west virginia department of environmental protection

Appendix H

Reasonable Progress Evaluation and

Long Term Strategy

Promoting a healthy environment.
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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 SO2 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 - 45
WV 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 - 74
WV 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 Interstate 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 Matter
WV Regional Haze SIP Appendix H - iv

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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 Goals (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 graphically show what would be a “uniform rate

of progress” toward natural conditions for each Class I area. This is known as the “glidepath. 

The RHR then requires states to establish RPGs for visibility improvement at each affected Class

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

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

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

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

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

Our long term strategy contains the following components:

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 analyses 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 (SO2) 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 SO2 emissions in these states by over 70 percent and NOx

emissions by over 60 percent from 2003 levels. The Clean Air Mercury Rule will build on

EPA’s Clean Air Interstate Rule (CAIR) to significantly reduce emissions from coal-fired

power plants -- the largest remaining sources of mercury emissions in the country. When

fully implemented, these rules will reduce utility emissions of mercury from 48 tons a year to

15 tons, a reduction of nearly 70 percent.

• NOx SIP Call. 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 (SO2) 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/SO2/NOx

emissions; comply with system-wide annual PM/SO2/NOx emissions limits; agree not to

buy, sell or trade SO2/NOx 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 NOx, SO2 and PM. 

• VEPCO: Virginia Electric and Power Co. agreed to spend $1.2 billion between by 2013

to eliminate 237,000 tons of SO2 and NOx emissions each year from eight coal-fired

electricity generating plants in Virginia and West Virginia. 

• Gulf Power 7: A 2002 agreement calls for Gulf Power to upgrade its operation to cut

NOx 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 SO2 by 54,000 tons per year

and its emissions of NOx by 8,000 tons per year, by installing and operating selective

catalytic reduction (SCR) technology; low-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 SO2 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 SO2 emissions of the #8

Power Boiler. This control device should result in reductions of over 3,500 tons of SO2 in

2018.

• AEP: American Electric Power agreed to spend $4.6 billion dollars to eliminate 72,000

tons of NOx emissions each year by 2016 and 174,000 tons of SO2 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, respectively. 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 reciprocating internal combustion engines (RICE). These

rules reduce emissions of a number of toxic air pollutants, including hydrogen chloride,

manganese, lead, arsenic and mercury by 2009. 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 SO2 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 Standards. The point source MACTs and associated

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

EPA’s Emission Standards Division (ESD) staff. We did not apply reductions for MACT

standards with an initial compliance date of 2001 or earlier, assuming that the effects of these

controls are already accounted for in the 2002 inventories supplied by the States.
WV Regional Haze SIP Appendix H - 5

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

inventories:

1.1. Point Source Controls

Different approaches were used for the 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 proposed 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 subtraction of future emission controls based on the

best available data from state rules, enforcement agreements, compliance plans, permits, and

discussions/commitments from individual companies. 

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 other 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 SO2 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 None None None None None

8 & 9 None None None None None 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 None None None None None

3 None None SCR None None None None None

McIntosh

ORISID=6124

1 None None SCR None None None None None
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 SO2 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 Scrubber Scrubber Scrubber Scrubber

2, 3 None None None None 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 None None None None None

CAN2 None None None None None None None None

CAN3 None None None None None 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 Scrubber
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 SO2 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 NOx and

121 tons of SO2 per unit to the 2009 and 2018

inventories.

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

Development, Inc. GA specified that the emissions from

this proposed plant be included in the 2018 projections.

Boilers 1 and 2 added 1,882 tons of NOx and 3,227 tons

of SO2 per unit to the 2018 inventory.

MS R D Morrow

ORISID=6061

1, 2 Revised the 2018 emissions to reflect controls not

indicated by IPM. The SO2 emissions are much lower

than IPM, but their expected NOx emissions are actually

higher than IPM. The controls will be coming online

2009 or 2010, so the 2009 inventory did not change. 

Jack Watson (2049)

Victor J Daniel (6073)

Chevron Oil (2047)

All MS DEQ specified that the emission projections

provided by the Southern Company for their units in

Mississippi were to be used instead of the IPM results.

