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



# R e g i o n a l H a z e S t a t e I m p l e m e n t a t i o n P l a n

F o r V i

r

g i n i a C l

a s s I A r e a s

– S h e n a n d o a h N a t i o n a l P a r k a n d J a m e s R i v e r F a c e W i l d e r n e s s A r e a

Virginia Department of Environmental Quality
Air Division

Finali-Virginia Regional Haze SIP 

## Preface: This document contains summaries of the technical analyses th at will be used by Virginia to support the regiona l 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 impairme nt is considered the “best unde rstood and most easily measured effect of air pollution.” Regional haze is caused by sources and activitie s that emit these fine particles and their precursors ove r 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, espe cially in Class I areas. In 1999, the U.S. Environmental Protection Agency (USEPA) fi nalized 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 to gether to improve visibility in 156 national parks and wilderness areas, including th e 18 Class I areas located in th e area covered by the Visibility Improvement – State and Tribe Association of the Southeast (VISTAS). The States are required to develop and implement air qual ity protection plans (state imple mentation plans, or SIPs) to reduce the pollution that causes visibility impairment.

These plans should establish goals and emissi on reduction strategies based on trends from various sources including area source emissions , mobile source emissi ons (both on-road and non-road emissions), commercial marine emi ssions, biogenic emissions, and wildfire and agriculture emissions. Under the regional haze regulat ion, states are required to develop SIPs to reduce visibility impairment with the intent that by 2064, the visibility in th e 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 fo r these State plans. The produc ts of the regional planning organizations will be used by States to establis h 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 a ll anthropogenic visibili ty 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 Cl ass I Federal Areas--the Shenandoah National Park
and the James River Face Wilderness Area.

In developing the SIP, Virginia has sought to develop reasonable progr ess goals and long-term strategies as well as to ex amine 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 c ondition of 11.4 dv by 2064. Likewise, for James River Face on the 20 percent worst days, Virginia has adopted a reasonable progress go al 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 perc ent 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 Fa ce, this reasonable progress goal of 12.4 dv will result a 1.8 dv reduction in visibility im pairment on the 20 percent best days. The aforementioned predicted reductions in visibil ity impairment are expected to result fromiii-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 Mana ger (FLM) coordination....................................................... 5

2. ASSESSMENT OF BASELINE AND CURRE NT CONDITIONS AND ESTIMATE OF
NATURAL BACKGROUND CONDITI ONS 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 NATURA L 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 ve rsion) 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 Vi rginia 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 Inve ntory Compared to the Uniform Rate of Progress Glidepaths for Virginia Class I Areas .................................................... 50

7.3. Relative Contribution from International Emi ssions to Visibility Impairment in 2018 at
VISTAS Class I areas....................................................................................................... 56

7.4. Relative Contributions to Vi sibility Impairment: Pollutants, Source Categories, and Geographic Areas ............................................................................................................. 58

7.5. Relative Contributions to Vi sibility Impairment: Geogra phic 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. SO 2 

### Areas of Influence ......................................................................................... 64

7.5.4. Emissions Sources within SO 2 

### Areas of Influence............................................... 64 7.5.5. Specific Source Types in the Areas of In fluence for Virginia Class I Areas ....... 69 7.6. Evaluating the Four Statutory Factors for Specific SO 2 

### 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 Reasona ble Progress for Individual Sources? ........ 74 7.7.1. Step 1: Determine pollutants of concern.............................................................. 74 7.7.2. Step 2: Determine which source sect ors should be evaluated for reasonable progress................................................................................................................. 74 7.7.3. Step 3: Determine if the Clean Air In terstate 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 Be st 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 Requireme nts for Subject-to-BART Sources ............... 94

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

7.10. What Additional Emissions Controls Were C onsidered 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. NH 3 

### 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 IMP LEMENTATION 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

VISTAS bylaws A-1

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

ARS Appendix A-Nephelometer Comparisons B-1a

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

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

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

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

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

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

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

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

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

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

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

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

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

ARS Appendix H-DV Glidepaths B-1h

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

ARS Appendix I-Speciated Glidepaths B-1i

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

ARS Appendix J-Back Trajectory Maps B-1j

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

ARS Appendix K-Residence Time Maps B-1k

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

ARS Appendix L-International Attribution Plots B-1l

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 Ligh t 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 PM 2.5 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 Attrib ution 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
PM 2.5 ” 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.Te sche, 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 Te mporal Profiles for Electric Ge nerating 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 NH 3 Emission Factors.pdf

Development of the VISTAS Dr aft 2002 Mobile Source Emissi ons Inventory (February 2004 Version) , PECHAN, February 9, 2004 D-1mobile

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

Final Report: Development of th e 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

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

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

Virginia 2002 Mobile Emissions Inventory by County D-2b

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

Virginia 2009 Mobile Emissions Inventory by County D-2c

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

Virginia 2018 Mobile Emissions Inventory by County D-2d

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

### LIST OF APPENDICES

x-Virginia Regional Haze SIP 

### Appendix
ID Description/

File Name*

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

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

Virginia 2009 Point Source Inventory by County D-2l

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

Virginia 2018 Point Source Inventory by County D-2m

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 Geophysi cs 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 P erformance 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 Result s 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

