Douglas W. Domenech 

Secretary of Natural Resources 

COMMONWEALTH of VIRGINIA 

DEPARTMENT OF ENVIRONMENTAL QUALITY 

Street address: 629 East Main Street, Richmond, Virginia 23219 

Mailing address.' P.O. Box 1105, Richmond, Virginia 23218 

TDD (804) 698-4021 

www.deq.virginia.gov 

OCT 042010 

Ms. Diana Esher, Director 

Air Protection Division (3APOO) 

U.S. Environmental Protection Agency, Region III 

1650 Arch Street 

Philadelphia, Pennsylvania 19103-2029 

Dear Ms. Esher: 

Reference: Regional Haze SIP 

David K. Paylor 

Director 

(804) 698-4000 

1-800-592-5482 

Pursuant to the requirements of Section 110 of the Clean Air Act, we are officially 

requesting approval of a revision to the Commonwealth of Virginia State Implementation Plan 

(SIP) approved under the authority of § 10.1-1307.2 A of the Virginia Air Pollution Control Law 

and submitted in accordance with the requirements of 40 CFR Part 51 (Requirements for 

Preparation, Adoption, and Submittal of Implementation Plans). 

This revision consists of a plan to reduce the pollution that causes visibility impairment. 

The plan establishes goals and emission reduction strategies based on trends from various 

sources including area source emissions, mobile source emissions (both on-road and non-road 

emissions), commercial marine emissions, biogenic emissions, and wildfire and agriculture 

emissions. The regional haze SIP will enable Virginia to reduce visibility impairment to the point 

that visibility in Class I areas (national parks) will be returned to natural conditions by 2064. 

Enclosed are the following: 

1. State implementation plan. 

2. Certification of public participation activities and compliance with state 

administrative procedures. 

3. Record of hearing and summary oftestimony. 
If you have any questions or need additional information, please let us know. 

DKPlkgs 

TEMPLATESISIP-PLAN\PLNOO 

SIPIREGIONAL HAZEIPLANIRH-SIP.DOC 

Enclosures 

David K. Paylor 
 ENCLOSURE 1 

Regional Haze State Implementation Plan

For Virginia Class I Areas –

Shenandoah National Park and James River

Face Wilderness Area

Virginia Department of Environmental Quality 

Air Division 

Final 
i-Virginia Regional Haze SIP 

Preface: This document contains summaries of the technical analyses that will be used by 

Virginia to support the regional haze state implementation plan pursuant to §§107(d)(3)(D) and 

(E) of the Clean Air Act. 
ii-Virginia Regional Haze SIP 

EXECUTIVE SUMMARY 

Haze is defined as visibility impairment caused by absorption and scattering of light by fine 

particles. Visibility impairment is considered the “best understood and most easily measured 

effect of air pollution.” Regional haze is caused by sources and activities that emit these fine 

particles and their precursors over a large region, including areas of concern, such as national 

parks, forests, and wilderness areas (“Class I” Federal areas). The federal Clean Air Act 

mandates requirements to protect visibility, especially in Class I areas. In 1999, the U.S. 

Environmental Protection Agency (USEPA) finalized the Subpart P of 40 CFR Part 51, 

Protection of Visibility, which is also known as the regional haze regulation. The regulation calls 

for state, tribal, and federal agencies to work together to improve visibility in 156 national parks 

and wilderness areas, including the 18 Class I areas located in the area covered by the Visibility 

Improvement – State and Tribe Association of the Southeast (VISTAS). The States are required 

to develop and implement air quality protection plans (state implementation plans, or SIPs) to 

reduce the pollution that causes visibility impairment. 

These plans should establish goals and emission reduction strategies based on trends from 

various sources including area source emissions, mobile source emissions (both on-road and 

non-road emissions), commercial marine emissions, biogenic emissions, and wildfire and 

agriculture emissions. Under the regional haze regulation, states are required to develop SIPs to 

reduce visibility impairment with the intent that by 2064, the visibility in the Class I areas will be 

returned to natural conditions. 

Five multi-state regional planning organizations (RPOs) currently are working together to 

develop the technical basis for these State plans. The products of the regional planning 

organizations will be used by States to establish monitoring strategies for evaluating visibility 

conditions, baselines, and trends, and to develop long-term (10 to 15 years) strategies for making 

"reasonable progress" toward eliminating all anthropogenic visibility impairment from 

mandatory Class I areas. With the help of the VISTAS RPO, Virginia has developed a SIP to 

address visibility impairment in the State’s Class I Federal Areas--the Shenandoah National Park 

and the James River Face Wilderness Area. 

In developing the SIP, Virginia has sought to develop reasonable progress goals and long-term 

strategies as well as to examine the reasonableness of Best Available Retrofit Technology 

(BART) reductions. As will be discussed further, for the 20 percent worst days, Virginia has 

adopted for Shenandoah a reasonable progress goal of a 7.4 deciview (dv) reduction in visibility 

impairment by 2018, which is more aggressive than the uniform rate of progress needed to 

achieve a natural background condition of 11.4 dv by 2064. Likewise, for James River Face on 

the 20 percent worst days, Virginia has adopted a reasonable progress goal of a 6.7 dv reduction 

in visibility impairment by 2018. Again, this goal is more aggressive than the uniform rate of 

progress needed to achieve natural background conditions of 11.1 dv by 2064. Virginia has also 

adopted a reasonable progress goal for the 20 percent best days for each area. For Shenandoah, 

this reasonable progress goal of 8.7 dv would result in a 2.2 dv reduction in visibility impairment 

on the 20 percent best days. For James River Face, this reasonable progress goal of 12.4 dv will 

result a 1.8 dv reduction in visibility impairment on the 20 percent best days. The 

aforementioned predicted reductions in visibility impairment are expected to result from 
iii-Virginia Regional Haze SIP 

implementation of existing and planned emission controls that will be discussed further 

throughout the remaining portion of this SIP document. 

Table 1.1. Goal Summary 

All Values in Deciviews 

(dv) 

James River Face 

Wilderness Area 

Shenandoah National 

Park 

20% Best Days 

Baseline 14.2 10.9 

Reasonable Progress Goal 12.4 8.7 

Improvement ∆1.8 ∆2.2 

Natural Conditions 4.4 3.1 

20% Worst Days 

Baseline 29.1 29.3 

Uniform Rate of Progress 24.9 25.1 

Reasonable Progress Goal 22.4 21.9 

Improvement ∆6.7 ∆7.4 

Natural Conditions 11.1 11.4 
TABLE OF CONTENTS 

iv-Virginia Regional Haze SIP 

1. INTRODUCTION.................................................................................................................. 1 

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

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

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

1.4. Class I areas in Virginia ..................................................................................................... 4 

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

2. ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND ESTIMATE OF 

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

2.1. Estimating Natural Conditions for Virginia Class I Areas................................................. 8 

2.2. Estimating Baseline Conditions for Virginia Class I Areas ............................................... 9 

2.3. Summary of Natural Background and Baseline Conditions for Virginia Class I Areas .... 9 

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

3. GLIDEPATHS TO NATURAL CONDITIONS IN 2064 ................................................... 16 

4. NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILITY IMPAIRMENT IN 

VIRGINIA CLASS I AREAS .............................................................................................. 17 

4.1. Baseline Emissions Inventory .......................................................................................... 17 

4.1.1. Stationary Point Sources....................................................................................... 18 

4.1.2. Stationary Area Sources........................................................................................ 25 

4.1.3. Off-Road Mobile Sources..................................................................................... 25 

4.1.4. Highway Mobile Sources...................................................................................... 26 

4.1.5. Biogenic Emission Sources................................................................................... 26 

4.1.6. Summary 2002 Base G2 (February 2007 version) Baseline Emissions Inventory 

for Virginia............................................................................................................ 26 

4.1.7. Model Performance Improvements through Emissions Inventory Improvements27 

4.2. Assessment of Relative Contributions from Specific Pollutants and Sources Categories27 

5. REGIONAL HAZE MODELING METHODS AND INPUTS........................................... 28 

5.1. Analysis Method............................................................................................................... 28 

5.2. Model Selection................................................................................................................ 29 

5.2.1. Selection of Photochemical Grid Model............................................................... 29 

5.2.2. Selection of Meteorological Model ...................................................................... 30 

5.2.3. Selection of Emissions Processing System........................................................... 31 

5.3. Selection of the Modeling Year........................................................................................ 32 

5.4. Modeling Domains ........................................................................................................... 34 

5.4.1. Horizontal Modeling Domain............................................................................... 34 

5.4.2. Vertical Modeling Domain ................................................................................... 36 
TABLE OF CONTENTS 

v-Virginia Regional Haze SIP 

6. MODEL PERFORMANCE EVALUATION ...................................................................... 36 

6.1. Modeling Performance Goals and Criteria....................................................................... 37 

6.2. VISTAS Domain-Wide Performance............................................................................... 38 

6.3. Virginia Class I Area Performance .................................................................................. 41 

7. LONG-TERM STRATEGY................................................................................................. 44 

7.1. Overview of the Long-Term Strategy Development Process........................................... 44 

7.2. Expected Visibility Results in 2018 for Virginia Class I Areas under existing and planned 

emissions controls (Base G2 Inventory) .......................................................................... 45 

7.2.1. Federal and State Control Requirements .............................................................. 45 

7.2.2. Additional State Programs to Reduce Emissions.................................................. 47 

7.2.3. Projected 2009 and 2018 Base G2 Emissions Inventories.................................... 47 

7.2.4. Model Results for the 2018 Base G2 Inventory Compared to the Uniform Rate of 

Progress Glidepaths for Virginia Class I Areas .................................................... 50 

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

VISTAS Class I areas....................................................................................................... 56 

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

Geographic Areas ............................................................................................................. 58

7.5. Relative Contributions to Visibility Impairment: Geographic Areas of Influence for 

Virginia Class I Areas ...................................................................................................... 62 

7.5.1. Back Trajectory Analyses..................................................................................... 63 

7.5.2. Residence Time Plots............................................................................................ 63 

7.5.3. SO2 Areas of Influence ......................................................................................... 64 

7.5.4. Emissions Sources within SO2 Areas of Influence............................................... 64 

7.5.5. Specific Source Types in the Areas of Influence for Virginia Class I Areas ....... 69 

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

of Influence....................................................................................................................... 72 

7.6.1. Cost of Compliance............................................................................................... 73 

7.6.2. Time Necessary for Compliance........................................................................... 73 

7.6.3. Energy and Non-Air Environmental Impacts ....................................................... 73 

7.6.4. Remaining Useful Life.......................................................................................... 74 

7.7. Which Control Measures Represent Reasonable Progress for Individual Sources? ........ 74 

7.7.1. Step 1: Determine pollutants of concern.............................................................. 74 

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

progress................................................................................................................. 74 

7.7.3. Step 3: Determine if the Clean Air Interstate Rule (CAIR) is sufficient for 

reasonable progress for subject EGU’s................................................................. 74 

7.7.4. Step 4: Determine which emission units would be evaluated based on impact... 75 

7.7.5. Step 5: Evaluate the four factors.......................................................................... 76 
TABLE OF CONTENTS 

vi-Virginia Regional Haze SIP 

7.8. What Control Determinations Represent Best Available Retrofit Technology (BART) for 

Individual Sources? .......................................................................................................... 89 

7.8.1. BART-Eligible Sources in Virginia...................................................................... 90 

7.8.2. Determination of Sources Subject to BART in Virginia ...................................... 91 

7.8.3. Determination of BART Requirements for Subject-to-BART Sources ............... 94 

7.9. Affects of the CAIR Remand ........................................................................................... 99 

7.10. What Additional Emissions Controls Were Considered as part of the Long-Term Strategy 

for Visibility Improvement by 2018?............................................................................. 100 

7.10.1. Smoke Management............................................................................................ 101 

7.10.2. Dust and Fine Soil from Construction Activities................................................ 101 

7.10.3. NH3 and Agricultural Emissions Mitigation....................................................... 102 

7.10.4. Base G4a Best and Final Inventory .................................................................... 102 

8. REASONABLE PROGRESS GOALS (RPGs) ................................................................. 105 

8.1. Reasonable Progress Goal Summary ............................................................................. 105 

8.2. Clean Air Interstate Rule Remand and Reasonable Progress Goals .............................. 108 

9. MONITORING STRATEGY ............................................................................................ 110 

10. INTERSTATE CONSULTATION .................................................................................... 112 

11. COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN REVISIONS ................. 114 

12. DETERMINATION OF ADEQUACY OF THE EXISTING PLAN................................ 120 
LIST OF APPENDICES 

vii-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Appendix A: VISTAS Documentation 

A-1 VISTAS bylaws 

Appendix A-1 VISTAS bylaws.pdf 

Memorandum of Understanding Visibility Improvement – State and Tribal Association of the 

Southeast (VISTAS) signed April 3, 2001 

A-2 

Appendix A-2 VISTAS MOU.pdf 

Listing of acknowledgements to consulting firms, agencies, and individuals that contributed to the 

regional haze SIP development process 

A-3 

Appendix A-3 VISTAS Acknowledgements.pdf 

Appendix B: Conceptual Description 

VISTAS Conceptual Description Support Document, Air Resource Specialists, Inc, September 30, 

2007 

B-1 

Appendix B-1 ARS Conceptual Description Support.pdf

B-1a ARS Appendix A-Nephelometer Comparisons 

Appendix B-1a ARS Conceptual Description Appendix A.pdf 

B-1b ARS Appendix B- Original and Revised Algorithm Comparisons by Sie 

Appendix B-1b ARS Conceptual Description Appendix B.pdf 

B-1c ARS Appendix C-File Key for Substituted Data 

Appendix B-1c ARS Conceptual Description Appendix C.pdf 

B-1d ARS Appendix D-Data Substitution Results for Individual Sites 

Appendix B-1d ARS Conceptual Description Appendix D.pdf 

ARS Appendix E-Extinction Trend Charts (Mm-1 B-1e , DV, and SVR) 

Appendix B-1e ARS Conceptual Description Appendix E.pdf 

B-1f ARS Appendix F-WinHaze Images (Baseline, 2018, and Natural Conditions) 

Appendix B-1f ARS Conceptual Description Appendix F.pdf 

B-1g ARS Appendix G-2000-2004 Timelines 

Appendix B-1g ARS Conceptual Description Appendix G.pdf 

B-1h ARS Appendix H-DV Glidepaths 

Appendix B-1h ARS Conceptual Description Appendix H.pdf 

B-1i ARS Appendix I-Speciated Glidepaths 

Appendix B-1i ARS Conceptual Description Appendix I.pdf 

B-1j ARS Appendix J-Back Trajectory Maps 

Appendix B-1j ARS Conceptual Description Appendix J.pdf 

B-1k ARS Appendix K-Residence Time Maps 

Appendix B-1k ARS Conceptual Description Appendix K.pdf 

B-1l ARS Appendix L-International Attribution Plots 

Appendix B-1l ARS Conceptual Description Appendix L.pdf 
LIST OF APPENDICES 

viii-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Revised IMPROVE Algorithm for Estimating Light Extinction from Particle Speciation Data by Ivar 

Tombach 

B-2 

Appendix B-2 Revised IMPROVE Algorithm.pdf

Presentation entitled, “VISTAS Special Monitoring Studies-Carbon Analyses for PM2.5 and Haze” 

by Patricia Brewer, Johann Engelbrecht, Roger Tanner, Scott Reynolds, John Calcagni 

B-3a 

Appendix B-3a VISTAS Carbon Studies_Jul2007.pdf (e-submittal) 

Presentation entitled, “Source Attribution for Carbon at Class I areas in Southeastern US” by Eric 

M. Fujita, David E. Campbell, Barbara Zielinski, Johann Engelbrecht, July 18, 2008 

B-3b 

Appendix B-3b VISTAS carbon studies summary.pdf (e-submittal) 

Characterization of Fine Particle Mass Using Particle-Phase Organic Compounds as Tracer 

FINAL REPORT, DRI, January 21, 2009 

B-3c 

Appendix B-3c DRI Final Report.pdf

Comparison of Particulate Carbon Source Contributions in the Southeastern U.S. Using 

Photochemical Grid and Receptor Modeling Final Report ENVIRON, June 29, 2009 

B-3d 

Appendix B-3d VISTAS OC Report.pdf 

Presentation entitled, “VISTAS Special Monitoring Studies Continuous Measures of Speciated 

PM2.5” by Patricia Brewer, Scott Reynolds, Roger Tanner, Eric Edgerton, Ben Hartsell, Jim Renfro, 

Hoke Kimball, John Calcagni, July 23, 2007 

B-4 

Appendix B-4 VISTAS Continuous Monitoring.pdf (e-submittal) 

Characterization of Meteorology and Its Relationships to Fine Particulate Mass and Visibility in 

the VISTAS Region Final Report, ICF, December 8, 2006 

B-5 

Appendix B-5 ICF Meteorological Characterization.pdf

Appendix C: Modeling Protocol and Quality Assurance Project Plan 

VISTAS Emissions and Air Quality Modeling – Phase I Task 6 Report: Modeling Protocol for the 

VISTAS Phase II Regional Haze Modeling, ENVIRON, Alpine Geophysics LLC, UC Riverside, 

May 6, 2004 

C-1 

Appendix C-1 VISTAS PhaseII Modeling Protocol.pdf

Quality Assurance Project Plan (Draft) for Visibility Improvements for States and Tribal 

Associations for the Southeastern States (VISTAS) Emissions and Air Quality Modeling, Revision 0

ENVIRON, Alpine Geophysics, UC Riverside, November 17, 2004 

C-2 

Appendix C-2 VISTAS_QAPP_Nov_17_2004.pdf

Model sensitivity evaluation for organic carbon using two multi-pollutant air quality models that 

simulate regional haze in the southeastern United States, Ralph E. Morris, Bonyoung Koo, Alex 

Guenther, Greg Yarwood, Dennis McNally, T.W.Tesche, Gail Tonnesen, James Boylan, Patricia 

Brewer, September 30, 2005 

C-3 

Appendix C-3 SOA Mods in CMAQ.pdf 

Appendix D: Emissions Inventory Preparation and Data 

Final Report-Development of the Draft 2002 VISTAS Emission Inventory for Regional Haze 

Modeling: Area Source Methodology, MACTEC, June 18, 2004 

D-1area 

Appendix D-1area – MACTEC 2002 Area Source.pdf
LIST OF APPENDICES 

ix-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Documentation of the Base G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission 

Inventories for VISTAS Revision 1, MACTEC, April 9, 2008 

D-1future 

Appendix D-1future – MACTEC baseyear and future year.pdf

MEMORANDUM: Development of Temporal Profiles for Electric Generating Units (EGUs) In the 

VISTAS States: Final Technical Memorandum Greg Stella/Alpine Geophysics, February 27, 2006 

D-1memo1 

Appendix D-1memo1 – Alpine Geophysics EGU CEM data.pad

MEMORANDUM: EGU Emission Factors and Emission Factor Assignment, Greg Stella/Alpine 

Geophysics, June 13, 2005 

D-1memo2 

Appendix D-1memo2 – Alpine Geophysics PM and NH3 Emission Factors.pdf

Development of the VISTAS Draft 2002 Mobile Source Emissions Inventory (February 2004 

Version), PECHAN, February 9, 2004 

D-1mobile 

Appendix D-1mobile – PECHAN 2002 Mobile Source.pdf

Final Report: Development of the Draft 2002 VISTAS Emission Inventory for Regional Haze 

Modeling-Point Sources, MACTEC, June 18, 2004 

D-1point 

Appendix D-1point – MACTEC 2002 Point Sources.pdf

D-2a Base G2 Emissions Summary Table for VISTAS States 

Appendix D-2a Emission Inventory Summaries.pdf (e-submittal) 

D-2b Virginia 2002 Mobile Emissions Inventory by County 

Appendix D-2b 2002 Mobile Emissions Inventory.pdf (e-submittal) 

D-2c Virginia 2009 Mobile Emissions Inventory by County 

Appendix D-2c 2009 Mobile Emissions Inventory.pdf (e-submittal) 

D-2d Virginia 2018 Mobile Emissions Inventory by County 

Appendix D-2d 2018 Mobile Emissions Inventory.pdf (e-submittal) 

D-2e Virginia 2002 Area Source Emissions Inventory by County 

Appendix D-2e 2002 Area Emissions Inventory.pdf (e-submittal) 

D-2f Virginia 2009 Area Source Emissions Inventory by County 

Appendix D-2f 2009 Area Emissions Inventory.pdf (e-submittal) 

D-2g Virginia 2018 Area Source Emissions Inventory by County 

Appendix D-2g 2018 Area Emissions Inventory.pdf (e-submittal) 

D-2h Virginia 2002 Non Road Emissions Inventory by County 

Appendix D-2h 2002 Non Road Emissions Inventory.pdf (e-submittal) 

D-2i Virginia 2009 Non Road Emissions Inventory by County 

Appendix D-2i 2009 Non Road Emissions Inventory.pdf (e-submittal) 

D-2j Virginia 2018 Non Road Emissions Inventory by County 

Appendix D-2j 2018 Non Road Emissions Inventory.pdf (e-submittal) 

D-2kact Virginia 2002 Actual Point Source Inventory by County 

Appendix D-2kact 2002 Actual Point Emissions Inventory.pdf (e-submittal) 
LIST OF APPENDICES 

x-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

D-2ktyp Virginia 2002 Typical Point Source Inventory by County 

Appendix D-2ktyp 2002 Typical Point Emissions Inventory.pdf (e-submittal) 

D-2l Virginia 2009 Point Source Inventory by County 

Appendix D-2l 2009 Point Emissions Inventory.pdf (e-submittal) 

D-2m Virginia 2018 Point Source Inventory by County 

Appendix D-2m 2018 Point Emissions Inventory.pdf (e-submittal) 

Appendix E: Air Quality and Meteorological Preparation and Results 

Draft VISTAS Emissions and Air Quality Modeling-Phase I Task 3 Report: Review and Assessment 

of Available Ambient Air Quality Data to Support Modeling and Modeling Performance Evaluation 

for the Three VISTAS Phase I Episodes, ENVIRON, Alpine Geophysics LLC, UC Riverside, UC 

Davis, July 22, 2003 

E-1 

Appendix E-1 UCR Ambient Data Assessment.pdf

Protocol for Annual MM5 Modeling in Support of VISTAS (Visibility Improvement – State and 

Tribal Association) (DRAFT) Task 3a Deliverable, Baron Advanced Meteorological Systems, LLC, 

February 9, 2004 

E-2 

Appendix E-2 MM5 Modeling Protocol.pdf

Appendix F: Model Performance Evaluation 

MM5 2002 Modeling in Support of VISTAS (Visibility Improvement – State and Tribal Association 

of the Southeast) Task 3f Deliverable, Baron Advanced Meteorological Systems, LLC, August 4, 

2004 

F 

Appendix F MM5 Modeling Support.pdf

Appendix G: Modeling Results and Supplemental Analysis 

Documentation and Evaluation of the GEOS-CHEM Simulation for 2002 Provided to the VISTAS 

Group Final Report, Harvard University, June 24, 2005 

G-1 

Appendix G-1 Harvard GEOS-CHEM Report.pdf

Accounting for Transport of International Emissions in CMAQ Modeling of the VISTAS Region,

Ivar Tombach, April 2007 

G-2 

Appendix G-2 International Emissions Impact.pdf

Charts for IMPROVE monitoring sites with domestic and international aerosol mass delineated by 

species for the 20% worst days in 2002 

G-3 

Appendix G-3 International Emissions Comparison Charts.pdf 

Appendix H: Reasonable Progress Evaluation/Long Term Strategy/BART 

H-1 Virginia’s Reasonable Progress Evaluation and Long Term Strategy 

Appendix H-1 RP and Long Term Strategy August 2010 Proposal.pdf 

H-2a VISTAS Area of Influence Analysis, February 28, 2007 

Appendix H-2a VISTAS Class I AOI Discussion.pdf

H-2b VISTAS Area of Influence spreadsheets for each Class I area based on 2018 emissions 

Appendix H-2b VISTAS ClassI AOIs percent impacts.pdf 
LIST OF APPENDICES 

xi-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Letter dated September 25, 2007, from VDEQ to MeadWestvaco Corporation – Packaging 

Resources Group requesting a reasonable progress evaluation 

H-3 

Appendix H-3 MeadWestvaco RP Correspondence.pdf 

Protocol for the Application of the CALPUFF Model for Analyses of Best Available Retrofit 

Technology (BART), VISTAS, Revision 3.2-August 31, 2006 

H-4 

Appendix H-4 VISTAS BART Modeling Protocol.pdf

Letter dated June 8, 2007 from the National Park Service to Mr. Mike Kiss of VDEQ concurring 

with the BART exemptions provided by VDEQ 

H-5 

Appendix H-5 NPS BART Exemption Concurrence.pdf 

FINAL Assessment of Reasonable Progress for Regional Haze In MANE-VU Class I Areas, 

MACTEC, July 9, 2007 

H-6 

Appendix H-6 MANE-VU Reasonable Progress Assessment.pdf

What is An Appropriate Threshold for Determining a Source is Subject to BART DRAFT, Ivar 

Tombach, October 30, 2006 

H-7 

Appendix H-7 BART Threshold Explanation Tombach_Nov 1 2006.pdf

H-8a Analysis for Best Available Retrofit Technology, GP Big Island, LLC, March 2007 

Appendix H-8a GP BART Submittal.pdf

H-8b Attachment A: Air Quality Impact Analysis, GP Big Island, LLC, March 2007 

Appendix H-8b GP BART Impact Analysis Att A.pdf

Regional Haze/Boiler BART Program Feasibility Study Report and Estimate-Appendix A: Basis of 

Estimated Costs

H-8c 

Appendix H-8c GP Basis of Costs.pdf

H-8d Attachment B: Engineering Analysis for Control Technology, GP Big Island, LLC, March 2007 

Appendix H-8d GP Eng Analysis.dpf

Regional Haze/Boiler BART Program Feasibility Study Report and Estimate-Appendix C: Detailed 

Capital Cost Estimates

H-8e 

Appendix H-8e GP Cap Cost Estimates.pdf

H-8f GP Big Island, LLC BART permit dated June 12, 2008 

Appendix H-8f GP BART Permit.pdf (e-submittal) 

MEMORANDUM: Engineering Analysis/BART Permit Statement of Basis for GP Big Island LLC 

(Registration # 30389) (Georgia-Pacific Corporation, Big Island Mill), Gary Bradley, Lillian 

Alexander/VDEQ, June 4, 2008 

H-8g 

Appendix H-8g GP BART VDEQ Engineering Analysis.pdf (e-submittal)

H-8h DEQ response to public comment for the GP BART permit 

Appendix H-8h DEQ response to public comments.pdf (e-submittal) 

Best Available Retrofit Technology Determination Report MeadWestvaco Packaging Resource 

Group-Covington Mill, MeadWestvaco, March 2007 

H-9a 

Appendix H-9a MeadWestvaco BART Submittal.pdf (e-submittal)
LIST OF APPENDICES 

xii-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Best Available Retrofit Technology Applicability Analysis MeadWestvaco Packaging Resource 

Group Covington Mill, MeadWestvaco, October 2006 

H-9b 

Appendix H-9b MeadWestvaco Impact Analysis.pdf

H-9c MeadWestvaco Packaging Resource Group-Covington Mill BART permit dated February 23, 2009 

Appendix H-9c MeadWestvaco BART permit.pdf (e-submittal) 

MEMORANDUM: Engineering Analysis (MeadWestvaco), Lillian Alexander/VDEQ, February 13, 

2009 

H-9d 

Appendix H-9d MeadWestvaco BART VDEQ Engineering Analysis.pdf (e-submittal)

Letter from the USDA Forest Service to VDEQ with comments on the MeadWestvaco BART 

Determination, July 24, 2008 

H-9e 

Appendix H-9e FLM comments 7-24-08.pdf (e-submittal) 

Letter from the USDA Forest Service to VDEQ with comments on the MeadWestvaco BART 

determination, October 3, 2007 

H-9f 

Appendix H-9f FLM comments 10-3-07.pdf (e-submittal) 

Letter from VDEQ to USDA, Forest Service (Ms. Cindy Huber) responding to comments dated 

October 3, 2007 - letter dated May 28, 2008 

H-9g 

Appendix H-9g DEQ response to FLM comments 5-82-08.pdf (e-submittal) 

Letter from VDEQ to USDA, Forest Service (Ms. Maureen Hyzer) responding to comments dated 

July 24, 2008 – letter dated September 22, 2008 

H-9h 

Appendix H-9h DEQ response to FLM comments 9-22-08.pdf (e-submittal) 

H-9i FLM comments on MW BART permit dated 11-14-08 submitted during the public comment period 

Appendix H-9i FLM comments 11-14-08 during public notice.pdf 

DEQ response to all public comments received during the public comment period for the MW 

BART permit 

H-9j 

Appendix H-9j DEQ response to public comments.pdf 

O-N Minerals (Chemstone) Company BART permit dated December 26, 2009 (Facility is now 

owned by Carmeuse.) 

H-10a 

Appendix H-10a ON BART Permit.pdf (e-submittal) 

MEMORANDUM:O-N Minerals (Chemstone) Company-BART Determination, Laura Justin, 

Janardan Pandey/VDEQ, December 23, 2009 

H-10b 

Appendix H-10b ON VDEQ Engineering Analysis.pdf (e-submittal)

Best Available Retrofit Technology Applicability Analysis O-N Minerals (Chemstone), Trinity 

Consultants, September 2006 

H-10b-A 

Appendix H-10b-A ON BART Impact Analysis.pdf (e-submittal)

Best Available Retrofit Technology Determination O-N Minerals (Chemstone), Trinity Consultants, 

February 2007 

H-10b-B 

Appendix H-10b ON BART Analysis.pdf (e-submittal)

H-10b-C Letter dated April 27, 2007, submitted by Chemstone in support of its BART determination 

Appendix H-10b-C ON letter dated 4-27-07.pdf (e-submittal) 
LIST OF APPENDICES 

xiii-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

H-10b-D Letter dated May 30, 2007, submitted by Chemstone in support of its BART determination 

Appendix H-10b-D ON letter dated 5-30-07.pdf (e-submittal) 

H-10b-E Letter dated July 12, 2007 from Chemstone in support of its BART determination 

Appendix H-10b-E ON letter dated 7-12-07.dpf (e-submittal) 

Letter dated August 30, 2007, submitted by Chemstone in support of its BART determination 

(application for de minimis SO2 limits) 

H-10b-F 

Appendix H-10b-F ON letter dated 8-30-07.pdf (e-submittal) 

Letter dated September 27, 2007, submitted by Chemstone in support of its BART determination 

(comments on draft permit) 

H-10b-G 

Appendix H-10b-G ON letter dated 9-27-07.pdf (e-submittal) 

H-10b-H October 30, 2007 rotary kiln emissions test summary report (letter dated 11/12/07) 

Appendix H-10b-H Kiln test report 10-30-07.pdf (e-submittal) 

H-10b-I November 30, 2007 revised SO2 BART proposal (cover letter dated December 5, 2007) 

Appendix H-10b-I SO2 BART proposal 22-30-07.pdf (e-submittal) 

Letter dated January 7, 2008, submitted by Chemstone in support of its BART determination 

(response to VRO 30-day letter for revised SO2 BART proposal) 

H-10b-J 

Appendix H-10b-J ON letter dated 1-7-08.pdf (e-submittal) 

Letter dated March 17, 2008, submitted by Chemstone in support of its BART determination 

(response to VDEQ and FLM modeling comments) 

H-10b-K 

Appendix H-10b-K ON letter dated 3-17-08.pdf (e-submittal) 

Letter dated July 15, 2008, submitted by Chemstone in support of its BART determination 

(response to June 2008 draft permit) 

H-10b-L 

Appendix H-10b-L ON letter dated 7-15-08.pdf (e-submittal) 

H-10b-M Recent listings for lime kilns in EPA’s RACT/BACT/LAER Clearinghouse (NOX) 

Appendix H-10b-M RBLC lime kiln listings NOx.pdf (e-submittal) 

H-10b-N Calculations showing derivation of BART SO2 limits for rotary kiln 

Appendix H-10b-N Calcs for SO2 rotary kiln.pdf (e-submittal) 

H-10b-O Calculations showing derivation of BART SO2 limits for calcimatic kiln 

Appendix H-10b-O Calcs for SO2 calc kiln.pdf (e-submittal) 

H-10b-P Comments dated March 2, 2009 from Don Shepherd (NPS) on draft BART permit 

Appendix H-10b-P FLM comments 3-2-09.pdf (e-submittal) 

Letters dated April 3, 2009, May 8, 2009 and June 4, 2009 submitted by Chemstone in response to 

VRO request to address FLM comments 

H-10b-Q 

Appendix H-10b-Q ON responses to FLM comments.pdf (e-submittal) 

H-10b-R Letter dated September 22, 2009 from VDEQ-VRO to FLM/NPS responding to FLM comments 

Appendix H-10b-R VDEQ response to FLM 9-22-09.pdf (e-submittal) 
LIST OF APPENDICES 

xiv-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Comments received on the draft permit during the public comment period (from NPS and 

Chemstone) 

H-10b-S 

Appendix H-10b-S public notice comments FLM & ON.pdf (e-submittal) 

H-10b-T VDEQ-VRO’s response to comments received during the public comment period. 