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 SO2 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 PM10 and PM25 emissions in

2018 by 95 percent based on change in allowable

emission rate

Unit 2: Install low NOx burners that meet 0.46

lb/mmBTU from 0.9 by May 1, 2004. Recalculated NOx

emissions using 0.46/lbs/mmBtu and IPM heat input

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

Dec. 31, 2012. Reduced PM10 and PM25 emissions in

2018 by 95 percent based on change in allowable

emission rate

Jeffries

ORISID=3319

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

Dec. 31, 2012. Reduced PM10 and PM25 emissions in

2018 by 94.44 percent based on change in allowable

emission rate

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

Dec. 31, 2012. Reduced PM10 and PM25 emissions in

2018 by 94.44 percent based on change in allowable

emission rate

W S Lee

ORISID=3264

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

SOFA NOx control technology by April 30, 2006 to

meet 0.27 lb/mmBTU, down from 0.45 lb/mmBtu.

Calculated NOx emissions using IPM heat input and

0.27 lbs/mmBtu
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 - 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 NOx for these units in

2009 and 111 tons in 2018. VA DEQ specified that the

permitted emission rates should be used, which equates

to 3,066 tons in 2009 and 2018.

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

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

control estimates. 

Unit 6: Replaced all 2009/2018 IPM results using

VADEQ’s growth and control estimates. 
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 SO2 Permit Rate was corrected from 2.7 to 0.678

lb/MMBtu. Used SO2 Permit Rate of 0.678 lb/MMBtu

and IPM predicted total fuel used to calculate SO2

emissions in 2009 and 2018

Mt. Storm

ORISID=3954

1, 2, 3 SO2 Permit Rate was corrected from 2.7 to 0.15

lb/MMBtu. Used SO2 Permit Rate of 0.15 lb/MMBtu

and IPM predicted total fuel used to calculate SO2

emissions in 2009 and 2018
WV 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 emission reductions were designed from Federal

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

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

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

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

initial compliance date of 2002 or greater. 

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

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

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

HAPs.
WV Regional Haze SIP Appendix H - 14

• NOx 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).

• NOx 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 are affected by two October 2003 Clean Air Act

settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the

Chevron refinery in Pascagoula, 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 Federal Register (FR) notices and discussions

with EPA’s Emission Standards Division (ESD) staff. We did not apply reductions for

MACT standards with an initial compliance date of 2001 or earlier, assuming that the

effects of these controls are already accounted for in the 2002 inventories supplied by the

States.

• 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 effectiveness and rule penetration) provided by the

States or originally developed for use in estimating 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 includes 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. Detailed inventory data (both before and after

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

the EPA's 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 between 1996 and 2010 (for 2009) and 2015 and 2020 (for

2018). This is done at the State-county-SCC-pollutant level of detail. According to EPA

documentation, the CAIR baseline emissions include the impacts of the Tier 4 (T4) non-road

diesel rulemaking, which implements a low sulfur fuel requirement that affects both future CMV

and locomotive emissions. 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

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual PM-2.5 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 

2018 OTW

0

20

40

60

80

100

120

140

160

180

200

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NH3 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW

1.5. Conclusion

In conclusion of this discussion on source sector controls, Figures 1.5-1 thru 1.5-4 depict

pollutant totals for NH3, PM2.5, NOx, and SO2 for the various sectors by state for 2002, 2009, and

2018 Base G2 modeling

Figure 1.5-1. Annual NH3 emissions – Base G2.

Figure 1.5-2.Annual PM2.5 emissions – Base G2.
WV Regional Haze SIP Appendix H - 17

0

100

200

300

400

500

600

700

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW

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

Figure 1.5-4.Annual SO2 emissions – Base G2.