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

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

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

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

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

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 Mo del 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

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

Appendix H-8a GP BART Submittal.pdf

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

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

Regional Haze/Boiler BART Program Feasibility Study Report and Estim ate-Appendix A: Basis of
Estimated Costs H-8c

Appendix H-8c GP Basis of Costs.pdf

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

Appendix H-8d GP Eng Analysis.dpf

Regional Haze/Boiler BART Progra m Feasibility Study Report and Es timate-Appendix C: Detailed Capital Cost Estimates H-8e

Appendix H-8e GP Cap Cost Estimates.pdf

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

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)

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

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 BA RT 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

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

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)

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

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

DEQ response to all public comments received du ring the public comment period for the MW BART permit H-9j

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

O-N Minerals (Chemstone) Comp any BART permit dated Decembe r 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)

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

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*

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

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

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

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 SO 2 limits) H-10b-F

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

Letter dated September 27, 2007, submitted by Chem stone 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)

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

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

November 30, 2007 revised SO 2 BART proposal (cover letter dated December 5, 2007) H-10b-I

Appendix H-10b-I SO 2 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 SO 2 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)

Recent listings for lime kilns in EPA’ s RACT/BACT/LAER Clearinghouse (NO X ) H-10b-M

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

Calculations showing derivation of BART SO 2 limits for rotary kiln H-10b-N

Appendix H-10b-N Calcs for SO 2 rotary kiln.pdf (e-submittal)

Calculations showing derivation of BART SO 2 limits for calcimatic kiln H-10b-O

Appendix H-10b-O Calcs for SO 2 calc kiln.pdf (e-submittal)

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

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)

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

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)

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

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

Appendix I: Data Access

The VISTAS products listing, with web links I

Appendix I Data Access.pdf

Appendix J: Consultation Process

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Email from VDEQ staff to MARAMA asking for info rmation on heating oil cost calculations dated
8-10-07 J-1h

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

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

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

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

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

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

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 (MAN E-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 co mments 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 co mments 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

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

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

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

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

Appendix K: Recommended Improvements

Recommended technical improvements to sup port regulatory decisions for regional haze K