Appendix H-10b-T VDEQ response to FLM & ON comments.pdf (e-submittal) 

Appendix I: Data Access 

I The VISTAS products listing, with web links 

Appendix I Data Access.pdf 

Appendix J: Consultation Process 

J-1a NJ consultation request letter dated 1-18-07 

Appendix J-1a NJ consult ltr 1-18-07.pdf 

J-1b DEQ’s response to the NJ consultation request letter, dated 2-20-07 

Appendix J-1b DEQ response to NJ 2-20-07.pdf 

J-1c NH consultation request letter dated 4-4-07 

Appendix J-1c NH consult ltr 4-4-07.pdf 

J-1d DEQ’s response to the NH consultation request letter, dated 4-16-07 

Appendix J-1d DEQ response to NH 04-16-07.pdf 

J-1e Consultation meeting minutes that took place in Atlanta, GA on 5-14-07 

Appendix J-1e Consult meeting Atlanta 5-14-07 minutes.pdf 

J-1f FLM/States consultation meeting minutes from the Asheville, NC meeting on 6-12-07 

Appendix J-1F FLM consult meeting Asheville 6-12-07 minutes.pdf 

J-1g NC letter requesting consultation dated 8-2-07 

Appendix J-1g NC consult ltr 8-2-07.pdf 

Email from VDEQ staff to MARAMA asking for information on heating oil cost calculations dated 

8-10-07 

J-1h 

Appendix J-1h E-mail re oil costs 8-10-07.pdf 

J-1i DEQ response letter to the NC consultation letter, dated 9-19-07 

Appendix J-1i DEQ response to NC 9-19-07.pdf 

J-1j Internal memorandum documenting consultation discussions with MDE, dated 11-2-07 

Appendix J-1j Memo re MDE consult 11-2-07 

J-1k Email with consultation information between VA and WVA, dated 11-19-07 

Appendix J-1k E-mail re WVA consult 11-19-07 
LIST OF APPENDICES 

xv-Virginia Regional Haze SIP 

Appendix 

ID 

Description/ 

File Name* 

Mid-Atlantic/Northeast Visbility Union (MANE-VU) Inter-RPO Consultation Briefing Book, 

MANE-VU 

J-2 

Appendix J-2 MANE-VU Inter-RPO Consultation Briefing book.pdf

US Department of Agriculture Forest Service comments on the regional haze consultation draft, 

dated 11-7-07 

J-3 

Appendix J-3 USDA FS Comments 11-7-07.pdf 

US Department of the Interior National Park Service comments on the regional haze consultation 

draft, dated 12-17-07 

J-4 

Appendix J-4 USDI NPS Comments 12-17-07.pdf 

US Department of Agriculture Forest Service comments on the regional haze consultation draft, 

dated 6-18-10 

J-5 

Appendix J-5 USDA FS Comments 6-18-10.pdf 

US Department of the Interior National Park Service comments on the consultation draft, dated 6-

24-10 

J-6 

Appendix J-6 USDI NPS Comments 6-24-10.pdf 

J-7 DEQ response to USDA FS consultation comments submitted 11-7-07 and 6-18-10 

Appendix J-7 DEQ response to FS comments dated 7-23-10.pdf 

J-8 DEQ response to USDI NPS consultation comments submitted 12-17-07 and 6-24-10 

Appendix J-8 DEQ response to NPS comments dated 7-23-10.pdf 

Appendix K: Recommended Improvements 

K Recommended technical improvements to support regulatory decisions for regional haze 

Appendix K Recommend Improvements.pdf 

Appendix L: Technical Support Document for Modeling and Results 

Final Report: Technical Support Document for VISTAS Emissions and Air Quality Modeling to 

Support Regional Haze State Implementation Plans, ENVIRON, Alpine Geophysics, LLC, UC 

Riverside, March 11, 2009 

L 

Appendix L TSD Air Quality Modeling Report.pdf (e-submittal)

*Files listed as an e-submittal are provided only in electronic file format to EPA since these files 

have been previously submitted on paper, are summaries of information provided on paper, or 

mainly contain numerical data that is better viewed in an electronic format. 
LIST OF TABLES AND FIGURES 

xvi-Virginia Regional Haze SIP 

Table 1.1. Goal Summary ................................................................................................................................ iii

Figure 1.2-1. Geographical Areas of Regional Planning Organizations.................................................................2

Figure 1.4-1. Virginia Class I areas ........................................................................................................................4

Figure 1.5-1. Class I Areas in the VISTAS Region................................................................................................6

Table 1.5-2. Mandatory Class I Federal Areas in the VISTAS Region.................................................................6

Figure 2-1. IMPROVE Monitoring Sites in the VISTAS Region and Adjacent Regions ...................................8

Table 2.3-1. Virginia Class I Areas’ Natural Background and Baseline Conditions...........................................10

Figure 2.4-1. Ave Extinction for the 20% Haziest Days in 2000-2004, New IMPROVE Equation.....................11

Figure 2.4-2. Ave Extinction for the 20% Clearest Days in 2000-2004, New IMPROVE Equation ...................11

Figure 2.4-3. IMPROVE Species Composition Data for James River Face 2000-2004.......................................12

Figure 2.4-4. IMPROVE Species Composition Data for Shenandoah 2000-2004 ...............................................13

Figure 3.1-1. Uniform Rate of Progress Glidepath for 20 percent worst days at James River Face.....................16

Figure 3.1-2. Uniform Rate of Progress Glidepath for 20 percent worst days at Shenandoah National Park ......17

Table 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission 

Reduction Strategies1 ......................................................................................................................20

Table 4.1.6. 2002 Emissions Inventory Summary for Virginia in tpy. ...............................................................26

Figure 4.2-1. SO2 Emissions in 2002 in the VISTAS States. ...............................................................................28

Figure 5.4.1-1. The MM5 Domain (blue grid), with Nested36 km CMAQ Domain...............................................35

Figure 5.4.1-2. Detailed View of the 12 km VISTAS Grid .....................................................................................35

Figure 6.0-1. Monitoring Networks Used for VISTAS 2002 Model Performance Evaluation.............................36

Table 6.1-1. Model Goals for the Fine Particulate Mass Component Species ....................................................37

Figure 6.2-1. Soccer Plot for Mean Fractional Error and Bias, Base G2..............................................................39

Figure 6.2-2. A Zoomed View of the Soccer Plot ................................................................................................39

Figure 6.2-3. Seasonal Soccer Plots Based on Base G1 Results for all VISTAS IMPROVE Monitors...............40

Figure 6.2-4. Bugle Plot—Mean Fraction Bias ....................................................................................................40

Figure 6.2-5. Bugle Plot of Mean Fractional Error...............................................................................................41

Figure 6.3-1. Stacked Bar Charts for Shenandoah on the 20% Best Days ...........................................................42

Figure 6.3-2. Stacked Bar Chart for Shenandoah on the 20% Worst Days ..........................................................43

Figure 6.3-3. Stacked Bar Chart for James River Face on the 20% Best Days ....................................................43

Figure 6.3-4. Stacked Bar Chart for James River Face on the 20% Worst Days..................................................44

Figure 7.2.3-1. Base G2 Annual SO2 for 2002, 2009, and 2018 VISTAS States ....................................................49

Figure 7.2.3-2. Base G2 Annual NOX for 2002, 2009, and 2018 VISTAS States...................................................49

Table 7.2.3-2. 2018 Virginia Base G2 Emissions Summary, tpy...........................................................................50

Figure 7.2.4-1. Uniform Rate of Progress for Shenandoah, 20% Worst Days ........................................................51

Figure 7.2.4-2. Uniform Rate of Progress for James River Face, 20% Worst Days................................................52

Figure 7.2.4-3. Visibility Improvement, 20% Worst Days, 2018 Base G2a............................................................52

Figure7.2.4-4. Shenandoah 20% Worst Visibility Days and Natural Conditions Visual Images ...........................53

Figure7.2.4-5. James River Face 20% Worst Visibility Days and Natural Conditions Visual Images ..................54

Figure 7.2.4-6. 20% Best Days Rate of Progress for Shenandoah...........................................................................55

Figure 7.2.4-7. 20% Best Days Rate of Progress for James River Face ..................................................................55

Figure 7.2.4-8. Visibility Improvement, 20% Best Days, 2018 Base G2a ..............................................................56

Figure 7.3-1. Estimated International Emissions Contributions ...........................................................................58

Figure 7.3-2. 2002 PM Concentrations: US Domestic Sources (left) and CMAQ International Contributions 

(right) ..............................................................................................................................................59

Table 7.4-1. Visibility Response Modeling Table Abbreviations .......................................................................60

Figure 7.4-1. Visibility Responses: Shenandoah to 2009 Base D 30% Reductions .............................................61

Figure 7.4-2. Visibility Responses: James River Face to 2009 Base D 30% Reductions.....................................61

Figure 7.5.1. Example Back Trajectories for 2002 20% Worst Visibility Days, Shenandoah .............................63

Figure 7.5.2. Example Residence Time Plot for 2000-2004 20% Worst Days ....................................................64

Figure 7.5.3. Shenandoah SO2 AoI for SO4 Extinction-Weighted Residence Time for 2000-2004 20% Worst 

Days ................................................................................................................................................65

Figure 7.5.4-1. Shenandoah 2002 and 2018 SO2 Distanc- Weighted Emissions, SO4 Extinction-Weighted 

Residence Time Plots......................................................................................................................66

Figure 7.5.4-2. James River Face 2002 and 2018 SO2 Distance Weighted Emissions, SO4 Extinction-Weighted 

Residence Time Plot .......................................................................................................................67

Table 7.5.4-1. State 2018 SO2 Point Source Contribution to Virginia Class I Areas .............................................67
LIST OF TABLES AND FIGURES 

xvii-Virginia Regional Haze SIP 

Table 7.5.4-2. State 2018 SO2 Point Source Contribution to North Carolina Class I Areas ..................................68

Table 7.5.4-3. State 2018 SO2 Point Source Contribution to Other Class I Areas .................................................68

Table 7.5.5-1. 2018 Emissions Contributions from Source Categories, Shenandoah Area of Influence ...............70

Table 7.5.5-2. 2018 Emissions Contributions from Source Categories, James River Face Area of Influence.......70

Table 7.5.5-3. Annual 2018 SO2 Emissions Percentage within Areas of Influence ...............................................71

Table 7.7.4-1. Emissions Points and Percent Contributions...................................................................................75

Table 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1% .............................77

Table 7.7.4-3: Units Outside Virginia with Visibility Impairment Contributions of at least 1% Virginia Class I 

Areas ...............................................................................................................................................80

Table 7.7.5.1-1. Virginia EGUs with Visibility Impairment Contributions of at least 1% .......................................87

Table 7.7.5. Celanese Acetate, LLC/Cinergy: Boilers and Stacks Combined for Point #1 ................................89

Table 7.8.1. Virginia BART Source List ............................................................................................................90

Table 7.8.2-1. BART Exemption Modeling Results ..............................................................................................92

Table 7.8.3-1. BART Determinations ....................................................................................................................95

Figure 7.9-1. SO2 Emissions Comparisons for VISTAS States, CAIR versus No CAIR, Legally Enforceable.100

Figure 7.9-2. NOX Emissions Comparisons for VISTAS States, CAIR versus No CAIR, Legally Enforceable100

Table 7.10.4-1. Base G2 and Base G4a Point Source Emissions Comparison for SO2, NOX, VOC, and CO........104

Table 7.10.4-2. Base G2 and Base G4a Point Source Emissions Comparison for PM10, PM2.5, and NH3 .............104

Table 8.1-1. Virginia Reasonable Progress Goals.............................................................................................105

Figure 8.1-1. 20% Worst Days Reasonable Progress for Shenandoah ...............................................................106

Figure 8.1-2. 20% Worst Days Reasonable Progress for James River Face.......................................................106

Figure 8.1-3. 20 Percent Best Days Rate of Progress for Shenandoah ...............................................................107

Figure 8.1-4. 20 Percent Best Days Rate of Progress for James River Face ......................................................107

Figure 8.2-1. Annual Emissions of SO2 from Acid Rain Program Units (Data from CAMD)...........................109

Table 9-1. IMPROVE Sites in Virginia..........................................................................................................110

Table 10-1. Virginia Electric Generating Units Identified by MANE-VU.......................................................115

Table 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to Brigantine..............................116
LIST OF ACRONYMS AND ABBREVIATIONS 

xviii-Virginia Regional Haze SIP 

AOI - Area of Influence 

BART - Best Available Retrofit Technology 

CAA - federal Clean Air Act 

CAIR - Clean Air Interstate Rule 

CAMR - Clean Air Mercury Rule 

CEM - Continuous Emissions Monitoring 

CERR - Consolidated Emissions Reporting Rule 

CMAQ - Community Multiscale Air Quality 

dv - Deciview 

EAC - Early Action Compacts 

EGU - Electric Generating Units 

EPA - Environmental Protection Agency 

FAA - Federal Aviation Administration 

FDDA - Four Dimensional Data Assimilation 

FLM - Federal Land Manager 

HAP - Hazardous Air Pollutants 

IMPROVE - Interagency Monitoring of Protected Visual Environments 

IPM - Integrated Planning Model 

LSD - Low Sulfur Diesel 

LTS - Long-Term Strategy 

MM5 - Mesoscale Meteorological Model 

mmbtu - Million British Thermal Units 

NAAQS - National Ambient Air Quality Standard 

NCCSA - North Carolina Clean Smokestacks Act 

NH3 - Ammonia 

NOX - Nitrogen Oxides 

OTB/OTW - On the Books/On the Way 

PBL - Planetary Boundary Layer 

PM - Particulate Matter 

PM2.5 - Particulate Matter with a diameter of 2.5 micrometers or less (fine particulate) 

PM10 - Particulate Matter with a diameter of 10 micrometers or less (coarse particulate) 

POM - Particulate Organic Matter 

PSAT - PM Source Apportionment Technology 

PSU/NCAR - Pennsylvania State University/National Center for Atmospheric Research 

RAMS - Regional Atmospheric Modeling System 

RPG - Reasonable Progress Goals 

RPO - Regional Planning Organization 

SAMI - Southern Appalachian Mountains Initiative 

SCC - Source Category Code 

SIP - State Implementation Plan 

SMOKE - Sparse Matrix Operator Kernel Emissions (model) 

SOA - Secondary Organic Aerosols 

SO2 - Sulfur Dioxide 

STN - Speciated Trends Network 
LIST OF ACRONYMS AND ABBREVIATIONS 

xix-Virginia Regional Haze SIP 

TDM - Travel Demand Models 

TPY - Tons Per Year 

UAM - Urban Airshed Model 

USEPA - U.S. Environmental Protection Agency 

VDEQ - Virginia Department of Environmental Quality 

VISTAS - Visibility Improvement - State and Tribal Association of the Southeast 

VOC - Volatile Organic Compound 

Abbreviations for Class I Area Monitoring Sites:

BRET1 - Breton Wilderness Area, LA 

BRIG - Brigantine Wilderness Area, NJ 

CACR1 - Caney Creek Wilderness Area, AR 

CHAS1 - Chassahowitzka Wilderness Area, FL 

COHU1 - Cohutta Wilderness Area, GA 

DOSO1 - Dolly Sods Wilderness Area, WV 

EVER1 - Everglades National Park, FL 

GRSM1 - Great Smoky Mountains National Park, TN 

HEGL1 - Hercules Glade Wilderness Area, MO 

JARI1 - James River Face Wilderness Area, VA 

LIGO1 - Linville Gorge Wilderness Area, NC 

MACA1 - Mammoth Cave National Park, KY 

MING1 - Mingo National Wildlife Refuge, MO 

OKEF1 - Okefenokee Wilderness Area, GA 

ROMA1 - Cape Romain Wilderness Area, SC 

SAMA1 - St. Marks National Wildlife Refuge, FL 

SHEN1 - Shenandoah National Park, VA 

SHRO1 - Shining Rock Wilderness Area, NC 

SIPS1 - Sipsey Wilderness Area, AL 

SWAN1 - Swanquarter National Wildlife Area, NC 

UPBU - Upper Buffalo Wilderness Area, AR 
1-Virginia Regional Haze SIP 

1. INTRODUCTION 

1.1. What is regional haze? 

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

including national parks, forests, and wilderness areas (federal “Class I” areas). Regional haze is 

caused by sources and activities emitting fine particles and their precursors. Those emissions are 

often transported over large regions. 

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

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

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

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

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

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

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

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

and annual levels of fine particles with diameter smaller than 2.5 μm (PM2.5). The most 

important sources of PM2.5 and its precursors are coal-fired power plants, industrial boilers, and 

other combustion sources. Other significant contributors to PM2.5 and visibility impairment 

include mobile source emissions, area sources, fires, and windblown dust. 

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

haze? 

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

for protecting visibility in Federal Class I areas that calls for the “prevention of any future, and 

the remedying of any existing, impairment of visibility in mandatory Class I Federal areas which 

impairment results from manmade air pollution.” Congress adopted the visibility provisions to 

protect visibility in 156 national parks and wilderness areas. On December 2, 1980, USEPA 

promulgated Subpart P of 40 CFR Part 51, Protection of Visibility (also known as the regional 

haze regulation) to address visibility impairment (45 FR 80084). The 1980 regulations were 

developed to address visibility impairment that is “reasonably attributable” to a single source or 

small group of sources. These regulations represented the first phase in addressing visibility 

impairment and deferred action on regional haze that emanates from a variety of sources until 

monitoring, modeling, and scientific knowledge about the relationships between pollutants and 

visibility impairment improved. 

In the 1990 Amendments to the CAA, Congress added § 169B, which requires that EPA 

promulgate regulations as needed in order to implement § 169. The regulation that USEPA 

promulgated on July 1, 1999 (64 FR 35713) revised the regional haze regulation of Subpart P of 

40 CFR Part 51 in order to integrate provisions addressing regional haze impairment and 

establish a comprehensive visibility protection program for Class I Federal areas. States are 

required to submit state implementation plans (SIPs) to USEPA that set out each state’s plan for 

complying with the regional haze regulation, including consultation and coordination with other 

states and with federal land managers. The timing of the SIP submittal is tied to USEPA’s 

promulgation of designations for the NAAQS, at 40 CFR Part 81. States must submit a regional 

haze implementation plan to USEPA within three years after the date of designation. Because 
2-Virginia Regional Haze SIP 

USEPA promulgated designation dates on December 17, 2004, regional haze SIPs must be 

submitted by December 17, 2007. 

The regional haze regulation addressed the combined visibility effects of various pollution 

sources over a wide geographic region. This wide reaching pollution net meant that many states 

– even those without Class I Areas – would be required to participate in haze reduction efforts. 

USEPA designated five Regional Planning Organizations (RPO) to assist with the coordination 

and cooperation needed to address the visibility issue. Those states that make up the 

southeastern portion of the contiguous United States are known as VISTAS (Visibility 

Improvement – State and Tribal Association of the Southeast), and include the following states: 

Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, 

Virginia, and West Virginia. 

Figure 1.2-1. Geographical Areas of Regional Planning Organizations 

1.3. General overview of regional haze SIP requirements 

The regional haze regulation at 51.308(d) requires states to demonstrate reasonable progress 

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

for reasonable progress, the regional haze regulation directs states to graphically show what 

would be a “uniform rate of progress” toward natural conditions for each mandatory Class I 

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

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

baseline visibility conditions for 2000-2004, natural background visibility conditions in 2064, 

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

of progress is also known as the “glidepath.” 
3-Virginia Regional Haze SIP 

The regional haze regulation then requires States to establish reasonable progress goals (RPGs), 

expressed in dv, for visibility improvement at each affected Class I area covering each 

(approximately) 10-year period until 2064. The goals must provide for reasonable progress 

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

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

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

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

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

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

all required analyses used to calculate the degree of visibility impairment under natural visibility 

conditions for the most impaired and least impaired days (see 40 CFR 51.308(d)(2)). In addition, 

states must include a monitoring strategy for measuring, characterizing, and reporting of regional 

haze visibility impairment that is representative of all mandatory Class I Federal areas within the 

state (see 40 CFR 51.308(d)(4)).

This first set of RPGs must be met through measures contained in the state’s long-term strategy 

covering the period from the present until 2018. The long-term strategy includes enforceable 

emissions limitations, compliance schedules, and other measures as necessary to achieve the 

RPGs, including all controls required or expected under all federal and state regulations by 2009 

and by 2018. During development of the long-term strategy, states are also required to consider 

specific factors such as the abovementioned ongoing control programs, measures to mitigate 

construction activities, source retirement and replacement schedules, smoke management 

programs for agriculture and forestry, and enforceability of specific measures (see 40 CFR 

51.308(d)(3)). 

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

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

regional haze regulation. 40 CFR 51.308(e) requires states to include a determination of BART 

for each BART-eligible source in the State that emits any air pollutant, which may reasonably be 

anticipated to cause or contribute to any impairment of visibility in any mandatory Class I 

Federal area. CAA § 169A(b) defines BART-eligible sources as sources in 26 specific source 

categories, in operation within a 15-year period prior to enactment of the 1977 CAA. States 

must determine BART according to five factors set out in § 169A(g)(7) of the CAA. Emission 

limitations representing BART and schedules for compliance with BART for each source subject 

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

SIPs for the first review period are due December 17, 2007. These plans will cover long-term 

strategies for visibility improvement between baseline conditions in 2000-2004 and 2018. States 

are required to evaluate progress toward RPGs goals every 5 years to assure that installed 

emissions controls are on track with emissions reduction forecasts in each SIP. The first interim 

review would be due to USEPA in December 2012. If emissions controls are not on track to 

meet SIP forecasts, then states would need to take action to assure emissions controls by 2018 

will be consistent with the SIP or to revise the SIP to be consistent with the revised emissions 

forecast. 
4-Virginia Regional Haze SIP 

1.4. Class I areas in Virginia 

Virginia has two Class I areas within its borders: Shenandoah National Park and James River 

Face Wilderness Area. The Air Division of VDEQ is responsible for developing the regional 

haze SIP. This SIP establishes RPGs for visibility improvement at each of these Class I areas, 

and a long-term strategy that will achieve those RPGs within the first regional haze planning 

period. 

Figure 1.4-1. Virginia Class I areas 

In developing this SIP, consideration has been given to the fact that emission sources outside of 

Virginia may affect visibility at these Virginia Class I areas and that emission sources within 

Virginia may affect visibility at Class I areas in neighboring states, as noted in Table 7.7.4-2. 

Through VISTAS, the southeastern states have worked together to assess state-by-state 

contributions to visibility impairment in specific Class I areas, including those in Virginia and 

those affected by emissions from Virginia. This technical work is discussed further in Sections 

5, 6, and 7 below. Consultations to date between Virginia and other states are summarized in 

Section 10. 

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

Southern Appalachian Mountain Initiative (SAMI) “to identify and recommend reasonable 

measures to remedy existing and prevent future adverse effects from human-induced air 

pollution on the air quality related values of the Southern Appalachian Mountains.” States 

cooperated with Federal Land Managers, USEPA, environmental organizations, and academia to 

complete a technical assessment of the impacts of acid deposition, ozone, and fine particles on 

sensitive resources in the Southern Appalachians. The SAMI Final Report was delivered in 

August 2002. The SAMI Assessment concluded that ammonium sulfate is the major contributor 

to visibility impairment in the Southern Appalachian Mountains and to improve visibility, it is 

most important to reduce SO2 emissions. SAMI also concluded that reducing ammonia 
5-Virginia Regional Haze SIP 

emissions would be helpful to reduce ammonium nitrate contributions to visibility impairment. 

Emissions controls for organic carbon, elemental carbon, and soil were expected to be less 

important for improving visibility. SAMI modeling found that on the haziest days, much of the 

benefit of emissions reductions would occur in close proximity to the location of the emission 

reductions. Emissions in surrounding SAMI states and states outside the SAMI region also 

contribute to air quality in the SAMI Class I areas. The SAMI states supported strong national 

multi-pollutant legislation to accomplish its mission. Emissions reductions to meet national 

health standards for ozone and fine particles were expected to also improve air quality in the 

Southern Appalachian Mountains. SAMI states committed to consider air quality benefits in the 

Southern Appalachians as they developed SIPs for the health standards. 

In 2002, the North Carolina legislation passed the North Carolina Clean Smokestack Act 

(NCCSA) that requires North Carolina utilities to reduce emissions of SO2 and NOX. The SAMI 

analyses and recommendations supported development of the NCCSA. While not directly 

affecting coal-fired power plants in Virginia, the NCCSA, by reducing emissions that may be 

transferred across state boundaries, will reduce visibility impairment in Virginia and is therefore 

mentioned throughout the SIP as an effective inter-state option to control emissions. Congress 

considered several legislative bills to reduce SO2 and NOX from electric generating utilities. In 

2004 USEPA promulgated the Clean Air Interstate Rule (CAIR) to require emissions reductions 

for SO2 and NOX from electric generating utilities in 26 eastern states. The CAIR rule allows for 

interstate trading of emissions to find cost effective reductions. Further reductions may be 

forthcoming from the Transport rule, which will take the place of the CAIR rule. These 

reductions will improve visibility in Class I areas in Virginia. 

1.5. State and Federal Land Manager (FLM) coordination 

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

consultation between the States and Federal Land Managers on the implementation of the 

visibility protection program, including development and review of implementation plan 

revisions and 5-year progress reports, and on the implementation of other programs having the 

potential to contribute to impairment of visibility in any mandatory Class I Federal area within 

the State. 

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

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

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

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

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

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

Memorandum of Agreement and Bylaws is included as Appendix A. 

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

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

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

documentation to member agencies so that they can develop their regional haze SIPs. Figure 

1.5-1 shows the 18 mandatory Class I Federal areas in the VISTAS Region, where visibility is an 

important value. Table 1.5-2 lists these Class I areas. 
6-Virginia Regional Haze SIP 

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

Table 1.5-2. Mandatory Class I Federal Areas in the VISTAS Region 

State Area Name Acreage 

Federal 

Land 

Manager 

40 CFR 81.401 Alabama Sipsey Wilderness 24,922 USDA-FS 

Chassahowitzka Wilderness 23,360 USDI-FWS 

40 CFR 81.407 Florida Everglades National Park 1,397,429 USDI-NPS 

St. Marks Wilderness 17,745 USDI-FWS 

Cohotta Wilderness 36,977 USDA-FS 

40 CFR 81.408 Georgia Okefenokee Wilderness 343,850 USDI-FWS 

Wolf Island Wilderness 5,126 USDI-FWS 

40 CFR 81.411 Kentucky Mammoth Cave National Park 51,303 USDI-NPS 

Great Smoky Mountains National Park 273,551 USDI-NPS 

Joyce Kilmer-Slickrock Wilderness 17,394 USDA-FS 

Linville Gorge Wilderness 12,002 USDA-FS 

Shining Rock Wilderness 18,483 USDA-FS 

40 CFR 81.422 North Carolina 

Swanquarter Wilderness 9,000 USDI-FWS 

40 CFR 81.426 South Carolina Cape Romain Wilderness 28,000 USDI-FWS 

Great Smoky Mountains National Park 241,207 USDI-NPS 40 CFR 81.428 Tennessee Joyce Kilmer-Slickrock Wilderness 17,394 USDA-FS 

James River Face Wilderness 8,886 USDA-FS 40 CFR 81.433 Virginia Shenandoah National Park 190,535 USDI-NPS 

Dolly Sods Wilderness 10,215 USDA-FS 40 CFR 81.435 West Virginia Otter Creek Wilderness 20,000 USDA-FS 
7-Virginia Regional Haze SIP 

A technical support document for the regional haze SIPs was prepared cooperatively by VISTAS 

staff and states to characterize regional haze in the southeastern United States. The report 

includes a review of the science and situation; calculation of initial baseline visibility; and review 

of monitoring data and data gaps. The report offers recommendations for additional monitoring; 

initial emission inventory characterization and projections; and compliance with existing control 

programs. Source contributions to VISTAS mandatory Class I Federal areas are also assessed. 

2. ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND 

ESTIMATE OF NATURAL BACKGROUND CONDITIONS IN CLASS I 

AREAS 

The goal of the regional haze regulation is to restore natural visibility conditions to the 156 Class 

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

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

measured in terms of light extinction, visual range, contrast, or coloration.” The regional haze 

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

anthropogenic emissions that cause haze. 

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

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

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

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

inverse megameters. Light extinction affects the clarity and color of objects being viewed. 

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

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

progress in improving visibility because each dv change is an equal incremental change in 

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

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

reasonable progress: 

• Natural conditions, 

• Baseline conditions, and 

• Current conditions. 

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

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

humidity factors. Total light extinction when converted to dv is calculated for the average of the 

20 percent best and 20 percent worst visibility days. 

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

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

improvement of visibility conditions. 

To assist states in conducting visibility-related research and in creating SIPs for the protection of 

visibility in the Class I Federal areas, the Interagency Monitoring of Protected Visual 
8-Virginia Regional Haze SIP 

Environments (IMPROVE) program was established in 1985. IMPROVE is a cooperative 

measurement effort governed by representatives from Federal and regional-state organizations. 

IMPROVE’s objectives are, among other things, to establish current visibility conditions in Class 

I Federal areas, to track changes in visibility, to identify emission sources responsible for 

anthropogenic visibility impairments, and to provide regional haze monitoring data for all Class I 

Federal areas where practical. IMPROVE’s monitoring network consists of aerosol and optical 

samplers. The network began in 1988 with 20 monitoring sites in Class I Federal areas and 

quickly grew to 30 sites by 1999. Finally, with the enactment of the regional haze regulation, the 

network has been expanded to 80 more sites (for a total of 110 sites) with additional sites for 

special projects. Figure 2-1 depicts the location of IMPROVE monitoring sites in the VISTAS 

region. 

Figure 2-1. IMPROVE Monitoring Sites in the VISTAS Region and Adjacent Regions 

The average of the IMPROVE monitoring data for 2000 through 2004 can be thought of as 

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

conditions to natural visibility conditions indicates the amount of improvement necessary to 

attain natural visibility by 2064. Each state must estimate natural visibility levels for Class I 

areas within its borders in consultation with Federal Land Managers and other states (40 CFR 

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

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

to in the SIP. 

2.1. Estimating Natural Conditions for Virginia Class I Areas 

Natural background visibility, as defined in Guidance for Tracking Progress Under the Regional 

Haze Rule (USEPA 2003), is based on annual average concentrations of fine particle 

components. The same annual average natural background visibility is assumed for all Class I 

areas in the eastern United States (separate values are estimated for the western United States). 

Natural background visibility for the 20 percent worst days is estimated by assuming that fine 
9-Virginia Regional Haze SIP 

particle concentrations for natural background are normally distributed and the 90th percentile of 

the annual distribution represents natural background visibility on the 20 percent worst days. 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

change between the original and new IMPROVE equation. 

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

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

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

IMPROVE equations, see Appendix B. 

2.2. Estimating Baseline Conditions for Virginia Class I Areas 

Baseline visibility conditions at each Virginia Class I area are estimated using sampling data 

collected at IMPROVE monitoring sites located in the Shenandoah National Park and the James 

River Face Wilderness Area. A five year average (2000 to 2004) was calculated for each of the 

20 percent worst and 20 percent best visibility days in accordance with 40 CFR 51.308(d)(2) and 

Guidance for Tracking Progress Under the Regional Haze Rule (USEPA, 2003). The light 

extinction and dv visibility values for these worst and best days are based on data and 

calculations included in Appendix B of this SIP. Appendix B includes a demonstration of the 

appropriateness of these values for each Class I area. 

2.3. Summary of Natural Background and Baseline Conditions for Virginia Class 

I Areas 

Table 2.3-1 presents estimated natural background and baseline visibility metrics for Virginia 

Class I areas. Baseline visibility using the 20 percent worst data at Shenandoah and James River 

Face is generally between 29 and 30 dv. Natural background visibility is predicted to be 

between 11 and 12 dv for Shenandoah and James River Face. 
10-Virginia Regional Haze SIP 

Table 2.3-1. Virginia Class I Areas’ Natural Background and Baseline Conditions 

Natural Background Conditions 

Class 1 area 

Average for 20 

percent Worst 

Days 

(deciviews) 

Average for 

20 percent 

Best Days 

(deciviews) 

Average for 20 

percent Worst 

Days 

Bext (Mm-1) 

Average for 20 

percent Best 

Days 

Bext (Mm-1) 

Shenandoah National Park 11.4 3.1 32.3 13.8 

James River Face 11.1 4.4 30.9 15.5 

Baseline Visibility Conditions 2000-2004 

Class 1 area

Average for 20 

percent Worst 

Days 

(deciviews) 

Average for 

20 percent 

Best Days 

(deciviews)

Bext (Mm-1) 

Average for 20 

percent Worst 

Days

Bext (Mm-1) 

Average for 20 

percent Best 

Days

Shenandoah National Park 29.3 10.9 196.5 31.2 

James River Face 29.1 14.2 189.5 42.3 

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

The 20 percent worst visibility days at the Southern Appalachian sites such as Shenandoah and 

James River Face generally occur in the period April to September. The peak hazy days occur in 

the summer under stagnant weather conditions with high relative humidity, high temperatures, 

and low wind speeds. The 20 percent best visibility days at the Southern Appalachian sites can 

occur at any time of year. 

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 both Shenandoah and James 

River Face. Sulfate levels on the 20 percent worst days account for 60-70 percent of the 

visibility impairment. Across the VISTAS region, sulfate levels are higher at the Southern 

Appalachian sites than at the coastal sites as shown in Figure 2.4-1. On the 20 percent clearest 

days, sulfate levels are more uniform across the region as shown in Figure 2.4-2. 

Figures 2.4-3 and 2.4-4 show the IMPROVE data in a time series with the species causing the 

visibility impairment delineated for the 20 percent worst days between 2000 and 2004. These 

charts demonstrate the daily and seasonal variability in visibility impairment for the two areas. 

Ammonium sulfate is a significant contributor on nearly all 20 percent worst visibility days. 

However, occasionally particulate organic matter (POM) can be a significant contributor as well. 