0

100

200

300

400

500

600

700

800

900

1,000

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU 2002 Typical

2009 OTW

2018 OTW
WV 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 and 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

Year

Haziness Index (Deciviews)

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

Uniform Rate of Progress = 4.3 dv by 2018
WV 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 from major 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 implementing existing state and federal regulations

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

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

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

VISTAS states or neighboring RPOs. The greatest benefits at Dolly Sods in 2009 are projected

to come from further reducing SO2 from electric generating utilities (EGUs). Additional, smaller

benefits are projected from additional SO2 emission reductions from non-utility, industrial point

sources. Reductions of nitrogen oxide emissions from point sources (EGU and non-EGU) or

ground level sources (on road vehicles, off road engines, and area sources) and reductions of

primary carbon from point or ground level sources are projected to be significantly less

beneficial than reductions in SO2 emissions. Reductions in anthropogenic VOC emissions show

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

measurable improvement. However, controlling the VOCs from vegetation is not possible or

appropriate. For this sensitivity run, further reducing SO2 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 benefits at Dolly Sods. Approximately 40% of the

benefit at Dolly Sods from further SO2 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 either ground or point sources. Reducing ammonia

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

reductions in SO2 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

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

Δ

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Emissions sensitivities for Otter Creek are the same as for Dolly Sods
WV 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 SO2 emissions from electric generating utilities would be most beneficial

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

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

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

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

be more effective in reducing ammonium nitrate than controlling nitrogen oxide emissions. 

Dolly_Sods, WV (Winter)

-7.00

-6.00

-5.00

-4.00

-3.00

-2.00

-1.00

0.00

1.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

°

Bext (Mm -1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL
WV Regional Haze SIP Appendix H - 22

Average Extinction for 20% Worst Days

New IMPROVE Algorithm (nia)

2000-2004

0

50

100

150

200

250

300

SWAN1ROMA1

OKEF1EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

BRIG1

BRET1

MING1

HEGL1

UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (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 Class 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 SO2 emissions from Electric Generating Utilities (EGU) and non-EGU industrial

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

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

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

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

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

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

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

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

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

area.

4.2. Source Type Analyses

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 SO2 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 VOC NOX CO SO2 PM-10 PM-2.5 NH3

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%

Storage & Transport 6% 0% 1% 0% 1% 1% 0%

Waste Disposal & Recycling 4% 2% 3% 0% 4% 9% 0%

Highway Vehicles 19% 21% 47% 0% 2% 2% 13%

Off-highway 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 partner with VISTAS’s Data Analysis contractor,

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

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

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

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

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

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

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

transformation and dispersion of emissions. 

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

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

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

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

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

archives.

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

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

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

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

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

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

The major model parameters selected for this analysis include those listed in Table 4.3-1.

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 following
WV 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 the meteorological conditions at a given location

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

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

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

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

sampling sites in and around the VISTAS region:

1. Breton, LA (BRET1)

2. Brigantine NWR, NJ (BRIG1)

3. Cadiz, KY (CADI1)

4. Caney Creek, AR (CACR1)

5. Cape Romain NWR, SC (ROMA1)

6. Chassahowitzka NWR, FL (CHAS1)

7. Cohutta, GA (COHU1)

8. Dolly Sods Wilderness, WV (DOSO1)

9. Everglades NP, FL (EVER1)

10. Great Smoky Mountains NP, TN (GRSM1)

11. Hercules-Glades, MO (HEGL1)

12. James River Face Wilderness, VA (JARI1)

13. Linville Gorge, 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 trajectories, ARS generated extinction-weighted

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

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

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

horizontal grid cells of latitude and longitude. 

Extinction data is based on the IMPROVE Regional Haze Rule dataset, as available from the

VIEWS website (http://vista.cira.colostate.edu/views/Web/IMPROVE/SummaryData.aspx) in

November 2005 and is calculated based on the original IMPROVE algorithm. For sites with less

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

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

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

nearby sites. 