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 pr ovided 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 Planni ng Organizations........................................................... ......2 Figure 1.4-1. Virg inia Class I areas ........................................................................................................................4 Figure 1.5-1. Class I Ar eas in the VI STAS Region.............................................................................. ..................6 Table 1.5-2. Mandatory Class I Fe deral Areas in th e VISTAS Region............................................................. ....6 Figure 2-1. IMPROVE Monito ring Sites in the VISTAS Re gion and Adjacen t Regions ...................................8 Table 2.3-1. Virginia Class I Areas’ Na tural Background and Baseline Co nditions...........................................10 Figure 2.4-1. Ave Extinction for the 20% Hazies t Days in 2000-2004, New IMPROVE Equation.....................11 Figure 2.4-2. Ave Extinction for the 20% Clear est Days in 2000-2004, New IMPROVE Equation ...................11 Figure 2.4-3. IMPROVE Species Compositi on Data for James River Face 2000-2004.......................................12 Figure 2.4-4. IMPROVE Species Composition Data fo r 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 fo r 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 Strategies 1 ......................................................................................................................20
Table 4.1.6. 2002 Emissions Invent ory Summary for Vi rginia in tpy. ............................................................ ...26 Figure 4.2-1. SO 2 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. Monito ring Networks Used for VISTAS 2002 Model Performan ce Evaluation.............................36
Table 6.1-1. Model Goals for the Fine Particulate Mass Co mponent Species ....................................................37 Figure 6.2-1. Soccer Plot for Mean Fractional Error an d 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 Ba se G1 Results for all VISTAS IMPROVE Monitors...............40 Figure 6.2-4. Bugle Plot—Mean Fr action Bias ................................................................................... .................40 Figure 6.2-5. B ugle Plot of Mean Fractional Error............................................................................. ..................41 Figure 6.3-1. Stacked Bar Charts fo r Shenandoah on th e 20% Best Days .......................................................... .42 Figure 6.3-2. Stacked Bar Chart fo r Shenandoah on th e 20% Worst Days .......................................................... 43 Figure 6.3-3. Stacked Bar Chart for Ja mes River Face on th e 20% Best Days ....................................................4 3 Figure 6.3-4. Stacked Bar Chart for Ja mes River Face on th e 20% Wors t Days..................................................44 Figure 7.2.3-1. Base G2 Annual SO 2 for 2002, 2009, and 20 18 VISTAS States ....................................................49 Figure 7.2.3-2. Base G2 Annual NO X for 2002, 2009, and 2018 VISTAS States...................................................49 Table 7.2.3-2. 2018 Virginia Ba se G2 Emissions Summary, tpy................................................................... ........50 Figure 7.2.4-1. Uniform Rate of Pr ogress for Shenando ah, 20% Worst Days ....................................................... .51 Figure 7.2.4-2. Uniform Rate of Progress for Ja mes River Face, 20 % Worst Days................................................5 2 Figure 7.2.4-3. Visibility Improvement, 20% Wo rst Days, 2018 Base G2a......................................................... ...52 Figure7.2.4-4. Shenandoah 20% Worst Visibility Days and Natu ral Conditions Visual Images ...........................53 Figure7.2.4-5. James Ri ver 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 Ra te of Progress for James River Face ........................................................... .......55 Figure 7.2.4-8. Visibility Improvement, 20% Be st Days, 2018 Base G2a .......................................................... ....56 Figure 7.3-1. Estimated Intern ational 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 Respons e Modeling Table Abbreviations ................................................................. ......60 Figure 7.4-1. Visibility Responses: Shenandoah to 2009 Base D 30% Reductions .............................................61 Figure 7.4-2. Visibility Re sponses: James River Face to 200 9 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 SO 2 AoI for SO 4 Extinction-Weighted Residence Time for 2000-2004 20% Worst Days ........................................................................................................................... .....................65 Figure 7.5.4-1. Shenandoah 2002 and 2018 SO 2 Distanc- Weighted Emissions, SO 4 Extinction-Weighted
Residence Ti me Plots........................................................................................................... ...........66 Figure 7.5.4-2. James Ri ver Face 2002 and 2018 SO 2 Distance Weighted Emissions, SO 4 Extinction-Weighted
Residence Ti me Plot ............................................................................................................ ...........67
Table 7.5.4-1. State 2018 SO 2 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 SO 2 Point Source Contribution to North Carolina Cl ass I Areas ..................................68
Table 7.5.4-3. State 2018 SO 2 Point Source Contribution to Other Class I Areas .................................................68
Table 7.5.5-1. 2018 Emissions Co ntributions from Source Categories, Shenandoah Area of Influence ...............70
Table 7.5.5-2. 2018 Emi ssions Contributions from So urce Categories, James River Face Area of Influence.......70
Table 7.5.5-3. Annual 2018 SO 2 Emissions Percentage with in Areas of Influence ...............................................71
Table 7.7.4-1. Emissions Poin ts and Percent Contribu tions..................................................................... ..............75 Table 7.7.4-2. Units within Virg inia 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 C ontributions of at least 1% .......................................8 7 Table 7.7.5. Celanese Acetate, LLC/Cinergy : Boilers and Stacks Comb ined for Point #1 ................................89 Table 7.8.1. Virgin ia BART So urce List ........................................................................................ ....................90
Table 7.8.2-1. BART Ex emption Mode ling Re sults ................................................................................ ..............92
Table 7.8.3-1. BART Determinations ............................................................................................ ........................95 Figure 7.9-1. SO 2 Emissions Comparisons for VISTAS States, CAIR versus No CAIR, Legally Enforceable.100 Figure 7.9-2. NO X Emissions Comparisons for VISTAS States, CA IR versus No CAIR, Legally Enforceable100 Table 7.10.4-1. Base G2 and Base G4a Point Source Emissions Comparison for SO 2 , NO X , VOC, and CO........104 Table 7.10.4-2. Base G2 and Base G4a Point Source Emissions Comparison for PM 10 , PM 2.5 , and NH 3 .............104 Table 8.1-1. Virginia R easonable Prog ress Goals............................................................................... ..............105 Figure 8.1-1. 20% Worst Days R easonable Progress for Shenandoah ............................................................... 106 Figure 8.1-2. 20% Worst Days Reason able Progress for Ja mes River Face.......................................................10 6 Figure 8.1-3. 20 Percent Best Da ys Rate of Progre ss for Shenandoah ............................................................ ...107 Figure 8.1-4. 20 Percent Best Days Rate of Progress fo r James River Face ...................................................... 107 Figure 8.2-1. Annual Emissions of SO 2 from Acid Rain Program Un its (Data from CAMD)...........................109
Table 9-1. IMPROVE Sites in Virginia..........................................................................................................110 Table 10-1. Virginia Electric Genera ting Units Identified by MANE-VU.......................................................115 Table 10-2. Contribution of Virginia 2018 Poin t 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
NH 3 

### - Ammonia
NO X 

### - Nitrogen Oxides OTB/OTW - On the Books/On the Way PBL - Planetary Boundary Layer
PM - Particulate Matter
PM 2.5 

### - Particulate Matter with a diameter of 2.5 micrometers or less (fine particulate)
PM 10 

### - 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 Appalach ian Mountains Initiative SCC - Source Category Code SIP - State Implementation Plan SMOKE - Sparse Matrix Operator Kernel Emissions (model) SOA - Secondary Organic Aerosols
SO 2 

### - 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, AR1-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 “Cla ss I” areas). Regional haze is caused by sources and activi ties emitting fine particles and thei r precursors. Those emissions are often transported ove r large regions.

Particles affect visibili ty through the scattering and absorption of light, and fine particles – particles similar in size to the wavelength of li ght – 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 (SO 2 

### ) and nitrogen oxides (NO X 

### ). Reducing fine particles in the atmosphere is gene rally considered to be an effective method of reducing regional haze, and thus improving visibilit y. 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 particle s with diameter smaller than 2.5 μ m (PM 2.5 

### ). The most important sources of PM 2.5 

### and its precursors are coal-fired power plants, industrial boilers, and other combustion sources. Other significant contributors to PM 2.5 

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

1.2. What are the requirements under the Cl ean Air Act for addressing regional
haze?

In § 169A of the 1977 Amendments to the Clea n 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 visib ility in mandatory Class I Federal areas which impairment results from manmade air pollution.” Congress adopted the visibility provisions to protect visibility in 156 nati onal 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 impairm ent (45 FR 80084). The 1980 regulations were developed to address visibility im pairment that is “reasonably attributable” to a single source or small group of sources. These regulations repres ented the first phase in addressing visibility impairment and deferred action on regional haze that emanates from a variety of sources until monitoring, modeling, and scientif ic knowledge about the relations hips between pollutants and visibility impairment improved.

