virginia, then source by source analysis for BART is not needed. The State of West Virginia has determined through modeling that ammonia (NH 3 ) emissions from point sources are not anticipated to cause or contribute significantly to any impairment of visibility in Class I areas and should be exempt for BART purposes.
7.6.a. Method VISTAS contracted with Georgia Institute of Technology to perform model sensitivity runs to determine the impact of point source ammonia on visibility in Class I areas. Georgia Tech performed emission sensitivities to examine the impact of emission reductions on regional haze using CMAQv4.5 with Secondary Organic Aerosols (SOA) mods on the VISTAS 12 km modeling domain, using the VISTAS 2009 OTW (on the way) Base F4 emissions. One such sensitivity run reduced, BART-eligible source ammonia by 100%. The purpose was to quantify the impact of ammonia emissions from VISTAS BART sources on Class I areas. Two episodes were examined: June 1-July 10, 2002 and November 19 – December 19, 2002. The approach included calculating the extinction coefficient in dv (deciviews), then determining the maximum impact of BART-eligible source ammonia. The chart below, taken from the VISTAS report BART in the VISTAS Region: Sensitivity to VOC, NH 3 , and Primary PM Emissions , included in Appendix L, shows the impact on the twenty-two Class I areas within the VISTAS domain.WV Regional Haze SIP Appendix H - 60 Figure 7.6.a-1. Maximum NH 3 Impact – Maximum Contributions of all BART-eligible NH 3 point sources in the VISTAS region to haze in Class I areas during the CMAQ-modeled periods. The chart shows the largest haze impact in delta dv over the two timeframes at each Class I area. These delta dv changes represent the haze contribution of all BART source ammonia emissions relative to assumed natural haze levels. The natural haze levels are based on EPA-default annual average natural concentrations for the East and monthly-varying “climatologically representative” relative humidity at each Class I area. During the periods modeled the ammonia emissions from all BART-eligible sources contributed more than 0.5 dv to haze at Mammoth Cave National Park (MACA), Kentucky; Mingo Wilderness (MING), Missouri, Cape Romain Na tional Wildlife Refuge Area (ROMA) South Carolina, and Swanquarter National Wildlife Refuge (SWAN), North Carolina. The majority of ammonia emissions in VISTAS region come from four BART-eligible sources as shown in Table 7.6.a-1 below.

Table 7.6.a-1 VISTAS Ammonia Emissions Facility State NH 3 Emissions (tpy) Distance to Nearest Class I area (km) Meadwestvaco Corp. SC 174 30 PCS Phosphate NC 206 31 PCS Nitrogen TN 1,252 180 PCS Nitrogen GA 1,765 220 

# Maximum NH3 

# Impact

0.0 0.5 1.0 1.5BRETBRIGCACRCHASCOHUDOSOEVERGRSMHEGLJARILIGOMACAMINGOKEFROMASAMASHENSHROSIPSSWANUPBUWOLFΔdVWV Regional Haze SIP Appendix H - 61 7.6.b. Conclusions The BART requirements of the regional haze rule allow states to determine whether or not ammonia is to be considered a visibility impairing pollutant to be addressed for BART purposes. NH 3 emissions from BART sources may impair visibility; however the majority of NH 3 emissions in the VISTAS region are from a few BART sources. Removal of the large NH 3 emission sources results in minimal impact on visibility at Class I areas in the VISTAS region. At their discretion states may ask those few large sources to evaluate NH 3 impacts and potential controls for NH 3 . Based on the CMAQ sensitivity analyses of the impact of ammonia emissions, West Virginia concluded that NH 3 is not a visibility impairing pollutant for BART purposes and that BART-eligible sources do not need to consider NH 3 emissions.