On the very few 20 percent worst visibility days that occur outside of the April through 

September time period, either POM, ammonium nitrate, or a combination of POM and 

ammonium nitrate offer significant contributions towards visibility impairment in the James 

River Face and Shenandoah. 
11-Virginia Regional Haze SIP 

Figure 2.4-1. Ave Extinction for the 20% Haziest Days in 2000-2004, New IMPROVE Equation 

Figure 2.4-2. Ave Extinction for the 20% Clearest Days in 2000-2004, New IMPROVE Equation 

VISTAS coastal VISTAS inland Neighboring non-VISTAS

0

50

100

150

200

250

300

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Extinction (Mm -1)

Sea Salt

Coarse

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

0

50

100

150

200

250

300

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

Extinction (Mm -1)

Sea Salt

Coarse

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

0

10

20

30

40

50

60

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR

0

10

20

30

40

50

60

Extinction (Mm-1)

Sea Salt

CM

Soil

EC

POM

NH4NO3

(NH4)2SO4

Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS

Swanquarter, NC

Cae Romain, SC

Okefenokee, GA

Everglades, FL

Chassahowitzka, FL

St. Marks, FL

Dolly Sods, WV

Shenandoah, VA

James River Face, VA

Linville Gorge, NC

Shining Rock, NC

Great Smoky Mtns., TN

Cohutta, GA

Sipsey, AL

Mammoth Cave, KY

Brigantine, NJ

Breton, LAMingo, MO

Hercules Glade, MO

Upper Buffalo, AR

Caney Creek, AR
12-Virginia Regional Haze SIP 

JARI1

Baseline Extinction, New IMPROVE Algorithm

20% W > 144

0

50

100

150

200

250

300

J-02

F-02

M-02

A-02

M-02

J-02

J-02

A-02

S-02

O-02

N-02

D-02

Extinction (Mm-1)

20% W > 145

0

50

100

150

200

250

300

J-01

F-01

M-01

A-01

M-01

J-01

J-01

A-01

S-01

O-01

N-01

D-01

Extinction (Mm-1)

0

50

100

150

200

250

300

J-00

F-00

M-00

A-00

M-00

J-00

J-00

A-00

S-00

O-00

N-00

D-00

Extinction (Mm-1)

20% W > 128

0

50

100

150

200

250

300

J-03

F-03

M-03

A-03

M-03

J-03

J-03

A-03

S-03

O-03

N-03

D-03

Extinction (Mm-1)

20% W > 123

0

50

100

150

200

250

300

J-04

F-04

M-04

A-04

M-04

J-04

J-04

A-04

S-04

O-04

N-04

D-04

Extinction (Mm-1)

Figure 2.4-3. IMPROVE Species Composition Data for James River Face 2000-2004 
13-Virginia Regional Haze SIP 

SHEN1

Baseline Extinction, New IMPROVE Algorithm

20% W > 136

0

50

100

150

200

250

300

J-02

F-02

M-02

A-02

M-02

J-02

J-02

A-02

S-02

O-02

N-02

D-02

Extinction (Mm-1)

20% W > 126

0

50

100

150

200

250

300

J-01

F-01

M-01

A-01

M-01

J-01

J-01

A-01

S-01

O-01

N-01

D-01

Extinction (Mm-1)

20% W > 127

0

50

100

150

200

250

300

J-00

F-00

M-00

A-00

M-00

J-00

J-00

A-00

S-00

O-00

N-00

D-00

Extinction (Mm-1)

20% W > 107

0

50

100

150

200

250

300

J-03

F-03

M-03

A-03

M-03

J-03

J-03

A-03

S-03

O-03

N-03

D-03

Extinction (Mm-1)

20% W > 128

0

50

100

150

200

250

300

J-04

F-04

M-04

A-04

M-04

J-04

J-04

A-04

S-04

O-04

N-04

D-04

Extinction (Mm-1)

Figure 2.4-4. IMPROVE Species Composition Data for Shenandoah 2000-2004 

POM is the second most important contributor to fine particle mass and light extinction on the 20 

percent haziest and the 20 percent clearest days at the Virginia Class I areas. Elevated levels of 

POM and elemental carbon (EC) indicate impact from wildfires or prescribed fire. Significant 

fire impacts are infrequent at Class I areas in Virginia. VISTAS collected additional samples of 
14-Virginia Regional Haze SIP 

carbon at five sites (Great Smoky Mountains, Millbrook, Cape Romain, Shenandoah, and 

Mammoth Cave) to better understand sources contributing to carbon in rural and urban areas. At 

Shenandoah and other mountain Class I areas, the majority of carbon is from either biogenic 

emissions from vegetation or from wood burning. Wood burning is more important in the fall, 

winter, and early spring months. Biogenic emissions, chiefly emissions of volatile organic 

compounds (VOCs) from vegetation, peak in spring and summer. Biogenic carbon emissions at 

Cape Romain, SC, were lower than emissions at the forested mountain sites. Carbon from 

gasoline and diesel engines is a relatively small contribution at the rural sites. At Millbrook, 

which was considered an urban site in the carbon study, carbon from fossil fuel combustion is a 

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

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

benefit in improving visibility in Class I areas. Controlling anthropogenic sources of carbon will 

likely be more effective at reducing levels of PM2.5 in urban areas. 

Ammonium nitrate is formed in the atmosphere by reaction of ammonia (NH3) and NOX. In the 

VISTAS region, nitrate formation is limited by availability of ammonia and by temperature. 

Ammonia preferentially reacts with SO2 and sulfate before reacting with NOX. Particle nitrate is 

formed at lower temperatures; at elevated temperatures nitric acid remains in gaseous form. For 

this reason, particle nitrate levels are very low in the summer and a minor contributor to visibility 

impairment. Particle nitrate concentrations are higher on winter days and are more important for 

the coastal sites where 20 percent worst days can occur on winter days. NOX is emitted by fossil 

fuel combustion by point, area, on road, and non road sources. Modeling data (see Section 7) 

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

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

effective in reducing ammonium nitrate levels than controls of NOX. 

 

Elemental carbon is a comparatively minor contributor to visibility impairment. Sources include 

agriculture burning, prescribed fires, wildland and wild fires, and incomplete combustion of 

fossil fuels. Elemental carbon levels are higher at urban monitors than at the Class I areas and 

suggest controls of fossil fuel combustion sources would be more effective at reducing PM2.5 in 

urban areas than at improving visibility in Class I areas. 

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

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

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

IMPROVE equation uses Chloride ion, Cl-

, from routine IMPROVE measurements to calculate 

sea salt levels. Cl- may react with nitrate and volatize off the filter, so that Cl-

 may underestimate 

sea salt levels. VISTAS funded sodium ion analyses of the IMPROVE filters from October 2003 

to December 2004 for nine sites. Sodium ion measures may overestimate sea salt levels because 

sodium nitrate is an additional source of sodium ion that cannot be distinguished from sodium 

chloride. Our best understanding to date suggests that using Cl- may underestimate sea salt 

levels by as much as a factor of two. This uncertainty has greatest implications for calculating 

sea salt levels under natural visibility conditions. 
15-Virginia Regional Haze SIP 

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

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

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

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

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

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

molecular weights of the other components. 

 

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

higher mass and lower light extinction on days with lower mass when compared to the old 

IMPROVE equation. This tends to increase calculated light extinction for current conditions and 

to decrease calculated light extinction for natural visibility conditions. Adding sea salt to the 

new IMPROVE equation increases light extinction for both current and natural visibility 

conditions. Increasing the mass multiplier for particulate organic matter in the new IMPROVE 

equation increases light extinction for current conditions more than for natural conditions. The 

new algorithm does not change the conclusion that in the VISTAS region and in Virginia, the 

most effective means to improve visibility is to reduce sulfate concentrations. 

With respect to PM2.5 trends in urban and Class I areas, IMPROVE data were compared to 

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

the similarities and differences in composition of fine particle mass. Several PM2.5

nonattainment areas are in close proximity to the Class I areas in the southeastern United States, 

including Atlanta, GA; Birmingham, AL; Charleston, WV; Chattanooga, TN; Louisville, KY; 

and Knoxville, TN. Ammonium sulfate concentrations are comparable between urban and 

nearby Class I areas, while organic carbon, elemental carbon, and nitrate concentrations are 

generally higher in urban areas than the Class I areas. These results suggest that sulfate is widely 

distributed regionally while urban areas see an additional incremental pollutant loading from 

local emissions sources. 

Fine particles of soil are minor contributors to visibility impairment at most sites on most days. 

Occasional episodes of elevated fine soil can be attributed to Saharan dust episodes, particularly 

at Everglades, Florida, but rarely are seen at Shenandoah or James River Face. No control 

strategies are indicated for fine soil. 

Classification and Regression Tree Analyses were used to characterize the relationship between 

meteorological conditions and visibility conditions at the Class I areas. Days were assigned to 

one of five visibility classes ranging from poor to good visibility. Days were then assigned to 

bins based on meteorological conditions. For the Virginia Class I areas poor visibility days were 

most likely to occur on days with high temperatures, high relative humidity, low wind speeds, 

and elevated PM2.5 mass at upwind urban areas. Precipitation was not a good predictor of 

visibility conditions. Weights were assigned to days based on frequency of occurrence of days 

with similar meteorological conditions. 

The above analyses are further discussed in Appendix B. 
16-Virginia Regional Haze SIP 

3. GLIDEPATHS TO NATURAL CONDITIONS IN 2064 

As stated in Section 1.3 above, the regional haze regulation directs states to graphically show 

what would be a “uniform rate of progress” toward natural conditions for each mandatory Class I 

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

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

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

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

anthropogenic impairment in 2064. 

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

achieving natural visibility conditions by 2064. 40 CFR 51.308(d)(1) of the regional haze 

regulation requires that RPGs must both: 

• provide for improvement in visibility for the most impaired days over the period 

of the implementation plan; and 

• ensure no degradation in visibility for the least impaired days over the same 

period. 

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

VISTAS region. The glidepaths were developed in accordance with USEPA guidance and used 

data collected from the IMPROVE monitoring sites as described in Section 2 above. The 

glidepath is one of the indicators used in setting RPGs. 

The following are glidepaths for the 20 percent most impaired days for Shenandoah and James 

River Face, assuming uniform rate of progress toward regional haze goals. Natural background 

visibility at both sites is predicted to be between 11 and 12 dv. 

Figure 3.1-1. Uniform Rate of Progress Glidepath for 20 percent worst days at James River Face. 

Uniform Rate of Reasonable Progress Glide Path

James River Face - W20% Data Days

29.1

27.6

24.9

21.9

18.9

15.9

12.9

11.1

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
17-Virginia Regional Haze SIP 

Figure 3.1-2. Uniform Rate of Progress Glidepath for 20 percent worst days at Shenandoah National Park 

4. NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILITY 

IMPAIRMENT IN VIRGINIA CLASS I AREAS 

4.1. Baseline Emissions Inventory 

The regional haze regulation at 40 CFR 51.308(d) (4) (v) requires a statewide emissions 

inventory of pollutants that are reasonably anticipated to cause or contribute to visibility 

impairment in any mandatory Class I area. An inventory was developed for the baseline year 

2002 and projected to 2009 and 2018. The pollutants inventoried include VOC, NOX, fine 

particulate (PM2.5), coarse particulate (PM10), NH3, and SO2. The baseline emissions inventory 

for 2002 was developed for Virginia following the methods described in Appendix D. 

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

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

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

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

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

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

emissions from the source category could be significant (dry cleaners, service stations, 

agricultural sources, fire emissions, etc.). These types of emissions are estimated on a 

countywide level. Non-road (or off-road) mobile sources are equipment that can move but do 

not use the roadways, such as lawn mowers, construction equipment, railroad locomotives, and 

aircraft. The emissions from these sources, like stationary area sources, are estimated on a 

countywide level. On-road mobile sources are automobiles, trucks, and motorcycles that use the 

Uniform Rate of Reasonable Progress Glide Path

Shenandoah - W20% Data Days

29.3

27.8

25.1

22.2

19.2

16.2

13.2

11.4

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
18-Virginia Regional Haze SIP 

roadway system. The emissions from these sources are estimated by vehicle type and road type 

and are summed to the countywide level. Biogenic sources are the natural sources like trees, 

crops, grasses, and natural decay of plants. The emissions from these sources are estimated on a 

countywide level. 

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

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

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

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

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

actual base year inventory; however, for sources whose emissions change significantly from year 

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

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

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

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

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

In the following sections, a synopsis of the inventories used for each source classification is 

provided. More detailed discussion of the emissions inventory development is contained in 

Appendix D. 

4.1.1. Stationary Point Sources 

Point source emissions are emissions from individual sources having a fixed location. Generally, 

these sources must have permits to operate, and their emissions are inventoried on a regular 

schedule. Major sources having emissions of 100 tons per year (tpy) of a criteria pollutant, 10 

tpy of a single hazardous air pollutant, or 25 tpy total hazardous air pollutant are inventoried 

annually. Smaller sources have been inventoried less frequently. The point source emissions 

data can be grouped as EGU sources and other industrial point sources, also called non-EGUs. 

4.1.1.1. Electric Generating Units 

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

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

provided by affected sources. These data provide hourly emissions profiles for SO2 and NOX

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

other pollutants (VOC, carbon monoxide, NH3, fine particles, soil) based on measured emissions 

of SO2 and NOX. 

Since the NOX emissions from EGU sources are a significant part of the emissions inventory, a 

typical base year emissions inventory was developed for these source to avoid anomalies in 

emissions due to variability in meteorology and economic and outage factors in 2002. This 

approach is consistent with the USEPA’s modeling guidance. To develop a typical year 2002 

emissions inventory for EGU sources, each unit’s average CEM heat input for 2000 through 

2004 was divided by the 2002 actual heat input to generate a unit specific normalizing factor. 

This normalizing factor was then multiplied by the 2002 actual emissions. The heat inputs for 
19-Virginia Regional Haze SIP 

the period 2000 through 2004 were used because the modeling design values use monitored data 

from this same five-year period. If a unit was shut down for an entire year during the 2000 

through 2004 period, the average of the years in which the unit was operational was used. If a 

unit was shut down in 2002, but not permanently shutdown, the emissions and heat inputs from 

2001 (or 2000) were used in the normalizing calculations. 

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

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

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

Model (IPM). IPM is a dynamic linear optimization model that can be used to examine air 

pollution control policies for various pollutants throughout the contiguous United States for the 

entire electric power system. The dynamic nature of IPM enables projection of the behavior of 

the power system over a specified future period. The optimization logic determines the leastcost means of meeting electric generation and capacity requirements while complying with 

specified constraints including air pollution regulations, transmission bottlenecks, and plantspecific operational constraints. The versatility of IPM allows users to specify which constraints 

to exercise, and it also allows users to populate IPM with their own datasets. 

Table 4-1 illustrates expected controls and emission reduction strategies to be installed at various 

EGU facilities in Virginia, as well as a listing of existing controls and emission reduction 

strategies for PM, NOX, and SO2. 

4.1.1.2. Other Sources 

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

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

Consolidated Emissions Reporting Rule (CERR), Subpart A of 40 CFR 51, for the year 2002. 

These emissions are temporally allocated to month, day, and hour using source category codebased allocation factors. 

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

control data consistent with USEPA’s CAIR analyses. This data was supplemented with statespecific growth factors and stakeholder input on growth assumptions. 
20-Virginia Regional Haze SIP 

Table 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction S

Size Existing Control Equipment and Emission Reduction Strategies2 Facility Name 

ORIS/Reg# Unit ID# MW mmbtu /hr NSR Permit? PM Year Installed NOX Year Installed SO2 Year Install

1 71.1 383 Yes FF At start up LNB, 

SNCR 

At start up SDA 

92% CE 

Altavista Power Station At start 10773/30859 

2 71.1 383 Yes FF At start up LNB, 

SNCR 

At start up SDA 

92% CE 

At start 

Birchwood Power Facility 54304/40809 

1 220 2,300 Yes FF At start up SCR At start up DLS 

94% CE 

At start 

3 69 912 No ESP(hot 

sided) 

Bremo Power Station --- BOOS 2004 None --- 

3

3796/40119 

4 185 1,699 No ESP(hot 

sided) 

--- LNB, 

ROFA 

2004 None --- 

1 113 1,300 No ESP --- ROFA, 

SNCR 

2003 Low S 

coal4

2007 

2 113 1,300 No ESP --- ROFA, 

SNCR 

2003 Low S 

coal4

2007 

3 185 1,663 No ESP --- LNB 

SCR 

2003 Low S 

coal4

2007 

Chesapeake Energy Center 3803/60163 

4 239 2,346 No ESP --- LNB 

SCR 

2003 Low S 

coal4

2007 

3 113 1,155 No ESP --- LNB 

OFA 

2003 None --- 

4 188 1,761 No ESP --- Staged 

comb SCR 

2003 None --- 

5 359 3.604 No ESP --- Staged 

comb SCR 

2002 None --- 

Chesterfield Power Station 3797/50396 

6 694 6,650 No ESP --- Staged 

comb SCR 

2004 FGD 

90% CE + polishing baghouse5

2008 

1 238 2,100 No ESP --- Staged 

Comb LNB SNCR 

2004 2007 2009 

None --- 

Clinch River6 3775/10236 

2 238 2,100 No ESP --- Staged 

Comb LNB SNCR 

2004 2007 2009 

None --- 
21-Virginia Regional Haze SIP 

Table 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction S

Size Existing Control Equipment and Emission Reduction Strategies2 Facility Name 

ORIS/Reg# Unit ID# MW mmbtu /hr NSR Permit? PM Year Installed NOX Year Installed SO2 Year Install

Clinch River6 3775/10236 

3 238 2,100 No ESP --- Staged 

Comb LNB SNCR 

2002 2007 2009 

None --- 

1 424 4,085 Yes FF At start up LNB/ 

OFA/ SNCR 

LNB & OFA at start up; SNCR 2003 

Wet FGD 94% CE 

Clover Power Station At start7213/30867 

2 424 4,085 Yes FF At start up LNB/ 

OFA/ SNCR 

LNB & OFA at start up; SNCR 2003 

Wet FGD 94% CE 

At start

BLR01A 375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

BLR01B 

115 

375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

BLR02A 375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

BLR02B 

115 

375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

BLR03A 375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

BLR03B 

115 

375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

BLR04A 375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start

Spruance Genco LLC 54081/51033 

BLR04B 

115 

375 Yes FF At start up OFA/ 

FGR/ SNCR/ Meth 

At startup SDA 

92% CE 

At start
22-Virginia Regional Haze SIP 

Table 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction S

Size Existing Control Equipment and Emission Reduction Strategies2 Facility Name 

ORIS/Reg# Unit ID# MW mmbtu /hr NSR Permit? PM Year Installed NOX Year Installed SO2 Year Install

BLR01A 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2008 

BLR01B 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2008 

BLR01C 

108.5 

200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2008 

BLR02A 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2008 

BLR02B 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2008 

James River Cogeneration 10377/50950 

BLR02C 

108.5 

200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2008 

BLR01A 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2007 

BLR01B 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2007 

BLR01C 

108.5 

200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2007 

BLR02A 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2007 

BLR02B 200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2007 

Cogentrix-Portsmouth 10071/61049 

BLR02C 

108.5 

200 Yes FF At start up OFA/ 

FGR 

2004 FGD 

90% CE 

2007 

51 100 572 No ESP --- Staged 

Comb LNB 

2004 2007 

None --- 

52 100 572 No ESP --- Staged 

Comb LNB 

2004 2007 

None --- 

Glen Lyn6 3776/20460 

6 238 2,040 No ESP --- Staged 

Comb LNB 

2004 2007 

None --- 
23-Virginia Regional Haze SIP 

Table 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction S

Size Existing Control Equipment and Emission Reduction Strategies2 Facility Name 

ORIS/Reg# Unit ID# MW mmbtu /hr NSR Permit? PM Year Installed NOX Year Installed SO2 Year Install

1 71.1 391 Yes FF At start up OFA/ 

SNCR 

At startup SDA 

92% CE 

Hopewell Power Station At start10771/51019 

2 71.1 391 Yes FF At start up OFA/ 

SNCR 

At startup SDA 

92% CE 

At start

1 69.9 834 Yes FF At startup OFA At startup SDA 

92% CE 

Mecklenburg Power Station At start52007/30861 

2 69.9 834 Yes FF At start up OFA At startup SDA 

92% CE 

At start

1 93 970 No ESP --- LNB 2005 Sorbent 

Inj 

2006 

2 93 970 No ESP --- LNB 2005 Sorbent 

Inj 

2006 

3 108 961 No ESP --- LNB/ 

SOFA 

2004 Sorbent 

Inj 

2006 

4 108 961 No ESP --- LNB/ 

SOFA 

2004 Sorbent 

Inj 

2006 

Potomac River Generating Station 3788/702287

5 108 961 No ESP --- LNB/ 

SOFA 

2004 Sorbent 

Inj 

2006 

1 71.1 400 Yes FF At start up Staged 

Comb/ OFA 

At start up SDA 

92% CE 

Southampton Power Station At start 10774/61093 

2 71.1 400 Yes FF At start up Staged 

Comb/ OFA 

At start up SDA 

92% CE 

At start 

1 173 1,697 No ESP --- ROFA/ 

SNCR 

2004 None --- 

Yorktown Power Station8

3809/60137 

2 182 1,745 No ESP --- ROFA/ 

SNCR 

2004 None --- 

1 The Virginia City Hybrid Energy Center, a coal fired power plant currently under construction in Wise County, Virginia, is not included in this li2 FF=Fabric Filter; ESP=electrostatic precipitator; DLS=dry lime scrubber; FGD=flue gas desulfurization unit; Sorbent inj=sorbent injection; FGR

OFA=over-fire air; SOFA=selective over-fire air; ROFA=rotating over-fire air; Staged comb=staged combustion; LNB=low NOX burners; SNCR

reaction; SCR=selective catalytic reaction; Meth=methane reburn; SDA=spray dry absorber 

3 No further add on controls are expected for Bremo Power Station. However, the July 1, 2008, PSD permit for the Virginia City Hybrid Energy C

Virginia, includes a condition requiring that, subject to State Corporation Commission approval, Bremo Power Station switch fuels within two yHybrid Energy Center facility commencing commercial operation. This fuel switch will nearly eliminate SO2 emissions from the facility. This p

the time of the best and final modeling. Therefore, these SO2 reductions were not included in the modeling exercise. 

4 A 40% reduction in SO2 emissions was estimated for the use of low sulfur coal. This value may fluctuate depending upon the quality and availab5 A control efficiency of 90% was used in calculating future year SO2 emissions estimates, based on the installation of these control devices. Actu

the device controlling unit #6 is 95%. The devices that will control units #3, #4, and #5 are also expected to achieve 95% control of SO2. 
24-Virginia Regional Haze SIP 

6 Both Clinch River and Glen Lyn are part of the AEP Eastern System consent agreement. The agreement requires LNB on Glen Lyn by the date o

agreement, which was December 10, 2007. The agreement also requires LNB and SNCR be installed on all three units at Clinch River. The LNB 

date of entry of the consent agreement and the SNCR by 12/31/2009. Additionally, Clinch River will have a plant wide annual limit of 21,700 tp

limit of 16,300 tpy starting 1/1/2015. Currently it is not known what mechanism will be used by Clinch River to achieve compliance with these S

7 Potomac River Generating Station installed sorbent injection to reduce SO2 emissions as part of a plan to comply with the SO2 NAAQS. On July 

received a state operating permit that required the use of sorbent injection, required the use of low sulfur (0.9% by weight S) coal, and limited SO

The permit also limits NOX emissions to 3,700 tpy. At the time of the best and final inventory submittal for the regional haze modeling effort, th

associated with this permit were not included since the permit was not yet final when the best and final inventory was being developed. 

8 Controls for SO2 were predicted on units #1 and #2 at Yorktown Power Station. However, due to the remand of CAIR and the vacatur of CAMR

for these units has not yet been determined by the owner. Virginia expects that some of the regulatory uncertainty currently being experienced by 

industry will be alleviated by the time the regional haze periodic report is due to be submitted to EPA. At that time, the control options assigned understood, and that information may be provided in the periodic report as an update to this table. 
25-Virginia Regional Haze SIP 

4.1.2. Stationary Area Sources 

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

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

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

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

households, or population. Stationary area source emissions are estimated at the countywide 

level. 

Virginia used the 2002 CERR data as the basis for the stationary area source inventory. In 

addition, the VISTAS contractor calculated emissions for animal husbandry, wildland fires, and 

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

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

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

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

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

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

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

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

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

to develop a typical year inventory. 

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

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

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

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

Growth and Analysis System Version 5 growth factors were used. Additionally, the VISTAS 

contractor generated, and Virginia staff reviewed, reduction estimates for areas of the 

Commonwealth where area source control measures have been implemented since 2002. These 

control measures reduce emissions from sectors such as architectural and industrial coatings, 

consumer products, portable fuel containers, auto body repair shops, and solvent cleaning. These 

measures apply to the localities in the Northern Virginia and Fredericksburg areas. 

4.1.3. Off-Road Mobile Sources 

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

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

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

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

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

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

the actual and typical base year emissions inventories. 

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

assumptions were used to create the 2018 future year inventories. The NONROAD model takes 

into consideration regulations affecting emissions from these source categories. For the largest 

airports in Virginia, the Federal Aviation Administration’s Terminal Area Forecast was used to 
26-Virginia Regional Haze SIP 

project growth in aircraft emissions. For the commercial marine, railroad locomotives, and the 

remaining airport emissions, the VISTAS contractor calculated the future growth in emissions 

using detailed inventory data (both before and after controls) for 1996 and 2010, obtained from 

The Clean Air Interstate Rule Emissions Inventory Technical Support Document (USEPA, 

2005). When available, state-specific growth factors were used. 

4.1.4. Highway Mobile Sources 

For on-road vehicles, the newest version of the USEPA on-road mobile source emission factor 

model, MOBILE6.2, was used. Key inputs for MOBILE6.2 include information on fuels used in 

the area, the age and distribution of registered vehicles, the average road speeds, the mix of 

vehicle types on the roads, the meteorological data for an area (e.g. temperature, humidity, 

barometric pressure), and any programs in place to reduce emissions from motor vehicles (e.g., 

inspection and maintenance programs). The MOBILE model also takes into consideration 

federal regulations that affect emissions from this source sector. 

The Virginia Department of Motor Vehicles provided statewide vehicle registration data for 

2002. These registration data files were used for both the 2002 and 2018 analysis years. The 

Virginia Department of Transportation provided 2002 vehicle miles traveled (VMT), road 

speeds, and growth rates to estimate vehicle miles traveled for 2018. The MOBILE model then 

is run separately to generate 2002 and 2018 inventories using input data reflective of that year. 

4.1.5. Biogenic Emission Sources 

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

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

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

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

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

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

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

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

agriculture, and urban portions of each county. 

4.1.6. Summary 2002 Base G2 (February 2007 version) Baseline Emissions 

Inventory for Virginia 

Table 4.1.6 is a summary of the 2002 baseline emission inventory for Virginia. The complete 

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

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

Table 4.1.6. 2002 Emissions Inventory Summary for Virginia in tpy. 

Sector VOC NOX PM2.5 PM10 NH3 SO2

Point 43,906 147,301 12,771 17,212 3,231 305,107 

Point-EGU 754 86,886 2,606 3,960 127 241,204 

Point-Non-EGU 43,152 60,415 10,165 13,252 3,104 63,903 

Area (including fires)1 174,851 51,753 45,292 239,096 43,975 105,982 

On-Road Mobile 157,989 219,835 3,067 5,312 7,770 8,196 
27-Virginia Regional Haze SIP 

Table 4.1.6. 2002 Emissions Inventory Summary for Virginia in tpy, continued. 

Sector VOC NOX PM2.5 PM10 NH3 SO2

Non-Road Mobile 74,866 63,219 8,288 8,728 48 8,663 

Biogenics 923,219 11,443 --- --- --- --- 

TOTAL 1,374,831 493,551 69,418 270,348 55,024 427,948 

1

Area (including fires) enumerates emissions from the entire area source category plus the emissions from fires. 

4.1.7. Model Performance Improvements through Emissions Inventory 

Improvements 

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

emissions inventory that, in turn, improved model performance. These inventory improvements 

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

summarized here: 

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

provide estimates of future year utility production and emissions. Continuous 

emissions monitoring data was used to define seasonal variability in production 

and emissions. For Base G2 emissions, states updated IPM model projections 

from 2005 with control data provided by utility companies in 2006 through winter 

2007. 

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

MOBILE model input and VMT data. 

• For NH3 emissions from agricultural sources, the Carnegie Mellon University 

ammonia model was used to improve annual and monthly estimates. 

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

prescribed fire, land clearing, and agricultural burning. MACTEC developed a 

2002 fire inventory. Where data allowed, Alpine Geophysics modeled fire events 

as point sources. In 2006, United States Forest Service and Fish and Wildlife 

Service provided projections of increased prescribed burning in 2009 and 2018; 

these data were incorporated in the Base G inventory for all states except Florida. 

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

was used in Base G. 

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

Atlantic Oceans, ENVIRON created gridded emissions for the VISTAS modeling 

domain using inventory data newly developed for USEPA by Dr. Corbett at 

University of Delaware. These emissions were incorporated in the Base G 

modeling. 

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

incorporated as available. 

4.2. Assessment of Relative Contributions from Specific Pollutants and Sources 

Categories 

Ammonium sulfate is the largest contributor to visibility impairment at the Virginia Class I 

areas, and reduction of SO2 emissions would be the most effective means of reducing ammonium 
28-Virginia Regional Haze SIP 

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

attributable to electric generating facilities and industrial point sources. 

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

5. REGIONAL HAZE MODELING METHODS AND INPUTS 

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

Virginia. The following sections outline the methods and inputs used by VISTAS for the 

regional modeling. Additional details are provided in Appendix C. 

5.1. Analysis Method 

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

system. VISTAS decided to use the following modeling system: 

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

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

a nonhydrostatic, prognostic meteorological model routinely used for urban- and 

regional-scale photochemical, fine particulate matter, and regional haze regulatory 

modeling studies. 

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

modeling system is an emissions modeling system that generates hourly gridded 

speciated emission inputs of mobile, nonroad mobile, area, point, fire, and 

biogenic emission sources for photochemical grid models. 

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

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

capable of addressing ozone, particulate matter, visibility, and acid deposition at a 

regional scale for periods up to one year. 

The USEPA Modeling Guidance recommends modeling an entire year or, at a minimum, several 

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

contribute to elevated levels of fine particulate matter. The year 2002 was selected by VISTAS 

as the modeling year for this demonstration. Meteorological inputs were developed for 2002 

VISTAS States SO2 Emissions - 2002 

Utilities

Industrial

On road

Non road

Other

Industrial: 20% Utilities: 76%

4.8 Million tons

VISTAS States SO2 Emissions - 2002 

Utilities

Industrial

On road

Non road

Other

Industrial: 20% Utilities: 76%

4.8 Million tons
29-Virginia Regional Haze SIP 

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

processed through the emissions model. These inputs were used in the air quality model to 

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

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

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

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

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

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

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

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

5.2. Model Selection 

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

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

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

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

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

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

verification at no or low cost. 

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

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

system for this modeling demonstration. 

5.2.1. Selection of Photochemical Grid Model 

5.2.1.1. Criteria 

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

needs to show that it meets the same general criteria as a model for a national ambient air quality 

standard (NAAQS) attainment demonstration: 

• The model has received a scientific peer review. 

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

basis. 

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

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

biased toward underestimates or overestimates. 

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

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

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

proprietary. 
30-Virginia Regional Haze SIP 

5.2.1.2. Overview of CMAQ 

The photochemical model selected for this study was CMAQ version 4.5. For more than a 

decade, the USEPA has been developing the Models-3 CMAQ modeling system with the 

overarching aim of producing a “One-Atmosphere” air quality modeling system capable of 

addressing ozone, fine particulate matter, visibility, and acid deposition within a common 

platform. The original justification for the Models-3 development emerged from the challenges 

posed by the 1990 CAAA and USEPA’s desire to develop an advanced modeling framework for 

“holistic” environmental modeling utilizing state-of-science representations of atmospheric 

processes in a high performance computing environment. The USEPA completed the initial 

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

operating science model under the Models-3 framework. 

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

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

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

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

modeling. 

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

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

5.2.2. Selection of Meteorological Model 

5.2.2.1. Criteria 

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

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

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

both the model’s ability to accurately replicate important meteorological phenomena in the 

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

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

established for the meteorological model to be used in this study: 

• Non-hydrostatic formulation 

• Reasonably current, peer reviewed formulation 

• Simulates cloud physics 

• Publicly available at no or low cost 

• Output available in I/O API format 

• Supports four dimensional data assimilation (FDDA) 

• Enhanced treatment of planetary boundary layer heights for AQ modeling 

5.2.2.2. Overview of MM5 

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

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

model has been under continuous development, improvement, testing, and open peer-review for 
31-Virginia Regional Haze SIP 

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

mesoscale studies. 

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

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

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

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

are directly compatible with the input requirements of “one atmosphere” air-quality models using 

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

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

Distinct planetary boundary layer (PBL) parameterizations are available for air-quality 

applications, both of which represent sub-grid-scale turbulent fluxes of heat, moisture, and 

momentum. One scheme uses a first-order eddy diffusivity formulation for stable and neutral 

environments and a modified first-order scheme for unstable regimes. The other scheme uses a 

prognostic equation for the second-order turbulent kinetic energy, while diagnosing the other key 

boundary layer terms. 

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

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

analyze standard surface and radiosonde observations, using the National Meteorological 

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

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

MM5 modeling systems in regulatory air quality application studies have involved comparisons 

with other prognostic models such as the Regional Atmospheric Modeling System (RAMS) and 

the Systems Application International Mesoscale Model. The MM5 enjoys a far richer 

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

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

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

somewhat better photochemical model inputs than alternative models. 

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

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

5.2.3. Selection of Emissions Processing System 

5.2.3.1. Criteria 

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

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

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

system. 

• File system compatibility with the I/O API. 

• File portability. 
32-Virginia Regional Haze SIP 

• Ability to grid emissions on a Lambert conformal projection. 

• Report capability. 

• Graphical analysis capability. 

• MOBILE6 mobile source emissions. 

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

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

time. 

• Ability to process control strategies. 

• No or low cost for acquisition and maintenance. 

• Expandable to support other species and mechanisms. 

5.2.3.2. Overview of SMOKE 

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

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

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

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

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

mobile sources, SMOKE actually simulates emissions rates based on input mobile-source 

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

 

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

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

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

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

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

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

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

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

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

processing. 

 

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

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

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

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

countries, and any pollutant can be processed by the system. 

Additional information about the SMOKE model is contained in Appendix C. 

5.3. Selection of the Modeling Year 

A crucial step to SIP modeling is the selection of the period of time to model so that air quality 

conditions may be well represented and so that changes in air quality in response to changes in 

emissions may be projected. The year 2002 was selected as the base year for several reasons. 
33-Virginia Regional Haze SIP 

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

of Air Quality Goals for Ozone, PM2.5, and Regional Haze (USEPA, 2007) identifies specific 

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

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

selection be derived from the following principal criteria: 

• Simulate a variety of meteorological conditions. 

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

baseline design value or visibility impairment. 

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

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

each monitor violating the NAAQS is based on multiple days. 

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

is to model a full, representative year. Moreover, the required RRF values should be based on 

model results averaged over the 20 percent worst and 20 percent best visibility days determined 

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

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

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

that are drawn from the years upon which the current design values are based, (c) include 

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

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

possible. Finally, USEPA explicitly recommended in its 2007 guidance to use 2002 as the 

baseline inventory year. 

VISTAS adopted a logical, stepwise approach in implementing the USEPA guidance in order to 

identify the most preferable, representative year for regional haze modeling. These steps 

include the following: 

• Relevant Meteorological Conditions: The VISTAS meteorological contractor 

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

VISTAS region directly relevant to the evaluation of candidate annual modeling 

episodes. 

• Initial Episode Typing: At the time of selection in 2003, meteorological and air 

quality data were available for 2002 for model inputs and model performance 

evaluation. VISTAS used Classification and Regression Tree Analyses to 

evaluate visibility conditions for 2000, 2001, and 2002, the candidate modeling 

years. The year 2002 was found to be representative of conditions in the other 

two years. Subsequently, these analyses were repeated with the meteorological 

and air quality monitoring data for 2000 to 2004 to evaluate how well the 2002 

modeling year represented the full 2000-2004 baseline period. This analysis 

confirmed that visibility and PM2.5 mass in 2002 were representative of the fiveyear baseline period for the VISTAS Class I areas. This analysis is discussed in 

more detail in the project report in Appendix B. 
34-Virginia Regional Haze SIP 

• Data Availability: In parallel with the CART analysis, episode characterization 

analyses, which were collaborative investigations by VISTAS states including 

North Carolina, Georgia, Florida, intensively studied the availability of PM2.5, 

meteorological, and emissions data and the relevance of alternative baseline 

modeling periods from a regulatory standpoint. Additionally, since 2002 was the 

year that USEPA was requiring states to provide emissions inventory data for the 

Comprehensive Emissions Reporting Rule, it made sense to use 2002 as the 

modeling year to take advantage of the 2002 inventory. 