In the 1990 Amendments to the CAA, Congr ess 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 provi sions addressing regiona l haze impairment and establish a comprehensive visibi lity protection program for Cla ss 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 h aze regulation, including consultati on 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. St ates must submit a regional haze implementation plan to USEPA within three years after the date of designation. Because2-Virginia Regional Haze SIP 

### USEPA promulgated designation dates on Dece mber 17, 2004, regional haze SIPs must be submitted by December 17, 2007.

The regional haze regulation addressed the combin ed visibility effects of various pollution sources over a wide geographic region. This wi de reaching pollution net meant that many states – even those without Class I Areas – would be requi red to participate in haze reduction efforts. USEPA designated five Regional Pl anning Organizations (RPO) to assist with the coordination and cooperation needed to addr ess the visibility issue. Those states that make up the southeastern portion of the contiguous Unite d States are known as VISTAS (Visibility Improvement – State and Tribal Association of the Southeast), and include the following states: Alabama, Florida, Georgia, Kentucky, Mississipp i, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia.

Figure 1.2-1. Geographical Areas of Regional Planning Organizations



### 1.3. General overview of region al 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 regulati on 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 ma ndatory Class I Federal area located outside the State that may be affected by emissions from sour ces within the State. States are to establish baseline visibility conditions for 2000-2004, natu ral background visibility conditions in 2064, and the rate of uniform progress between base line 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 reasonabl e progress goals (RPGs), expressed in dv, for visibility improvement at each affected Class I area covering each (approximately) 10-year period until 2064. The goa ls must provide for reasonable progress towards achieving natural visibil ity 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 impa ired days over the same peri od (see 40 CFR 51.308(d)(1)).

In order to ensure that visi bility goals are prop erly met and set, SIPs must include determinations, for each Class I area, of the base line visibility conditions (expressed in dv) for the most impaired and least impaired days. SIPs must also contain supp orting documentation for all required analyses used to calculate the degree of visibility impairment under natural visibility conditions for the most impaired and least impair ed days (see 40 CFR 51.308(d)(2)). In addition, states must include a monitoring strategy for me asuring, 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 meas ures contained in the st ate’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 expect ed 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 ong oing control programs, measures to mitigate construction activities, source retirement and replacement schedules, smoke management programs for agriculture and forestry, and enfo rceability of specific measures (see 40 CFR 51.308(d)(3)).

In addition, a specific component of each state’ s first long-term strate gy is dictated by the specific best available retrof it technology (BART) requireme nts in 40 CFR 51.308(e) of the regional haze regulation. 40 CFR 51.308(e) requires states to in clude 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 contribu te to any impairment of visibi lity in any mandatory Class I Federal area. CAA § 169A(b) defines BART-eligi ble 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 D ecember 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 progre ss toward RPGs goals every 5 ye ars to assure that installed
emissions controls are on track with emissions re duction 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 VDE Q is responsible for developing the regional
haze SIP. This SIP establishes RPGs for visibil ity improvement at each of these Class I areas, and a long-term strategy that will achieve thos e RPGs within the firs t regional haze planning period.

Figure 1.4-1. Virginia Class I areas



### In developing this SIP, consideration has been gi ven 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 area s 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 discus sed 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 pa rtnership known as the Southern Appalachian Mountai n Initiative (SAMI) “to iden tify and recommend reasonable measures to remedy existing and prevent futu re adverse effects fr om human-induced air pollution on the air quality related values of th e 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 Sout hern 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 Appalach ian Mountains and to improve visibility, it is most important to reduce SO 2 

### emissions. SAMI also conc luded that reducing ammonia5-Virginia Regional Haze SIP 

### emissions would be helpful to reduce ammonium n itrate contributions to visibility impairment. Emissions controls for organic carbon, elemen tal carbon, and soil were expected to be less important for improving visibility. SAMI modeli ng 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 th e 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 mi ssion. 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 co mmitted to consider air qua lity benefits in the Southern Appalachians as they develope d 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 SO 2 

### and NO X 

### . The SAMI analyses and recommendations supported develo pment 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 visibi lity 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 SO 2 

### and NO X 

### from electric generating utilities. In 2004 USEPA promulgated the Clean Air Interstate Rule (CAIR) to require emissions reductions
for SO 2 

### and NO X 

### from electric generating util ities 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 w ill 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 deve lopment and review of implementation plan revisions and 5-year progress reports, and on th e implementation of other programs having the potential to contribute to impairme nt of visibility in any mandat ory Class I Federal area within
the State.