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

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

(POM), Light Absorbing Carbon (LAC), Soil, and Coarse Mass (CM). Weighting trajectories

for the 20% worst days by sulfate extinction gave greater importance to days influenced by SO2

emissions and lesser importance to days influenced by organic carbon emissions. This allowed a
WV 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 ENVIRON. 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, provided 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., geodetic 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 analysis and GIS processing involved re-projecting

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

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

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

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

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

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

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

Using the trajectories with the 100-m start height, the State has defined the SO2 Areas of

Influence as the area with grid cells showing 10% (area shaded in yellow in following plots) or

greater residence time (the frequency that winds pass over that area on the way to the Class I

area on the 20% 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 SO4 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. Finally, county boundaries were overlaid to identify

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

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

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

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

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

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

Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory

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

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

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

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

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

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

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

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

inventories. Figures 4.4-5 and 4.4-6 display the gridded point source SO2 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 SO2 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 SO2 emissions for the VISTAS region in tons/year. (2018

Base G)

As a way of incorporating the effects of transport, deposition, and chemical transformation of

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

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

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

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

The final step in the development of the displays and data sets involves the combination of the

residence times and gridded emission data. The distance weighted (1/d) gridded point source

SO2 emissions are multiplied by the total extinction-weighted back-trajectory residence times

(SO2 * Bext-weighted RT * (1/d)) on a grid cell by grid cell basis. These results are then

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

for both the 2002 and 2018 base year inventories. Figure 4.4-7 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 SO2 emissions and extinction-weighted residence times are

overlayed with county boundaries and exported to comma-delimited ASCII data files for further

analyses of emissions and control options for specific sources. The following sets of plots show

the comparison of 2002 versus 2018 SO2 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 SO2 Emissions multiplied by SO4 extinction-weighted

residence time plots.

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

gridded SO2 emissions and defined the SO2 Areas of Influence as those areas with residence time

greater than 10%, based on trajectories with start height of 100m and four start times per day.

Extinction-weighted residence plots for Class I areas indicate that the areas of probable influence

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

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

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

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

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

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

from the Class I area can contribute to visibility impairment on some 20% 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 (EC) are indicators of fire. Some states may

need to consider emissions from residential wood burning, forest fires (wild and prescribed),

land clearing, and agricultural burning.

Nitrate (NH4NO3) levels in winter can be significant and are dependent on availability of NH3;

nearly 80% of NH3 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 SO2 reductions in this first Regional Haze SIP.

4.6. Summary of Emission Inventories Used in Cost Curve Analysis

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

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

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

of transport 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 NOx CO SO2 PM10 PM2.5 NH3

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

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

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

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

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

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

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

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

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

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

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

Table 4.6-2. 2018 Base Case Annual Emissions Summary

Base G Annual Emissions - 2018 Base Case (Tons)

State VOC NOx CO SO2 PM10 PM2.5 NH3

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

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

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

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

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

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

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

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

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

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

VISTAS 3,904,780 2,669,125 22,621,023 2,349,107 2,357,445 1,029,017 787,325
WV 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 ranking of the highest residual sub source types was

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

weighted analysis, these emission reviews and summaries like those presented in Figure 4.6-1,

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 States to review existing emission reductions

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

the scenario. These tables presented comparisons of 2002 and 2018 emission levels, for SO2,

and future year control technology assignment (by IPM forecasting and State modification) for

point sources. Non-EGU unit-specific technology assignments were identified using the control

efficiency tables provided by the VISTAS emissions inventory contractor, MACTEC.Ultimately,

the final control strategy decisions will include the application of BART subject source

reductions in the future year base case. 

Figure 4.6-1. VISTAS Base G2 SO2 Emissions Contribution by Major Source Sector.

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

West Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

West Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018
WV 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 SO2 and NOX, we made some assumptions, based on IPM documentation, as to what pollutant

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

primary and secondary control device code combinations for SO2, are presented in Table 4.7-1. 

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, or EPA CAMD CEM data sets to obtain these

variables when missing. Unit level boiler capacity (MMBtu/hr) or NETDC (MW) values are

required for capital and operating and maintenance cost calculations for many of the SO2 applied

technologies. In cases where these nameplate capacity values could not be identified, emission

weighted capacities (based on the final EPA 2002 NEI) were assigned to boilers using a primary

(highest emitting) SCC. Table 4.7-2 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 SO2 Control

Efficiencies
WV 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, PM10, PM2.5, SO2, NOX, as well as visibility impairment

(regional haze) from point, area, and mobile sources. PM10 and PM2.5 as included in

AirControlNET represent primary emissions of PM. The control measure data file in

AirControlNET includes not only the technology's control efficiency, and calculated emission

reductions for that source, but also estimates the costs (annual and capital) for application of the

control measure.