8.0. Explanation of BART Exemption Modeling 8.1. Background West Virginia opted to consider its BART-eligible sources subject to BART unless the source demonstrated exemption via modeling. BART-eligible sources can be excluded from BART determinations by demonstrating that the source cannot be reasonably expected to cause or contribute to visibility impairment in a Class I area. The threshold for determining that a source causes visibility impairment is set at 1.0 dv change from natural conditions over a 24 hour averaging period. The BART guidelines also propose that the threshold at which a source may “contribute” to visibility impairment should not be higher than 0.5 deciviews; however, depending on factors affecting a specific Class I area it may be set lower than 0.5 deciviews. As stated in the BART regulation EPA’s preferred approach for determining cause or contribution is an assessment with an air quality model such as CALPUFF or other appropriate model followed by comparison of the estimated 24-hour visibility impacts against a threshold above estimated natural conditions to be determined by the State. EPA recommends that the 98 th percentile value from the modeling be compared to the State’s chosen contribution threshold to determine if a source does not contribute to visibility impairment and thus is not subject to BART. Comparison of the 98 thpercentile value to the threshold must be made for each Class I area. For an annual period, this implies the 8 thhighest 24-hr value at a particular Class I area is compared to the contribution threshold. For a 3-year modeling period, the 98 thpercentile value may be interpreted as the highest of the three annual 98 thpercentile values at a particular Class I area or the 22 ndhighest value in the combined three year record, whichever is more conservative. West Virginia worked with VISTAS on development of the VISTAS Protocol for the Application of the CALPUFF Model for Analyses of Best Available Retrofit Technology (BART) (Attachment H.4). The common protocol was established to provide the basis for a common understanding among the organizations perfor ming BART analyses or reviewing BART modeling results in the VISTAS region. The VISTAS protocol describes common procedures for carrying out air quality modeling to support BART determinations that are consistent with the 40 CFR Part 51 Appendix Y guidelines. The protocol provides a consistent model, CALPUFF, and modeling guidelines for BART determinations, clearly delineated mode ling steps, a common CALPUFF configuration,WV Regional Haze SIP Appendix H - 62 guidance for site-specific modeling, and common expectations for reporting model results. Details of the CALPUFF system can be found in Chapter 3 of the VISTAS protocol, specific recommendations for its application for BART purposes are found in Chapter 4, and specific information that should be included in site-specific protocols is found in Chapter 5. VISTAS contracted EarthTech to develop a ve rsion of the CALPUFF model appropriate for BART purposes. The VISTAS version of the CALPUFF model is CALPUFF Version 5.754 and CALMET Version 5.7. For BART modeling purposes VISTAS made publicly available 12-km CALMET output files for the entire VISTAS modeling domain (easte rn United States) and provided CALMET output files for five 4-km grid subdomains covering th e VISTAS states and VISTAS Class I areas. To generate the CALMET input files, the VISTAS contractor used the MM5 databases developed by EPA for 2001, VISTAS for 2002, and Midwest RPO for 2003. For the 12 km grid large domain covering the entire VISTAS region, the No-Obs setting was used. For the 4 km grid available surface and upper air observations were used in addition to MM5 meteorological model outputs. Specific model settings were provided with the CALMET files and via the CALPUFF website so that work could be replicated. For CALPUFF modeling, source emissions were to be defined using the maximum 24-hour actual emission rate during normal operation for the most recent 3 or 5 years. If maximum 24- hour actual emissions were not available, continuous emission data, permit allowable emissions, potential emissions, and emission factors from AP- 42 source profiles could be used as available. Key points on specific CALPUFF, CALPOST, and POSTUTIL configuration that were to be used for BART modeling are: • After running CALPUFF for an individua l facility, NO3 should be repartitioned in POSTUTIL. • Ozone data from non-urban monitors should be used as the background ozone input. • The Pasquill-Gifford dispersion method should be used. • In CALPOST Method 6 with monthly average RH for calculating extinction as recommended by EPA should be used. • EPA default calculations of light extinction under current and natural background conditions should be used. In addition a source may also calculate visibility using the recently revised IMPROVE algorithm. Additional discussion of the CALPUFF model and VISTAS recommended settings can be found in the VISTAS protocol in Appendix L. 8.2. West Virginia BART Sources – Exemption Modeling WVDAQ requested that its BART sources follow the VISTAS modeling protocol in development of their site specific protocols and e xplain any deviations that they proposed to use. WVDAQ also provide the non-EGU BART sources the opportunity to have the VISTAS contractor to perform the site-specific modeling, provided the source submitted site specific information sufficient to allow the use of the VISTAS modeling protocol.WV Regional Haze SIP Appendix H - 63 In the site-specific modeling demonstrations, the CALPUFF model incorporating three years of pre-processed MM5 meteorological data was used to evaluate the deciview change compared to natural background conditions at each of the Class 1 areas within 300 km of the source. The 4 km MM5 dataset prepared by VISTAS was used. The 98 thpercentile delta-deciview (dv) value was determined at each Class 1 area and compared to the 0.5 dv contribution threshold. Twenty-one (21) of the twenty-two (22) facilities submitted site-specific data or modeling protocols and the modeling demonstrations we re based upon the VISTAS modeling protocol. The site-specific information is included in Appendix L. The individual facility modeling demonstrations were reviewed by WVDAQ Modeling staff and shared with both EPA and the FLMs for their review and comment. WVDAQ staff reviewed the demonstrations to determine whether the sources have less than 0.5 dv impact on any Class I area within 300 km of the source. Sources demonstrating less than 0.5 dv impact are considered exempt. Sources contributing 0.5 dv impact or great er are considered subject to BART and were required to proceed to an analysis of what control measures, if any, constitute BART for the source.