Successful implementation of a regional h aze 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 Ch erokee Indians; the States of Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolin a, South Carolina, Tennessee, Virginia, and West Virginia; and the local air pollution cont rol programs located in these St ates. 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 inte rim visibility goals, and provide adequate documentation to member agencies so that they can develop their regi onal haze SIPs. Figure 1.5-1 shows the 18 mandatory Class I Federal areas in the VISTAS Region, wh ere 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 Everglades National Park 1,397,429 USDI-NPS 40 CFR 81.407 Florida

St. Marks Wilderness 17,745 USDI-FWS

Cohotta Wilderness 36,977 USDA-FS
Okefenokee Wilderness 343,850 USDI-FWS 40 CFR 81.408 Georgia 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 Wilder ness 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-FS7-Virginia Regional Haze SIP 

### A technical support document for the regional h aze 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 a nd situation; calculation of initial baseline visibility; and review of monitoring data and data gaps. The report o ffers recommendations for additional monitoring; initial emission inventory charac terization and projections; and co mpliance with existing control programs. Source contributions to VISTAS mand atory Class I Federal areas are also assessed.

2. ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND
ESTIMATE OF NATURAL BACKGRO UND CONDITIONS IN CLASS I
AREAS

The goal of the regional haze regulation is to rest ore natural visibility conditions to the 156 Class
I areas identified in the 1977 Clean Air Ac t Amendments. 40 CFR 51.301(q) defines natural
conditions: “Natural conditions include naturall y occurring phenomena that reduce visibility as measured in terms of light extinction, visual ra nge, contrast, or colorati on.” The regional haze
SIPs must contain measures that make “rea sonable progress” toward this goal by reducing anthropogenic emissions that cause haze.

An easily understood measure of visibility to mo st people is visual range . Visual range is the greatest distance, in kilometers or miles, at wh ich a dark object can be viewed against the sky. For evaluating the relative contributions of polluta nts to visibility impairment, however, the most useful measure of visibility impa irment 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). D eciviews 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 ey e. Most people can detect a change in visibility at one dv.

For each Class I area, there are thr ee metrics of visibility that ar e part of the determination of reasonable progress:

• Natural conditions,

• Baseline conditions, and

• Current conditions.

Each of the three metrics includes the concentrati on 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 conve rted to dv is calculated for the average of the 20 percent best and 20 percent worst visibility days.

“Natural” visibility is determined by estimating th e 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 condu cting visibility-related re search and in creating SIPs for the protection of visibility in the Class I Federal areas, th e Interagency Monitoring of Protected Visual8-Virginia Regional Haze SIP 

### Environments (IMPROVE) program was estab lished in 1985. IMPROVE is a cooperative measurement effort governed by representatives fr om Federal and regional-state organizations. IMPROVE’s objectives are, among other things, to es tablish current visibili ty conditions in Class I Federal areas, to track changes in visibil ity, 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 monito ring network consists of aerosol and optical samplers. The network began in 1988 with 20 monitoring sites in Cla ss I Federal areas and quickly grew to 30 sites by 1999. Finally, with th e 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 de picts 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 da ta for 2000 through 2004 can be thought of as “current” visibility conditions fo r this initial review period. Th e comparison of initial baseline conditions to natural visibility conditions in dicates 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 a nd 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 impa irment 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 Gu idance for Tracking Progress Under the Regional
Haze Rule (USEPA 2003), is based on annual average concen trations 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 wo rst days is estimated by assuming that fine9-Virginia Regional Haze SIP 

### particle concentrations for natural ba ckground are normally distributed and the 90 th 

### percentile of the annual distribution represen ts natural background visibility on the 20 percent worst days.

In the 2003 guidance, USEPA also provided that st ates may use a “refined approach” to estimate
the values that characterize the na tural visibility conditions of th e Class I areas. The purpose of such a refinement would be to provide more accu rate estimates with changes to the extinction algorithm that may include the concentration va lues, factors to calculate extinction from a measured particular species and particle size, the extinction coefficien ts for certain compounds, geographical variation (by altitude ) of a fixed value, and the addi tion of visibility pollutants.

In 2005 the IMPROVE Steering Committee made r ecommendations 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 calc ulating 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 e ffect 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 absorpti on by gaseous nitrogen dioxide. Site-specific values are used for Rayl eigh scattering to account for the site-specific effects of elevation and temperat ure. Separate relative humidity enhancement factors are used for small and large size distribut ions of ammonium sulfate and ammonium nitrate and for sea salt. The elemental carbon (light-absorbing carb on), fine soil, and co arse mass terms do not change between the original and new IMPROVE equation.

The VISTAS states chose to use the new IMPR OVE 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 Shenandoa h National Park and the James River Face Wilderness Area. A five year averag e (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. Natura l 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 Sout hern 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 wi th high relative humidity, high temperatures, and low wind speeds. The 20 percent best visibil ity days at the Southern Appalachian sites can occur at any time of year.