Since available versions of AirControlNET contain the preprocessed application of control

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

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

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

SCC Description NETDC (MW)

10100201 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Wet 

Bottom (Bituminous Coal) 200

10100202 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom (Bituminous Coal) 500

10100203 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace 

(Bituminous Coal) 200

10100212 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom (Tangential) (Bituminous Coal) 500

10100215 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cell Burner 

(Bituminous Coal) 1300

10100218 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Atmospheric Fluidized 

Bed Combustion: Circulating Bed (Bitum. Coal) 200

10100222 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom (Subbituminous Coal) 400

10100223 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace 

(Subbituminous Coal) 400

10100226 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom Tangential (Subbituminous Coal) 500

10100401 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Normal Firing 400

10100404 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Tangential Firing 500

10100501 External Combustion Boilers; Electric Generation; Distillate Oil; Grades 1 and 2 Oil 400

10100601 

External Combustion Boilers; Electric Generation; Natural Gas; Boilers > 100 Million Btu/hr except 

Tangential 400

10100701 External Combustion Boilers; Electric Generation; Process Gas; Boilers > 100 Million Btu/hr 200

10100801 External Combustion Boilers; Electric Generation; Petroleum Coke; All Boiler Sizes 600

10101204 External Combustion Boilers; Electric Generation; Solid Waste; Tire Derived Fuel : Shredded 200

10300811 External Combustion Boilers; Commercial/Institutional; Landfill Gas; Landfill Gas 200

20100101 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine 200

20100109 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine: Exhaust 200

20100201 Internal Combustion Engines; Electric Generation; Natural Gas; Turbine 200

 

 All other boilers 100
WV 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 SO2 control strategy in

AirControlNET against the EGU and non-EGU point source inventories to develop a master list

of available, incremental control strategies for the entire VISTAS 36 km domain necessary for

VISTAS States to design command-and-control or cost-effectiveness based control strategies by

source or domain. 

4.9. Development of AoI-Based Cost Curves

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

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

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

the entire domain. 

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

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

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

developed in AirControlNET and improved upon with stakeholder input will help attain

reasonable further progress emission reduction objectives while presumably minimizing the

number and type of controlled sources in each AoI.

Using a geocoded county list from these AoIs, we parsed the master list of incremental control

measures from all point sources located within the boundaries of the AoIs. This parsed list was

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

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

Each individual source had its own cost effectiveness curve generated. 

In aggregate, the results of these applications are SO2 emission cost curves for all EGU and nonEGU point sources within the geographic domain of the AoI. Incremental controls on area and

mobile sources were not considered in this analysis. An illustrative example of the steps

involved with the cost effectiveness curve design can be found in the 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 SO2 point source emissions

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

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

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 SO2 emissions from EGU and non-EGU point sources in geographic

Areas of Influence (AoIs) are sources which should be considered for further controls. VISTAS

developed source matrices for SO2 AoIs for each Class I area, using data delivered by

ENVIRON for 2002 and 2018 SO2 emissions multiplied by SO4 extinction weighted residence

time plots. 

Spreadsheets were developed for each Class I area with:

• Plant name

• Point ID

• Tons SO2 projected for 2018

• Q (tons)

• Current control efficiency, CE (%)

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

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

• 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 SO2 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 focus 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 level 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 problem
WV 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 NOx SIP Call.

3. For the CAIR rule, a PM contribution of 0.2 μg/m3

 was used to demonstrate a significant

impact, which is 1.3% of the annual PM2.5 standard of 15 μg/m3

.

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 reasonable further progress was as protective or

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

for NOx, which has a NAAQS of 100 μg/m3 and a significance level of 1 μg/m3, 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 SO2 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 SO2 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 projections for 2018, current control efficiency (CE%),

distance from Class I area, Q/d, RT maximum, 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 SO2 control efficiency, annual SO2 emissions

reduction from 2018 Base Case, total annualized cost (in 2005 dollars), and cost per ton reduced

for application of specific control measures.