Table 8.2-1. BART Exemption Modeling Results 12 km Modeling - Maximum Predicted Visibilit y Impact (delta-deciview) per Class I Areas Company Year Dolly Sods, WV Otter Creek,

WV Shenandoah, VA James River Face, VA Linville Gorge,

NC Great Smoky Mountains, TN Mountain State Carbon (009-00002) 2001 0.057 0.059 0.091 n/a n/a n/a 2002 0.055 0.051 0.061 n/a n/a n/a 2003 0.048 0.051 0.065 n/a n/a n/a Mittal Steel USA - Weirton, Inc. 2001 0.131 0.148 0.170 n/a n/a n/a 2002 0.182 0.155 0.081 n/a n/a n/a 2003 0.185 0.299 0.102 n/a n/a n/a ERGON Corp. - West Virginia, Inc. 2001 0.031 0.022 0.055 n/a n/a n/a 2002 0.032 0.036 0.026 n/a n/a n/a 2003 0.035 0.054 0.020 n/a n/a n/aTable 8.2-1. BART Exemption Modeling Results 12 km Modeling - Maximum Predicted Visibilit y Impact (delta-deciview) per Class I Areas Company Year Dolly Sods, WV Otter Creek,

WV Shenandoah, VA James River Face, VA Linville Gorge,

NC Great Smoky Mountains, TN

WV Regional Haze SIP Appendix H - 64

Century Aluminum (035-00002) 2001 0.077 0.081 0.092 0.052 n/a n/a 2002 0.067 0.075 0.071 0.054 n/a n/a 2003 0.037 0.049 0.040 0.030 n/a n/a DuPont - Belle (039-00001) 2001 0.091 0.087 0.129 0.10 0.107 0.076 2002 0.070 0.078 0.069 0.125 0.096 0.056 2003 0.124 0.124 0.157 0.126 0.206 0.081 Clearon (039-00011) 2001 0.017 0.026 0.019 0.017 0.010 n/a 2002 0.010 0.015 0.012 0.022 0.009 n/a 2003 0.011 0.015 0.020 0.017 0.009 n/a Pocahontas Coal Co - Eastern Gulf Prep Plant ((081-00012) 2001 0.033 0.038 0.073 0.098 0.062 0.054 2002 0.033 0.037 0.065 0.117 0.052 0.034 2003 0.068 0.065 0.064 0.136 0.044 0.050 GE Woodmark (107-00010) 2001 0.060 0.072 0.061 0.040 n/a n/a 2002 0.036 0.040 0.061 0.033 n/a n/a 2003 0.044 0.055 0.034 0.035 n/a n/a Pinnacle Mining - No. 50 Coal Prep Plant (109-00006) 2001 0.022 0.022 0.066 0.075 0.034 0.049 2002 0.019 0.019 0.036 0.069 0.050 0.027 2003 0.039 0.047 0.055 0.120 0.032 0.046Table 8.2-1. BART Exemption Modeling Results 12 km Modeling - Maximum Predicted Visibilit y Impact (delta-deciview) per Class I Areas Company Year Dolly Sods, WV Otter Creek,

WV Shenandoah, VA James River Face, VA Linville Gorge,

NC Great Smoky Mountains, TN

WV Regional Haze SIP Appendix H - 65

Kepler Processing (109-00013) 2001 0.018 0.013 0.039 0.029 0.023 0.029 2002 0.012 0.010 0.021 0.029 0.026 0.013 2003 0.024 0.031 0.032 0.056 0.022 0.032

Table 8.2-2. BART Exemption Modeling Results 4km Modeling - 98 th Percentile Visibility Impact (delta-deciview) per Class I Area Company Year Dolly Sods, WV Otter Creek,

WV Shenandoah,

VA James River Face, VA Linville Gorge,

NC Great Smoky Mountains, TN AEP - Appalachian Power Co. - John Amos (079-00006) 2001 0.054 0.073 0.062 0.075 0.029 n/a 2002 0.054 0.081 0.055 0.052 0.014 n/a 2003 0.059 0.082 0.074 0.062 0.018 n/a AEP - Ohio Power Co. - Mitchell (051-00005) 2001 0.094 0.097 0.076 0.031 n/a n/a 2002 0.045 0.058 0.053 0.022 n/a n/a 2003 0.076 0.077 0.066 0.029 n/a n/a AEP - Appalachian Power Co. - Mountaineer ((053-00009) 2001 0.259 0.344 0.253 0.164 n/a n/a 2002 0.172 0.266 0.281 0.142 n/a n/a 2003 0.201 0.250 0.217 0.142 n/a n/aTable 8.2-2. BART Exemption Modeling Results 4km Modeling - 98 th Percentile Visibility Impact (delta-deciview) per Class I Area Company Year Dolly Sods, WV Otter Creek,