• Years to be used by other RPOs: VISTAS also considered what years other RPOs 

would be modeling, and several had already chosen calendar year 2002 as the 

modeling year. 

After a lengthy process of integrated studies, the episode selection process culminated in the 

selection of calendar year 2002 (January 1 through December 31) as the most current, 

representative, and pragmatic choice for VISTAS regional haze modeling. All of the USEPA 

criteria for regional haze episode selection were directly considered in this process together with 

many other considerations (e.g., timing of new emissions or aerometric data deliveries by the 

USEPA or the states to the modeling teams). 

5.4. Modeling Domains 

5.4.1. Horizontal Modeling Domain 

USEPA’s modeling guidance recommends a 12-km modeling grid resolution for PM2.5 modeling 

while a 36-km grid is considered acceptable for regional haze. For the VISTAS modeling, a 

coarse 36-km grid resolution was used for modeling the entire United States, and a finer 12-km 

grid was used to model the eastern United States. 

The CMAQ model was run in one-way nested grid mode. This allowed the larger outer domains 

to feed concentration data to the inner nested domain. One-way nesting is believed to be 

appropriate for the generally stagnant conditions experienced during Virginia ozone episodes. 

Two-way nesting was not considered due to numerical and computational uncertainty associated 

with the technique. 

The horizontal coarse grid modeling domain boundaries were determined through a national 

effort to develop a common grid projection and boundary. A smaller 12-km grid modeling 

domain was selected in an attempt to balance location of areas of interest, such as ozone and fine 

particulate matter nonattainment areas, as well as Class I areas for regional haze. Processing 

time was also a factor in choosing a smaller 12-km grid modeling domain. 

The coarse 36-km horizontal grid domain covers the continental United States. This domain was 

used as the outer grid domain for MM5 modeling with the CMAQ domain nested within the 

MM5 domain. Figure 5.4.1-1 shows the MM5 horizontal domain as the outer most, blue grid 

with the CMAQ 36-km domain nested in the MM5 domain. 
35-Virginia Regional Haze SIP 

Figure 5.4.1-1. The MM5 Domain (blue grid), with Nested36 km CMAQ Domain 

To achieve finer spatial resolution in the VISTAS states, a one-way nested high resolution 

(12-km grid resolution) was used. Figure 5.4.1-2 shows the 12-km grid modeling domain for the 

VISTAS region. This is the modeling domain for which the RPGs will be assessed. 

Figure 5.4.1-2. Detailed View of the 12 km VISTAS Grid 
36-Virginia Regional Haze SIP 

5.4.2. Vertical Modeling Domain 

The CMAQ vertical structure is primarily defined by the vertical grid used in the MM5 

modeling. The MM5 model employed a terrain-following coordinate system defined by 

pressure, using 34 layers that extend from the surface to the 100 millibar level. A layeraveraging scheme was used to generate 19 vertical layers for CMAQ to reduce the computational 

cost of the CMAQ simulations. The effects of layer averaging were evaluated in conjunction 

with the VISTAS modeling effort and were found to have a relatively minor effect on the model 

performance metrics when both the 34 layer and the 19 layer CMAQ models were compared to 

ambient monitoring data. 

6. MODEL PERFORMANCE EVALUATION 

The initial modeling effort focused on evaluating previous regional air quality modeling 

applications and testing candidate model configurations for the SMOKE emissions and CMAQ 

model for the VISTAS 36-km and 12-km modeling domains. This effort resulted in a report 

recommending the model configuration for the annual emissions and air quality modeling, which 

is included as part of the VISTAS Emissions and Air Quality Modeling Protocol. The evaluation 

of the meteorological modeling configuration can be found in Appendix F, with a summary of 

the final meteorological and air quality modeling configuration in the modeling protocol 

contained in Appendix E and Appendix C, respectively. 

Figure 6.0-1. Monitoring Networks Used for VISTAS 2002 Model Performance Evaluation 

Air quality model performance for the 2002 modeling year was initially tested in 2004 using an 

early version of the VISTAS emissions inventory. In keeping with the one-atmosphere objective 

of the CMAQ modeling platform, model performance was evaluated based on measured ozone, 
37-Virginia Regional Haze SIP 

fine particles, and acid deposition in the Air Quality System (AQS), IMPROVE, STN, 

Southeastern Aerosol Research and Characterization (SEARCH), National Acid Deposition 

Program (NADP), and Clean Air Status and Trends Network (CASTNet) monitoring networks 

(Figure 6.0-1). 

6.1. Modeling Performance Goals and Criteria 

In 2004, VISTAS established model performance goals and criteria for components of fine 

particle mass (Table 6.1-1) based on previous model performance for ozone and fine particles. 

The EPA modeling guidance for fine particulate matter at the time noted that PM models might 

not be able to achieve the same level of performance as ozone models. VISTAS’ evaluation 

considered several statistical performance measures and displays. Fractional bias and mean 

fractional error were selected as the most appropriate metrics to summarize model performance; 

other metrics were also calculated and are included for IMPROVE monitors in the full model 

performance evaluation (Appendix F). 

Table 6.1-1. Model Goals for the Fine Particulate Mass Component Species 

Fractional Bias Mean Fractional 

Error Comment 

<15 percent <35 percent Goal for PM model performance based on ozone model 

performance, considered excellent performance 

<30 percent <50 percent Goal for PM model performance, considered good 

performance 

<60 percent <75 percent Criteria for PM model performance, considered average 

performance. Exceeding this level of performance indicates 

fundamental concerns with the modeling system and 

triggers diagnostic evaluation. 

Several graphic displays of model performance were prepared, including: 

• Scatter plots of predicted and observed concentrations and deposition by species, 

monitoring network, and month. 

• Time series plots of predicted and observed concentrations and deposition by 

species, monitoring site, and month. 

• Spatially averaged time series plots. 

• Time series plots of monthly fractional bias and error for a species, region, and 

network. 

• Performance goal plots (“soccer plots”) that summarize model performance by 

species, region, and season. 

• Concentration performance plots (“bugle plots”) that display fractional bias or 

error as a function of concentration by species, region, monitoring network, and 

month. 

The soccer plots and bugle plots are relatively new tools in model performance evaluations, and 

they have recently been included as model performance evaluation displays in USEPA’s 

Guidance on the use of Models and Other Analyses for Demonstrating Attainment of Air Quality 

Goals for Ozone, PM2.5, and Regional Haze (USEPA, 2007). Both soccer plots and bugle plots 

offer a convenient way to examine model performance with respect to set goals and criteria. The 

bugle plots have the added benefit of adjusting the goals and criteria to consider the 
38-Virginia Regional Haze SIP 

concentration of the species. Analysis of bugle plots generally suggests that greater emphasis 

should be placed on performance of those components with the greatest contribution to PM mass 

and visibility impairment (e.g., sulfate and organic carbon) and that greater bias and error could 

be accepted for components with smaller contributions to total PM mass (e.g., elemental carbon, 

nitrate, and soil). 

6.2. VISTAS Domain-Wide Performance 

Further discussion of model performance in this document will focus on the comparison of 

observational data from the IMPROVE monitors and model output data from the 2002 VISTAS 

BaseG2-actual annual air quality modeling. Focus is limited to the IMPROVE monitoring 

network as these sites are the locations used in projecting attainment visibility improvement 

goals in the Class I areas. 

The evaluation will primarily focus on the air quality model’s performance with respect to 

individual components of fine particulate matter, as good model performance of the component 

species will dictate good model performance of total or reconstituted fine particulate matter. 

Model performance of the total fine particulate matter and the resulting total light extinction will 

also be provided as a means to discuss the overall model performance for this implementation 

plan. 

In these analyses, mean fractional bias (error) is used in lieu of mean bias (error), to prevent low 

observations and model predictions from skewing the metrics. A full list of model performance 

statistics is found in Appendix F. The soccer and bugle plots for the all of the VISTAS 

IMPROVE monitors are included here for summary purposes. Plots have been developed for the 

average monthly concentrations and the performance statistics for all of the most significant light 

scattering component species (sulfate, nitrate, and organic carbon) for the 20 percent best days 

and 20 percent worst days. Plots for individual IMPROVE monitors associated with Virginia 

Class I areas are included in Appendix F. 

The soccer plots of monthly concentrations (Figures 6.2.-1 and 6.2.-2) show that values for 

nitrate generally fall outside of criteria performance thresholds. Sulfates and organic carbon 

generally fall within goal thresholds, with a couple of months falling just outside the goal 

thresholds but well within the criteria thresholds. Figure 6.2-3 contains separate soccer plots for 

each season. The seasonal plots emphasize poorer nitrate performance in the summer (does not 

even appear on the plots provided because performance is off scale with other constituents), 

when observed nitrate is quite low and predicted nitrate is even lower. When concentration is 

factored into performance criteria, nitrate performance improves with respect to mean fractional 

bias and mean fractional error (Figures 6.2.-4 and 6.2.-5). 

Additionally, performance assessed at the “one atmosphere” level was also deemed acceptable 

for ozone and particulate matter at various monitoring sites (STN, FRM, CASTNet, etc.). 

Overall, VISTAS found the Base G2 modeling results to be representative and acceptable for use 

in modeling projections for ozone, particulate matter, and regional haze. 
39-Virginia Regional Haze SIP 

Figure 6.2-1. Soccer Plot for Mean Fractional Error and Bias, Base G2 

Figure 6.2-2. A Zoomed View of the Soccer Plot 

All Sites CMAQ 12km - 2002 Monthly

0.0

20.0

40.0

60.0

80.0

100.0

120.0

140.0

160.0

180.0

200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional Bias

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

All Sites CMAQ 12km - 2002 Monthly

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

-75.0 -25.0 25.0 75.0

Fractional Bias

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal
40-Virginia Regional Haze SIP 

Figure 6.2-3. Seasonal Soccer Plots Based on Base G1 Results for all VISTAS IMPROVE Monitors 

All Sites CMAQ 12km - 2002 Monthly

0.0

50.0

100.0

150.0

200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Average Concentration (μg/m3)

Mean Fractional Error 

Sulfate

Nitrate

Organics

Criteria

Goal

Figure 6.2-4. Bugle Plot—Mean Fraction Bias 
41-Virginia Regional Haze SIP 

All Sites CMAQ 12km - 2002 Monthly

-200.0

-150.0

-100.0

-50.0

0.0

50.0

100.0

150.0

200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0

Average Concentration (μg/m3)

Mean Fractional Bias 

Sulfate

Nitrate

Organics

(+) Criteria

(+) Goal

(-) Goal

(-) Criteria

Figure 6.2-5. Bugle Plot of Mean Fractional Error 

6.3. Virginia Class I Area Performance 

The following section provides stacked bar charts comparing observed fine particulate matter 

composition and modeled fine particulate matter composition. The charts display the 20 percent 

best days and the 20 percent worst days. 

The stacked bar chart allows a side by side comparison of each day observed and modeled 

compositional and total light extinction. Within each bar the color codes are: 

• Yellow = light extinction due to sulfates (bextSO4). 

• Red = light extinction due to nitrates (bextNO3). 

• Green = light extinction due to organic carbon (bextOC). 

• Black = light extinction due to elemental (bextEC). 

• Brown = light extinction due to soil (bextSoil). 

• Gray = light extinction due to coarse mass (bextCM). 

The components are presented in the same order for both the observed (left bar) and modeled 

data (right bar), so that identification of days when the prediction light extinction for the 

component differs from the observed value is simplified. The total height of the bar provides the 

total reconstructed particulate matter light extinction value. 

A cursory view of the stacked bar charts in Figures 6.3-1, 6.3-2, 6.3-3, and 6.3-4 reiterates that 

sulfates are a large contributor to light extinction in the Virginia Class I areas on both 20 percent 

best days and 20 percent worst days. The bar charts also suggest that organic carbon and nitrates 

are important on the 20 percent best days. 

Comparing the 20 percent best day charts to the 20 percent worst day charts illustrates that the 

various components of particle pollution play a more prominent role in the 20 percent best days 

than with the 20 percent worst days. Also, the species make-up on the 20 percent best days varies 
42-Virginia Regional Haze SIP 

more widely compared to the 20 percent worst days. This suggests accurately modeling each 

species is especially important on the 20 percent best days. 

The bar charts for the 20 percent worst days show that model performance does improve across 

the sites. Light extinction due to sulfate prediction is better, but still falls short on some days. 

Light extinction due to organic carbon also becomes more important to total light extinction. 

Much like the sulfate component, the organic carbon component accuracy has improved 

performance over the 20 percent best day series, thought some days are still poorly predicted. 

Overall, Virginia found model performance to fall within acceptable limits. Virginia further 

asserts the one atmosphere modeling performed by the VISTAS contractors is representative of 

conditions in the southeastern states and is applicable for use in attainment demonstrations. 

Best 20% Observed vs 2002gt2a at Shenandoah

Observation (left) vs Modeled Base G2a (right)

0

20

40

60

80

100

120

140

160

180

200

5 14 23 26 38 50 62 68 77 158 206 221 245 269 284 320 335 338 341 344 347 356 359 _ _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-1. Stacked Bar Charts for Shenandoah on the 20% Best Days 
43-Virginia Regional Haze SIP 

Worst 20% Observed vs 2002gt2a at Shenandoah

Observations (left) vs Modeled G2a (right)

0

50

100

150

200

250

300

350

400

450

500

59 146 149 155 161 164 170 176 182 185 197 200 203 212 215 224 233 236 239 254 257 260 272 275 _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-2. Stacked Bar Chart for Shenandoah on the 20% Worst Days 

Best 20% Observed vs 2002gt2a at James River Face

Observation (left) vs Modeled G2a (right)

0

10

20

30

40

50

60

70

80

90

8 11 23 26 35 44 59 68 77 101 104 113 116 134 158 245 299 302 326 332 335 356 359 _ _ Avg

Julian Day in Best 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-3. Stacked Bar Chart for James River Face on the 20% Best Days 
44-Virginia Regional Haze SIP 

Worst 20% Observed vs 2002gt2a at James River Face

Observation (left) vs Modeled G2a (right)

0

50

100

150

200

250

300

350

137 146 152 155 161 182 185 191 197 200 203 212 215 218 224 233 236 239 254 257 263 266 272 275 _ Avg

Julian Day in Worst 20% group

bEXT (1/Mm)

bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-4. Stacked Bar Chart for James River Face on the 20% Worst Days 

7. LONG-TERM STRATEGY 

As stated in Section 1.3, the regional haze regulation requires states to establish RPGs, expressed 

in dv, for visibility improvement at each affected Class I area covering each (approximately) 10-

year period until 2064. This first set of RPGs 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 Virginia’s long-term strategy. 

7.1. Overview of the Long-Term Strategy Development Process 

The monitored data and modeling analyses cited in Sections 2 and 5 above establish that for the 

VISTAS region, the key contributors to regional haze in the 2000-2004 baseline timeframe were 

large stationary sources of SO2 emissions. Keeping that key conclusion in mind, this section 

addresses the following questions: 

• Assuming implementation of existing federal and state air regulatory 

requirements in Virginia and the VISTAS region, how much visibility 

improvement, compared to the glidepath, is expected at James River Face and 

Shenandoah between now and 2018? 

• If additional emission reductions were needed, from what pollutants and source 

categories would the greatest visibility benefits be realized between the baseline 

and 2018? 

• Narrowing down further, emissions in what geographic locations are found to 

have the greatest impact on visibility in specific Class I areas? 
45-Virginia Regional Haze SIP 

• What types of emissions sources are found in those geographic locations? 

• Which specific individual sources in those geographic locations have the greatest 

visibility impacts at a given Class I area? 

• What additional emission controls represent reasonable progress for those specific 

sources? 

• What additional emission controls represent BART in Virginia? 

• Given the additional emission reductions expected from reasonable progress and 

BART, how much additional visibility improvement, compared to the glidepath, 

is expected at Class I areas in Virginia between the baseline and 2018? 

7.2. Expected Visibility Results in 2018 for Virginia Class I Areas under existing 

and planned emissions controls (Base G2 Inventory) 

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

These programs are described in more detail below. 

7.2.1. Federal and State Control Requirements 

The first phase of CAIR caps emissions of SO2 and NOX from EGUs in the eastern United States 

beginning in 2010 and 2009, respectively. The second phase of CAIR would have reduced SO2

emissions from EGUs in these states by more than 70 percent and NOX emissions by more than 

60 percent from 2003 levels. CAIR has been remanded to USEPA, and a transport rule proposal 

is expected to be finalized by 2011. 

The Clean Air Mercury Rule (CAMR) was estimated to reduce mercury emissions from utilities 

by nearly 70 percent. This rule was vacated, and EPA is expected to finalize new requirements 

for hazardous air pollutant emissions from utility boilers by November 16, 2011. 

 

Phase I of the NOX SIP call applies to certain EGUs and large non-EGUs, including large 

industrial boilers, turbines, and cement kilns. Those states affected by the NOX SIP call in the 

VISTAS region have developed rules for the control of NOX emissions that have been approved 

by the USEPA. The NOx SIP Call has resulted in a 68 percent reduction in NOX emissions 

from large stationary combustion sources. For this analysis, the emissions for NOX SIP callaffected sources were capped at 2007 levels, and the capped levels were carried forward for the 

2009 and 2018 future year inventories. 

Under the NCCSA, coal-fired power plants in North Carolina must achieve a 77 percent cut in 

NOX emissions by 2009 and a 73 percent cut in SO2 emissions by 2013. 

A number of consent agreements also impose specific controls that were included in this 

inventory development process: 

• TECO (US District Court, Middle District of Florida): Under a settlement 

agreement, Tampa Electric installed permanent emissions control equipment by 

2008 to meet stringent pollution limits; implemented a series of interim pollutionreduction measures to reduce emissions while the permanent controls were 

designed and installed; and retired pollution emission allowances that Tampa 
46-Virginia Regional Haze SIP 

Electric or others could use, or sell to others, to emit additional NOX, SO2, and 

PM. 

• VEPCO (US District Court, Eastern District of Virginia): Virginia Electric and 

Power Company (also known as Virginia-Dominion Power) agreed to spend $1.2 

billion by 2013 to eliminate 237,000 tons of SO2 and NOX emissions each year 

from eight coal-fired electricity generating plants in Virginia and West Virginia. 

• Gulf Power (State of Florida “Agreement for the purpose of Ensuring Compliance 

with the Ozone Ambient Air Quality Standards,” dated August 28, 2002): This 

agreement called for Gulf Power to upgrade its operation to cut NOX emission 

rates by 61 percent at its Crist generating plant by 2007, with major reductions 

beginning in early 2005. The Crist plant is a significant source of NOX emissions 

in the Pensacola area. 

• Dupont (US District Court for the Southern District of Ohio): A 2007 agreement 

called for the James River plant, located in Virginia, to install dual absorption 

pollution control equipment by September 1, 2009, resulting in emission 

reductions of approximately 1,000 tons SO2 annually. 

• Stone Container (US District Court, Eastern District of Virginia): A 2004 

agreement called for the West Point Paper Mill, owned by Smurfit/Stone 

Container and located in West Point, Virginia, to control with a wet scrubber the 

SO2 emissions from the #8 Power Boiler. This control device will result in 

reductions of over 3,500 tons of SO2 in 2018. 

New 1-hour ozone SIPs for Atlanta, Birmingham, and Northern Kentucky have been submitted 

to USEPA to demonstrate attainment of the one-hour ozone NAAQS. These SIPs require NOX

reductions from specific coal fired power plants and address transportation plans in these cities. 

The NC SIP for the Charlotte/Rock Hill/Gastonia nonattainment area includes Reasonable 

Achievable Control Technology (RACT) for NOX for two facilities located in the nonattainment 

area: Philip Morris USA and Norandal USA. 

USEPA set a PM emissions standard for new heavy-duty engines of 0.01 grams per brakehorsepower-hour (g/bhp-hr), to take full effect for diesel engines in the 2007 model year. This 

rule also includes standards for NOX and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr 

and 0.14 g/ bhp-hr, respectively. These NOX and NMHC standards will be phased in together 

between 2007 and 2010, for diesel engines. Sulfur in diesel fuel must be lowered to enable 

modern pollution-control technology to be effective on these trucks and buses. USEPA required 

a 97 percent reduction in the sulfur content of highway diesel fuel -- from levels of 500 parts per 

million (low sulfur diesel) to 15 parts per million (ultra-low sulfur diesel). 

USEPA mobile rules include the Tier 2 fleet averaging program for on-road vehicles, modeled 

after the California LEV II standards. Manufacturers can produce vehicles with emissions 

ranging from relatively dirty to very clean, but the mix of vehicles a manufacturer sells each year 

must have average NOX emissions below a specified value. Tier 2 standards became effective in 

the 2005 model year. 
47-Virginia Regional Haze SIP 

USEPA has adopted new standards for emissions of NOX, hydrocarbons, and carbon monoxide 

from several groups of previously unregulated nonroad engines. Included in these are large 

industrial spark-ignition engines and recreational vehicles. Nonroad spark-ignition engines are 

those powered by gasoline, liquid propane gas, or compressed natural gas rated over 19 kilowatts 

(kW). These engines are used in commercial and industrial applications and include forklifts, 

electric generators, airport baggage transport vehicles, and a variety of farm and construction 

applications. Nonroad recreational vehicles include snowmobiles, off-highway motorcycles, and 

all-terrain vehicles. These rules were initially effective in 2004 and will be fully phased in by 

2012. 

The nonroad diesel rule sets standards that will reduce emissions by more than 90 percent from 

nonroad diesel equipment and will reduce sulfur levels by 99 percent from previous levels in 

nonroad diesel fuel starting in 2007. This step will apply to most nonroad diesel fuel in 2010 and 

to fuel used in locomotives and marine vessels in 2012. 

The applied MACT control efficiencies for industrial boiler/process heater/reciprocating internal 

combustion engines were 4 percent for SO2 and 40 percent for PM10 and PM2.5. However, as of 

June 08, 2007, the Industrial Boiler/Process Heater MACT standard was vacated. A mandate 

without a stay was issued July 30, 2007. As a result sources that were subject to the rule may 

need to file applications for permits containing MACT limits derived on a case-by-case basis 

within a time specified by USEPA or Virginia.

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 USEPA estimates 

to be small compared to the overall inventory.

Various point source MACTs and associated emission reductions for VOCs and PM were 

implemented. No reductions occurring prior to 2002 were counted. 

Seven localities in Virginia, along with VDEQ and USEPA Region III, entered into early action 

compacts (EACs). By approving the EACs, USEPA agreed to defer the effective date of the 

nonattainment designation for participating areas. Virginia worked with the USEPA, state and 

local governments, industry, environmental groups, and other interested parties to develop 

strategies to reduce precursors to ozone. As well as requiring NOX RACT on major sources of 

NOX emissions, the compacts contained many directionally correct programs implemented to 

reduce emissions from these areas. 

7.2.2. Additional State Programs to Reduce Emissions 

In addition to accounting for specific emission reductions due to ongoing air pollution programs 

as required under the regional haze regulation section 40 CFR 51.308(d)(3)(v)(A), states are also 

required to consider the air quality benefits of measures to mitigate the impacts of construction 

activities (40 CFR 51.308(d)(3)(v)(B)) and agricultural and forestry smoke management (40 

CFR 51.308(d)(3)(v) (E)). Section 7.10 provides more information on these activities. 

7.2.3. Projected 2009 and 2018 Base G2 Emissions Inventories 

The Base G inventories for 2009 and 2018 account for post-2002 emission reductions from 

promulgated and proposed federal, state, local, and site-specific control programs as of July 1, 
48-Virginia Regional Haze SIP 

2004. In general, emissions inventories were developed for 2018 using current control 

information in Virginia and growing the 2002 inventory using EGAS, MOBILE6, and IPM for 

EGUs. 

For EGUs, IPM results were adjusted based on state and local agency knowledge of planned 

emission controls at specific EGUs. These updates for Base G2 are documented in the 

MACTEC emissions inventory report entitled, Documentation of the Base G 2002 Base Year, 

2009, and 2018 Emission Inventories for Visibility Improvement State and Tribal Association of 

the Southeast (VISTAS) (Bernard and Sabo, 2007).

For non-EGUs, future year emissions were developed from recently updated growth and control 

data consistent with the data used in USEPA’s CAIR analyses, supplemented by state and local 

agency data and updated forecasts from the Department of Energy. 

Area source controls were estimated using known state level Stage I controls on gasoline 

dispensing facilities and open burning estimates, as well as controls used to project emissions for 

USEPA’s Heavy Duty Diesel rulemaking and for the CAIR rulemaking. 

Mobile source controls included local controls underlying the 2002 baseline inventory (vehicle 

emission inspection, Stage II vapor recovery, anti-tampering, etc.) with changes based on 

specific state input. Non-road control data and projections for 1996, 2010, 2015, and 2020 were 

obtained from The Clean Air Interstate Rule Emissions Inventory Technical Support Document

(USEPA, 2005), and straight line projections were used to estimate 2009 and 2018 levels. 

The following bar charts show expected decreases in emissions of SO2 and NOX across the 

VISTAS states from 2002 through 2018. (Similar charts for other visibility impairing pollutants 

are contained in Appendix H). Note that for SO2 emissions in particular, which are the largest 

contributors to haze, emissions from electric generating facilities are expected to decrease 

dramatically (70 percent) between 2002 and 2018. However, even after implementation of 

CAIR, EGU emissions are projected to remain the largest contributor to haze, comprising more 

than half of remaining SO2 emissions in every state. 

The tables below summarize the 2009 and 2018 Base G2 emissions inventory. The complete 

inventory and discussion of the methodology is contained in Appendix D. 
49-Virginia Regional Haze SIP 

Figure 7.2.3-1. Base G2 Annual SO2 for 2002, 2009, and 2018 VISTAS States 

Figure 7.2.3-2. Base G2 Annual NOX for 2002, 2009, and 2018 VISTAS States 

West Virginia

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

West Virginia

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

Alabama

Florida

Kentucky

Georgia

Mississippi

South Carolina

North Carolina

Tennessee

Virginia

100

200

300

400

500

600

700

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002

2009

2018

0

100

200

300

400

500

600

700

800

900

1,000

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

2002

2009

2018

0

100

200

300

400

500

600

700

800

900

1,000

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

Miscellaneous

Nonroad Onroad

Industrial Other Fuel Combustion EGU

2002

2009

2018
50-Virginia Regional Haze SIP 

Table 7.2.3-1. 2009 Virginia Base G2 Emissions Summary, tpy 

Sector VOC NOX PM2.5 PM10 NH3 SO2

Point 44,504 113,593 14,055 18,652 3,743 255,672 

Point-EGU 778 62,547 4,067 5,606 694 193,112 

Point-Non-EGU 43,726 51,046 9,988 13,046 3,049 62,560 

Area (including fires) 148,028 53,071 46,276 254,542 46,734 106,108 

On-Road Mobile 95,694 132,699 2,216 4,160 8,990 1,067 

Non-Road Mobile 57,009 54,993 7,136 7,510 53 1,707 

Biogenics 923,219 11,443 --- --- --- --- 

TOTAL 1,268,454 365,799 69,683 284,864 59,520 364,554 

Table 7.2.3-2. 2018 Virginia Base G2 Emissions Summary, tpy 

Sector VOC NOX PM2.5 PM10 NH3 SO2

Point 54,200 122,019 23,570 27,662 4,226 183,164 

Point-EGU 1,014 66,074 11,976 12,551 622 114,255 

Point-Non-EGU 53,186 55,945 11,594 15,111 3,604 68,909 

Area (including fires) 152,186 56,736 48,942 277,969 50,296 109,538 

On-Road Mobile 55,992 57,192 1,404 2,813 9,653 949 

Non-Road Mobile 49,052 40,393 5,891 6,208 61 507 

Biogenics 923,219 11,443 --- --- --- --- 

TOTAL 1,234,649 287,783 79,807 314,652 64,236 294,158 

7.2.4. Model Results for the 2018 Base G2 Inventory Compared to the Uniform 

Rate of Progress Glidepaths for Virginia Class I Areas 

Using 2000 through 2004 IMPROVE monitoring data, the dv values for the 20 percent best days 

in each year are averaged together, producing a single average dv value for the best days. 

Similarly, the dv values for the 20 percent worst days in each year are averaged together, 

producing a single average dv value for the worst days. 

Figures 7.2.4-1 and 7.2.4-2 illustrate the predicted visibility improvement by 2018 resulting from 

the Base G2 inventory that represents implementation of existing federal and state regulations, 

compared to the Uniform Rate of Progress glidepath for Shenandoah and James River Face. The 

red lines show the target natural condition in 2064 for the 20 percent worst days, and the 

incremental dv changes resulting from a uniform rate of progress between current and natural 

conditions in 2064, for average 20 percent worst visibility days in the 2000-2004 baseline period. 

The purple lines show the improvement expected from existing and planned emission controls 

during the period of the first long term strategy. Method 1 prediction refers to the recommended 

method of visibility improvement in USEPA guidance documents. 
51-Virginia Regional Haze SIP 

Note that at both Shenandoah and James River Face, visibility improvements on the 20 percent 

worst days are expected to be better than the uniform rate of progress glidepath by 2018. In fact, 

as illustrated in Figure 7.2.4-3, visibility improvements at all the VISTAS mountain Class I areas 

and most of the coastal Class I areas are projected to be better than the uniform rate of progress. 

In Figure 7.2.4-3 the percentage of the target reduction achieved for the Virginia Class I areas 

using the new IMPROVE equation is 155 to 175 percent. This means that the rate of 

improvement is 55 to 75 percent greater than the uniform rate of progress by 2018. 

The expected change in visibility at Shenandoah and James River Face between the 2000-2004 

baseline conditions on the 20 percent worst days, the 2018 projections for the G2a inventory, and 

natural conditions are illustrated in Figures 7.2.4-4 and 7.2.4-5 

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. Figures 7.2.4-6 and 7.2.4-7 

show graphically the progress expected on the 20 percent best visibility days using 2018 Base 

G2 emission reductions. As illustrated in Figure 7.2.4-6, visibility on the 20 percent best days is 

projected to improve in 2018 at all VISTAS Class I areas as a result of the 2018 Base G2a 

emissions reductions. In Figure 7.2.4-8 the percentage of the target achieved for the Virginia 

Class I areas is between -10 and -20 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). 

Uniform Rate of Reasonable Progress Glide Path

Shenandoah - 20% Data Days

Base G2A Projections, 12 km grid, New IMPROVE Equation

29.3

28.1

25.1

22.2

19.2

16.2

13.2

11.4

22.1

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

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

Figure 7.2.4-1. Uniform Rate of Progress for Shenandoah, 20% Worst Days 
52-Virginia Regional Haze SIP 

Uniform Rate of Reasonable Progress Glide Path

James River Face - 20% Data Days

Base G2A Projections, 12 km grid, New IMPROVE Equation

29.1

27.9

24.9

21.9

18.9

15.9

12.9

11.1

22.6

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

`

Figure 7.2.4-2. Uniform Rate of Progress for James River Face, 20% Worst Days 

Figure 7.2.4-3. Visibility Improvement, 20% Worst Days, 2018 Base G2a 

CMAQ Base G2a Visibility Improvement between 2002 and 2018

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%

200%

COHU

DOSOGRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVEROKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

CMAQ Base G2a Visibility Improvement between 2002 and 2018

0%

20%

40%

60%

80%

100%

120%

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200%

COHU

DOSOGRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVEROKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

0%

20%

40%

60%

80%

100%

120%

140%

160%

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200%

COHU

DOSOGRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVEROKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm
53-Virginia Regional Haze SIP 

Figure7.2.4-4. Shenandoah 20% Worst Visibility Days and Natural Conditions Visual Images 
54-Virginia Regional Haze SIP 

Figure7.2.4-5. James River Face 20% Worst Visibility Days and Natural Conditions Visual Images 
55-Virginia Regional Haze SIP 

Uniform Rate of Reasonable Progress Glide Path

Shenandoah - Best 20% Days

Base G2A Projections, 12 km grid, New IMPROVE Equation

8.8

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Condition (Best Days) Observation Method 1 Prediction

Baseline = 10.9 dV

Figure 7.2.4-6. 20% Best Days Rate of Progress for Shenandoah 

Uniform Rate of Reasonable Progress Glide Path

James River Face - Best 20% Days

Base G2A Projections, 12 km grid, New IMPROVE Equation

12.5

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

Baseline Condition (Best Days) Observation Method 1 Prediction

Baseline = 14.2 dV

Figure 7.2.4-7. 20% Best Days Rate of Progress for James River Face 
56-Virginia Regional Haze SIP 

Figure 7.2.4-8. Visibility Improvement, 20% Best Days, 2018 Base G2a 

7.3. Relative Contribution from International Emissions to Visibility Impairment 

in 2018 at VISTAS Class I areas 

Emissions from Mexico, Canada, Central America, Asia, and Africa contribute to PM2.5 loadings 

and visibility impairment at Class I areas in the continental United States. To evaluate the 

relative contribution of international emissions to visibility at Class I areas in the southeastern 

United States, VISTAS used a combination of modeling results from the global threedimensional chemical transport model (GEOS-Chem) and CMAQ. VISTAS used the GEOSChem global model to generate initial and boundary conditions for the CMAQ modeling domain. 

GEOS-Chem was run for the 2002 modeling year using a 4 x 5 degree horizontal grid resolution 

and a 3-hour temporal resolution. Because emissions were based on monthly averages, the 

model does not capture the episodic variability in emissions. The GEOS-Chem outputs were 

used to calculate initial and boundary conditions for the national CMAQ modeling domain. The 

national CMAQ domain included portions of Canada and Mexico, so emissions for these 

countries were included within the national CMAQ modeling domain or as part of the boundary 

conditions outside the national modeling domain, as appropriate. 

Two complementary methods were used to calculate the impact of international emissions at 

Class I areas. Because the international emissions inventory used in GEOS-CHEM did not 

distinguish between wildfires and anthropogenic fires, all international fire emissions were 

assumed to be wildfire, and the contributions attributable to international anthropogenic fires are 

underestimated in these projects. 