The WVDAQ reviewed the sources, emissions, control options, and costs from the SO2 AoI

matrices and defined sources for which the Four Factor Analysis was to be conducted. The same

few categories of point sources, fuel combustion from electric utilities and from industrial

sources, contribute to the majority of SO2 emissions, with little contribution from other sources. 

Therefore, the WVDAQ eliminated other source categories 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 visibility
WV 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 consumption. The State should also consider any

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

generated by a particular control technology.

6.1.d. Remaining Useful Life of the Source

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

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

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

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

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

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

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

of Influence 

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

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

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

assigned future year control technology from IPM forecasting; 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 AirControNET database, modified for the VISTAS

emission inventories. The core of AirControlNET is a relational database system in which

control technologies are linked to sources within EPA emissions inventories. The system

contains a database of control measure applicability, efficiency, and cost information for

reducing emissions. The control measure data file in AirControlNET includes not only the
WV 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 SO2 control

strategy in AirControlNET against the EGU and non-EGU point source inventories to develop a

master list of incremental control strategies for each unit in the VISTAS 36 km domain.

For the sources within the 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 SO2 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 the statutory factors for reasonable further progress. 

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

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

• the costs of compliance

• the time necessary for compliance

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

• the remaining useful life of any potentially affected sources.

6.2.a. Cost of Compliance

Coal-fired electric utilities and coal-fired industrial boilers are the largest source categories

contributing to SO2 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

SO2 in 2018. 

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

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

analyses for accuracy. 

Bituminous coal is commonly burned in boilers in the eastern US. Switching to another

bituminous coal with lower sulfur content or blending bituminous coals can often reduce SO2

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 without

affecting 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 heat 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 sulfate byproduct is produced that may be further

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

include initial construction costs and ongoing operational and maintenance costs for the absorber

tower, sorbent handling, and waste product handling facilities. Costs per ton vary with boiler

size, type, and facility siting considerations. 

For oil-fired boilers, lower sulfur oil may be an option. Costs evaluation should consider 

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

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

precedence for such installations. 

6.2.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 and 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 increased 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 SO2 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 Class
WV Regional Haze SIP Appendix H - 46

I areas in the Southern Appalachian region and that these sulfates were produced in large part

from SO2 emissions from coal combustion. 

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

Since SO2 point source emissions in 2018 are projected to represent greater than 95 percent of

the total SO2 emissions inventory, the VISTAS States concluded that the focus should be on

electric generating unit (EGU) and non-EGU point sources of SO2 emissions.

Step 3: Determine if CAIR is sufficient for reasonable progress for subject EGU’s. 

The WVDAQ calculated the fractional contribution from all emission units within the SO2 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 SO2 reduction

from the EGUs projected due to CAIR. The EGUs in West Virginia are projected to reduce their

2002 SO2 emissions by 47 percent by 2009 and a total of 78 percent by 2018. The projected SO2

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 commencement 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 SO2 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 Station1 001 Dolly Sods, Shenandoah

023-0003 Mount Storm Power Station1 002 Dolly Sods, Shenandoah

023-0003 Mount Storm Power Station1 003 Dolly Sods, Shenandoah

033-0015 Harrison Power Station1 001 Dolly Sods, Shenandoah

033-0015 Harrison Power Station1 002 Dolly Sods, Shenandoah
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% 

WV Regional Haze SIP Appendix H - 47

033-0015 Harrison Power Station1 003 Dolly Sods, Shenandoah

023-0014 North Branch Power Station2 001 Dolly Sods

023-0014 North Branch Power Station2 002 Dolly Sods

073-0005 Pleasants Power Station1 001 Dolly Sods, Shenandoah

073-0005 Pleasants Power Station1 002 Dolly Sods, Shenandoah

061-0001 Ft. Martin Power Station3 001 Dolly Sods

061-0001 Ft. Martin Power Station3 002 Dolly Sods

079-0006 John Amos Power Station3 001 Dolly Sods, James River Face

079-0006 John Amos Power Station3 002 James River Face

079-0006 John Amos Power Station3 003 James River Face, Shenandoah

053-0009 Mountaineer Power Station1 001 Dolly Sods, Shenandoah 1

Currently equipped wet scrubbers with SO2 control efficiency >90% 2

Circulating Fluidized Bed (CFB) boiler with SO2 control efficiency >90% 3

Construction has commenced on wet scrubbers with SO2 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 SO2 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 Shenandoah
WV 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 SO2 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 comprehensive review of the cost-effectiveness of EGU SO2

controls, which is appropriate to consider as a benchmark in determining a reasonable cost

effectiveness for SO2 control for purposes of the reasonable progress assessment.