Ammonium sulfate is the most im portant 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 percen t worst days account for 60-70 percent of the visibility impairment. Across the VISTAS regi on, sulfate levels are higher at the Southern Appalachian sites than at the co astal sites as shown in Figure 2.4- 1. On the 20 percent clearest days, sulfate levels are more uniform acr oss 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 (P OM) can be a significant contributor as well. On the very few 20 percent worst visibility da ys that occur outside of the April through September time period, either POM, ammonium nitrate, or a combination of POM and ammonium nitrate offer significan t 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 300Swanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, ARExtinction (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 300Swanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, ARExtinction (Mm-1)

Sea Salt
Coarse
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

0 10 20 30 40 50 60Extinction (Mm-1)

Sea Salt

CM
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTASSwanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, AR 0 10 20 30 40 50 60Extinction (Mm-1)

Sea Salt

CM
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTASSwanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, AR12-Virginia Regional Haze SIP JARI1 Baseline Extinction, New IMPROVE Algorithm

20% W > 144

0 50 100 150 200 250 300

J-

02 F- 0 2 M-02 A - 02 M- 02 J- 02 J- 02 A - 02 S-02 O-02 N -02 D -02Extinction (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 -01Extinction (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-00Extinction (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 - 0 3 N-03 D-03Extinction (Mm-1)

20% W > 123

0 50 100 150 200 250 300

J-04 F- 0 4 M- 04 A -04 M- 04 J - 04 J - 04 A - 04 S -04 O- 0 4 N -04 D -04Extinction (Mm-1)

Figure 2.4-3. IMPROVE Species Composition Data for James River Face 2000-200413-Virginia Regional Haze SIP SHEN1 Baseline Extinction, New IMPROVE Algorithm

20% W > 136

0 50 100 150 200 250 300

J-

02 F- 0 2 M-02 A - 02 M- 02 J- 02 J- 02 A - 02 S-02 O-02 N -02 D -02Extinction (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 -01Extinction (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-00Extinction (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 - 0 3 N-03 D-03Extinction (Mm-1)

20% W > 128

0 50 100 150 200 250 300

J-04 F- 0 4 M- 04 A -04 M- 04 J - 04 J - 04 A - 04 S -04 O- 0 4 N -04 D -04Extinction (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 of14-Virginia Regional Haze SIP 

### carbon at five sites (Great Smoky Mountains, Millbrook, Ca pe Romain, Shenandoah, and Mammoth Cave) to better understand sources contri buting 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 vegetatio n, peak in spring and summer. Biogenic carbon emissions at Cape Romain, SC, were lower th an emissions at the forested mountain sites. Carbon from gasoline and diesel engines is a relatively sma ll contribution at the rura l sites. At Millbrook,
which was considered an urban site in the car bon 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 controllin g anthropogenic sources of carbon will have little benefit in improving visibility in Class I areas. Controlling anth ropogenic sources of carbon will likely be more effective at reducing levels of PM 2.5 

### in urban areas.

Ammonium nitrate is formed in the atmosphere by reaction of ammonia (NH 3 

### ) and NO X 

### . In the VISTAS region, nitrate formation is limited by availability of ammonia and by temperature. Ammonia preferentia lly reacts with SO 2 

### and sulfate before reacting with NO X 

### . Particle nitrate is formed at lower temperatures; at elevated temper atures nitric acid remains in gaseous form. For this reason, particle nitrate levels are very low in the summer and a minor c ontributor to visibility impairment. Particle nitrate c oncentrations are higher on winter days and are more important for the coastal sites where 20 percent wo rst days can occur on winter days. NO X 

### is emitted by fossil fuel combustion by point, area, on road, and non ro ad sources. Modeling data (see Section 7) indicate that in the VISTAS region ammoni um nitrate formation is limited by ammonia concentrations and suggest that for winter days, controls of ammonia sources would be more effective in reducing ammonium nitr ate levels than controls of NO X



### .

Elemental carbon is a comparatively minor contribut or to visibility impairment. Sources include agriculture burning, prescribed fires, wildland and wild fires, and incomplete combustion of
fossil fuels. Elemental carbon leve ls are higher at urban monitors than at the Class I areas and suggest controls of fossil fuel combustion so urces would be more effective at reducing PM 2.5 

### in urban areas than at improving visi bility in Class I areas.

Sea salt is observed at the coastal sites. Sea sa lt contributions to visibi lity impairment are most important on the 20 percent clearest days when sulf ate and POM levels are lo w. Sea salt levels do not contribute signific antly to visibility on the 20 percen t 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 vola tize off the filter, so that Cl - 

### may underestimate
sea salt levels. VISTAS funded sodium ion an alyses of the IMPROVE filters from October 2003
to December 2004 for nine sites. Sodium ion meas ures 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 uncer tainty has greatest implications for calculating
sea salt levels under natura l 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 th e light extinction efficiency of coarse mass is very low compared to the ex tinction efficiency for sulf ate, nitrate, and carbon.

An unidentified component is reported by IMPR OVE as the difference between the total PM 2.5 

### mass measured on the filter and th e sum of the measured compone nts. 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 hi gher 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 calcula ted light extinction for current conditions and to decrease calculated light extinction for natura l visibility conditions. Adding sea salt to the new IMPROVE equation increases light extincti on for both current and natural visibility conditions. Increasing the mass mu ltiplier for particulate orga nic matter in the new IMPROVE equation increases light extinction for current cond itions more than for natural conditions. The new algorithm does not change th e conclusion that in the VISTAS region and in Virginia, the most effective means to improve visibili ty is to reduce sulf ate concentrations.