2018 Base G2a CMAQ Visibility Projection for 20% Best Days

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

COHU

DOSO

GRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVER

OKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

2018 Base G2a CMAQ Visibility Projection for 20% Best Days

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

COHU

DOSO

GRSM

JARI

LIGO

MACA

SHEN

SHRO

SIPS

CHAS

EVER

OKEF

ROMA

SAMA

SWAN

BRET

BRIG

CACR

HEGL

MING

UPBU

Percent of target reduction achieved

VISTAS non-VISTAS

CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm
57-Virginia Regional Haze SIP 

• International emissions as the difference between two GEOS-Chem runs - 

International emissions are represented by the difference between two GEOSChem runs. In the first run United States anthropogenic emissions were 

removed, and in the second run both United States and international 

anthropogenic emissions were removed. The difference represents international 

anthropogenic emissions, in the absence of United States anthropogenic emissions 

(e.g. compared to 2064 levels). Harvard University provided GEOS-Chem results 

to VISTAS for 2002 international contribution on 4 x 5 degree grid. Concurrent 

Harvard modeling for the Electric Power Research Institute (EPRI) provided 

GEOS-Chem results for 2001 international contribution on a 1 x 1 degree grid 

scale. 

• International emissions as the difference between two CMAQ 36-km simulations, 

both using 2018 Base F emissions and boundary conditions from GEOS-Chem - 

International emissions are represented by the difference between two CMAQ 36-

km simulations, both using 2018 Base F emissions and boundary conditions from 

GEOS-Chem. In the first CMAQ run, all global natural and anthropogenic 

emissions in 2018 are active. In the second CMAQ run, only global (United 

States and international) natural emissions are active. Here the impacts of 

international emissions are compared against 2018 conditions rather than natural 

background conditions. 

Separate from VISTAS, the Central Regional Air Planning Association (CENRAP) RPO used 

PM Source Apportionment Technology (PSAT) in the CAMx regional air quality model to 

calculate the impact of Canadian and Mexican emissions and boundary conditions on visibility at 

Class I areas in 2002. 

As illustrated in Figure 7.3-1 for annual average contributions to sulfate at VISTAS and 

neighboring Class I areas, the estimated international contributions are higher at Class I areas 

near the Canadian and Mexican borders and along the eastern coast. The estimated international 

contribution is higher using CMAQ and PSAT than in the GEOS-Chem runs because the grid 

scale is finer (more accurate dispersion of emissions) and because the background atmosphere 

includes loadings from current United States anthropogenic emissions (greater photochemical 

activity). Similar charts for nitrate and organic carbon mass, for impacts on 20 percent worst 

visibility days, and for impacts of international emissions on calculated light extinction are 

included in Appendix H. 

For the Virginia Class I areas, accounting for the international contribution does not change the 

conclusion that reductions of United States anthropogenic emissions will result in visibility 

improvement greater than the uniform rate of progress by 2018. As the atmosphere becomes 

closer to natural background conditions in the future, the incremental contribution from 

international emissions will become more important. The information is included in this SIP 

documentation to provide reference for future assessments of reasonable progress. 
58-Virginia Regional Haze SIP 

Figure 7.3-1. Estimated International Emissions Contributions 

In Figure 7.3-2, CMAQ projections of contributions from international emissions to PM mass on 

20 percent worst visibility days in 2002 at Shenandoah (SHEN) and James River Face (JARI) are 

compared to measured PM components at the site on those days. The stacked bar chart separates 

domestic and international attributes of mass on the 20 percent worst days. The amounts of 

international contributions at either the Shenandoah or James River Face are small compared to 

total emissions. 

7.4. Relative Contributions to Visibility Impairment: Pollutants, Source 

Categories, and Geographic Areas 

An important step toward identifying further reasonable progress measures is to identify the key 

pollutants contributing to visibility impairment at each Class I area. To understand the relative 

benefit of further reducing emissions from different pollutants, source sectors, and geographic 

areas, VISTAS engaged the Georgia Institute of Technology to perform emission sensitivity 

model runs using CMAQ. Emissions sensitivities were initially performed for three episodes 

representing winter and summer conditions: January 2002, July 2001, and July 2002. These 

runs used the initial 2018 projections inventory and considered 30 percent reductions from 

specific pollutants, source categories, and geographic areas. Emissions sensitivities were 

repeated using the 2009 Base D projection inventory and two, month-long episodes from 2002: 

June 1 through July 10 and November 19 through December 19. Emissions in 2009 were 

reduced by 30 percent for each pollutant sensitivity run. The pollutant contributions that were 

evaluated were: 

Transboundary Man-Made Impacts

0.0

0.2

0.4

0.6

0.8

1.0

1.2

BRIG

HEGL

CACR

MINGUPBU

BRETEVER

CHAS

SAMA

COHU

OKEF

ROMA

SIPS

SHRO

GRSM

LIGO

MACA

SWAN

JARI

DOSO

SHEN

(NH

4) 2SO

4 Conc. (

μg/m 3

)

GEOS_4x5 GEOS_1x1 CMAQ
59-Virginia Regional Haze SIP 

SHENANDOAH

Domestic and International Aerosol Mass by Species

20% Worst Days (2002)

0

5

10

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50

Domestic

International

Domestic

International

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International

2/28 5/26 5/29 6/4 6/10 6/13 6/19 6/25 7/1 7/4 7/16 7/19 7/22 7/31 8/3 8/12 8/21 8/24 8/27 9/11 9/14 9/17 9/29 10/2

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

JAMES RIVER FACE

Domestic and International Aerosol Mass by Species

20% Worst Days (2002)

0

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5/17 5/26 6/1 6/4 6/10 7/1 7/4 7/10 7/16 7/19 7/22 7/31 8/3 8/6 8/12 8/21 8/24 8/27 9/11 9/14 9/20 9/23 9/29 10/2

Mass (μg/m3

)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt

Figure 7.3-2. 2002 PM Concentrations: US Domestic Sources (left) and CMAQ International Contributions 

(right) 
60-Virginia Regional Haze SIP 

• SO2 from EGU sources in each VISTAS state, other RPOs in the VISTAS 12 km 

grid, and boundary conditions from outside the 12 km domain. 

• SO2 from non-EGU point sources in each VISTAS state, other RPOs, and 

boundary conditions. 

• NOX from ground level (on-road plus non-road plus area) sources in each 

VISTAS state and other RPOs. 

• NOX from point (EGU plus non-EGU) sources in each VISTAS state and other 

RPOs. 

• NH3 from all sources in VISTAS and other RPOs. 

• VOCs from anthropogenic and biogenic sources in the 12 km modeling domain. 

• Primary carbon from all ground level sources in each VISTAS state and other 

RPOs. 

• Primary carbon from all point sources in each VISTAS state and other RPOs. 

• Primary carbon from all fires in each VISTAS state and other RPOs. 

Results are shown in Figures 7.4-1 and 7.4-2 for the average of the 20 percent worst visibility 

days for Shenandoah and James River Face. To clarify the information in these figures, the 

abbreviations noted in the legend of each figure are spelled out in Table 7.4-1. 

Table 7.4-1. Visibility Response Modeling Table Abbreviations 

BIO Biogenic emissions ANTRO Anthropogenic emissions 

BCs Boundary Condition emissions MRPO Midwest Regional Planning Organization 

emissions 

M-VU MANE-VU emissions CEN CENRAP emissions 

VISTAS VISTAS emissions WV West Virginia emissions 

VA Virginia emissions TN Tennessee emissions 

SC South Caroline emissions NC North Carolina emissions 

MS Mississippi emissions KY Kentucky emissions 

GA Georgia emissions FL Florida emissions 

AL Alabama emissions SO2_EGU SO2 emissions from EGUs 

SO2_nonEGU SO2 emissions from non-EGUs NOX _Ground Ground level NOX emissions 

NOX_Point NOX emissions from point sources NH3 Ammonia emissions 

VOCs Volatile Organic Compound emissions PC_Ground Ground level primary carbon emissions 

PC_Point Point source primary carbon emissions PC_Fires Primary carbon emissions from fires 
61-Virginia Regional Haze SIP 

Shenandoah, VA (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

∆

Bext (Mm-1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 7.4-1. Visibility Responses: Shenandoah to 2009 Base D 30% Reductions 

James River Face, VA (20% Worst Days)

-18.00

-16.00

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

2.00

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

∆

Bext (Mm -1)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 7.4-2. Visibility Responses: James River Face to 2009 Base D 30% Reductions 
62-Virginia Regional Haze SIP 

As Figures 7.4-1 and 7.4-2 illustrate, the greatest visibility benefits on the 20 percent worst days 

for Shenandoah and James River Face are projected to result from further reducing SO2 from 

EGUs. At the VISTAS mountain Class I areas, such as James River Face, Shenandoah, Great 

Smoky Mountains, Linville Gorge, Joyce-Kilmer, Dolly Sods, Otter Creek, and Cohutta, benefits 

are projected from SO2 reductions from EGUs in several VISTAS states including Alabama, 

Georgia, Kentucky, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia. 

Contributions from other RPOs and from the boundary conditions are comparatively small, and 

the greatest benefits would likely be from further EGU reductions within the VISTAS states. 

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

industrial point sources. 

Because ammonium nitrate is a small contributor to PM2.5 mass and visibility impairment on the 

20 percent worst days at the mountain Class I areas, the benefits of reducing NOX and NH3

emissions at these sites are small. 

VOCs do contribute to visibility impairment, but as shown in the charts above, this contribution 

is from biogenic sources such as vegetative emissions. Controlling anthropogenic sources of 

VOC emissions has little if any visibility benefit at the Class I areas. Reducing primary carbon 

from point sources, ground level sources, or fires is projected to have small to no visibility 

benefit. This is consistent with the monitoring data that shows that most of measured organic 

carbon is secondary in origin and that primary carbon is only a small fraction of the total 

measured carbon (Appendix B). Reducing carbon from fires was not found to be effective 

because there was little fire activity at these sites on the days modeled in the sensitivity analyses. 

Note that these results from the emission sensitivity runs are consistent with the conclusions 

drawn from the 2000-2004 baseline monitoring data (see Section 2.4). The results indicate that 

sulfate is the dominant contributor to visibility impairment on the 20 percent worst days at all 

sites and that ammonium nitrate may be important for sites where the 20 percent worst days 

occur in the winter. Virginia concludes that reducing SO2 emissions from EGU and non-EGU 

point sources in the VISTAS states would have the greatest visibility benefits for the Virginia 

Class I areas.

7.5. Relative Contributions to Visibility Impairment: Geographic Areas of 

Influence for Virginia Class I Areas 

Once the key pollutants and source categories contributing to visibility impairment at each Class 

I area have been identified, it is necessary to focus on where the greatest contributing sources are 

located. SO2 emission reductions from EGU and non-EGU point sources in the VISTAS states 

have already been established as the greatest contributors to visibility impairment. To select the 

specific point sources that would be considered for each Class I area, the next step was to 

identify the specific geographic areas that most likely influence visibility in each Class I area and 

then to identify the major SO2 point sources located in those geographic areas. An SO2 Area of 

Influence (AoI) was defined for each Class I area to represent the geographic area containing 

sources that would likely have the greatest impact on visibility at that Class I area. All SO2 point 

sources within these AoI were identified and ranked by their 2018 Base G emissions. The 

following sections contain a broad overview of the steps in the AoI analyses. See Appendix H 

for a more detailed discussion of these analyses and plots for additional Class I areas. 
63-Virginia Regional Haze SIP 

7.5.1. Back Trajectory Analyses 

The first step was to generate meteorological back trajectories for IMPROVE monitoring sites in 

Virginia and neighboring Class I areas for the 2000-2004 baseline period. Back trajectory 

analyses use interpolated measured or modeled meteorological fields to estimate the most likely 

central path of air masses that arrive at a receptor at a given time. The method essentially 

follows a parcel of air backward in hourly steps for a specified length of time. Figure 7.5.1 is an 

example of a back trajectory analysis for Shenandoah for the 20 percent worst days in 2002. 

Figure 7.5.1. Example Back Trajectories for 2002 20% Worst Visibility Days, Shenandoah 

Trajectories were started at 100 meters and 500 meters above the surface and run backward from 

the site for 72 hours. These individual back trajectories for 20 percent worst days in 2002 were 

also useful in evaluating model performance for individual days at the Class I areas. 

7.5.2. Residence Time Plots 

The next step was to plot residence time for each Class I area using five years of back trajectories 

for the 20 percent worst visibility days in 2000-2004. Residence time is the frequency that winds 

pass over a specific geographic area on the path to a Class I area. Separate residence time plots 

were generated using trajectories with 100m and 500m start heights. As illustrated in Figure 

7.5.2, winds influencing Shenandoah on the 20 percent worst days come from all directions and 

there is no single predominant wind direction influencing the 20 percent worst visibility days. 
64-Virginia Regional Haze SIP 

Residence Time for 20% Worst Days in 2000-2004 

Shenandoah, VA

Figure 7.5.2. Example Residence Time Plot for 2000-2004 20% Worst Days 

7.5.3. SO2 Areas of Influence 

The next step was to develop sulfate extinction-weighted residence time plots to define the 

geographic area with highest probability of influencing the receptor on the 20 percent worst days 

in 2000-2004 that were dominated by sulfate. Each back trajectory was weighted by sulfate 

extinction for that day. This allows us to focus on the 20 percent worst days that are influenced 

by sulfate and place less importance on days influenced by organic carbon from fires. Sulfateweighted back trajectories for the 20 percent worst days were combined for five years of data. 

The resulting sulfate extinction-weighted residence time plots were used to define the geographic 

AoI for sources of SO2 emissions. In Figure 7.5.3 the area representing 10 percent or greater 

residence time is outlined in red and the area representing 5 percent or greater residence time is 

outlined in gray. The VISTAS states focused their analyses on the AoI defined by 5 percent or 

greater sulfate extinction-weighted residence time. 

7.5.4. Emissions Sources within SO2 Areas of Influence 

Residence time plots were then combined with geographically-gridded emissions data based on 

the 2002 baseline and 2018 Base G emissions inventories. Plots were generated for the AoI 

defined by trajectories with 100 meter and 500 meter start heights. As a way of incorporating the 

effects of transport, deposition, and chemical transformation of point source emissions along the 

path of the trajectories, these data were weighted by 1/d, where d was calculated as the distance, 

in kilometers, between the center of the grid cell in which a source is located and the center of 

the grid cell in which the IMPROVE monitor is located. The distance-weighted point source 

SO2 emissions are then combined with the gridded extinction-weighted back-trajectory residence 

times at a spatial resolution of 36 km. 
65-Virginia Regional Haze SIP 

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%

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

Figure 7.5.3. Shenandoah SO2 AoI for SO4 Extinction-Weighted Residence Time for 2000-2004 20% Worst Days 

The final step was to combine the residence times and gridded emissions data in plots and data 

sets. The distance weighted (1/d) gridded point source SO2 emissions were multiplied by the 

total extinction-weighted back-trajectory residence times on a grid cell by grid cell basis. These 

results were then normalized by the domain-wide total and displayed as a percentage. The 

analysis was done using both the 2002 and 2018 base year inventories. 

Figure 7.5.4-1 illustrates the result of this final analysis step for the 2002 and 2018 distanceweighted, gridded emissions, sulfate extinction-weighted, residence time plots for Shenandoah. 

These maps help visualize where the emissions reductions will be occurring between 2002 and 

2018. The change in SO2 emissions between 2002 and 2018 can be seen by comparing 

emissions source strengths in the two plots. Note that the emissions from each source are 

normalized by the total emissions in the domain. Sources that reduce SO2 emissions by 2018 

will show a lower contribution to emissions in the domain. On the 2018 map, the grid cells with 

these sources will show a lighter color gradient than on the 2002 map. Because the total 

emissions in the domain are smaller in 2018, a source that does not change emissions between 

2002 and 2018 may actually appear to increase in importance in 2018 compared to 2002. 
66-Virginia Regional Haze SIP 

2002 vs 2018 SO2 Emissions weighted by Residence Time

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%.

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

2002 SO2 emissions 2018 SO2 emissions

Figure 7.5.4-1. Shenandoah 2002 and 2018 SO2 Distanc- Weighted Emissions, SO4 Extinction-Weighted 

Residence Time Plots. 

Figure 7.5.4-2 illustrates gridded SO2 distance-weighted emissions, sulfate extinction-weighted 

residence time plots for 2018 emissions for James River Face. This plot illustrates the relative 

importance of Virginia sources of SO2 compared to sources in neighboring states. Additional 

analyses, including 2002 and 2018 distance-weighted emissions residence time plots for the 

Class I areas in Virginia and neighboring states are contained in Appendix H. These analyses 

serve as the basis for consultation among the VISTAS states. 

Finally, Tables 7.5.4-1 through 7.5.4-3 show, in tabular form, the relative contributions of point 

source SO2 emissions from nearby states to the Virginia Class I areas and the North Caroline 

Class I areas (Linville Gorge, Swanquarter, Joyce Kilmer, Shining Rock, and Great Smoky 

Mountains). A table for other Class I areas in nearby states is also included for Dolly Sods 

(WV), Brigantine (NJ), and Mammoth Cave (KY). These data are not results from a source 

apportionment modeling exercise. These numbers represent a relative metric based on the 

magnitude of emissions from a source, its distance to the Class I areas of concern, and the sulfate 

extinction-weighted residence time plots developed using back trajectories. 
67-Virginia Regional Haze SIP 

Max Value = 34%

Comparison 2002 vs 2018 SO2 Emissions * Residence Time 

Using 100 m Start Height – James River, VA

2002 SO2 emissions 2018 SO2 emissions

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

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

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

Max Value = 12%

Figure 7.5.4-2. James River Face 2002 and 2018 SO2 Distance Weighted Emissions, SO4 Extinction-Weighted 

Residence Time Plot 

Table 7.5.4-1. State 2018 SO2 Point Source Contribution to Virginia Class I 

Areas 

Virginia Class I Areas State 

Shenandoah James River Face 

Washington D.C. 0.06% 0.36% 

Delaware 1.46% 0.59% 

Kentucky 1.10% 2.02% 

Maryland 23.99% 3.12% 

New York 0.19% --- 

North Carolina 3.97% 9.31% 

Ohio 4.63% 3.60% 

Pennsylvania 6.11% 1.59% 

South Carolina --- 0.89% 

Tennessee 0.36% 1.69% 

Virginia 38.33% 62.08% 

West Virginia 19.85% 15.10% 
68-Virginia Regional Haze SIP 

Table 7.5.4-2. State 2018 SO2 Point Source Contribution to North Carolina Class I 

Areas 

North Carolina Class I Areas 

State Great Smoky 

Mountains 

Shining 

Rock 

Linville 

Gorge Swanquarter Joyce Kilmer 

Alabama 3.1% 1.84% 1.35% ---- 6.53% 

Delaware --- --- --- 2.83% --- 

Florida --- --- --- 2.35% --- 

Georgia 7.7% 7.22% 1.98% 3.34% 20.46% 

Kentucky 1.0% 0.81% 0.90% 0.10% 1.38% 

Maryland --- --- --- 1.34% --- 

New Jersey --- --- --- 1.10% --- 

North Carolina 7.4% 58.84% 34.75% 58.69% 9.08% 

Ohio 0.9% 0.64% 1.76% --- --- 

Pennsylvania --- --- --- 0.50% --- 

South Carolina 2.4% 14.89% 3.93% 15.35% 5.14% 

Tennessee 74.5% 12.19% 36.28% --- 55.87% 

Virginia 2.3% 2.95% 16.52% 13.78% 1.53% 

West Virginia 0.5% 0.63% 2.52% 0.63% --- 

Table 7.5.4-3. State 2018 SO2 Point Source Contribution to Other Class I 

Areas 

Class I Areas 

State 

Dolly Sods, WV Brigantine, NJ Mammoth Cave, KY 

Washington D.C. --- 0.05% --- 

Alabama --- --- 4.33% 

Connecticut --- 0.05% --- 

Delaware --- 27.83% --- 

Georgia --- --- 1.79% 

Illinois --- --- 0.53% 

Indiana --- --- 21.22% 

Kentucky 1.34% --- 53.60% 

Maryland 11.81% 7.67% --- 

Mississippi --- --- 0.04% 

Missouri --- --- 0.53% 
69-Virginia Regional Haze SIP 

Table 7.5.4-3. State 2018 SO2 Point Source Contribution to Other Class I 

Areas 

Class I Areas 

State 

Dolly Sods, WV Brigantine, NJ Mammoth Cave, KY 

New Jersey --- 40.11% --- 

New York --- 0.56% --- 

North Carolina 0.80% 0.75% --- 

Ohio 7.37% 0.52% 3.95% 

Pennsylvania 5.26% 13.63% --- 

South Carolina 0.09% --- --- 

Tennessee 1.25% --- 13.46% 

Virginia 5.73% 7.90% --- 

West Virginia 66.35% 0.94% 0.54% 

7.5.5. Specific Source Types in the Areas of Influence for Virginia Class I Areas 

The next step in the analysis was to review the emissions inventories to determine the source 

categories, as well as specific sources, found to have the greatest impact on visibility in 

Shenandoah and James River Face. Lists of SO2 point sources within the AoI for each Class I 

area were developed using the most current (BaseG) VISTAS 2002 base year and 2018 future 

year emissions. For this purpose the AoI was defined as the counties with maximum sulfate 

extinction-weighted residence times greater than five percent. For SO2 sources within each AoI, 

the following attributes were defined for each individual unit: 

• State, county, source (plant), and industry identification codes. 

• SO2 emissions for 2002 and 2018. 

• 2018 control efficiency. 

• Distance to Class I areas (defined by centroid of the Class I area). 

• Emissions divided by distance (Q/d), a metric that accounts for the dispersion of 

emissions over distance. 

• Maximum sulfate extinction weighted residence time (RTmax). 

The review was conducted in a top-down fashion, starting with an analysis of the major source 

categories in each SO2 AoI to determine which major categories had the highest residual 

contribution to the area in 2018. It was also important to identify reductions that are projected to 

occur between 2002 and 2018 within each category or at specific units. This allowed VISTAS 

states to determine if certain source categories or units that had yet to be controlled under the 

future year base case had the potential for reduction. Once the highest source types were 

identified, subcategories within those source types were reviewed. The contributions from major 

source categories to the 2018 Base G2 inventory for the SO2 AoI for the Virginia Class I areas 

are listed in Tables 7.5.5-1 and 7.5.5-2. 
70-Virginia Regional Haze SIP 

Table 7.5.5-1. 2018 Emissions Contributions from Source Categories, Shenandoah Area of Influence 

Tier VOC NOX CO SO2 PM10-Pri PM2.5-Pri NH3

Fuel Combustion Electric Utilities 1% 26% 1% 53% 14% 25% 1% 

Fuel Combustion Industrial 1% 17% 2% 28% 5% 6% 0% 

Fuel Combustion Other 7% 9% 4% 6% 7% 14% 1% 

Chem & Allied Product Mfg 2% 1% 1% 2% 1% 1% 1% 

Metals Processing 1% 2% 4% 4% 3% 6% 0% 

Petroleum & Related Industries 1% 0% 0% 2% 0% 0% 0% 

Other Industrial Processes 3% 6% 0% 5% 9% 10% 1% 

Solvent Utilization 39% 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% 20% 45% 0% 2% 2% 20% 

Off-Highway 16% 18% 37% 1% 3% 7% 0% 

Miscellaneous 0% 0% 1% 0% 50% 18% 85% 

Table 7.5.5-2. 2018 Emissions Contributions from Source Categories, James River Face Area of Influence 

Tier VOC NOX CO SO2 PM10-Pri PM2.5-Pri NH3

Fuel Combustion Electric Utilities 1% 26% 1% 53% 15% 27% 1% 

Fuel Combustion Industrial 1% 17% 2% 28% 4% 6% 0% 

Fuel Combustion Other 7% 8% 4% 6% 7% 14% 1% 

Chem & Allied Product Mfg 2% 1% 1% 2% 1% 1% 1% 

Metals Processing 1% 2% 4% 4% 3% 5% 0% 

Petroleum & Related Industries 0% 0% 0% 2% 0% 0% 0% 

Other Industrial Processes 4% 5% 0% 4% 9% 11% 1% 

Solvent Utilization 39% 1% 0% 0% 0% 1% 0% 

Storage & Transport 7% 0% 0% 0% 0% 1% 0% 

Waste Disposal & Recycling 4% 2% 4% 0% 5% 9% 0% 

Highway Vehicles 19% 21% 47% 0% 2% 2% 11% 

Off-Highway 14% 17% 36% 1% 3% 5% 0% 

Miscellaneous 1% 0% 2% 0% 50% 18% 85% 

These tables indicate that for Virginia Class I areas, EGUs and industrial boilers are the two 

major sources categories contributing to 2018 SO2 emissions in the AoI. Together these two 

source categories contribute greater than 80 percent of the 2018 SO2 emissions for the AoI for 

the Virginia Class I areas. 
71-Virginia Regional Haze SIP 

These tables can also be used to evaluate the major source categories contributing to emissions 

of NOX, NH3, and PM emissions in 2018. For instance, highway vehicles and off road vehicles 

are major sources of NOX emissions, in addition to electric utilities and industrial boilers. The 

source category “miscellaneous” (which includes agricultural sources and fires) is the major 

contributor to NH3 and primary PM. The emissions sensitivities discussed in Section 7.4 

indicated very small benefits from controlling NOX, NH3, and primary PM emissions at the 

Virginia Class I areas, but if these emissions were of concern, different source categories would 

need to be addressed. 

The contributions to SO2 emissions in 2018 from the three highest source categories, electric 

utilities, industrial boilers, and other fuel combustion, have been further broken out into 

subcategories. Table 7.5.5-3 lists subcategories for the AoI for the Virginia Class I areas. 

Within electric utilities, all the SO2 emissions are attributable to coal fired power plants. Within 

industrial boilers, most emissions are attributable to coal fired boilers with lesser contributions 

from oil and gas boilers. Commercial and institutional coal and oil boilers have smaller 

contributions. 

Table 7.5.5-3. Annual 2018 SO2 Emissions Percentage within Areas of Influence 

Tier Shenandoah James River Face 

Fuel Combustion Electrical Utility – Coal 51% 51% 

Fuel Combustion Electric Utility-Oil 1% 1% 

Fuel Combustion Electric Utility-Gas 0% 0% 

Fuel Combustion Electric Utility-Other 0% 0% 

Fuel Combustion Electric Utility-IC 1% 1% 

Fuel Combustion Industrial-Coal 22% 23% 

Fuel Combustion Industrial-Oil 3% 3% 

Fuel Combustion Industrial-Gas 2% 2% 

Fuel Combustion Industrial-Other 1% 1% 

Fuel Combustion Industrial-IC 0% 0% 

Fuel Combustion Other-Commercial Institutional Coal 2% 2% 

Fuel Combustion Other-Commercial/Institutional Oil 1% 1% 

Fuel Combustion Other-Commercial/Institutional Gas 0% 0% 

Fuel Combustion Other-Misc Fuel Combustion except Residential 0% 0% 

Fuel Combustion Other-Residential Wood 0% 0% 

Fuel Combustion Other-Residential Other 2% 2% 

These analyses indicate that Virginia should consider what additional control measures for 

electric utilities and industrial boilers are reasonable. The lists of individual sources are also 

being used to determine if individual sources in other sources categories are major contributors 

to SO2 emissions in the AoI. 
72-Virginia Regional Haze SIP 

7.6. Evaluating the Four Statutory Factors for Specific SO2 Emissions Sources in 

Each Area of Influence 

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

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

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

assigned future year control technology from IPM forecasting, from state modifications made to 

EGU assumptions, and from control efficiency tables for non-EGU point sources. 

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

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

control measures. 

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

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

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

assumptions. 

For non-EGUs, VISTAS used USEPA’s AirControlNET 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 USEPA emissions inventories. The system 

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

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

technology's control efficiency, and calculated emission reductions for that source, but also 

estimates of 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 domain. 

For the sources within the AOIs for each Virginia Class I area, the master list of incremental 

control measures was sorted to determine the costs of incremental control measures. These data 

were combined in a master spreadsheet with the distance from the emission release point to the 

Class I area IMPROVE monitor (in km), the 2018 residual emissions and distance (Q/d) or 

squared distance (Q/d2

), and the normalized 2018 SO2 point source emissions times distanceweighted residence time (RTMax) values for the county in which the emission release point was 

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

statutory factors for reasonable further progress. 

The regional haze regulation 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. 
73-Virginia Regional Haze SIP 

7.6.1. Cost of Compliance 

As defined in Section 7.5.5, coal-fired electric utilities and coal-fired industrial boilers were the 

largest source categories contributing to SO2 in 2018 in the AoI defined for the Virginia Class I 

areas. Industrial boilers using oil and commercial and institutional boilers using coal or oil had 

small contributions to SO2 in 2018. 

Emissions of SO2 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 post-combustion 

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 United States. Switching to 

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

emissions with low impact to boiler performance. While sub-bituminous coal has a lower sulfur 

content than bituminous coal, it also has a lower heat rate and so more coal has to be burned to 

generate the same energy output. For boilers that are designed for bituminous coal, only a small 

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

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

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

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

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

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

is passed through an absorbent for SO2 (generally limestone or lime) in a wet scrubber, a dry 

scrubber, or a spray dryer. A calcium sulfate by-product is produced that may be further 

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

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

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

size, type, and facility siting considerations. 

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

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

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

for such installations. 

7.6.2. Time Necessary for Compliance 

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

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

post-combustion controls will require three 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. 

7.6.3. Energy and Non-Air Environmental Impacts 

Switching to lower sulfur fuel or installing post-combustion controls may reduce boiler heat rate 

and energy output. Scrubbers and spray dryers will require additional safeguards for fuel 

handling and waste handling systems to avoid additional non-air environmental impacts such as 
74-Virginia Regional Haze SIP 

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

be considered specific to individual sources. Carbon dioxide is emitted as a by-product of flue 

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

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

strategies. 

7.6.4. Remaining Useful Life 

The remaining useful life of a process is specific to the unit for which controls are considered. 

7.7. Which Control Measures Represent Reasonable Progress for Individual 

Sources? 

The following summarizes the process for determining reasonable progress for Virginia sources. 

For a detailed discussion of the reasonable progress assessments for all units’ contributions 

greater than 1 percent to any Class I area in Virginia or in neighboring states, see Appendix H. 

7.7.1. 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 determined that controlling SO2 emissions was the appropriate step in addressing 

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

findings of SAMI, which confirmed that sulfate particles account for the greatest portion of the 

haze affecting Class I areas in the Southern Appalachian region and that these sulfates were 

produced in large part from coal combustion SO2 emissions. 

7.7.2. 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 

EGU and non-EGU point sources of SO2 emissions. 

7.7.3. Step 3: Determine if the Clean Air Interstate Rule (CAIR) is sufficient for 

reasonable progress for subject EGU’s 

The coal-fired EGUs in Virginia are expected to reduce SO2 emissions by approximately 50 

percent between 2002 and 2018 due to the installation of SO2 controls, the use of very low sulfur 

fuels, or fuel switching. Projected SO2 emission reductions are the result of CAIR, which relies 

on trading and the use of banked Title IV allowances, and the requirements of the AEP Eastern 

System Consent Agreement. CAIR emission reductions are not directly enforceable, and 

emission reduction estimates are based on information provided by facility owners as well as 

permit applications and other documents submitted to Virginia. Virginia intends to re-evaluate 

the IPM predictions of SO2 for CAIR at the time of the first required periodic report in 2012 to 

ensure that the predicted reductions are indeed taking place where they are expected and needed. 

Based on the confirmed CAIR controls and the reductions stemming from the AEP Consent 

Agreement, Virginia believes that these emissions reductions, coupled with the expected 2018 

visibility improvement at Virginia Class I areas, constitutes reasonable progress for this source 

category. However, should data from IMPROVE monitors indicate that the expected visibility 

improvements are not being achieved either at Virginia Class I areas or at Class I areas outside of 

Virginia upon which Virginia facilities have an impact, the determination that CAIR is sufficient 
75-Virginia Regional Haze SIP 

to meet reasonable progress requirements for EGUs may be re-examined prior to 2018, for 

instance in 2012 when the progress report is scheduled to be submitted. 

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

Virginia has calculated the fractional contribution from all emission units within the SO2 AoI for 

a given Class I area and identified the EGUs and non-EGUs with a contribution of 1 percent or 

more to the visibility impairment at that area. This methodology is not an exact quantification of 

the source-by-source contributions to visibility impairment on the 20 percent worst visibility 

days at a specific Class I area. Rather, this analysis is a relative metric used to infer this 

determination. Emission units located within Virginia with a contribution of one percent or more 

to the visibility impairment of that Class I area were identified. For several of these Class I 

areas, including but not limited to Brigantine, Great Smoky Mountains, Joyce Kilmer, and 

Shining Rock, no Virginia units were identified with a contribution of at least 1 percent to 

visibility impairment with the AoI. 

The cutoff of 1 percent was chosen because this cutoff created a practical listing of facilities to 

examine for reasonable progress but also addressed almost half of the calculated percent 

visibility contribution to the Class I areas. For the Virginia Class I areas, the breakout of points 

or units versus the calculated percent contributions are shown in Table 7.7.4-1. 

Table 7.7.4-1. Emissions Points and Percent Contributions 

Visibility 

Contribution Cutoff 

Total # of Points for 

RP review 

Total % contribution 

Reviewed 

Shenandoah 

≥ 1% 18 44.3% 

≥0.1% and < 1% 167 49% 

<0.1% 147 6.7% 

James River Face 

≥ 1% 12 49.9% 

≥0.1% and < 1% 152 41.2% 

<0.1% 172 8.9% 

Since resource constraints do not allow for the unit-by-unit review of hundreds of emissions 

points, using a 1 percent cutoff to create the list of facilities subject to a reasonable progress 

review was necessary to allow attention to be focused on those units responsible for the largest 

portion of calculated visibility impairment. 

Table 7.7.4-2 shows facilities and units in Virginia that have a calculated visibility impact of at 

least 1 percent on any Class I area. Table 7.7.4-2 provides two sets of 2018 SO2 emissions data. 

The first set was used as part of the G2 inventory and was used to calculate the expected 

visibility impact. The second set of updated 2018 SO2 emissions data in this table reflects new 

information received after the G2 inventory effort, including expected BART reductions and 

limitations imposed due to permitting, shutdowns, and enforcement proceedings 
76-Virginia Regional Haze SIP 

Table 7.7.4-3 shows facilities and units in other states calculated to have at least a 1 percent 

impact on James River Face and Shenandoah. Table 7.7.4-3 also shows information garnered 

from other states during consultation in regards to future emissions at these out-of-state facilities. 