In the CAIR preamble EPA notes that:

The SO2 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 SO2 controls based on the Energy

Information Administration’s projections for electricity growth and natural gas

prices. These sensitivity analyses showed marginal SO2 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 SO2 emission reduction requirements for the CAIR final

rule.

(I) Reference Lists of Cost-Effective SO2 Controls

For today’s action, EPA updated the reference list of controls included in the NPR

of the average and marginal cots per ton of recent SO2 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 reference 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 SO2 controls. This table includes average costs

for recent BACT permitting decisions for SO2. 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 SO2 controls, because they represent cost-effective controls that have been

demonstrated.

TABLE IV-3. – Average Costs per Ton of Annual SO2 Controls

SO2 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 SO2 controls (www.epe.gov/ttn/catc/).

We identified actions in the data base for large, utility scale, coal-fired boiler units for which

cost effectiveness data were reported. The range of 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 reported 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 engines 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). Estimated 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 per ton of recent State and regional decisions

for annual SO2 controls.
WV Regional Haze SIP Appendix H - 50

Table IV-4.– Marginal Costs per Ton of Annual SO2 Controls

SO2 control action Marginal cost

per ton

New Hampshire Rule 1

$600

WRAP Regional SO2 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 SO2 emissions of all existing

fossil steam units.

2

"An Assessment of Critical Mass for the Regional SO2 Trading Program,” prepared for the

Western Regional Air Partnership Market Trading Forum by ICF Consulting Group, September

27, 2002, available in the docket. This analysis looked at the implications of one or more States

choosing to opt-out of the WRAP regional SO2 trading program. (1999$ per ton).

(II) Cost Effectiveness of the CAIR Annual SO2 Reductions

. . .Table IV-5 provides the average and marginal costs of annual SO2 reductions

under the CAIR for 2010 and 2015.(When presenting 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 assumptions about natural gas price and electric

growth.)

Table IV-5. – Estimated Costs per Tons of SO2 Controlled Under CAIR, Cap

Levels Beginning in 2010 and 20151

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 SO2 control costs under the CAIR reflect annual EGU SO2 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 SO2 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 SO2. . . . ”
WV Regional Haze SIP Appendix H - 51
WV Regional Haze SIP Appendix H - 52

After review of EPA’s CAIR cost analyses the WV DAQ determined that the CAIR SO2 control

costs vary by year of analysis (2010 vs. 2015) and may range from $400 to $3,400 per ton SO2

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 was 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 SO2 limit for

Kiln 7 was reduced to 900 tpy; actual SO2 emissions in 2002 from Kiln 7 were 1,247 tons and

projected SO2 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 SO2 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 SO2, so BACT for SO2 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 SO2 controls available.

Cost of Compliance - Precalciner System

The Mid-Atlantic/Northeast Visibility Union (MANE-VU) RPO contracted with MACTEC, Inc.

to evaluate control options and the four statutory factors for assessing Reasonable Progress

Goals (RPGs) for regional haze in the MANE-VU region. The project report [Assessment of
WV 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 SO2 emissions from electric utilities, industrial

boilers, kilns, residential heating oil and wood combustion. For kilns, the report identifies four

control options for SO2 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 SO2 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 SO2 control.

MACTEC, in their report, provided cost estimates for the other three control options identified

above.

Table 6.3-3. SO2 Control Costs for Large Preheater Kilns (2006 Dollars)

Capitol Cost

(106 $)

Annual Operating Costs

(106 $)

SO2 Cost Effectiveness

($/ton SO2 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 SO2 controls available for the new

precalciner system at Capitol Cement.