With respect to PM 2.5 

### trends in urban and Class I areas, IMPROVE data were compared to monitoring data from the Speciated Trends Ne twork (STN) in nearby urban areas to understand the similarities and differences in compos ition of fine particle mass. Several PM 2.5 

### nonattainment areas are in close proximity to the Cl ass I areas in the southeastern United States, including Atlanta, GA; Birmingham, AL; Char leston, WV; Chattanooga, TN; Louisville, KY; and Knoxville, TN. Ammonium sulfate concen trations are comparable between urban and nearby Class I areas, while organic carbon, elem ental carbon, and nitrat e 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 c ontributors to visibility impairment at most sites on most days. Occasional episodes of elevated fi ne 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 ra nging from poor to good visibility. Days were then assigned to bins based on meteorological condi tions. For the Virginia Class I ar eas poor visibility days were most likely to occur on days with high temperatures, high relative humidity, low wind speeds,
and elevated PM 2.5 

### mass at upwind urban areas. Preci pitation was not a good predictor of visibility conditions. Weights we re 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, th e regional haze regulation direct s states to graphically show what would be a “uniform rate of progress” to ward natural conditions for each mandatory Class I
Federal area within the State as well as for each mandatory Cla ss I Federal area located outside the State, which may be affected by emissions from sources within the Stat e. 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 fo r 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 develope d in accordance with USEPA guidance and used data collected from the IMPROVE monitoring s ites as described in Section 2 above. The glidepath is one of the indicat ors 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 to ward regional haze goals. Natural background visibility at both sites is predic ted 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
YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation17-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: CHIE F CAUSES OF VISIBILITY
IMPAIRMENT IN VIRG INIA 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 anti cipated 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 inventor ied include VOC, NO X 

### , fine particulate (PM 2.5 

### ), coarse particulate (PM 10 

### ), NH 3 

### , and SO 2 

### . 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 sour ces, and biogenic sources. Stationary point sources are those sources that emit greater than a specified tonnage per ye ar, with data provided at the facility level. Electric generating util ities and industrial sources are the major categories for stationary point sources. Stationary ar ea 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 si gnificant (dry cleaners, service stations, agricultural sources, fire emissions, etc.). These types of emissions are estimated on a countywide level. Non-road (or off-road) mob ile sources are equipment that can move but do not use the roadways, such as lawn mowers, c onstruction equipment, ra ilroad locomotives, and aircraft. The emissions from these sources, li ke stationary area sour ces, are estimated on a countywide level. On-road mobile sources are au tomobiles, 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
YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation18-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. Biogeni c sources are the natural sources like trees, crops, grasses, and natural decay of plants. Th e emissions from these sources are estimated on a countywide level.

In addition to the various source classificati ons, there are also various types of emission
inventories. The first is the actua l base year inventory. This inve ntory 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 evaluati ng the air quality model performance.

The second type of inventory is th e typical base year inventory. Th is inventory is similar to the actual base year inventory; howev er, for sources whose emissions change significantly from year to year, a more typical emission value is used. In this modeli ng effort, typical emissions were developed for the electric generating units (EGUs) and the wildland fire emissions. The air quality modeling runs using the t ypical base year inve ntory provide results which are then used to calculate relative respons e factors for future years. These re lative response factors for future years are then used to dem onstrate reasonable progress to ward visibility goals.

In the following sections, a synopsis of the inve ntories used for each source classification is provided. More detailed discus sion of the emissions inventor y development is contained in Appendix D.

4.1.1. Stationary Point Sources

Point source emissions are emissions from indivi dual sources having a fixe d 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 po llutant, or 25 tpy total hazardous air pollutant are inventoried annually. Smaller sources have been inventorie d less frequently. The point source emissions data can be grouped as EGU sour ces and other industrial point s ources, also called non-EGUs.

4.1.1.1. Electric Generating Units

The actual base year inventory for the EGU s ources 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 SO 2 

### and NO X 

### that can be used in air quality modeling. Emi ssions profiles are used to estimate emissions of other pollutants (VOC, carbon monoxide, NH 3 

### , fine particles, soil) ba sed on measured emissions
of SO 2 

### and NO X



### .

Since the NO X 

### emissions from EGU sources are a signifi cant part of the emissions inventory, a typical base year emissions i nventory was developed for these source to avoid anomalies in emissions due to variability in meteorology a nd economic and outage factors in 2002. This approach is consistent with the USEPA’s mode ling 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 ge nerate a unit specific normalizing factor. This normalizing factor was then multiplied by the 2002 actual emissions. The heat inputs for19-Virginia Regional Haze SIP 

### the period 2000 through 2004 were used because th e modeling design values use monitored data from this same five-year period. If a unit wa s 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, VI STAS, 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 optimiza tion model that can be used to examine air pollution control policies for vari ous pollutants throughout the con tiguous United States for the entire electric power system. Th e 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, transm ission 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 emissi on reduction strategies to be installed at various EGU facilities in Virginia, as well as a lis ting of existing controls and emission reduction strategies for PM, NO X 