7.7.5. Step 5: Evaluate the four factors 

Each emissions 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 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, Virginia believes it is not 

equitable to require non-EGUs to bear a greater economic burden than EGUs for a given control 

strategy. In other words, it is not 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, Virginia reviewed 

USEPA’s CAIR analysis. (See USEPA CAIR analysis at 70 FR 25201-25208, May 12, 2005.) 

The CAIR analysis is a recent and comprehensive review of the cost-effectiveness of EGU SO2

controls, making it appropriate to consider as a benchmark in determining a reasonable costeffectiveness for SO2 control for purposes of the reasonable progress assessment. 

In the CAIR preamble, USEPA 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 $1,110 per ton for years 2010 and 2015, respectively. 
77-Virginia Regional Haze SIP 

Table 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1% 

Data used for Contribution Calculation Updated 

County Plant ID Plant Name Point ID Unit Description 2002 SO2

tpy 

2018 SO2

tpy 

% 

Contribution 

2018 SO2

tpy 

Swanquarter Isle of Wight 51-093- 00006 International Paper Company 4 #7 Boiler 543 mmbtu/hr burning coal, #6 oil, wood, and TRS gases 3,720 4,299 1.19% 3,814 

TwS

a 

em

ErepinthP

Linville Gorge Russell 51-167- 00003 AEP-Clinch River 1 238 MW EGU coal fired using approximately 0.8% S coal. 8,158 10,014 4% Russell 51-167- 00003 AEP-Clinch River 2 238 MW EGU coal fired using approximately 0.8% S coal. 8,115 10,131 4% Russell 51-167- 00003 AEP-Clinch River 3 238 MW EGU coal fired using approximately 0.8% S coal. 8,804 9,911 4% 

16,300 

Te

tpAT

Dolly Sods City of Covington 

51-580-0003 MeadWestvaco 25 

Combined stack for #6 boiler, 550 mmbtu/hr firing coal; #7 boiler, 440 mmbtu/hr firing coal, bark, and wood; #8 boiler 580 mmbtu/hr firing coal, bark, and wood; and #9 boiler 807 mmbtu/hr firing coal 

8,552 9,997 1.1% 6,817 

Ustrudto euS7restastredoppdfr

S
78-Virginia Regional Haze SIP 

Table 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1% 

Data used for Contribution Calculation Updated 

County Plant ID Plant Name Point ID Unit Description 2002 SO2

tpy 

2018 SO2

tpy 

% 

Contribution 

2018 SO2

tpy 

James River Face City of Covington 

51-580-0003 MeadWestvaco 25 

Combined stack for #6 boiler, 550 mmbtu/hr firing coal; #7 boiler, 440 mmbtu/hr firing coal, bark, and wood; #8 boiler 580 mmbtu/hr firing coal, bark, and wood; and #9 boiler 807 mmbtu/hr firing coal 

8,552 9,997 18.4% 6,817 

S

Botetourt 51-023- 0003 Roanoke Cement Company 22 #5 kiln: 184 tph preheater/precalciner kiln 2,885 3,976 7.3% 3,104 F

3

Bedford 51-019- 0003 Georgia Pacific Big Island 1 #4 Boiler, 284 mmbtu/hr coal/#2 oil fired boiler. 1,090 1,223 5.5% 219 

Tincfo

7

Rockbridge 51-163- 0001 Mohawk Industries – Lees Carpet 7 155 mmbtu/hr coal fired boiler with a 1% S content limitation 293 291 4% --- NGiles 51-071- 0002 AEP-Glyn Lyn 3 238 MW coal fired EGU 7,488 9,981 3.6% --- NGiles 51-071- 0004 Celanese Acetate LLC 1 

Stack consists of Boiler #1, 91 mmbtu/hr; Boiler #3, 184 mmbtu/hr; Boiler #5, 246 mmbtu/hr; Boiler #2, 91 mmbtu/hr; Boiler #4, 184 mmbtu/hr; Boiler #6 246 mmbtu/hr; and Boiler #7 322 mmbtu/hr burning coal with about a 1.1% S content. 

6,560 6,510 2.5% --- 

N

Fluvanna 51-065- 0001 Dominion- Bremo 2 185 MW coal fired EGU 7,993 6,253 2.2% --- 

TSaaEcrePA m

thS
79-Virginia Regional Haze SIP 

Table 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1% 

Data used for Contribution Calculation Updated 

County Plant ID Plant Name Point ID Unit Description 2002 SO2

tpy 

2018 SO2

tpy 

% 

Contribution 

2018 SO2

tpy 

Bedford 51-019- 0003 Georgia Pacific Big Island 2 #5 Boiler, 339 mmbtu/hr coal, wood, wood/paper waste. 251 286 1.3% --- 

Na thlibam7fao

pefu

thli

Shenandoah Fluvanna 51-065- 0001 Dominion- Bremo 2 185 MW coal fired EGU 7,993 6,253 8.9% --- 

TSaaEcrePA m

thS

Prince William 

51-153-0002 

DominionPossum Point 5 786 MW residual oil fired EGU burning 0.7% S oil 4,368 6,100 4.9% --- N

Fluvanna 51-065- 0001 Dominion- Bremo 1 69 MW coal fired EGU 4,371 2,614 3.7% --- SChesterfield 51-041- 0002 Dominion- Chesterfield 8 694 MW coal fired EGU 38,088 3,633 2.4% --- 

Nha b4

Chesterfield 51-041- 0002 Dominion- Chesterfield 6 359 MW coal fired EGU 19,129 1,561 1% --- 

Nhth2Cb
80-Virginia Regional Haze SIP 

Table 7.7.4-3: Units Outside Virginia with Visibility Impairment Contributions of at least 1% Virginia Class I Areas 

Data used for Contribution Calculation Up

State County Plant ID Plant Name Point ID Plant Description 2002 SO2

tpy 

2018 SO2

tpy 

% 

Contribut

ion 

2018 SO

tpy 

James River Face 

003 39,570 10,821 1.79% --- 

WV Putnam 002 27,651 6,694 1.11% --- 54-079- 0006 Appalachian Power –John E. Amos Plant 

001 

Electrical Services 

30,015 6,613 1.09% --- 

NC Rockingham 37-157- 00015 Duke Energy Corporation – Dan River G-21 Electrical Services 2,637 3,464 1.19% --- 

Shenandoah 

1 10,160 9,610 4.14% ~961 

MD Alleghany 24-001- 0011 Westvaco Luke Plant 2 Paper Mill 8,923 8,441 3.64% --- 

28 1,506 2,652 1.74% --- 

MD Frederick 24-021- 0005 Eastalco Aluminum 29 Primary Production of Al 1,506 2,652 1.74% --- MD Washington 24-043- 0005 Allegheny-R. Paul Smith Plant 2 Electrical Services 3,770 2,568 1.57% 644 

14 37,757 3,037 1.48% --- 

MD Charles 24-017- 0014 Mirant Mid-Atlantic LLC 15 Electrical Services 32,587 2,987 1.45% --- 
81-Virginia Regional Haze SIP 

Table 7.7.4-3: Units Outside Virginia with Visibility Impairment Contributions of at least 1% Virginia Class I Areas 

Data used for Contribution Calculation Up

State County Plant ID Plant Name Point ID Plant Description 2002 SO2

tpy 

2018 SO2

tpy 

% 

Contribut

ion 

2018 SO

tpy 

WV Berkeley 54-003- 0006 Capitol Cement Corporation 010 Hydraulic Cement 1,247 1,717 1.28% --- 

001 8,817 3,191 1.18% 

WV Grant 002 9,572 3,191 1.18% 54-023- 0003 Mount Storm Power Plant 

003 

Electrical Services 

2,779 2,923 1.08% 

--- 

001 2,582 5,998 1.04% 

WV Harrison 002 2,731 5,954 1.03% 54-033- 0015 Monongahela Power Company- Harrison 

003 

Electrical Services 

3,355 5,908 1.03% 

--- 
82-Virginia Regional Haze SIP 

USEPA 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 lists of controls included in the 

NPR of the average and marginal cost 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. 

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 costeffective 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.epa.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 lb/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

Contorl 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 or 0.1lb/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. 
83-Virginia Regional Haze SIP 

Table IV-4 provides the marginal cost per ton of recent State and regional 

decisions for annual SO2 controls.” 

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 training 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 costs 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 IV-2 shows that the “knee” in the 2015 marginal cost-effectiveness 

curve also appears to occur at about $2,000 per ton of SO2 . . . 
84-Virginia Regional Haze SIP 

After review of USEPA’s CAIR cost analyses, Virginia 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, USEPA found a consistent marginal cost for both years at $2,000 per ton. 

These values establish benchmarks against which cost effectiveness may be evaluated for 

reasonable progress in this round of regional haze planning. 

Other factors may also be considered, as documented in the USEPA guidance memorandum 

Guidance for Setting Reasonable Progress Goals Under the Regional Haze Program (USEPA, 

2007). This document makes the following points regarding setting reasonable progress goals: 

• States may reasonably defer reductions to later planning periods in order to 

maintain a consistent glidepath toward the long-term goal (Page 1-4). 
85-Virginia Regional Haze SIP 

• The significant emission reductions resulting from BART and other CAA 

programs for some states may be all that is necessary to achieve reasonable 

progress in the first planning period (Page 4-1, Page 5-1). 

• States may reasonably conclude that BART determinations satisfy the reasonable 

progress goal requirements for source reviews in the first regional haze planning 

period and that additional emission controls are not necessary for these units in 

the first round of regional haze planning (Page 4-3, Page 5-1). 

• Average and incremental costs should be evaluated, and cost estimates should be 

based on USEPA’s Air Pollution Control Cost Manual (USEPA, 2002). Simple 

cost effectiveness estimates based on a dollar-per-ton calculation may not be as 

meaningful as a dollar-per-deciview calculation (Page 5-2). 

7.7.5.1. EGU Unit Information and Conclusions 

The following units in Table 7.7.5.1-1 are EGUs subject to the CAIR regulation for SO2. As 

noted above, currently CAIR requirements are considered adequate for reasonable progress 

toward visibility improvements. However, should data from IMPROVE monitors indicate that 

the expected visibility improvements are not being achieved either at Virginia Class I areas or at 

Class I areas outside of Virginia upon which Virginia facilities have an impact, this 

determination may be re-examined prior to 2018, for instance in 2012 when the progress report is 

scheduled to be submitted. 

7.7.5.2. Non-EGU Information and Conclusions 

In the following review of non-EGU control information, in many instances controls were 

deemed to not be cost-effective. In cases where no cost effective controls could be identified, the 

three remaining statutory factors of time necessary for compliance, the energy and non-air 

quality environmental impacts of compliance, and the remaining useful life of the emissions unit, 

were deemed not applicable since there were no cost effective controls to evaluate within the 

framework of these three requirements. 

7.7.5.2.1. International Paper Company: 

Point ID #4 was identified in the Swanquarter AoI as having a visibility impairment contribution 

of 1.19 percent in 2018, based on an estimated 2018 emissions rate of 4,299 tpy SO2. Point ID 

#4 is the facility’s #7 power boiler, which has a maximum heat input of 543 mmbtu/hr and burns 

coal, #6 oil, wood, and total reduced sulfur (TRS) gases. It is equipped with a mechanical dust 

collector and an ESP. Coal is the predominant fuel, and the coal burned generally has a sulfur 

(S) content of 0.8 percent by weight. The incineration of TRS gases creates much of the SO2

emitted from this unit. 

Since 2002, the facility has installed a TRS scrubber on the non-condensable gases being 

incinerated in this unit. This TRS scrubber reduces the SO2 emissions associated with 

incineration by 200-300 tpy. Additionally, the facility has taken a facility-wide SO2 cap of 7,980 

tpy, which is significantly beneath the 2002 total facility-wide annual SO2 emissions of 8,693 tpy 

and the estimated 2018 SO2 emissions for the entire facility of 10,006 tpy. To help reduce 

emissions beneath this cap, the facility has decommissioned boiler #8, Point ID #17, which in 
86-Virginia Regional Haze SIP 

2002 accounted for SO2 emissions of 900 tpy. Based on these facility changes, Virginia 

currently estimates that 2018 SO2 emissions from Boiler #7 will be on the order of 3,800 tpy. 

There were no controls suggested by the VISTAS control cost spreadsheet for boiler #7. Based 

on the current use of 0.8 percent S coal, requiring the use of lower S content coal would not be 

practical nor would lower S content coal provide much reduction. Review of existing data 

provided by VISTAS for similar sized boilers indicates a control cost for FGD greater than 

$10,000 per ton of SO2 removed. 

Based on this VISTAS information, additional control of SO2 appears to be more costly than 

may be currently deemed reasonable. However, should data from the IMPROVE monitoring 

network indicate that additional reductions in SO2 are necessary for Class I areas such as 

Swanquarter to meet their goals, a more rigorous engineering analysis for this unit may be 

requested. 

7.7.5.2.2. MeadWestvaco 

Point ID #25 is a single stack for the exhaust of four different boilers: boiler #6 burning coal 

with a heat input of 550 mmbtu/hr; boiler #7 burning coal, bark and wood pelletized fuel with a 

heat input of 440 mmbtu/hr; boiler #8 burning coal, bark, and wood pelletized fuel with a heat 

input of 580 mmbtu/hr; and #9 boiler burning coal with a heat input of 807 mmbtu/hr. Boilers 

#7 and #8 burn predominantly bark and wood pelletized fuel. Boilers #6 and #9 are equipped 

with ESPs and low NOX burners. Boilers #7 and #8 are equipped with ESPs and flue gas 

recirculation. The stack is equipped with a rudimentary SO2 scrubber designed to allow 

emissions from the stack to meet a 3 hour average of 3,300 pounds of SO2 per hour and 9,132.3 

tpy. The boilers use coal with approximately 1.7 percent by weight S content. 

Boiler #9 is subject to BART. The current BART determination indicates that improvements to 

the scrubber must be made to lower annual SO2 emissions to approximately 8,020 tpy. 

VISTAS supplied no control cost information for these units. A detailed review of control 

options for this stack has resulted in a reasonable progress determination for this round of 

Regional Haze planning that additional upgrades could be made to the existing scrubber system 

by 2015. These upgrades would reduce annual SO2 emissions to 6,817 tpy. These reductions 

were not included in the emissions inventory for the reasonable progress visibility goal since the 

control technology for the reasonable progress determination had not yet been determined. See 

Appendix H for the correspondence regarding this determination. 
87-Virginia Regional Haze SIP 

Table 7.7.5.1-1. Virginia EGUs with Visibility Impairment Contributions of at least 1% 

Data used for Contribution 

Calculation 

Updated 201

County Plant ID Plant Name Point ID Unit Description 2002 

SO2

tpy 

2018 

SO2

tpy 

% 

contribution 

2018 

SO2

tpy 

C

Linville Gorge Russell 51-167-0003 AEP-Clinch River 1 238 MW EGU coal fired using approximately 0.8% S coal. 8,158 10,014 4% Russell 51-167-0003 AEP-Clinch River 2 238 MW EGU coal fired using approximately 0.8% S coal. 8,115 10,131 4% Russell 51-167-0003 AEP-Clinch River 3 238 MW EGU coal fired using approximately 0.8% S coal. 8,804 9,911 4% 

16,300 The facili

cap on SO

2015, basagreemen7.2.1. 

James River Face Giles 51-071-0002 AEP-Glyn Lyn 3 238 MW coal fired EGU 7,488 9,981 3.6% --- No changFluvanna 51-065-0001 Dominion- Bremo 2 185 MW coal fired EGU 7,993 6,253 2.2% --- 

The faciliCorporatiswitch fueCity Hybrcommerciis in the Juthe Energeliminate 

from this Section 7

Shenandoah Fluvanna 51-065-0001 Dominion- Bremo 2 185 MW coal fired EGU 7,993 6,253 8.9% --- See abovePrince William 51-153-0002 Dominion- Possum Point 5 786 MW residual oil fired EGU burning 0.7% S oil 4,368 6,100 4.9% --- No changFluvanna 51-065-0001 Dominion- Bremo 1 69 MW coal fired EGU 4,371 2,614 3.7% --- See aboveChesterfield 51-041-0002 Dominion- Chesterfield 8 694 MW coal fired EGU 38,088 3,633 2.4% --- 

No changinstalled aand polishSee Table 

Chesterfield 51-041-0002 Dominion- Chesterfield 6 359 MW coal fired EGU 19,129 1,561 1% --- 

No changsubmitted to control device. Tconstructi
88-Virginia Regional Haze SIP 

7.7.5.2.3. Roanoke Cement Company 

Point #22 at Roanoke Cement Company consists of a preheater, precalciner cement kiln. This 

kiln is subject to the NOX Budget Trading Program as well as Subparts F and LLL of 40 CFR 63. 

It is controlled by an ESP for particulate matter. For SO2 emissions, the kiln has a process lime 

injection system to assist in meeting the SO2 limitations when one or both of the raw mills are off 

line. The S content of the coal burned in the kiln is limited by permit to 1.0 percent on an annual 

average and of the coke burned in the kiln to 3.5 percent on an annual average. The kiln is 

limited to 3,104.4 tpy of SO2. Compliance is determined via a continuous emissions monitor 

located on the main stack. 

VISTAS data did not provide any applicable control technologies for review on this facility. 

However, LADCO created as part of the BART process a document dealing with cement kilns, 

Midwest Regional Planning Organization (RPO) Cement Best Available Retrofit Technology 

(BART) Engineering Analysis (MACTEC, 2005). Table 3.8 of this document summarizes 

control costs of SO2 for small, medium, and large preheater kilns and for advanced flue gas 

desulfurization, wet flue gas desulfurization, and dry flue gas desulfurization. Costs per ton of 

SO2 removed range from $9,663 per ton of SO2 removed to well above $60,000 per ton of SO2

removed. Based on this information, SO2 controls are not cost effective for this facility during 

this round of regional haze planning. 

7.7.5.2.4. Georgia Pacific – Big Island 

Units identified for reasonable progress review at the Georgia Pacific – Big Island facility are 

Point IDs #1 and #2. Point ID #1 is Boiler #4, a pulverized coal and #2 oil fired 284 mmbtu/hr 

boiler. Point ID #2 is Boiler #5, a stoker unit capable of burning coal, wood, and paper waste 

with a capacity of 339 mmbtu/hr. Boiler #5 predominantly burns wood and paper waste. Both 

are controlled by multicyclones and ESPs. Both units are subject to BART. 

Boiler #4 will be controlled via the BART process by a flue gas desulfurization unit with a 

design control efficiency of 90 percent. Annual SO2 emissions will be limited to 219 tpy. Boiler 

#5 will be controlled by the BART process via a fuel limitation strategy such that coal may be 

burned no more than 10 percent of the time, based on the annual capacity factor. Annual SO2

emissions will be limited to 374 tpy. In the G2 emissions inventory, estimated 2018 SO2

emissions from this unit are approximately 286 tpy. This estimate of future emissions, which is 

based on past utilization, may better represent future emission from this unit than will the 

maximum BART limitation. Therefore, Table 7.7.4-2 shows a 2018 SO2 estimated emissions 

rate from this unit of 286 tpy. 

The estimated cost for a caustic scrubber per ton of SO2 removed was $12,371 for the No. 5 

Boiler based on typical fuel sulfur content for less than 10 percent coal and more than 90 percent 

waste type fuel (normal mix). Therefore, further controls beyond BART would not be 

economically feasible for reasonable progress during this round of regional haze planning. 
89-Virginia Regional Haze SIP 

7.7.5.2.5. Mohawk Industries 

Point ID #7 is Boiler #7, which is a 155 mmbtu/hr coal fired unit controlled by two 

multicyclones. The average annual sulfur content of the coal used by this boiler is limited to no 

more than 1 percent. Inventory data shows that the average S content of the coal generally used 

by this boiler is on the order of 0.84 percent. 

VISTAS data shows that controlling this unit with flue gas desulfurization would cost on the 

order of $32,000 per ton of SO2 removed. Based on this cost estimate, and the use of relatively 

low S coal, no economical SO2 control currently exists for this unit. Therefore, additional 

controls for reasonable progress are not feasible for this round of regional haze planning. 

7.7.5.2.6. Celanese Acetate, LLC (now Cinergy Solutions of Narrows, LLC) 

Point #1 for this facility is actually seven coal fired boilers that exhaust through three different 

stacks. All boilers are controlled by ESPs. Coal burned by these boilers contains approximately 

1.1 percent S. 

Table 7.7.5. Celanese Acetate, LLC/Cinergy: Boilers and Stacks Combined for 

Point #1 

Stack ID Unit ID Unit Size 

Babcox & Wilcox coal boiler #1 91 mmbtu/hr 

3BHBL001E1 Riley coal boiler #3 184 mmbtu/hr 

Riley coal boiler #5 246 mmbtu/hr 

Babcox & Wilcox coal boiler #2 91 mmbtu/hr 

3BHBL002E1 Riley coal boiler #4 184 mmbtu/hr 

Riley coal boiler #6 246 mmbtu/hr 

3BHBL003E1 Foster Wheeler coal boiler #7 322 mmbtu/hr 

VISTAS data shows that controlling all seven coal fired boilers as if they exhausted through one 

stack would cost approximately $3,140 per ton of SO2 removed. However, control costs would 

be higher due to the need to control three stacks. 

Based on this VISTAS information, additional control of SO2 appears to be more costly than 

may be currently deemed reasonable for this round of planning. However, should data from the 

IMPROVE monitoring network indicate that additional reductions in SO2 are necessary for Class 

I areas such as James River Face to meet their goals, a more rigorous engineering analysis for 

these units may be requested. 

7.8. What Control Determinations Represent Best Available Retrofit Technology 

(BART) for Individual Sources? 

Section 169A of the CAA directs States to assess certain large, older emission sources for 

additional controls in order to address visibility impacts. States are directed to conduct BART 

determinations for such sources in specific source categories that contribute to visibility 

impairment in Class I areas. The 1999 regional haze regulation includes the BART requirement, 

and it directs states to include BART in their regional haze SIPs. On July 6, 2005, USEPA 
90-Virginia Regional Haze SIP 

published a revised final rule, including Appendix Y to 40 CFR Part 51, Guidelines for BART 

Determinations Under the Regional Haze Rule (hereinafter referred to as the “BART 

Guidelines”). The BART Guidelines provide direction to states on determining which of these 

sources should be subject to BART and how to determine BART for each source. 

A BART-eligible source is one that has the potential to emit 250 tons or more of a visibilityimpairing air pollutant, was put in place between August 7, 1962 and August 7, 1977, and whose 

operations fall within one or more of 26 specifically listed source categories. Under the CAA, 

BART is required for any BART-eligible source that a State determines “emits any air pollutant 

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

such area.” 

For those sources subject to BART, § 169A(g)(7) of the CAA requires that States must consider 

the following factors in making BART determinations: (1) the costs of compliance, (2) the 

energy and non-air quality environmental impacts of compliance, (3) any existing pollution 

control technology in use at the source, (4) the remaining useful life of the source, and (5) the 

degree of improvement in visibility which may reasonably be anticipated to result from the use 

of such technology. 

7.8.1. BART-Eligible Sources in Virginia 

The following is a list of facilities with BART-eligible sources in Virginia that shows the number 

of BART-eligible units at each facility. 

Table 7.8.1. Virginia BART Source List 

Registration 

Number Name Number of BART-Eligible Units or Processes 

10354 Island Creek Coal Co/Virginia Pocahontas Mine 1 

20225 Chemical Lime Company - Kimballton Plant 2 

20328 MeadWestvaco Packaging Resource Group 7 

21418 Duke Energy (formerly Cinergy Solutions of Narrows) 1 

30121 Intermet Foundry Archer Creek 8 

30389 Georgia Pacific Corp Big Island Plant 2 

40126 Stone Container Corporation (D/B/A Smurfit Stone) 4 

50232 Honeywell Nylon LLC-Hopewell 21 

50396 Dominion Virginia Power - Chesterfield 2 

60137 Dominion - Yorktown 1 

60214 International Paper Company 20 

70225 Dominion Virginia Power - Possum Point 1 

80252 O-N Minerals Global Chemstone Operation 2 

TOTAL BART-ELIGIBLE UNITS 72 

The BART-eligible sources were identified using the methodology in the BART Guidelines: 

• One or more emissions units at the facility fit within one of the 26 categories 

listed in the BART Guidelines; 
91-Virginia Regional Haze SIP 

• The emission unit(s) were in existence on August 7, 1977 and began operation at 

some point on or after August 7, 1962; and 

• The limited potential emissions from all emission units identified in the previous 

two bullets were greater than 250 tons or more per year of any of these visibilityimpairing pollutants: SO2, NOX, and PM10. 

The BART Guidelines recommend addressing SO2, NOX, and PM. The BART Guidelines also 

suggest that states use their best judgment in determining whether to address VOC or NH3

emissions. Virginia addressed SO2, NOX, and PM10 as an indicator for particulate matter to 

identify BART-eligible units, as the BART Guidelines recommend. As discussed in detail in 

Appendix H, VISTAS modeling demonstrated that VOCs from point sources are not visibilityimpairing pollutants and that ammonia from point sources is only visibility-impairing in rare 

instances where the facility emits large quantities. For this reason Virginia did not evaluate 

emissions of VOCs and ammonia in BART determinations, with the exception of Honeywell 

Nylon LLC Hopewell, Registration Number 50232. Due to the large quantity of ammonia 

emitted by this facility, this facility’s ammonia emissions were also considered in the facility’s 

visibility analysis. 

7.8.2. Determination of Sources Subject to BART in Virginia 

Under the BART Guidelines, Virginia may consider exempting some sources from BART if it is 

found that they do not cause or contribute to visibility impairment in a Class I area. In 

accordance with the BART guidelines, Virginia chose to perform source-specific analyses to 

determine which sources cause or contribute to visibility impairment using the CALPUFF 

model. The CALPUFF modeling protocol used for determining which facilities are subject to 

BART is included in Appendix H. In accordance with the guidelines, a contribution threshold of 

0.5 dv was used for determining which sources were subject to BART. 

Ten of Virginia’s BART-eligible sources submitted modeling to demonstrate exemptions. 

Results of these demonstrations are summarized in Table 7.8.2-1. Additional details are 

available in Appendix H. Facilities found to be subject to BART must complete a BART 

analysis. 

Table 7.8.2-1 identifies the facilities that were able to demonstrate exemption from BART based 

on modeling conducted using the VISTAS modeling protocol and the new IMPROVE equation. 

Virginia proposed to exempt these units in appropriate newspapers on or about the week of 

January 19, 2007. No adverse comments were received during the public comment period. 

Correspondence dated June 8, 2007, from the National Park Service was received concurring 

with these exemptions. 
92-Virginia Regional Haze SIP 

Table 7.8.2-1. BART Exemption Modeling Results 

Class I Areas Impacted Delta-Deciview Visibility Impact 

(Exemption Threshold <= 0.5 Deciviews) 

Island Creek Coal Company – Virginia Pocahontas Mine REGISTRATION NUMBER: 10354 

SHENANDOAH NATIONAL PARK (VA) 0.054 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.119 

JOYCE-KILMER-SLICKROCK (NC) 0.066 

DOLLY SODS WILDERNESS AREA (WV) 0.045 

OTTER CREEK WILDERNESS AREA (WV) 0.057 

LINVILLE GORGE WILDERNESS AREA (NC) 0.132 

SHINING ROCK WILDERNESS AREA (NC) 0.158 

GREAT SMOKY MOUNTAINS (NC/TN) 0.149 

Chemical Lime Company – Kimballton REGISTRATION NUMBER: 20225

SHENANDOAH NATIONAL PARK (VA) 0.2182

JAMES RIVER FACE WILDERNESS AREA (VA) 0.2472

DOLLY SODS WILDERNESS AREA (WV) 0.1442

OTTER CREEK WILDERNESS AREA (WV) 0.1502

LINVILLE GORGE WILDERNESS AREA (NC) 0.4071

SHINING ROCK WILDERNESS AREA (NC) 0.3191

GREAT SMOKY MOUNTAINS (NC/TN) 0.2901

Duke Energy Generation Services REGISTRATION NUMBER: 21418

SHENANDOAH NATIONAL PARK (VA) 0.143 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.203 

JOYCE KILMER-SLICKROCK (NC) 0.025 

DOLLY SODS WILDERNESS AREA (WV) 0.113 

OTTER CREEK WILDERNESS AREA (WV) 0.120 

LINVILLE GORGE WILDERNESS AREA (NC) 0.120 

SHINING ROCK WILDERNESS AREA (NC) 0.052 

GREAT SMOKY MOUNTAINS (NC/TN) 0.058 

Intermet Foundry REGISTRATION NUMBER: 30121

SHENANDOAH NATIONAL PARK (VA) 0.247 

DOLLY SODS WILDERNESS AREA (WV) 0.045 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.318 

OTTER CREEK WILDERNESS AREA (WV) 0.052 

LINVILLE GORGE WILDERNESS AREA (NC) 0.030 

Smurfit-Stone Container Corporation – West Point Plant REGISTRATION NUMBER: 40126

SHENANDOAH NATIONAL PARK (VA) 0.123 
93-Virginia Regional Haze SIP 

Table 7.8.2-1. BART Exemption Modeling Results 

Class I Areas Impacted Delta-Deciview Visibility Impact 

(Exemption Threshold <= 0.5 Deciviews) 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.063 

DOLLY SODS WILDERNESS AREA (WV) 0.026 

OTTER CREEK WILDERNESS AREA (WV) 0.023 

BRIGANTINE WILDERNESS AREA (NJ) 0.089 

SWANQUARTER WILDERNESS AREA (NC) 0.074 

Honeywell International Inc. – Hopewell Plant REGISTRATION NUMBER: 50232

SHENANDOAH NATIONAL PARK (VA) 0.3442

JAMES RIVER FACE WILDERNESS AREA (VA) 0.2352

DOLLY SODS WILDERNESS AREA (WV) 0.2111

OTTER CREEK WILDERNESS AREA (WV) 0.1291

SWANQUARTER WILDERNESS AREA (NC) 0.2152

Dominion – Chesterfield Power Station REGISTRATION NUMBER: 50396

SHENANDOAH NATIONAL PARK (VA) 0.082 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.046 

DOLLY SODS WILDERNESS AREA (WV) 0.015 

OTTER CREEK WILDERNESS AREA (WV) 0.013 

BRIGANTINE WILDERNESS AREA (NJ) 0.044 

SWANQUARTER NATIONAL WILDERNESS AREA (NC) 0.035 

Dominion - Yorktown Power Station REGISTRATION NUMBER: 60137

SHENANDOAH NATIONAL PARK (VA) 0.065 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.034 

SWANQUARTER NATIONAL WILDERNESS AREA (NC) 0.105 

International Paper REGISTRATION NUMBER: 60214

SHENANDOAH NATIONAL PARK (VA) 0.250 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.250 

SWANQUARTER NATIONAL WILDERNESS AREA (NC) 0.410 

Dominion – Possum Point Power Station REGISTRATION NUMBER: 70225

SHENANDOAH NATIONAL PARK (VA) 0.414 

JAMES RIVER FACE WILDERNESS AREA (VA) 0.080 

DOLLY SODS WILDERNESS AREA (WV) 0.050 

OTTER CREEK WILDERNESS AREA (WV) 0.039 

BRIGANTINE WILDERNESS AREA (NJ) 0.100 

1

 12-km screening modeling results are below the BART exemption threshold 

2

 4-km refined modeling results are below the BART exemption threshold 
94-Virginia Regional Haze SIP 

Three of Virginia’s BART-eligible sources are EGUs, and these sources have four BARTeligible units. These units are Unit #3 at Yorktown Power Station, Unit #5 at Possum Point 

Power Station, and Units #5 and #6 at Chesterfield Power Station. USEPA has determined that, 

as a whole, the CAIR cap-and-trade program improves visibility more than implementing BART 

for individual sources in states affected by CAIR. A state that opts to participate in the CAIR 

program under 40 CFR part 96 subparts AAA through EEE need not require affected BARTeligible EGU to install, operate, and maintain BART for SO2 or NOX emissions. Given that 

Virginia is participating in CAIR and accepts USEPA’s overall finding that CAIR “substitutes” 

for BART for SO2 and NOX, Virginia’s EGUs were allowed to submit BART exemption 

modeling demonstrations for PM emissions only. These EGUs demonstrated that they do not 

contribute to visibility impairment in Class I areas. 

However, it is important to note that Unit #3 at Yorktown and Unit #5 at Possum Point are oil 

fired units, which are currently not utilized on a frequent basis. Units #5 and #6 at Chesterfield 

Power Station have already been retrofitted with selective catalytic reduction (SCR) for NOX

control. Unit #6 has been retrofitted with a flue gas desulfurization unit and a polishing 

baghouse. A flue gas desulfurization unit is under construction to control SO2 emissions from 

Unit #5. See Table 4-1. 

In total, ten of Virginia’s thirteen BART-eligible sources were able to demonstrate that they did 

not cause or contribute to visibility impairment in any Class I area within 300 km of the source. 

7.8.3. Determination of BART Requirements for Subject-to-BART Sources 

Three sources (MeadWestvaco Packaging Resource Group, Georgia Pacific-Big Island, and O-N 

Minerals Global Chemstone Operation) were unable to demonstrate a contribution of less than 

0.5 dv at all Class I areas within 300 km from their BART-eligible sources. These three sources 

are considered to be “subject to BART” and were required to submit permit applications 

containing their evaluation of potential BART options and proposed BART determinations. 

These facilities submitted their initial proposed BART determinations in the spring of 2007. 

Table 7.8.3-1 summarizes the BART determinations for the various BART-eligible units at these 

facilities. Each permit also contains a requirement that each facility must maintain the BART 

control equipment and establish procedures to ensure that the equipment is properly operated and 

maintained.
95-Virginia Regional Haze SIP 

Table 7.8.3-1. BART Determinations 

Georgia Pacific – Big Island: Power Boiler #4 (Permit issued 6/12/08, SIP submittal to EPA dated July 17, 2008) 

Short Term 

Limit 

Long Term 

Limit 

Control 

Efficiency 

Work Practice or 

Control Device 

Compliance 

Date Records, Reporting, and Monitoring 

SO2 50.0 lbs/hr 219.0 tpy 90.0% *1.8% S coal; 

*Caustic scrubber 

Scrubber and coal limitation effective 01/01/12. Short term limit effective 180 days after scrubber start up. Long term limit effective 07/01/13. 