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

The three remaining statutory factors: 1) time necessary for compliance, 2) the energy and nonair quality environmental impacts of compliance, and 3) the remaining useful life of the

emissions unit, while required to be considered, were deemed not applicable, since there were no

cost effective controls to evaluate.

7.0. 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 the
WV 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 SO2, NOX, and direct particulate matter (PM)

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

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

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

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 in
WV 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-eligible 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 SO2, NOx, PM10, VOC, or ammonia, based upon the Standard Industrial 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 Pineville
Table 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 less 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

0.6

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV

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, GA
WV 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 sources 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 allows 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 (NH3) 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, NH3, 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 NH3 Impact – Maximum Contributions of all BART-eligible NH3

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 National 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 NH3 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

1.5

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV
WV 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.

NH3 emissions from BART sources may impair visibility; however the majority of NH3

emissions in the VISTAS region are from a few BART sources. Removal of the large NH3

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 NH3 impacts and potential

controls for NH3. Based on the CMAQ sensitivity analyses of the impact of ammonia emissions,

West Virginia concluded that NH3 is not a visibility impairing pollutant for BART purposes and

that BART-eligible sources do not need to consider NH3 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 98th

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 98th percentile value to the threshold must be made for each Class I

area. For an annual period, this implies the 8th highest 24-hr value at a particular Class I area is

compared to the contribution threshold. For a 3-year modeling period, the 98th percentile value

may be interpreted as the highest of the three annual 98th percentile values at a particular Class I

area or the 22nd highest 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 performing 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 modeling 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 version 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 (eastern United States) and provided CALMET output

files for five 4-km grid subdomains covering the 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 individual 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 explain 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 98th percentile 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 were 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 greater 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 Visibility Impact (delta-deciview) per Class I Areas

Company Year Dolly

Sods,

WV

Otter

Creek,

WV

Shenandoah, VAJames

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/a
Table 8.2-1. BART Exemption Modeling Results

 12 km Modeling - Maximum Predicted Visibility Impact (delta-deciview) per Class I Areas

Company Year Dolly

Sods,

WV

Otter

Creek,

WV

Shenandoah, VAJames

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 0.046
Table 8.2-1. BART Exemption Modeling Results

 12 km Modeling - Maximum Predicted Visibility Impact (delta-deciview) per Class I Areas

Company Year Dolly

Sods,

WV

Otter

Creek,

WV

Shenandoah, VAJames

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 - 98th 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/a
Table 8.2-2. BART Exemption Modeling Results

 4km Modeling - 98th 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/a
WV 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 SO2.

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 the 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 these 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). These 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 - 98th 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 0.364
Table 8.2-3. Exemption Modeling Results for Facilities with >0.5 deciview of Impact

 4km Modeling - 98th 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 SO2 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 NOx, and the remaining facility (2 units) has installed

SNCR, to meet either the requirements of the NOx SIP Call or CAIR. Five of the seven facilities

(11 units) currently have scrubbers installed to reduce SO2 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 sources 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 SO2 or NOx

emissions. West Virginia is participating in CAIR, and accepts EPA’s overall finding that CAIR

“substitutes” for BART for NOx and SO2. 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 develop 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 Equation

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 increasing 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 that the mass concentration of particulate

organic matter in rural areas is greater than represented by the old equation.

5. The new algorithm includes a NO2 term to represent times when light absorption by NO2

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 area
WV 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 Class 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 two 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 kilns
WV 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 cease 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 visibility improvement at each affected Class I area

covering each (approximately) 10-year period until 2064. This first set of reasonable progress

goals must be met through measures contained in the state’s long-term strategy covering the

period from the baseline until 2018. This section discusses development of 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 SO2 emissions would be the most effective means of reducing ammonium sulfate. 

Ninety-eight percent of SO2 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 SO2 emissions from major point sources.

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

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

greater than a 77% reduction from EGU SO2 emissions in West Virginia. Overall the SO2

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

any of the Class I areas in West Virginia or in neighboring States. The WVDAQ concluded that

the reduction in EGU SO2 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 before 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 or
WV 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 NH3 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 NH3 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 11.3
WV 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 Software; US EPA, OAQPS, Research Triangle

Park, NC.

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