WV Shenandoah,

VA James River Face, VA Linville Gorge,

NC Great Smoky Mountains, TN

WV Regional Haze SIP Appendix H - 66

Allegheny Energy - Ft. Martin (061-00001) 2001 0.103 0.128 0.10 0.028 n/a n/a 2002 0.098 0.142 0.068 0.027 n/a n/a 2003 0.121 0.113 0.078 0.021 n/a n/a Allegheny Energy - Harrison (033-00015) 2001 0.216 0.278 0.185 0.067 n/a n/a 2002 0.173 0.253 0.147 0.049 n/a n/a 2003 0.196 0.233 0.181 0.059 n/a n/a Allegheny Energy - Pleasants (073-00005) 2001 0.059 0.062 0.046 0.019 n/a n/a 2002 0.037 0.053 0.037 0.018 n/a n/a 2003 0.039 0.049 0.036 0.016 n/a n/a Bayer (051-0009) 2001 0.125 0.0139 0.093 0.056 n/a n/a 2002 0.075 0.121 0.080 0.058 n/a n/a 2003 0.080 0.100 0.073 0.042 n/a n/a Columbian Chemicals (051-00019) 2001 0.261 0.328 0.378 0.247 n/a n/a 2002 0.295 0.298 0.407 0.228 n/a n/a 2003 0.257 0.296 0.272 0.176 n/a n/a Cabot Corporation (073-00006) 2001 0.380 0.391 0.425 0.242 n/a n/a 2002 0.405 0.441 0.372 0.370 n/a n/a 2003 0.333 0.396 0.401 0.220 n/a n/aWV Regional Haze SIP Appendix H - 67 Consistent with BART regulation requirements and EPA guidance, BART-eligible sources at electric utilities complying with EPA’s Clean Air Interstate Rule (CAIR) that wished to demonstrate exemption were allowed to model only direct PM fine emissions. Compliance with CAIR constitutes BART for these sources for NOx and SO 2 . West Virginia submitted a CAIR SIP to the EPA in June 2006. The submittal was believed to be approvable at that time. EPA subsequently revised various aspects of the the CAIR program through other rule-makings, including promulgation of a Federal Implementation Plan (FIP). West Virginia then submitted an “abbreviated SIP” to be consistent with the FIP and related EPA guidance. West Virginia is subject to th e CAIR FIP (as modified by the abbreviated SIP) until a full SIP is submitted and approved. Review of the demonstrations submitted led to the determination that the BART-eligible source at each facility in Tables 8.2-1 and 8.2-2 should be exempt from BART determination requirements. The modeled impacts from the facilities in Table 8.2-1 ranged from 0.009 at Linville Gorge, NC to 0.299 at Otter Creek, WV, and the impacts from facilities in Table 8.2-2 ranged from 0.014 at Linville Gorge, NC to 0.441 at Otter Creek, WV. Based on these demonstrations, WVDAQ proposes to exempt th ese nineteen sources from further BART evaluation. Two additional facilities conducted modeling in an effort to demonstrate a contribution less than 0.5 dv. One facility is a coal-fired power plant (Mt. Storm) and one is a chemical manufacturer with a coal-fired industrial boiler (PPG). Thes e facilities were unable to demonstrate less than 0.5 dv of impact. One additional facility, Capitol Cement, a portland cement manufacturer did not conduct modeling, but chose to acknowledge that Kiln 9 is BART subject. Table 8.2-3 shows the impacts from these sources.
Table 8.2-3. Exemption Modeling Results for Facilities with >0.5 deciview of Impact

4km Modeling - 98 th Percentile Visibility Impact (delta-deciview) per Class I Area Company Year Dolly Sods, WV Otter Creek, WV Shenandoah, VA James River Face, VA Dominion - Mt. Storm (023-00003) 2001 0.770 0.205 0.538 0.124 2002 0.636 0.286 0.381 0.097 2003 0.416 0.297 0.401 0.098 PPG Industries ((051-00002) 2001 0.557 0.669 0.786 0.513 2002 0.635 0.615 0.816 0.507 2003 0.578 0.596 0.587 0.364Table 8.2-3. Exemption Modeling Results for Facilities with >0.5 deciview of Impact 4km Modeling - 98 th Percentile Visibility Impact (delta-deciview) per Class I Area Company Year Dolly Sods, WV Otter Creek, WV Shenandoah, VA James River Face, VA

WV Regional Haze SIP Appendix H - 68

Capitol Cement (003-00006) 2001 Not available. Capitol Cement elected not to do exemption modeling. 2002 2003