*Coal S content monitoring & record keeping *Liquid flow rate *Air pressure drop *Monitoring of devices/reporting of data *Stack testing *Calculation of emission rates 

NOX 169.0 lbs/hr 740.2 tpy --- *LNB At issuance. *Calculation of emission rates PM/PM10 0.07 lbs/mmbtu 

19.9 lbs/hr 

87.0 tpy --- *ESP At issuance. *ESP voltages 

*Monitoring of devices/reporting of data *Calculation of emission rates 

Georgia Pacific – Big Island: Power Boiler #5 (Permit issued 6/12/08, SIP submittal to EPA dated July 17, 2008) 

Short Term 

Limit 

Long Term 

Limit 

Control 

Efficiency 

Work Practice or 

Control Device 

Compliance 

Date Records, Reporting, and Monitoring 

SO2 485.1 lbs/hr 374.0 tpy --- *1.3% S coal; 

*Good operational practice *Firing coal no more than 10% of the annual capacity factor 

Hourly limit effective at issuance. Annual limit effective 12 months after permit issuance (06/12/09). Coal S content limit effective 01/01/12. 

*Coal S content monitoring & record keeping *Records on other fuels fired *Records on capacity *Calculation of emission rates 

NOX 139.3 lbs/hr 610.1 tpy --- *OFA At issuance. *Calculation of emission rates 

*Emissions and capacity calculations 

PM/PM10 0.07 lbs/mmbtu 

23.7 lbs/hr 

103.9 tpy --- *ESP At issuance. *ESP voltages 

*Monitoring of devices/reporting of data *Calculation of emission rates 
96-Virginia Regional Haze SIP 

Table 7.8.3-1. BART Determinations 

MeadWestvaco Power Boiler # 9 (PWR009) (Permit issued 2/23/09, SIP submittal to EPA dated 3/6/09) 

Short Term 

Limit 

Long Term 

Limit 

Control 

Efficiency 

Work Practice or 

Control Device 

Compliance 

Date Records, Reporting, and Monitoring 

SO2 1,831 lbs/hr on 

an annual average 

8,020 tpy --- *FGD *Liquid flow rates 

*Air pressure drops *SO2 CEMs 

*Fuel consumption records *Emissions and capacity calculations 

NOX 242.1 lbs/hr 1,060 tpy --- *LNB *Fuel consumption records PM/PM10 166.4 lbs/hr 

0.07 lbs/mmbtu 

728.9 tpy --- *ESP 

*At issuance or 01/01/09. 

*ESP voltages *Fuel consumption records 

MeadWestvaco Power Boiler #10 (PWR010) (Permit issued 2/23/09, SIP submittal to EPA dated 3/6/09) 

Short Term 

Limit 

Long Term 

Limit 

Control 

Efficiency 

Work Practice or 

Control Device 

Compliance 

Date Records, Reporting, and Monitoring 

SO2 --- --- --- *Fuel restriction of 

at least 90% natural gas utilization. *Proper operation and maintenance. 

*Fuel consumption records *Emissions and capacity calculations 

NOX 66.0 lbs/hr on 

natural gas 

--- --- *Operation at no 

more than 50% of rated capacity on annual basis. *Proper maintenance. 

*Fuel consumption records 

PM/PM10 2.51 lbs/hr on 

natural gas 

--- --- *Fuel restriction of 

at least 90% natural gas utilization. *Proper operation and maintenance. 

*At issuance. 

*Fuel consumption records *Emissions and capacity calculations 
97-Virginia Regional Haze SIP 

Table 7.8.3-1. BART Determinations 

MeadWestvaco Power Recovery Furnace #1 (REC001) (Permit issued 2/23/09, SIP submittal to EPA on 3/6/09) 

Short Term Limit Long Term Limit Control Efficiency Work Practice or Control Device Compliance Date Records, Reporting, and Monitoring 

SO2 713.7 lb/hr --- --- *Proper boiler 

operation and maintenance 

At issuance. *Fuel consumption records 

*Emissions calculations 

NOX 211.2 lb/hr --- --- *Proper boiler 

operation and maintenance 

At issuance. *Fuel consumption records 

*Emissions and capacity calculations 

PM/PM10 0.044 gr/dscf @8% 

O2

PM: 150.0 lb/hr PM: 85.0 lb/hr annual average PM10: 103.8 lb/hr 

PM10: 58.8 lb/hr annual average 

PM: 350 tpy PM10: 242 tpy 

--- *ESP At issuance. *ESP voltages 

*Fuel consumption records *Emissions and capacity calculations 

MeadWestvaco Smelt Dissolving Tanks (REC002 and REC003) (Permit issued 2/23/09, SIP submittal to EPA on 3/6/09)

Short Term Limit Long Term Limit Control Efficiency Work Practice or Control Device Compliance Date Records, Reporting, and Monitoring 

SO2 14.8 lbs/hr 64.8 tpy --- NOX --- --- --- PM/PM10 PM: 14.1 lbs/hr 

PM10: 12.6 lbs/hr 

PM: 58.0 tpy PM10: 51.9 tpy 

--- 

*Venturi scrubber with basic solution 

At issuance. *Emissions and capacity calculations 
98-Virginia Regional Haze SIP 

Table 7.8.3-1. BART Determinations 

O-N Minerals (Global Chemstone) Rotary Kiln U5 (Permit issued 12/28/09, SIP submittal to EPA on 01/14/10) 

Short Term Limit Long Term Limit Control Efficiency Work Practice or Control Device Compliance Date Records, Reporting, and Monitoring 

SO2 14.7 lbs/hr 

 0.29 lbs/tsf 

--- --- *Inherent 

process scrubbing or wet scrubber *S content of fuel no greater than 1% 

09/10/11 or 08/01/12 Short term emissions limits effective 09/10/10. 

*Scrubber: liquid flow rate and differentipressure. *CEM (beginning 09/10/10). *Emission calculations. *BART monitoring plan. *S content records and fuel consumption*Hours of operation. 

NOX 87.0 lbs/hr 

1.74 lbs/tsf 

--- --- *Indirect firing 

*Good combustion practices 

At issuance. *BART monitoring plan. 

*Annual combustion apparatus inspectionfor NOX optimizations. 

PM/PM10 6.0 lbs/hr 

0.12 lbs/tsf 

--- --- *Multicyclone 

*Fabric filter 

At issuance. *Differential pressure drop. 

*BART monitoring plan. 

O-N Minerals (Global Chemstone) Calcimatic Kiln U12 (Permit issued 12/28/09, SIP submittal to EPA on 01/14/10) 

Short Term Limit Long Term Limit Control Efficiency Work Practice or Control Device Compliance Date Records, Reporting, and Monitoring 

SO2 2.6 lbs/hr 

0.16 lbs/tsf 

--- --- *Venturi 

scrubber 

At issuance. *Scrubber liquid flow rate, exit gas 

temperature, differential pressure. *BART monitoring plan. *Fuel consumption, S content. *Emission calculations. 

NOX 9.8 lbs/hr 

0.61 lbs/tsf 

--- --- *Good 

combustion practices 

At issuance. *BART monitoring plan. 

*Annual combustion apparatus inspectionfor NOX optimization. 

PM/PM10 9.6 lbs/hr 

0.60 lbs/tsf 

---- --- *Multicyclone 

*Venturi scrubber 

At issuance. *Scrubber liquid flow rate, exit gas 

temperature, differential pressure. *BART monitoring plan. 
99-Virginia Regional Haze SIP 

7.9. Affects of the CAIR Remand 

The U.S. Court of Appeals for the D.C. Circuit ruled on petitions for review of CAIR and CAIR 

Federal Implementation Plans, including their provisions establishing the CAIR NOX annual and 

ozone season and SO2 trading programs. On July 11, 2008, the Court issued an opinion vacating 

and remanding these rules; however, parties to the litigation requested rehearing of aspects of the 

Court's decision, including the vacatur of the rules. On December 23, 2008, the Court granted 

rehearing only to the extent that it remanded the rules to EPA without vacating them. The 

December 23, 2008 ruling leaves CAIR in place until EPA issues a new rule to replace CAIR in 

accordance with the July 11, 2008 decision. EPA informed the Court that development and 

finalization of a replacement rule could take about two years. Therefore, a new rule is expected 

to be published in July of 2010. The contents of this rule are not known at this time. In an effort 

to determine how this remand may affect EGU emissions in future years, states in VISTAS 

undertook an effort to evaluate future year emissions under a “No CAIR Legally Enforceable” 

scenario. This scenario took into consideration reductions in EGU emissions that would be 

required by state enforceable or federally enforceable mandates. These mandates included 

emission reductions from programs such as Georgia’s Multipollutant Control for Electric Utility 

Steam Generating Units, federal consent orders such as those noted in Section 7.2.1 and the AEP 

consent order as noted in Section 7.10.4, and various permitting actions. However, this scenario 

did not consider controls or reductions that were solely the result of CAIR. 

The analysis showed that CAIR in 2018 resulted in significant SO2 emissions reductions for 

Virginia and in significant SO2 and NOX emission reductions in the nearby states of West 

Virginia and Tennessee when compared to the “No CAIR Legally Enforceable” scenario. North 

Carolina results for 2018 remain largely unaffected due to the mandates of the North Carolina 

Clean Smokestacks Act. The CAIR reductions are therefore important to Virginia’s efforts 

towards improving visibility impairment at Class I areas since sulfates are responsible for a large 

fraction of the visibility impairment in VISTAS Class I areas. After the remanded rule is 

proposed, the proposal will be examined to determine how the 2018 SO2 emissions inventory in 

Virginia will be affected. Should the proposed rule prove to engender less emissions reductions 

than the remanded rule, Virginia will most likely provide this information in the form of 

comments on the rule to the formal docket. Figures 7.9-1 and 7.9-2 show the results of the “No 

CAIR Legally Enforceable” versus CAIR analysis in graphical form for future years 2012 and 

2018. 
100-Virginia Regional Haze SIP 

SO2 EGU Emissions (Tons/Year)

0

100,000

200,000

300,000

400,000

500,000

600,000

AL FL GA KY MS NC SC TN VA WV

2002 Actual

2002 Typical

2012 No CAIR

2012 CAIR

2018 No CAIR

2018 CAIR

Figure 7.9-1. SO2 Emissions Comparisons for VISTAS States, CAIR versus No CAIR, Legally Enforceable 

NOx EGU Emissions (Tons/Year)

0

50,000

100,000

150,000

200,000

250,000

300,000

AL FL GA KY MS NC SC TN VA WV

2002 Actual

2002 Typical

2012 No CAIR

2012 CAIR

2018 No CAIR

2018 CAIR

Figure 7.9-2. NOX Emissions Comparisons for VISTAS States, CAIR versus No CAIR, Legally Enforceable 

7.10. What Additional Emissions Controls Were Considered as part of the LongTerm Strategy for Visibility Improvement by 2018? 

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

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

for smoke management; the role of dust and fine soil at Class I areas and status of state plans to 

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

emissions from agricultural sources were mitigated. A CMAQ modeling run was performed in 
101-Virginia Regional Haze SIP 

the fall of 2007 to account for the cumulative benefits of the Base G2a emissions controls, 

BART controls, and additional measures to achieve reasonable progress by 2018. A final 

CMAQ modeling run was performed in January of 2008 to account for expected BART controls 

and other inventory changes that took place between development of the Base G2a and Base G4a 

estimates. This final Regional Haze SIP contains revised RPGs for each Class I area in Virginia 

reflecting these final decisions. 

7.10.1. Smoke Management 

As discussed in Section 2.4 and demonstrated in Figures 2.4-1 and 2.4-2, elemental carbon 

(sources include agriculture, prescribed wildland fires, and wildfires) is a relatively minor 

contributor to visibility impairment at the Class I areas in Virginia. POM may also be an 

indicator of fire emissions although significant fire impacts are infrequent at Class I areas in 

Virginia. The Virginia Department of Forestry has developed smoke management guidelines 

(VDOF, 1998), and these guidelines specifically note that Federal Class I air quality areas are 

sensitive areas that need special consideration if located near planned prescribed burns. Since 

elemental carbon is a relatively minor contributor to visibility impairment at both Shenandoah 

and James River Face and since significant fire impacts are infrequent at Virginia Class I areas, 

these management practices are adequate visibility protection for this SIP submittal period. 

Future submittals may review and update these findings if, for example, fire impacts becomes a 

more significant contributor to visibility impairment. 

7.10.2. Dust and Fine Soil from Construction Activities 

As discussed in Section 2.4 and demonstrated in Figures 2.4-1 and 2.4-2, fine soils are a 

relatively minor contributor to visibility impairment at the Class I areas in Virginia. The 

Virginia Department of Transportation (VDOT) uses the following requirements in all road and 

bridge construction specifications for contracts. These requirements for dust control and erosion 

control may be found at Section 107.14(b)(2) of VDOT’s 2007 Road and Bridge Specifications 

(VDOT, 2007): 

107.14—Environmental Stipulations. 

By signing the bid, the bidder shall have stipulated (1) that any facility to be used in the performance of the 

Contract (unless the Contract is exempt under the Clean Air Act as amended [42 U.S.C. 1857, et seq., as 

amended by P.L. 91-604], the Federal Water Pollution Control Act as amended [33 U.S.C. 1251 et seq. as 

amended by P.L. 92-500], and Executive Order 11738 and regulations in implementation thereof [40 

C.F.R., Part 15]) is not listed on the EPA’s List of Violating Facilities pursuant to 40 C.F.R. 15.20; and (2) 

that the Department will be promptly notified prior to the award of the Contract if the bidder receives any 

communication from the Director, Office of Federal Activities, EPA, indicating that a facility to be used for 

the Contract is under consideration to be listed on the EPA’s List of Violating Facilities. 

... 

(b) Pollution: . . . 

2. Air: The Contractor shall comply with the provisions of Section 107.01 and the State Air Pollution 

Control Law and Rules of the State Air Pollution Control Board, including notifications required 

therein. 

Burning shall be performed in accordance with of applicable local laws and ordinances and under the 

constant surveillance of watchpersons. Care shall be taken so that the burning of materials does not 
102-Virginia Regional Haze SIP 

destroy or damage property or cause excessive air pollution. The Contractor shall not burn rubber 

tires, asphalt, used crankcase oil, or other materials that produce dense smoke. Burning shall not be 

initiated when atmospheric conditions are such that smoke will create a hazard to the motoring public 

or airport operations. Provisions shall be made for flagging vehicular traffic if visibility is obstructed 

or impaired by smoke. At no time shall a fire be left unattended. 

Asphalt mixing plants shall be designed, equipped, and operated so that the amount and quality of air 

pollutants emitted will conform to the Rules of the State Air Pollution Control Board. 

Emission standards for asbestos incorporated in the EPA’s National Emission Standards for Hazardous 

Air Pollutants apply to the demolition or renovation of any institutional, commercial, or industrial 

building, structure, facility, installation, or portion thereof that contains friable asbestos... 

(c) Forests: The Contractor shall take all reasonable precautions to prevent and suppress forest fires 

in any area involved in construction operations or occupied by him as a result of such operations. 

The Contractor shall cooperate with the proper authorities of the state and federal governments in 

reporting, preventing, and suppressing forest fires. Labor, tools, or equipment furnished by the 

Contractor upon the order of any forest official issued under authority granted the official by law 

shall not be considered a part of the Contract. The Contractor shall negotiate with the proper 

forest official for compensation for such labor, tools, or equipment. 

7.10.3. NH3 and Agricultural Emissions Mitigation 

The USEPA’s Air Quality Compliance Agreement (70 FR 4958) will help to reduce air 

pollution, ensure compliance with the CAA, and monitor and evaluate animal feeding operations 

(AFOs). This document should also help to promote a national consensus on estimating 

emissions from AFO’s. 

Additionally, the treatment, storage, and land application of sewage sludge, industrial waste 

(sludge and wastewater), municipal wastewater, and animal waste are regulated activities in the 

Commonwealth of Virginia. A Virginia Pollution Abatement permit may be issued by VDEQ 

whenever an owner handles waste and wastewater in a manner that does not involve discharging 

to a sewage treatment work, or to state waters pursuant to a valid Virginia Pollutant Discharge 

Elimination System permit. In general, land application of industrial waste or spray irrigation of 

industrial and municipal wastewater is covered by a Virginia Pollution Abatement individual 

permit. 

AFOs are covered by a Virginia Pollution Abatement individual or general permit. A separate 

Virginia Pollution Abatement general permit covers confined poultry feeding operations for 

poultry waste management. VPDES permits may be required for some AFOs. The general 

permit and regulations regarding AFOs may be found at 9VAC5-25-191. This regulation 

requires AFOs to implement a Nutrient Management Plan approved by the Virginia Department 

of Conservation. The purpose of this plan is address the form, source, amount, timing, and 

method of nutrient application on each field to achieve realistic production goals, while 

minimizing nitrogen and phosphorus loss to ground and surface waters. 

7.10.4. Base G4a Best and Final Inventory 

As part of the effort to create reasonable progress goals for this round of regional haze planning, 

in the fall of 2007 VISTAS created a best and final inventory exercise, identified as Base G4a. 
103-Virginia Regional Haze SIP 

In Virginia, Base G4a captured the emission reductions from a variety of facilities and programs. 

These include: 

• SO2 emission reductions from BART determinations for Meadwestvaco and 

Georgia-Pacific Big Island. Reductions from the O-N/Carmeuse BART 

determination were not included since the results of that analysis were not yet 

known at the time of the Base G4a inventory effort. 

• Reductions in NOX and SO2 from the American Electric Power (AEP) federal 

consent agreement. In this agreement, filed in the US District Court for the 

Southern District of Ohio-Eastern Division, AEP agreed to spend $4.6 billion 

dollars to eliminate 72,000 tons of NOX emissions annually by 2016 and 174,000 

tons of SO2 emissions annually by 2018 from sixteen plants located in Indiana, 

Kentucky, Ohio, Virginia, and West Virginia. 

• Facility shutdown information was included in this inventory exercise so that the 

list of operating units in the future year inventory was as accurate as possible. 

• Emissions from the new Virginia City Hybrid Energy Center, the coal-fired power 

plant located in Wise County, Virginia, were added to this inventory effort to 

ensure that the facility’s emissions would not adversely affect downwind 

nonattainment areas and Class I areas. The final permit for this facility was not 

yet issued at the time of inventory development. The final permit contained 

emissions limits for SO2 that were significantly smaller than those used in the G4a 

best and final inventory and modeling effort. 

• Other changes were made to the Virginia inventory that included updates to a 

variety of non-EGU facilities based on new enforceable limits, updates to the 

inventory to ensure that estimates of new growth in the electrical generating 

sector were reflective of permitting information, and corrections of inventory 

errors. 

This SO2 inventory exercise reduced Virginia’s 2018 non-EGU emissions from an estimated 

69,000 tons SO2/year to approximately 58,000 tons SO2/year and Virginia’s 2018 EGU 

emissions from an estimated 114,000 tons SO2/year to approximately 99,000 tons SO2/year. 

Table 7.4.10-1 and 7.4.10-2 compare the point source Base G2 and Base G4a emissions by state 

in the VISTAS Region for 2018. Appendix D provides more detail on the G4a inventory 

changes. 
104-Virginia Regional Haze SIP 

Table 7.10.4-1. Base G2 and Base G4a Point Source Emissions Comparison for SO2, NOX, VOC, and CO 

SO2 NOX VOC 

State 

Base G2 Base G4a ∆ Base G2 Base G4a ∆ Base G2 Base G4a ∆ Base G2 

Alabama 249,075 239,154 -9,921 142,676 142,319 -357 57,243 57,242 -1 226,13Florida 213,387 265,838 52,451 126,543 140,604 14,061 45,233 45,860 627 150,96Georgia 138,778 127,864 -10,914 131,541 125,680 -5,861 43,123 43,098 -25 212,37Kentucky 266,744 262,784 -3,960 105,411 105,411 0 57,287 57,287 0 156,58Mississippi 41,824 40,888 -936 71,804 82,787 10,983 46,452 46,609 157 82,14North Carolina 161,085 166,480 5,395 100,154 98,912 -1,242 72,220 72,178 -42 82,42South Carolina 146,851 147,787 935 95,477 95,082 -396 44,562 42,918 -1,644 83,77Tennessee 189,919 169,354 -20,565 95,168 94,234 -934 94,242 93,432 -810 148,66Virginia 183,164 156,778 -26,386 122,019 120,078 -1,941 54,200 54,166 -34 92,56West Virginia 168,128 167,901 -227 94,600 94,754 154 17,952 16,968 -984 131,29

1,758,956 1,744,827 -14,129 1,085,393 1,099,861 14,468 532,513 529,757 -2,756 1,366,9

Table 7.10.4-2. Base G2 and Base G4a Point Source Emissions Comparison for PM10, PM2.5, and NH3

PM10 PM2.5 NH3 State 

Base G2 Base G4a ∆ Base G2 Base G4a ∆ Base G2 Base G4a 

Alabama 37,746 37,711 -34 27,366 27,352 -14 3,536 3,536 Florida 56,478 59,283 2,805 46,315 48,903 2,588 4,805 4,805 Georgia 48,182 48,005 -177 36,399 36,297 -102 6,474 6,474 Kentucky 26,848 26,848 0 18,172 18,172 0 1,377 1,377 Mississippi 30,046 30,249 203 17,772 17,971 199 1,591 1,591 North Carolina 53,113 51,012 -2,101 41,616 39,962 -1,654 2,129 2,129 South Carolina 43,965 42,314 -1,651 36,118 34,493 -1,625 2,396 2,404 Tennessee 58,221 57,940 -281 46,919 46,680 -239 2,455 2,454 Virginia 28,944 27,662 -1,282 23,570 22,378 -1,192 4,227 4,210 West Virginia 28,084 19,986 -8,098 20,165 12,240 -7,924 593 521 

411,625 401,010 -10,615 314,412 304,450 -9,962 29,584 29,502 
105-Virginia Regional Haze SIP 

8. REASONABLE PROGRESS GOALS (RPGs) 

The regional haze regulation at 40 CFR 51.308(d)(1) requires states to establish RPGs for each 

Class I area within the State (expressed in dv) that provide for reasonable progress towards 

achieving natural visibility. In addition, USEPA released guidance on June 7, 2007, to use in 

setting RPGs. The goals must provide improvement in visibility for the most impaired days and 

ensure no degradation in visibility for the least impaired days over the SIP period. 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 RPG. 

8.1. Reasonable Progress Goal Summary 

In accordance with the requirements of 40 CFR 51.308(d)(1), this regional haze plan establishes 

RPGs for each Class I area in Virginia. The reasonable progress goals shown below reflect the 

additional visibility improvements predicted from the SO2 reductions in the Base G4a emissions 

inventory. Also shown are the expected 2018 visibility values calculated using the Base G2 

inventory. To determine the rate of progress represented by each RPG, Virginia compared 

baseline visibility conditions to natural visibility conditions in each Class I area and determined 

the uniform rate of visibility improvement (in dv) that would need to be maintained during each 

implementation period in order to attain natural visibility conditions by 2064. The RPGs are 

based on the available Base G4a modeling results and represent the best data available at this 

time. 

Table 8.1-1. Virginia Reasonable Progress Goals 

Expected Visibility by 

2018, dv 

Class I Area 

Natural 

Conditions, 

dv 

Baseline 

Visibility, dv * Base G2 Base G4a 

Reasonable Progress Goal 

Base G4a 

(Improvement by 2018) 

dv 

Deciview 

Improvement 

Needed from Base 

G4a 

2018-2064 

Shenandoah 11.4 20% WD 29.3 22.1 21.9 ∆ 7.4 dv ∆ 10.8 

National Park 3.1 20% BD 10.9 8.8 8.7 ∆ 2.2 dv --- 

James River Face 11.1 20% WD 29.1 22.6 22.4 ∆ 6.7 dv ∆ 11.0 

Wilderness Area 4.4 20% BD 14.2 12.5 12.4 ∆ 1.8 dv --- 

*WD=Worst Day, BD=Best Day 
106-Virginia Regional Haze SIP 

Uniform Rate of Reasonable Progress Glide Path

Shenandoah - W20% Data Days

Base G4a Projections, 12 km grid, New IMPROVE Equation

29.3

27.8

25.1

22.1

19.1

16.2

13.2

11.4

21.9

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews)

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

Figure 8.1-1. 20% Worst Days Reasonable Progress for Shenandoah 

Uniform Rate of Reasonable Progress Glide Path

James River Face - W20% Data Days

Base G4a Projections, 12 km grid, New IMPROVE Equation

29.1

27.6

24.9

21.9

18.9

15.9

12.9

11.1

22.4

0

5

10

15

20

25

30

35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

Year

Haziness Index (Deciviews) 

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

Figure 8.1-2. 20% Worst Days Reasonable Progress for James River Face 
107-Virginia Regional Haze SIP 

Reasonable Progress Assessment 

Shenandoah - Best 20% Days

Base G4a Projections, 12 km grid, New IMPROVE Equation

8.7

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)

Observation Method 1 Prediction

Baseline = 10.9 dV

Figure 8.1-3. 20 Percent Best Days Rate of Progress for Shenandoah 

Reasonable Progress Assessment

James River Face - Best 20% Days

Base G4a Projections, 12 km grid, New IMPROVE Equation

12.4

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)

Observation Method 1 Prediction

Baseline = 14.2 dV

Figure 8.1-4. 20 Percent Best Days Rate of Progress for James River Face 
108-Virginia Regional Haze SIP 

8.2. Clean Air Interstate Rule Remand and Reasonable Progress Goals 

The RPG analysis described in Section 8.1 contains uncertainty even though the analysis was 

based on the best available data as of January of 2008. One major uncertainty was introduced 

when CAIR was remanded to EPA. Unless new regulations are promulgated that are as 

protective or more protective than CAIR, significant SO2 reductions in Virginia and the 

surrounding states may be unrealized in 2018. Since sulfate is the most important contributor to 

visibility impairment at the Shenandoah National Park and the James River Face Wilderness 

Area, the RPGs listed above may also not be realized if 2018 emissions from the EGU and nonEGU point source sector exceed the levels estimated in the Base G4a inventory. 

The current era of regulatory uncertainty makes predicting future emissions very difficult. Both 

EGU and non-EGU point source SO2 emissions will be affected, and most likely reduced, by a 

number of regulations that have been recently promulgated, recently proposed, or are slated for 

proposal in the near future. The following is a listing and short description of several of these 

regulatory actions: 

• The 2010 SO2 NAAQS, published on June 2, 2010, set a new 1-hour standard for 

SO2 of 75 ppb. This standard is significantly more stringent than the previous 

primary standard and has a compliance year of 2017. EPA is anticipating an 

approach for implementing the new 1-hour SO2 standard that would use 

monitoring and refined dispersion modeling of SO2 sources to determine 

compliance with the new standard. Such an approach may necessitate that a 

variety of control strategies be implemented on large sources of SO2 emissions. 

• The proposed MACT for industrial, commercial, and institutional boilers and 

process heaters at major sources was published on April 29, 2010. This proposal 

would reduce emissions of toxic air pollutants, including mercury, other metals, 

and organic air toxics, from new and existing applicable units. Controls on units 

to meet limitations for acid gases would have as a co-benefit the reduction of SO2

emissions from these types of units. 

• The CAIR replacement regulation, called the Transport Regulation, may provide 

additional future year SO2 emission reductions that will benefit visibility in Class 

I areas. 

• The as-yet-unpublished EGU MACT may have reduction of SO2 emissions as a 

co-benefit to the control of acid gases that are also HAPs. 

Other uncertainties are economic in nature. For instance, recent advances in the ability to extract 

natural gas from geological formations reduced the cost of natural gas in 2009 as compared to 

coal. This reduced price for natural gas encouraged the use of cleaner combined cycle EGUs 

over dirtier coal fired units. In 2009 less pollution was emitted overall due to a weak economy. 

Other factors that might impact future year emissions estimates from EGUs are the growing 

emphasis on Renewable Portfolio Standards, the increased federal funding for energy research, 

and the state and federal tax credits being offered for the purchase of energy efficient home 

appliances and equipment. 

Given these uncertainties, a high level of confidence cannot currently be placed on the 2018 

EGU point source emissions inventory projections for Base G4a. The Base G4a inventory 
109-Virginia Regional Haze SIP 

represents Virginia’s best estimate of future year emissions. If the Transport regulation is at least 

as stringent as CAIR, the Base G4a estimates should be conservative and provide a sound basis 

for the RPGs. 

Other data available for consideration are the 2008 20 percent worst days IMPROVE values 

provided by the VIEWS Trends Analysis tool located on the VIEWS website 

(http://views.cira.colostate.edu/web/Trends/). Average measurements for the 20 percent worst 

days in 2008 show visibility impairment of 25.56 dv for the James River Face Wilderness Area 

and 25.23 dv for the Shenandoah National Park. These values, which are approaching the 

visibility estimates for the uniform rate of progress in 2018, show that both areas are benefiting 

from existing programs. This same data set shows that sulfate contributions to each site’s 

visibility impairment dropped significantly in 2008. These encouraging results for 2008 may not 

necessarily be indicative of the beginning of a trend, but they do seem to support the modeling 

results showing that SO2 emission reductions are key for visibility improvement. Data from 

EPA’s Clean Air Markets website for facilities subject to the Acid Rain program show a marked 

downward trend in emissions for 2008 and 2009, as shown in Figure 8.2-1. Visibility 

impairment values for the year 2009 are expected to be available on VIEWS later this summer. 

Figure 8.2-1. Annual Emissions of SO2 from Acid Rain Program Units (Data from CAMD) 

During the mid course review, which is addressed in Section 11 and is due to EPA in 2012, this 

type of data evaluation will prove to be useful in understanding what changes, if any, need to be 

made to this plan for visibility improvement at the Shenandoah National Park and the James 

River Face Wilderness Area. 
110-Virginia Regional Haze SIP 

9. MONITORING STRATEGY 

The regional haze SIP is to be accompanied by a strategy for monitoring regional haze visibility 

impairment. Specifically, the regional haze regulation states at 40 CFR 51.308(d)(4): 

(4) Monitoring strategy and other implementation plan requirements. The State must 

submit with the implementation plan a monitoring strategy for measuring, characterizing, 

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

mandatory Class I Federal areas within the State. This monitoring strategy must be 

coordinated with the monitoring strategy required in §51.305 for reasonably attributable 

visibility impairment. Compliance with this requirement may be met through 

participation in the IMPROVE network. The implementation plan must also provide for 

the following: 

(i) The establishment of any additional monitoring sites or equipment needed to 

assess whether reasonable progress goals to address regional haze for all 

mandatory Class I Federal areas within the State are being achieved. 

(ii)-(vi) [Other implementation plan requirements that pertain to reporting and use 

of monitoring data and an emission inventory.] 

Such monitoring is intended to provide the data needed to satisfy four objectives: 

• Track the expected visibility improvements resulting from emissions reductions 

identified in this SIP. 

• Foster better understanding of the atmospheric processes important to haze. 

• Identify chemical species in the ambient particulate matter and relate them to 

emissions from sources. 

• Evaluate regional air quality models for haze and construct relative response 

factors for using those models. 

The primary monitoring network for regional haze, both nationwide and in Virginia, is the 

IMPROVE network. Given that IMPROVE monitoring data from 2000-2004 serve as the 

baseline for the regional haze program, the future regional haze monitoring strategy must 

necessarily be based on, or be directly comparable to, IMPROVE. The IMPROVE 

measurements provide the only long-term record available for tracking visibility improvement or 

degradation. Therefore, Virginia intends to rely on the IMPROVE network for complying with 

the regional haze monitoring requirement in the regional haze regulation. 

There are currently two IMPROVE sites in the Commonwealth. Table 9-1 shows the site 

designations for these monitors 

Table 9-1. IMPROVE Sites in Virginia 

Class I Area IMPROVE Site Designation 

Shenandoah National Park SHEN (1) 

James River Face Wilderness Area JARI (1) 
111-Virginia Regional Haze SIP 

In addition to the IMPROVE measurements, some ongoing long-term limited monitoring 

supported by Virginia and the Federal Land Managers provides additional insight into progress 

toward regional haze goals. Such measurements include: 

• An ozone monitor and an SO2 monitor are operated by the National Park Service 

at Shenandoah National Park. A continuous PM2.5 monitor is operated at 

Shenandoah National Park by VDEQ. 

• An ozone monitor is operated by the National Forest Service at James River Face. 

Additional haze-related measurements were made in Virginia in 2002-2005 as part of special 

monitoring studies by VISTAS. These studies were intended to better understand source 

contributions to PM2.5 mass and visibility. They included continuous monitoring of sulfate, 

nitrate, and carbon to better understand daily trends in PM2.5, detailed analyses of carbon 

collected on filters to identify source contributions to carbon, and additional analyses of sodium 

and ammonium on IMPROVE filter samples. 

In addition, Virginia operates a comprehensive PM2.5 network of the filter based Federal 

Reference Method samplers, continuous PM2.5 monitors, STN protocol filter based speciated 

samplers, and the continuous speciated particulate monitors described above. These PM2.5

measurements help Virginia characterize air pollution levels in areas across the Commonwealth, 

and therefore they aid in the analysis of visibility improvement in and near the Class I areas. 

Virginia will use the continuous speciation data from the sites discussed above to further the 

understanding of both PM2.5 and visibility formation and trends in Virginia. Virginia will 

operate the units discussed above as long as funds allow. 

The IMPROVE measurements are central to Virginia’s regional haze monitoring strategy. Any 

reduction in the scope of the IMPROVE network in Virginia would jeopardize the 

Commonwealth’s ability to demonstrate reasonable progress toward visibility improvement in its 

Class I areas. In particular, Virginia’s regional haze strategy relies on emission reductions from 

programs that occur on different time scales and will most likely not be spatially uniform. 

Monitoring at every Class I area is important to document the different air quality responses to 

the emissions reductions. 

Each of the current IMPROVE monitors in Virginia represents a different airshed; therefore, 

reduction of the IMPROVE network by shutting down one of these monitoring sites would 

impede the ability to track progress toward reducing haze in the affected Class I area. In the 

event this occurs, Virginia, in consultation with the USEPA and relevant Federal Land 

Managers, will develop an alternative approach for meeting the tracking goal, perhaps by 

seeking contingency funding to carry out limited monitoring or by relying on data from nearby 

urban monitoring sites to demonstrate trends in speciated PM2.5 mass. 

Data produced by the IMPROVE monitoring network will be used nearly continuously for 

preparing the 5-year progress reports and the 10-year SIP revisions, each of which relies on 

analysis of the preceding five years of data. Consequently, the monitoring data from the 

IMPROVE sites needs to be readily accessible and up to date. Presumably, IMPROVE will 
112-Virginia Regional Haze SIP 

continue to process information from its own measurements at about the same pace and with the 

same attention to quality as it has shown in the recent past. The VIEWS web site has been 

maintained by VISTAS and other RPOs to provide ready access to the IMPROVE data and data 

analysis tools. Virginia is encouraging VISTAS and the other RPOs to maintain VIEWS or a 

similar data management system to facilitate analysis of the IMPROVE data. 