Although PPG initially modeled a visibility impact greater than 0.5 dv on multiple Class I areas, PPG elected to accept a permit limit on its BART eligible unit which reduces its visibility impact to below the exemption threshold of 0.5 deciview of impact on any Class I area. Permit R14- 027B requires 4690.56 tpy of SO 2 emission reductions from Boiler 5 by May 1, 2008. Therefore, PPG is considered BART exempt. [See Appendix L.6 for copies of the application and permit.] Seven of West Virginia’s BART-eligible sources are EGUs, with a total of 16 units and a generating capacity of 11,714 MW or approximately 80% of West Virginia’s coal-fired generating capacity. Six of the seven facilities (14 units) have already installed Selective Catalytic Reduction (SCRs) to reduce NO x , and the remaining facility (2 units) has installed SNCR, to meet either the requirements of the NO x SIP Call or CAIR. Five of the seven facilities (11 units) currently have scrubbers installed to reduce SO 2 emissions (scrubbers were installed on 3 of the units in 2007 to meet CAIR). Construction has commenced at the two remaining facilities (5 units) with startup scheduled in 2008 for one unit, 2009 for two units and 2010 for the remaining two units. The EPA has determined that, as a whole, the CAIR cap-and-trade program improves visibility more than implementing BART for individual sour ces in states affected by CAIR. A state that opts to participate in the CAIR program under 40 CFR Part 96 AAA-EEE need not require affected BART-eligible EGUs to install, operate and maintain BART controls for SO 2 or NO x emissions. West Virginia is participating in CAIR, and accepts EPA’s overall finding that CAIR “substitutes” for BART for NO x and SO 2 . Given that all BART-eligible units have already installed, or are installing scrubbers and NOx controls, our EGUs were allowed to submit BART exemption modeling demonstrations for PM emissions only. Only one EGU facility (3 units) demonstrated that they significantly contributed to visibility in any Class I area based on PM. 8.3. BART-Eligible Sources in Other States Within 300 km of West Virginia Class I Areas At this time the other VISTAS states are at various points in their processes for addressing BART. West Virginia intends to provide a summary of the available relevant BART decisions for any BART-subject sources that fall into the AoI for any of West Virginia’s Class I areas when the proposed WV SIP is made available for general public comment.WV Regional Haze SIP Appendix H - 69 8.4. Use of the New IMPROVE Equation During the regional haze SIP development process, the IMPROVE Steering Committee made recommendations for a new IMPROVE equation. Among other things, the new equation includes components that take into account the effects of sea salt and site specific Rayleigh scattering. These are important components to appropriately consider for coastal facilities. Additional discussion of the new IMPROVE equation can be found in Appendix C.
VISTAS contracted Dr. Ivar Tombach to deve lop a post processor to allow CALPOST outputs to be used with the new IMPROVE equation. A discussion of the rationale for use of the new IMPROVE equation follows. Rationale for Need for Use of New IMPROVE Equati on The new IMPROVE equation is a much better representation of the effects of particulate matter on light extinction than the old equation and takes into account the latest scientific understanding of several parameters. 1. The new algorithm overcomes biases of the old algorithm on the haziest days and the clearest days as demonstrated by comparing the measured light extinction from nephelometers at Class I areas to light extinction calculated using each of the equations. 2. The new algorithm recognizes spatial and temporal variation in light extinction as size distribution of the aerosol changes by increasi ng extinction efficiency as sulfate, nitrate and organics concentrations increase. 3. The new algorithm incorporates a term to reflect the contribution of fine sea salt and its hygroscopic growth with increasing relative humidity recognizing research findings showing that fine sea salt can be an important contributor to light extinction in coastal areas. 4. The new algorithm reflects research finding th at the mass concentration of particulate organic matter in rural areas is greater than represented by the old equation. 5. The new algorithm includes a NO 2 term to represent times when light absorption by NO 2 is a meaningful contributor to light extinction. 6. The new algorithm incorporates site-specific Rayleigh scattering values to better represent sites close to sea level or with very hot or cold climates. With this combination of revisions to the IMPROVE equation, the resulting apportionment of extinction to various components is more accurate on the haziest and clearest days. This is important for development of emission control strategies since the benefits of controlling each species’ concentration will be represented more correctly with the new algorithm.
8.5. Conclusion In total, nineteen of West Virginia’s twenty-two BART-eligible sources were able to demonstrate that they did not cause or contribute to visibility impairment in any Class I areaWV Regional Haze SIP Appendix H - 70 within 300 km of the source. Two sources, PPG and Mt. Storm Power Station, were unable to demonstrate a contribution of less than 0.5 dv at some Class I areas within 300 km of their BART-eligible sources, which resulted in these sources being considered “subject to BART”. One additional source, Capitol Cement, acknowledged that it was “subject to BART”. These three sources were required to submit permit applications containing their evaluation of potential BART options and proposed BART determination. Copies of the BART determinations, and DAQ reviews for these sources are included in Attachment L.
9.0. BART DETERMINATIONS For those facilities subject to BART, the state must determine what constitutes BART controls for the source by considering various control options and selecting the best alternative taking into consideration any pollution control equipment in use at the source, the costs of compliance with control options, the remaining useful life of the facility, the energy and non air-quality environmental impacts of compliance, and the degree of improvement in visibility that may reasonably be anticipated to result from the use of such technology. Under North Carolina’s approach, facilities that are subject to BART were required to propose BART considering these factors via a permitting process. 9.1. BART Subject Sources Only Dominion’s Mt. Storm Power Station in Mt. Storm was unable to demonstrate a contribution of less than 0.5 deciview at all Cla ss I area within 300 km from their BART eligible sources. Therefore, Mt. Storm was the only source considered to be “subject to BART” and required to submit a permit application containing an evaluation of potential BART options and a proposed BART determination. Mt. Storm submitted a BART determination on November 3, 2006. A copy of the BART determination was sent to EPA and the Federal Land Managers for review on January 22, 2007. On September 5, 2007, the company submitted a permit application to incorporate the results of the BART determination. The WV DAQ published a legal ad, which commenced the thirty day public comment period, on September 18, 2007. A copy of the application and draft permit were sent to the Federal Land Managers for review, via email, on September 17, 2007. Permit R13- 2735 was issued December 13, 2007. [See Appendix L for copies of the application, draft permit and permit.] The current PM controls at Mt. Storm were determined to satisfy BART. However, the allowable PM10 emission rate was lowered from 0.5 lb/mmBtu to 0.03 lb/mmBtu, resulting in a reduction of up to 508 tpy per unit, or a maximum reduction of 1524 tpy. Capitol Cement in Martinsburg chose not to submit exemption modeling, but simply to acknowledge that Kiln 9 was BART-subject. Capitol Cement had previously applied for and been granted a PSD (Prevention of Significant Deterioration) permit (R14-026, issued June 2, 2005) for the replacement of two existing long wet process cement kilns and associated clinker coolers with a modern precalciner system and associated equipment. The only BART-eligible unit at the facility (Kiln 9) was one of the tw o kilns being replaced, and the permit included a requirement for the permanent shutdown of the existing kilns when full-production was achieved with the replacement kilns or no later than 180 days after startup. Therefore, the company requested that the permit be modified to require the permanent shutdown of the Kiln 9 system by the BART compliance deadline or when full-production was achieved with the replacement kilnsWV Regional Haze SIP Appendix H - 71 or no later than 180 days after startup, whichever came first. The WVDAQ issued an Administrative Update to permit R14-026B on October 11, 2006, requiring that “Operation of the existing kiln 9 system shall permanently ceas e after the pre-heater-precalciner kiln system achieves full production or within 1280 days after the pre-heater-precalciner kiln system first becomes operational or before the BART compliance deadline (approximately 2013) whichever comes first”. [See Appendix L for copies of letter and permit.]

10.0. FINAL LONG TERM STRATEGY AND REASONABLE PROGRESS GOALS As stated in section 2.0 above, the regional haze rule requires States to establish reasonable progress goals, expressed in deciviews, for visi bility improvement at each affected Class I area covering each (approximately) 10-year period until 2064. This first set of reasonable progress goals must be met through measures contained in the state’s long-term strategy covering the period from the baseline until 2018. This section discusses development of West Virginia’s long-term strategy. 10.1. Long-Term Strategy
Ammonium sulfate is the most important contributor to visibility impairment and fine particle mass on the 20 percent worst and 20 percent best visibility days at Dolly Sods. Sulfate levels on the 20 percent worst days account for 87 percent of the visibility impairment. Across the VISTAS region, sulfate levels are higher at the Southern Appalachian sites than at the coastal sites. On the 20 percent clearest days, sulfate levels are more uniform across the region. Reduction of SO 2 emissions would be the most effective means of reducing ammonium sulfate. Ninety-eight percent of SO 2 emissions in West Virginia are attributable to electric generating facilities and industrial point sources. Thus, the long-term strategy for this first Regional Haze SIP focused on reductions in SO 2 emissions from major point sources. There are significant control programs in place in West Virginia and the region to reduce SO 2 emissions between the baseline period and 2018. Most notably, CAIR is predicted to result in greater than a 77% reduction from EGU SO 2 emissions in West Virginia. Overall the SO 2 emissions in West Virginia are predicted to decrease from a 2002 level of 586,567 tons per year to 190,653 tons per year in 2018. Such large SO 2 reductions are predicted to result in significant improvements in visibility. At Dolly Sods, 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. At Dolly Sods, a 4.3 deciview improvement in visibility would meet the uniform rate of progress in 2018; expected emissions reductions by 2018 are projected to achieve a 7.3 deciview improvement. In fact, visibility improvements at all of the VISTAS mountain Class I areas and most of the coastal Class I areas are projected to be better than the uniform rate of progress. The percentage of the target reduction achieved for Dolly SOds using the new IMPROVE equation is 165 percent. This means that the rate of improvement is 65 percent greater than the uniform rate of progress by 2018. In addition to improving visibility on the 20 percent worst visibility days, states are also required to protect visibility on the 20 percent best days at the Class I areas. Visibility on the 20 percentWV Regional Haze SIP Appendix H - 72 best days is projected to improve in 2018 at all VISTAS Class I areas as a result of the 2018 Base G2 emissions reductions. The percentage of the target achieved for Dolly Sods is about -10 percent. Zero percent change would mean no change in visibility; -10 percent means that visibility is better than no change, or a 10 percent improvement (values lower than current conditions.) The WVDAQ completed a reasonable progress assessment after modeling the Clean Air Act controls discussed above. The assessment did not identify any cost effective control measures for the SO 2 non-EGU units that contributed greater than one percent to visibility impairment at any of the Class I areas in West Virginia orin neighboring States. The WVDAQ concluded that the reduction in EGU SO 2 emissions from CAIR were reasonable for this long-term strategy. The WVDAQ is still in the process of reviewing the BART determinations from one of the two facilities that were determined to be subject to BART. Any further reductions resulting from the BART determinations will be considered in the final reasonable progress goals in the official Regional Haze SIP submittal in December 2007. 10.2. What Additional Emissions Controls Were Considered as Part of the Long-Term Strategy for Visibility Improvement by 2018? 40 CFR 51.308(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 the Class I areas and status of state planning for smoke management, the role of dust and fine soil at the Class I areas and status of plans to mitigate emissions from construction activities, and the role of ammonia and potential benefits if emissions from agricultural sources were mitigated. Elemental carbon (sources include agriculture, prescribed fires and wildfires) is a relatively minor contributor to visibility impairment at Dolly Sods. West Virginia has rule 45CSR6 [effective date July 1, 2001] – To Prevent and Control Air Pollution from Combustion of Refuse – which includes a prohibition of open burning of land clearing debris, unless specific conditions are met. West Virginia has proposed revisions to 45CSR6, which include a provision for prescribed burning – the controlled application of fire to vegetation under specified environmental conditions and precautionary measures, which allows the fire to be confined to a predetermined area for the purpose of accomplishing specifically planned wildlife and forest management objectives – in accordance with a written prescribed fire plan approved by the West Virginia Division of Forestry, or in the case of federal lands, approved by the appropriate Agency Administrator and endorsed by the West Virginia Division of Forestry. The proposed revisions to 45CSR6 are scheduled to go befo re the 2008 Legislature for approval and are expected to become effective in the June 2008 timeframe. WVDAQ has worked with the WV Division of Forestry and the Federal Land Managers to develop the language allowing prescribed burns. The proposed rule are included in Attachment H-6. Fine soils are a relatively minor contributor to visibility impairment at Dolly Sods. Nevertheless, in regard to construction activities, the WVDAQ has rule 45CSR17 [effective date August 31, 2000] – To Prevent and Control Particulate Matter Air Pollution from Materials Handling, Preparation, Storage and Other Sources of Fugitive Particulate Matter – which prohibits the discharge “beyond the boundary lines of the property lines on which the discharge originates orWV Regional Haze SIP Appendix H - 73 at any public or residential location, which causes or contributes to statutory air pollution”. Copies of this rule are included in Attachment H-6. In addition, the WVDAQ has a number of rules in place that require the control of fugitive dust within plant boundaries, these include 45CSR2 – To Prevent and Control Particulate Air Pollution form Combustion of Fuel in Indirect Heat Exchangers; 45CSR3 – To Prevent and Control Air Pollution from the Operation of Hot Mix Asphalt Plants; 45CSR5 – To Prevent and Control Air Pollution from the Operation of Coal Preparation Plants, Coal Handling Operations and Coal Refuse Disposal Areas; and 45CSR7 – To Prevent and Control Particulate Matter Air Pollution from Manufacturing Processes and Associated Operations. In regard to agricultural ammonia, West Virginia does not have a large agricultural industry with correspondingly large ammonia emissions. West Virginia accounts for 1.9 percent of the ammonia emissions in the VISTAS region, which as shown in Table 7.9-1 is the smallest contribution in the region. North Carolina, with it’s large agricultural industry, has ammonia emissions which totaled 173,083 tons in 2002 (26.1%), or 13.9 times West Virginia’s total.