10. INTERSTATE CONSULTATION 

The VISTAS states have jointly developed the technical analyses to define the visibility 

improvement by 2018 under existing federal and state regulations compared to the uniform rate 

of progress, SO2 AoI for each Class I area, and methods to prioritize contributions from 

individual sources within the AoI. The states collectively accept the conclusions of these 

analyses. 

In December 2006 the VISTAS State Air Directors held their first formal consultation meeting to 

review the Base G modeling results and the SO2 AoI analyses. The Air Directors agreed to look 

at reasonable control measures for sources on the lists for the SO2 AoI. Each state would 

consider sources within their state and would identify sources in neighboring states that they 

would like to have that neighboring state consider. States acknowledged that the review process 

would differ among states since some Class I areas are projected to see visibility improvements 

near the uniform rate of progress while most Class I areas are projected to have greater 

improvements than the uniform rate of progress. 

 In May 2007, the VISTAS State Air Directors met for their second formal interstate 

consultation. States shared their lists of sources in their state and neighboring states for each 

Class I area. They also shared their criteria for listing sources and their plans for further 

interstate consultation. 

Virginia has evaluated the impact of Virginia sources on Class I areas in neighboring states and 

determined that there are no additional reasonable control measures that should be implemented 

to mitigate impacts in Class I areas in neighboring states, with the exception of the 

MeadWestvaco Packaging Resource Group as explained in Section 7.7.5.2.2. Virginia has 

consulted with the respective states regarding evaluations showing no cost-effective controls 

available for those units contributing at least one percent to visibility impairment at Class I areas. 

Consultation correspondence and documentation may be found in Appendix J. 

The Mid-Atlantic/Northeast Visibility Union (MANE-VU) states of New Jersey and New 

Hampshire sent letters to Virginia in the spring of 2007 stating that based on 2002 emissions, 

Virginia contributed to Class I visibility impairment in those states. The letters from these states, 

and responses from Virginia, are included in Appendix J. MANE-VU states asked Virginia to 

participate in further consultation with these states, and Virginia participated in a consultation 

meeting between VISTAS and MANE-VU in Atlanta, Georgia, on August 20, 2007. 

The MANE-VU states identified 167 stacks, 8 of which are located in Virginia. These 8 stacks 

identified by MANE-VU vent the emissions from 10 EGUs. The Virginia stacks, units, and 

emissions are identified in Table 10-1. MANE-VU has asked states to reduce the SO2 emissions 

from these units by 90 percent. MANE-VU also requested a control strategy to provide a 28 

percent reduction in SO2 emissions from sources, other than EGUs, that would be equivalent to 
113-Virginia Regional Haze SIP 

their proposed low sulfur residential fuel oil strategy. Many of the units and stacks listed in 

Table 10-1 will have reduced emissions by 90 percent or more in 2018. Table 10-1 demonstrates 

that these units are expected to reduce emissions from 2002 levels by approximately 82 percent 

in 2018. The information in Table 10-1 is based on federal consent decrees, knowledge of owner 

control program installation timelines, and IPM projections. 

Virginia’s non-EGUs are predicted to emit 57,790 tons of SO2 in 2018. See Appendix D. 

MANE-VU requested a 28 percent reduction in these emissions, or approximately 16,181 tpy of 

reductions. Two EGUs in Virginia not on the MANE-VU listing of 167 stacks already have in 

place enforceable conditions that, while not originally intended for this purpose, should facilitate 

the bulk of the requested reductions. Dominion – Bremo Power Station (ORIS 3796) and Mirant 

Potomac River Generating Station (ORIS 3788) have requirements limiting their SO2 emissions 

in 2018, and these emission reductions were not included in the reasonable progress modeling 

exercise that developed the RPGs listed in Section 8.1. These requirements came into place after 

the reasonable progress goal modeling was performed. 

Bremo Power Station is scheduled to convert to a cleaner fuel two years after the commencement 

of commercial operation of the Virginia City Hybrid Energy Center. This conversion is a 

requirement in the July 1, 2008, PSD permit for the Energy Center. The Energy Center is 

expected to begin commercial operation in 2013, so the fuel switch at Bremo should take place 

in the 2015 time frame, well before MANE-VU’s requested 2018 deadline. It should be noted 

that State Corporation Commission approval must be gained for the fuel switch. Bremo Power 

Station emitted approximately 12,000 tons of SO2 in 2002 and was expected, prior to the permit 

requirement for the fuel switch, to emit over 8,800 tons of SO2 in 2018. The switch to a fuel 

with little or no sulfur would eliminate nearly all these emissions. 

In 2008 the Mirant Potomac River Generating Station received a permit limiting annual SO2

emissions from the facility to 3,813 tpy and requiring the use of sorbent injection for SO2

control. This limit was upheld by the Virginia Supreme Court. In 2002, this facility emitted 

over 15,000 tons of SO2. Prior to the implementation of this limit, the facility was expected to 

emit 12,000 tons of SO2 in 2018. The permit requirements represent an 8,100 tpy reduction in 

2018 SO2 emissions from this facility. 

These two facilities alone provide reductions of 16,900 tons of SO2 annually from the 2018 

expected emission inventory. As noted in Section 7.7.5.2.2, reasonable progress requirements 

imposed upon one industrial source are expected to result in over 1,000 tons of SO2 emission 

reductions by 2018. Additional SO2 reductions in both the EGU and non-EGU point inventories 

can reasonably be expected due to the renewed emphasis placed on energy efficiency and 

renewable energy source development. Based on this analysis, the Commonwealth of Virginia 

should easily meet the target SO2 reduction set forth in MANE-VU’s request. 

MANE-VU’s analysis examined 2002 emissions from the 8 stacks and 10 units in Virginia to 

determine estimated visibility impacts from these units. In contrast, the analysis conducted by 

VISTAS, as described in Section 7, focused on 2018 emission estimates and 2018 calculated 

visibility contribution. Evaluation of this data for Brigantine shows that no Virginia stack 

contributes 1 percent or more to the calculated visibility impairment in that Class I area. Table 
114-Virginia Regional Haze SIP 

10-2 presents this data. Of the top 25 units on this listing, 23 units are controlled, will be 

controlled, have reduced emissions through fuel switches, are temporarily shut down, or are 

predicted by IPM to be shutdown by 2018. The conclusion that can be drawn from Table 10-2 is 

that existing and future air pollution control programs in Virginia should reduce the already 

minute expected 2018 SO2 point source impacts from Virginia emissions on Brigantine to even 

lower levels. 

11. COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN REVISIONS 

40 CFR 51.308(f) requires a state to revise its regional haze plan and submit a plan revision to 

USEPA by July 31, 2018 and every ten years thereafter. In accordance with the requirements 

listed in 40 CFR 51.308(f), Virginia commits to revising and submitting this regional haze plan 

by July 31, 2018, and every ten years thereafter. 

In addition, 40 CFR 51.308(g) requires periodic reports evaluating progress towards the RPGs 

established for each mandatory Class I area. In accordance with the requirements listed in 40 

CFR 51.308(g), Virginia commits to submitting a report on reasonable progress to USEPA every 

five years following the initial submittal of the SIP. The report will be in the form of a SIP 

revision. The reasonable progress report will evaluate the progress made toward the reasonable 

progress goal for each mandatory Class I area located within Virginia and in each mandatory 

Class I area located outside Virginia that may be affected by emissions from within Virginia. 

Review of the reductions achieved in the point EGU and point non-EGU emissions inventory 

may be included with the first periodic report. Consultation on the periodic reports will include 

early involvement of FLMs in the periodic review process. Additionally, should revisions be 

needed to the regional haze plan, the FLMs will be offered the opportunity for review of such 

revisions prior to the revisions being made final. 

The requirements listed in 40 CFR 51.308(g) include the following: 

• Description of the status of implementation. 

• Summary of emission reductions achieved thus far, including the status of 

implementation of the CAIR compliance plans for EGUs compared to the control 

assumed in the modeling. (Virginia recognizes that the 2018 projections of EGU 

controls from the IPM runs represent one solution to how the CAIR requirements 

will be met. Additionally, remand of the CAIR rule could potentially change 

outcomes from these regulations. By the time of the first periodic report, the 

Virginia anticipates that the actual compliance strategy for the various utility 

companies will be much more defined and that USEPA will have published the 

new transport rule. An assessment of those actual compliance plans will be done 

for the first periodic report.) 

• Assessment of changes in visibility conditions at each Class I area (current vs. 

baseline) expressed as 5-year averages of annual values for 20 percent best and 

worst days. 

• Analysis of emission changes over the 5-year period, identified by source or 

activity. 
115-Virginia Regional Haze SIP 

Table 10-1. Virginia Electric Generating Units Identified by MANE-VU 

Plant ORIS ID/ Inventory ID Unit MW 2002 SO2 Emissions (tons) SO2 controls Control Installation Date SO2 Control Efficiency 

2018 

Projected 

SO2

Emissions 

(tons) 

Dominion – 3 185 9,233 Low S coal 2007 40% 2,766 Chesapeake Power Station 

3803 51-550-00026 4 239 12,505 Low S coal 2007 40% 4,155 

IPM predicts thescrubbers in 201

4 188 9,416 FGD 2010 90% 744 5 359 19,129 FGD 2010 90% 1,561 

Dominion – Chesterfield Power Station 

3797 51-041-0002 

6 694 38,088 FGD 2008 95% 3,633 

AEP – Clinch River 3775 1 238 8,158 Low S coal --- --- 5,430 

51-167-00003 2 238 8,115 Low S coal --- --- 5,494 

Based on federa(units 1, 2, and 3beginning in 20

1 173 11,551 FGD 2010 90% 652 2 182 12,426 FGD 2018 90% 617 

Dominion – Yorktown Power Station 

3809 51-199-00001 

3 875 11,498 Predicted by IPM to shutdown in 2018 Oil fired boiler. 

ESTIMATED EMISSIONS TOTAL: 140,119 25, 052 Based on federa

of owner controprojects, these uapproximately 82018. 
116-Virginia Regional Haze SIP 

Table 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to Brigantin

FIPS 

County Plant ID Plant Point ID SIC (2002 G) (2018 G) Distance (km) Q/d RT Max** Q/d*RTMax Per

153 00002 DOMINION - POSSUM POINT 5 4911 4,368 6,100 265.83 22.95 26.98 619.191 101 00001 STONE CONTAINER CORP (D/B/A SMURFIT-STON 2 2611 3,562 4,006 296.83 13.50 23.79 321.165 093 00006 INTERNATIONAL PAPER COMPANY 4 2621 3,720 4,299 377.94 11.38 27.29 310.5602 510 00003 POTOMAC RIVER GENERATING STATION 1 4911 2,245 2,400 235.03 10.21 26.98 275.4658 510 00003 POTOMAC RIVER GENERATING STATION 2 4911 2,384 2,400 235.03 10.21 26.98 275.4658 510 00003 POTOMAC RIVER GENERATING STATION 3 4911 3,514 2,400 235.03 10.21 26.98 275.4658 510 00003 POTOMAC RIVER GENERATING STATION 4 4911 3,669 2,400 235.03 10.21 26.98 275.4658 510 00003 POTOMAC RIVER GENERATING STATION 5 4911 3,445 2,400 235.03 10.21 26.98 275.4658 199 00001 DOMINION - YORKTOWN POWER STATION 6 4911 11,551 2,775 305.95 9.07 27.29 247.5203 099 ORIS54304 SEI BIRCHWOOD POWER FACILITY 1 4911 0 2,789 282.04 9.89 25.00 247.25 041 00002 DOMINION - CHESTERFIELD POWER STATION 8 4911 38,088 3,633 345.27 10.52 19.94 209.7688 065 00001 DOMINION - BREMO POWER STATION 2 4911 7,993 6,253 387.00 16.16 12.92 208.7872 670 00055 JAMES RIVER COGENERATION COMPANY 1 4911 2,490 3,221 345.20 9.33 16.45 153.4785 670 00055 JAMES RIVER COGENERATION COMPANY 2 4911 2,563 3,193 345.20 9.25 16.45 152.1625 093 00006 INTERNATIONAL PAPER COMPANY 3 2621 1,679 1,907 377.94 5.04 27.29 137.5416 199 00004 GIANT YORKTOWN REFINERY 26 2911 984 1,290 306.01 4.21 27.29 114.8909 670 00058 COGENTRIX HOPEWELL 1 4911 28 2,209 344.54 6.41 16.45 105.4445 
117-Virginia Regional Haze SIP 

Table 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to Brigantin

FIPS 

County Plant ID Plant Point ID SIC (2002 G) (2018 G) Distance (km) Q/d RT Max** Q/d*RTMax Per

670 00058 COGENTRIX HOPEWELL 2 4911 29 2,209 344.54 6.41 16.45 105.4445 093 00006 INTERNATIONAL PAPER COMPANY 6 2621 1,154 1,349 377.94 3.57 27.29 97.4253 041 00002 DOMINION - CHESTERFIELD POWER STATION 6 4911 19,129 1,561 345.27 4.52 19.94 90.1288 740 ORIS10071 COGENTRIX PORTSMOUTH GEN1 4911 0 1,070 333.78 3.20 27.29 87.328 740 ORIS10071 COGENTRIX PORTSMOUTH GEN2 4911 0 1,070 333.78 3.20 27.29 87.328 065 00001 DOMINION - BREMO POWER STATION 1 4911 4,371 2,614 387.00 6.75 12.92 87.21 550 00026 DOMINION - CHESAPEAKE 4 4911 12,505 1,039 340.98 3.05 27.29 83.2345 199 00004 GIANT YORKTOWN REFINERY 7 2911 677 820 306.01 2.68 27.29 73.1372 093 00006 INTERNATIONAL PAPER COMPANY 17 2621 900 1,010 377.94 2.67 27.29 72.8643 041 00078 DUPONT DE NEMOURS E I & COMPANY INC JAME 2 2819 1,145 1,117 344.34 3.24 19.94 64.6056 670 00003 STONE CONTAINER CORPORATION HOPEWELL 2 2631 1,188 1,334 344.26 3.87 16.45 63.6615 093 00006 INTERNATIONAL PAPER COMPANY 7 2621 737 861 377.94 2.28 27.29 62.2212 041 00081 PHILIP MORRIS USA INC - PARK 500 3 2141 1,070 1,062 341.81 3.11 19.94 62.0134 023 00003 ROANOKE CEMENT COMPANY 22 3241 2,885 3,976 532.37 7.47 8.12 60.6564 199 00001 DOMINION - YORKTOWN POWER STATION 5 4911 12,426 652 305.95 2.13 27.29 58.1277 670 00026 HONEYWELL NYLON INC- HOPEWELL 10C 2869 1,491 1,198 344.48 3.48 16.45 57.246 550 00026 DOMINION - CHESAPEAKE 3 4911 9,233 692 340.98 2.03 27.29 55.3987 199 00001 DOMINION - YORKTOWN POWER STATION 3 4911 11,498 617 305.95 2.02 27.29 55.1258 199 00004 GIANT YORKTOWN REFINERY 6 2911 477 579 306.01 1.89 27.29 51.5781 041 00081 PHILIP MORRIS USA INC - PARK 500 2 2141 823 817 341.81 2.39 19.94 47.6566 101 00001 STONE CONTAINER CORP (D/B/A SMURFIT-STONE) 5 2611 504 590 296.83 1.99 23.79 47.3421 
118-Virginia Regional Haze SIP 

Table 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to Brigantin

FIPS 

County Plant ID Plant Point ID SIC (2002 G) (2018 G) Distance (km) Q/d RT Max** Q/d*RTMax Per

041 00002 DOMINION - CHESTERFIELD POWER STATION 4 4911 9,416 744 345.27 2.15 19.94 42.871 085 00042 BEAR ISLAND PAPER COMPANY LLC 1 2621 470 528 317.85 1.66 23.79 39.4914 550 00026 DOMINION - CHESAPEAKE 1 4911 5,261 461 340.98 1.35 27.29 36.8415 670 00003 STONE CONTAINER CORPORATION HOPEWELL 1 2631 766 760 344.26 2.21 16.45 36.3545 670 ORIS10771 LG&E WESTMORELAND HOPEWELL GEN1 4911 0 758 345.55 2.19 16.45 36.0255 550 00026 DOMINION - CHESAPEAKE 2 4911 5,307 447 340.98 1.31 27.29 35.7499 019 00003 GEORGIA PACIFIC CORP BIG ISLAND PLT 1 2631 1,090 1,223 478.58 2.56 12.76 32.6656 760 00308 PHILIP MORRIS USA MANUFACTURING CENTER 1 2111 532 528 341.69 1.54 19.94 30.7076 550 00038 PERDUE FARMS INCORPORATED 5 2075 371 368 337.09 1.09 27.29 29.7461 101 00001 STONE CONTAINER CORP (D/B/A SMURFIT-STON 4 2611 315 365 296.83 1.23 23.79 29.2617 093 00006 INTERNATIONAL PAPER COMPANY 5 2621 286 326 377.94 0.86 27.29 23.4694 760 ORIS54081 COGENTRIX OF RICHMOND INCORPORATED GEN1 4911 0 358 343.41 1.04 19.94 20.7376 760 ORIS54081 COGENTRIX OF RICHMOND INCORPORATED GEN2 4911 0 358 343.41 1.04 19.94 20.7376 760 ORIS54081 COGENTRIX OF RICHMOND INCORPORATED GEN3 4911 0 358 343.41 1.04 19.94 20.7376 760 ORIS54081 COGENTRIX OF RICHMOND INCORPORATED GEN4 4911 0 358 343.41 1.04 19.94 20.7376 031 00156 DOMINION - ALTAVISTA POWER STATION 1 4911 50 778 495.79 1.57 12.76 20.0332 083 00046 DOMINION - CLOVER POWER STATION 2 4911 1,000 699 471.38 1.48 13.43 19.8764 083 00046 DOMINION - CLOVER POWER STATION 1 4911 982 691 471.38 1.47 13.43 19.7421 093 00006 INTERNATIONAL PAPER COMPANY 8 2621 218 255 377.94 0.67 27.29 18.2843 095 00022 OWENS-BROCKWAY GLASS CONTAINER 21 3221 194 256 309.26 0.83 21.72 18.0276 069 00034 GLOBAL STONE CHEMSTONE CORPORATION 22 3274 263 345 313.98 1.10 15.22 16.742 117 ORIS52007 MECKLENBURG COGENERATION FACILITY GEN1 4911 0 487 479.28 1.02 13.70 13.974 
119-Virginia Regional Haze SIP 

Table 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to Brigantin

FIPS 

County Plant ID Plant Point ID SIC (2002 G) (2018 G) Distance (km) Q/d RT Max** Q/d*RTMax Per

117 ORIS52007 MECKLENBURG COGENERATION FACILITY GEN2 4911 0 487 479.28 1.02 13.70 13.974 143 00003 BURLINGTON INDUSTRIES INCORPORATED HURT 1 2262 490 487 500.00 0.97 12.76 12.3772 081 00002 GEORGIA PACIFIC CORP JARRATT PLANT 6 2493 303 301 396.69 0.76 15.52 11.7952 019 00003 GEORGIA PACIFIC CORP BIG ISLAND PLT 2 2631 251 286 478.58 0.60 12.76 7.656 143 00100 OWENS-BROCKWAY GLASS CONTAINER INC 21 3221 215 284 533.04 0.53 12.76 6.7628 
120-Virginia Regional Haze SIP 

• Analysis of any significant changes in or out of the state which have impeded 

progress. 

• Assessment of the sufficiency of the implementation plan to meet RPGs. 

• Review and any modifications to the visibility monitoring plan. 

All requirements listed in 40 CFR 51.308(g) shall be addressed in the SIP revision for reasonable 

progress. 

Virginia also commits to ongoing consultation with the FLMs throughout the implementation 

process, including annual discussion of the implementation process and the most recent 

IMPROVE monitoring data and VIEWS data. 

There are several technical improvements that are recommended in the emissions inventory and 

air quality models that are used to support regulatory decisions for regional haze. These 

improvements recommended, as funding is available, to support the next long term strategy. The 

following is a summary. Appendix K contains a fuller discussion of possible technical 

improvements. 

First and foremost, continued improvements are needed in the integrated one-atmosphere air 

quality models that are used to project air quality responses to emissions reductions. As the 

understanding of partitioning between gaseous and aerosol phases improves, this understanding 

needs to be reflected in the models. Improvements can also be made in how the models handle 

individual pollutants. Sulfate performance for the CMAQ regional air quality model is good 

overall. However, sulfate deposition is frequently overestimated in the models, particularly in 

the summer months. CMAQ’s processes also should be reviewed for sulfate formation over 

water. Nitrate is overestimated by the model in the winter and underestimated in the summer, 

although summer monitored values of nitrate are very low. Additional improvements in seasonal 

allocation of ammonia emissions would improve model estimates of ammonium nitrate 

formation. Organic carbon is generally underestimated in the summer months. Improvements 

are needed in the characterization of both primary carbon emissions and formation of secondary 

organic carbon. 

Other improvements needed include better tools for organic carbon source apportionment, and 

more consistent measurement techniques between rural and urban monitoring networks. To 

better understand the contribution of fire from natural forest fires, prescribed burning, land 

clearing, and agricultural burning, states need improved recordkeeping. Additional 

improvements to international emissions inventory are also needed, to improve understanding of 

boundary conditions for modeling domains and of the contributions from international emissions 

to pollutant concentrations at the VISTAS Class I areas. 

12. DETERMINATION OF ADEQUACY OF THE EXISTING PLAN 

Depending on the findings of the five-year progress report, Virginia commits to taking one of the 

following actions listed in 40 CFR 51.308(h). The findings of the five-year progress report will 

determine which action is appropriate and necessary. 
121-Virginia Regional Haze SIP 

• Virginia determines that the existing SIP requires no further substantive revision 

in order to achieve established goals. Virginia notifies the Administrator that 

further revision of the SIP is not needed at this time. 

• Virginia determines that the existing SIP may be inadequate to ensure reasonable 

progress due to emissions from other states which participated in the regional 

planning process. Virginia notifies the Administrator and the states that 

participated in regional planning. Virginia collaborates with states through the 

regional planning process to address the SIP’s deficiencies. 

• Virginia determines that the current SIP may be inadequate to ensure reasonable 

progress due to emissions from another country. Virginia provides notification, 

along with available information, to the Administrator. 

• Virginia determines that the existing SIP is inadequate to ensure reasonable 

progress due to emissions within the state. Virginia will revise its SIP to address 

the plan’s deficiencies within one year 
ENCLOSURE 2 

CERTIFICATION OF PUBLIC PARTICIPATION ACTIVITIES 

AND COMPLIANCE WITH 

STATE ADMINISTRATIVE PROCEDURES 

As required by 40 CFR 51.102(f) and Section 2.1(b) and (d) through (g) of Appendix V 

of 40 CFR Part 51, the following information regarding public participation activities and 

compliance with state administrative procedures is provided. 

PUBLIC PARTICIPATION ACTIVITIES

As required by 40 CFR 51.102(a), a hearing to accept public testimony concerning a 

proposed revision to the Commonwealth of Virginia State Implementation Plan was held 

in the second floor conference room A, Department of Environmental Quality, 629 East 

Main Street, Richmond, Virginia, at 10:00 a.m. on September 16, 2010. 

In the National Capital Interstate Air Quality Control Region, the public was given notice 

of the hearing in the Washington Examiner on August 18, 2010 (copy attached). 

Similar notices were placed in at least one paper of general circulation in each of 

Virginia's other Air Quality Control Regions. As required by Section 2.1(g) of Appendix 

V of 40 CFR Part 51, the hearing was held in accordance with the information found in 

the public notice, and according to the state's laws. 

The Regional Administrator for the U.S. Environmental Protection Agency was notified 

of the hearing, as was each local air pollution control agency which will be significantly 

impacted by the revision and is located in the affected Air Quality Control Regions. In 

addition, the District of Columbia, Maryland and Tennessee, which share affected 

interstate Air Quality Control Regions with Virginia, were notified of the hearing. These 

notifications follow the requirements of 40 CFR Part 51.102(d). 

The complete record of the hearings, along with any testimony received and responses 

thereto, is located at the Air Division of the Department of Environmental Quality. The 

Department contact to access this information is the Director, Air Division. A summary 

of the testimony received and responses thereto is attached. 

COMPLIANCE WITH STATE ADMINISTRATIVE PROCEDURES

As required by § 2.2-4031 of the Code of Virginia, notice of the hearing was given to the 

public in the Virginia Register on August 30, 2010 (copy attached). 

TEMPLATES\SIP-PLAN\PLN02 

SIP\REGIONAL HAZE\PLAN\RH-SIP-2.DOC 
PROOF OF PUBLICATION 

NGTON • 

I. Alicia Willis, oCThe Washington Examiner, (Virginia Edition) a newspaper in the area 

of Virginia, published in the English language and located in the Virginia area, and 

entered in a newspaper ofrecord according 10 the Laws and Regulations oftbe United 

States of America for 52 successive weeks or more prior to the issue of August 18, 2010 

certify that the notice of: 

ClelD AJr Act 

DEQ- Alr Quality Division 

Attached 0 bas been published on August 18, 201 

Alicia Wil 5 

18 day of August 2010 

Adverti~ent#: 696787 

End Date: August 18,1010 

Run Dates: August 18,2010 

Clean Air Act 

DEQ- Air QUality Division 

lOI S 15'" SIJ'eet NW, Suite 500, WaabiD&toD. DC 2OOOS . 6850 Venar Ct:IIIer)oI Boor, SpriD&fie\d., VA 

22151 

202.4S9.4923 pbooc . 202.903.2018 w 

Official Court Document 

Retain For Your Records 

DO NOT DISCARD 
=:~o>uAA~= (1IIM1"....1I11 ~($IoI) .... ~IO' ___ 

~,:~~._ ... ~n::~,= _ .!IO"I 

..... ' .. ""'~IW'1I' 
GENERAL NOTICES/ERRATA 

AIR POLLUTION CONTROL BOARD 

State Implementation Plan Revision - Visibility 

Impairments in Federal Class I Areas 

Notice of action: The [)cpanmenl of Environmental Quality 

(DEQ) is seeking comments and armouncing a public hearing 

on a proposed plan to improve vi~ihility impairment in 

federal Cia$:! I ar<':as. federal Cla$$ I arcas arc defined in the 

Clean Air Act as national parks over 6,00CI Heft'S lind 

wilderness areas and memorial parks over 5,000 acres, 

o:slablishcd as of 1971. Vil'£inia is home (0 two such areas, 

the ShenandOAh National Park and the James River Face 

Wilderness Area. If adopted, the Commonwealth intends to 

submit the plan a~ II rcvi;;ion to the Commonwealth of 

Virginia St:ltc Implcmcnt:lIion Plan (SIP) in accordance with 

the requirements of § 110(10) amI § 169 A of the fedeml Clean 

Air Act (CAA). The SII' is the pl:m developed by the 

Ccmmonwealth in order to fulfill its res(Xlnsibilities under the 

federal CM to attain and maintain the ambient air quality 

~tilIldards prcm lgated by Ihe U.S. EnvirofUTlental Proteclion 

Agency (EPA) under the Act 

Purpose of notice; ORQ ~ :£eking comments on the overnll 

plilIl. and on the issue of whether the plan will enable the 

Commonwealth to meet fedcrnl requirements for C<lntmJling 

air JXlllutants that reduce visibility in Classl areas. 

Public comment period: Augu.~t 16, 2010, to September 11, 

2010. 

Public hearing: September 16. 2010 - 10 a.m.- 2nd Floor 

Conference Room A, Department of Environmental Quality, 

629 East Main Street, RiclunDnd, VA 

Description of proposal : Virginia u; required to demonstrnte 

reasonable progress toward meeting the national goal of a 

return 10 naturol visibilily corn.!itioru; by 2064 for each CI95s I 

area within the state and for Class I areas located outside the 

state Ihal mlly be affecto:d by emissions from sources within 

the state. The ~n establishes bR.~eline vi~ibility conditim\'l 

for 2000.2004. natural background visibility conditions in 

2064, and Ihe rate of unifonn progress (glio:kpath) between 

haseline and background conditions. The pl~n est.1blishcs 

reasonable progress goals (RPGs), which provide for 

reallOllable progre5.~ towan:! acbieving naruml visibility 

conditions. provide for impmvement in visibility for the most 

impaired day~ over th~ period of the impl~mentation pl~ 

and ensure no degradation in visibility for the least impaired 

days over the same period. 

In order to ensure th~t visibility gools ~re properly met and 

set, the regional haze SIP includes determinations_ for each 

Clas.~ I arca, of tbe baseline visibility eondition..~ for the most 

impaired and least impaireJ days. The SIP also contains 

supporting docwnentation for all required analyses used to 

calcul~t.:: the degree of visibility impairment for the most 

impaired and least impaired days. In addition, the plan 

inelude~ a monitoring !;I.ratcgy for measuring. ch~racterizing, 

and reporting of regional haze visibility impairment thai is 

rcpre..~en ~tive of all la~~ I areas within tbc sme. 

This first sci of RPGs must be met through me!lSures 

containcd in the stlllC'S long-tcnn stT3tegy covering the period 

from the present WItil 201 S. The 101l.g~term strategy includes 

enforceeble emis:;ions lim itations, compliance s<;;hedule~, and 

other me"""r"" "" ne"""""ry to "chi"ve the RPO", inc1lJrline 

all controls required or e.>;pe<;led under all federal and state 

rcgulation..~ by 2018. During development of the ong~term 

strategy. the Commonwealth considered specific faclOrs such 

liS the ebovementioned ongoing control progrnms, mcasure; 

to mitigate constmction Bctivities, source retirement and 

replecemenl schedules, smoke man~gemenl progrwns for 

agriculture and fo c~try, and enforceability of ~cifie 

measures 

In addition, the pl:m dcmon..~lrates implementation of best 

available retrofitteclmology (BART) requirements, including 

a determination of BART fo,' each source that emits Hny air 

pollutant that may reasonably be Mticipated to cause or 

contribule 10 any impairmenl of visibility in any Cla:ss I are~. 

BART-cligible sources arc !IOurees in 26 ~cific SQurce 

c3to:gories that began operation within a I S-yc3r penod prior 

to enactment of the 1971 CAA. Emi5.~ion Iimit9tion..~ 

representing BART and schedules for compliance with 

BART for each source subject to BART are includ~d in the 

long~teml strategy. 

Federal infomJation: This noticc is being gi\'en to s~tisfy the 

public participation requiremenL~ of federal n.:gulation..~ (40 

CFR 51.102) Tbe propoSilI will be submitted !IS a revision to 

tbe Commonwea ltb of Virgini~ SIP under § 110(~) 3nd 

§ 169A of the federal CM in accordance with 40 CFR 

51.10·t. It is planned to submit all provisi= of the propooal 

as a revision to the Commonwealth of Virginia SIP. 

C()II.'3ultation with federal land managcrs (FLMs): As 

provided in 40 CFR 51302(bX2), the FLMs were given the 

opportunity to comm .... nl on the proposed plan on Octob<.-r I, 

2007, and M~y 19, 2010. FLMs were also given opponunity 

to comment on BART requirements. FLM comments on 

BART documents lire located III Appendi~e5 H-%, H-9f, H9i, HIOb-P, and H-IOb-S. DEQ responses to these comments 

are located in Appendices II-%, H-9h, 11-9j, H-ICb-R. and IIIOh.T. FLM eommcnL~ on the entire SIP are loc~ ed in 

Appendices J-3, J-4, J-5. and J-6. OEQ responses to these 

commenlS are located in Appendices J_ 7 and J-8 

How to comment: DEQ Hccepl~ written comments by email, 

fax, and postal mail, In order to be considered, comments 

must include the full nilllle, addn!ss, and telephone nWllber of 

Ihe person commenting and be receil'ed by the DEQ contact 

listed below by the last day of the comment period. Both oral 

and written comments are 3ccepted at the pllblic hearing. 

DEQ prefers that comments be provided in writing, along 

Volume 2t5, Issue 215 Vi"ginia Register of Regulations Augus/30, 2010 

2901 
General Notices/Errata 

with any supporting docwm::nts or exhibits. All testimony, 

e.>JJihilS, and documents re<:eived ilIC part of the public 

record. Please note this prolXlsed plan is being concurrently 

reviewed by EPA. 

To review the proposal: The proposal and any suppo:xting 

documents an: available on the DEQ Air Pub1i(; Notices for 

Plans website (http}/w\\'w.dell_virginia.gov/air/permittingl 

planolcs.html). The documents may also be obt.-'lincd by 

contacting the DEQ representative named below. The public 

may review the documents between 8JOa,m. and 4:30p,m. 

of each businc:lS day until the d~e of the public comment 

period at the fol1owing DEQ locations: 

1) Main Street Offi ce, 8th Floor, 629 E. Main St, 

Richmond VA, telephone (804) 698-4070, 

2) Southwc,:;t Regional Office, 355 Dcadmorc St, 

Abingdon VA. tckphonc (540) 676.4800, 

3) Blue Ridge Regional Office, ROBnoke LOCBlion. 3019 

Peters Creek Rd., Roanoke VA, telephone (540) 562·6700, 

4) Blue Ridge Regional Office, Lynchburg Location, 1705 

Timberlake Rd., Lynchburg VA, telephone (804) 582· 

5120, 

S) Vlliley Regional Office. 4411 Early Rd., Hllrrisooburg 

VA, telephone (540) 574·7800, 

6) Piedmont Regional Office, 4949·A Cox Rd., Glen Allen 

VA, telephone (804) 527-5020, 

7)Northern Regional Office, 13901 Crown Court, 

Woodbridge VA, telephone (703) 583-3800, and 

8) Tidewater Regional Office. 5636 Southern Blvd., 

Virginia &ach, VA telephone (757) 518-201X.l. 

Contact !nfonnation: Doris A. McLeod, Department of 

Environmental Quality, 629 F.a.~t Main Street, P.O. 80.'\ 1105, 

Richmond, VA 23218, l\:1cphonc (804) 698-4197, FAX (804) 

698-4510, or email dori.~.l1lc1cod@dcq virginL-l.g<N . 

Vo/uroo 26. Issue 26 Vr ginia Register of Regulations 

21102 

August 30, 2010 
ENCLOSURE 3 

RECORD OF HEARING AND SUMMARY OF TESTIMONY 

As required by 40 CFR 51.102(e), the complete record of the hearing, along with a list 

of witnesses and the text of the written presentations or summary of the oral 

presentations, is located at the Air Division of the Department of Environmental Quality. 

The department contact to access this information is the Director, Air Division. 

The state did not receive testimony on this particular revision. 

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