Table 10.2-1. VISTAS Ammonia Emissions State 2002 NH 3 Emissions (tons) State % Contribution to Total Alabama 66,519 10.0 Florida 58,602 8.3 Georgia 95,936 14.5 Kentucky 57,563 8.7 Mississippi 63,929 9.6 North Carolina 173,084 26.1 South Carolina 36,509 5.5 Tennessee 43,258 6.5 Virginia 55,570 8.4 West Virginia 12,461 1.9 Total 663,431 100 Nevertheless, as shown in Table 10.2-2, the majority (~80%) of the ammonia emissions are attributable to the area sources sector, with ~90% of those emissions attributable to Agricultural Livestock Production. Due to the small size of the agricultural industry in West Virginia and the relatively small amount of ammonia emitted in the state, the WVDAQ has determined that controls are not warranted on agricultural sources. For a more detailed area source emissions inventory see Appendix D.WV Regional Haze SIP Appendix H - 74 Table 10.2-2. West Virginia NH 3 Emissions Sector 2002 (tons) 2002 (%) 2009 (tons) 2009 (%) 2018 (tons) 2018 (%) Point 453 3.64 671 4.93 593 4.12 Area 9,963 79.95 10,625 78.14 11,504 80.02 NonRoad 9 0.07 11 0.08 13 0.09 OnROad 2,036 16.34 2,292 16.86 2,268 15.76 Biogenics N/A N/A N/A N/A N/A N/A Total 12,461 100 13,598 100 14,377 100

10.3. Reasonable Progress Goals The regional haze rule at 40 CFR 51.308(d)(1) requires States to establish reasonable progress goals (RPG) for each Class I area within the state (expressed in deciviews) that provide for reasonable progress towards achieving natural visibility. In addition, EPA 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 State Implementation Plan (SIP) period. The state must also provide an assessment of the number of years it would take to attain natural visibility conditions if improvement continues at the rate represented by the reasonable progress goal. In accordance with the requirements of 40 CFR §51.308(d)(1), this Regional Haze Implementation Plan establishes reasonable progress goals for Dolly Sods and Otter Creek Wilderness areas. To calculate the rate of progress represented by each reasonable progress goal, WVDAQ compared baseline visibility conditions to natural visibility conditions in each class I area and determined 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. The WVDAQ will summarize expected visibility improvements under existing federal and state regulations, BART determinations in West Virginia and neighboring states, and any additional control measures found to be reasonable to implement in this review period. These controls will be modeled in CMAQ as part of the long-term strategy. The modeling results will be used to set the final reasonable progress goal. At this time, WVDAQ commits that the reasonable progress goals will be at least as stringent as the Base G2a modeling results and may be more stringent when BART and reasonable measures are taken into account. VISTAS has already demonstrated that the 2018 Base G2a control scenario provides for an improvement in visibility significantly better than the uniform rate of progress for Dolly Sods and Otter Creek 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.WV Regional Haze SIP Appendix H - 75 Table 10.3-1. West Virginia Reasonable Progress Goals Class I Area Baseline Visibility (Deciviews) Reasonable Progress Goal (Deciview Improvement Expected by 2018, 20% Worst Days) Reasonable Progress Goal (Deciview Improvement Expected by 2018, 20% Best Days) Deciview Improvement Needed 2018 - 2064

Dolly Sods Wilderness Area 29.0 7.3 1.2 11.3 Otter Creek Wilderness Area 29.0 7.3 1.2 11.3WV Regional Haze SIP Appendix H - 76 

### REFERENCES: 1. Boylan Ph.D., James, 2006, VISTAS Joint Tech Analysis-Planning Call. Power Point Presentation: Summary BART_VOC_NH3_PM.ppt. 2. Brewer, P.F.; and Adloch, J.P., 2005, Trends in Speciated Fine Particulate Matter and Visibility across Monitoring Networks in the Southeastern United States . J Air and Waste Management Association , 55, 1663-1674. 3. Federal Register / Vol. 70, No. 128 / Wednesday, July 6, 2005 / Rules and Regulations. 4. Hand, J.L.; and Malm, W.C.,2006, Review of the IMPROVE Equation for Estimating Ambient Light Extinction Coefficients - Final Report. March 2006. Prepared for Interagency Monitoring of Protected Visual Environments (IMPROVE), Colorado State University, Cooperative Institute for Research in the Atmosphere, Fort Collins, CO. 5. MACTEC, 2006, Documentation of the Base G 2002 Base Year, 2009 and 2018, Emissions Inventory VISTAS. 6. Pechan, E.H., and Associates, Inc., 2005, AirControlNET User Guide. 7. Pitchford, Marc., 2006, Natural Haze Levels II: Application of the New IMPROVE Alogrithm to Natural Species Concentrations Estimates. Final Report of the Natural Haze Levels II Committee to the RPO Monitoring/Data Analysis Workgroup. Sep 2006. 8. Sorrels, Larry, 2006, AirControlNET 4.1 Softwa re; US EPA, OAQPS, Research Triangle Park, NC. 9. U.S. Environmental Protection Agency. (2003). Guidance for Tracking Progress under the Regional Haze Program; EPA-54/B-03-004, 2003.