### , and SO 2



### .

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 anal yses. This data was supplemented with statespecific growth factors and stakeh older input on growth assumptions.20-Virginia Regional Haze SIPTable 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction Strategies1SizeExisting Control Equipment andEmission Reduction Strategies2Facility NameORIS/Reg#Unit ID#MWmmbtu/hrNSRPermit?PMYearInstalledNOXYearInstalledSO2YearInstalledProjectedControl orStrategy2ProjectedYear toInstall1 71.1 383 Yes FF At start up LNB,SNCRAt start up SDA92%CEAt start up n/a n/aAltavista Power Station10773/308592 71.1 383 Yes FF At start up LNB,SNCRAt start up SDA92%CEAt start up n/a n/aBirchwood Power Facility54304/408091 220 2,300 Yes FF At start up SCR At start up DLS94%CEAt start up n/a n/a3 69 912 No ESP(hotsided)--- BOOS 2004 None --- None NoneBremo Power Station33796/401194 185 1,699 No ESP(hotsided)--- LNB,ROFA2004 None --- None None1 113 1,300 No ESP --- ROFA,SNCR2003Low Scoal42007 n/a n/a2 113 1,300 No ESP --- ROFA,SNCR2003Low Scoal42007 n/a n/a3 185 1,663 No ESP --- LNBSCR2003 Low Scoal42007 n/a n/aChesapeake Energy Center3803/601634 239 2,346 No ESP --- LNBSCR2003 Low Scoal42007 n/a n/a3 113 1,155 No ESP --- LNBOFA2003 None --- FGD 90%CE520124 188 1,761 No ESP --- StagedcombSCR2003 None --- FGD 90%CE520115 359 3.604 No ESP --- StagedcombSCR2002 None --- FGD 90%CE52011Chesterfield Power Station3797/503966 694 6,650 No ESP --- StagedcombSCR2004 FGD90%CE +polishingbaghouse52008 n/a n/a1 238 2,100 No ESP --- StagedCombLNBSNCR200420072009None --- SO2Cap66Clinch River63775/102362 238 2,100 No ESP --- StagedCombLNBSNCR200420072009None --- SO2Cap6621-Virginia Regional Haze SIPTable 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction Strategies1SizeExisting Control Equipment andEmission Reduction Strategies2Facility NameORIS/Reg#Unit ID#MWmmbtu/hrNSRPermit?PMYearInstalledNOXYearInstalledSO2YearInstalledProjectedControl orStrategy2ProjectedYear toInstallClinch River63775/102363 238 2,100 No ESP --- StagedCombLNBSNCR200220072009None --- SO2Cap661 4244,085 Yes FF At start up LNB/OFA/SNCRLNB & OFAat start up;SNCR 2003WetFGD94%CEAt startup n/an/aClover Power Station7213/308672 424 4,085 Yes FF At start up LNB/OFA/SNCRLNB & OFAat start up;SNCR 2003WetFGD94%CEAt startup n/a n/aBLR01A375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/an/aBLR01B115375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/a n/aBLR02A375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/an/aBLR02B115375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/a n/aBLR03A375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/an/aBLR03B115375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/a n/aBLR04A375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/an/aSpruance Genco LLC54081/51033BLR04B115375 Yes FF At start up OFA/FGR/SNCR/MethAt startup SDA92%CEAt startup n/a n/a22-Virginia Regional Haze SIPTable 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction Strategies1SizeExisting Control Equipment andEmission Reduction Strategies2Facility NameORIS/Reg#Unit ID#MWmmbtu/hrNSRPermit?PMYearInstalledNOXYearInstalledSO2YearInstalledProjectedControl orStrategy2ProjectedYear toInstallBLR01A200 Yes FF At start up OFA/FGR2004 FGD90%CE2008 n/a n/aBLR01B200 Yes FF At start up OFA/FGR2004 FGD90%CE2008 n/a n/aBLR01C108.5200 Yes FF At start up OFA/FGR2004 FGD90%CE2008 n/a n/aBLR02A200 Yes FF At start up OFA/FGR2004 FGD90%CE2008 n/a n/aBLR02B200 Yes FF At start up OFA/FGR2004 FGD90%CE2008 n/a n/aJames River Cogeneration10377/50950BLR02C108.5200 Yes FF At start up OFA/FGR2004 FGD90%CE2008 n/a n/aBLR01A200 Yes FF At start up OFA/FGR2004 FGD90%CE2007 n/a n/aBLR01B200 Yes FF At start up OFA/FGR2004 FGD90%CE2007 n/a n/aBLR01C108.5200Yes FF At start up OFA/FGR2004 FGD90%CE2007 n/a n/aBLR02A200 Yes FF At start up OFA/FGR2004 FGD90%CE2007 n/a n/aBLR02B200 Yes FF At start up OFA/FGR2004 FGD90%CE2007 n/a n/aCogentrix-Portsmouth10071/61049BLR02C108.5200 Yes FF At start up OFA/FGR2004 FGD90%CE2007 n/a n/a51 100 572 No ESP --- StagedCombLNB20042007None --- n/a n/a52 100 572 No ESP --- StagedCombLNB20042007None --- n/a n/aGlen Lyn63776/204606 238 2,040 No ESP --- StagedCombLNB20042007None --- n/a n/a23-Virginia Regional Haze SIPTable 4-1. Virginia Coal Fired Power Plants: Existing and Future Expected Controls and Emission Reduction Strategies1SizeExisting Control Equipment andEmission Reduction Strategies2Facility NameORIS/Reg#Unit ID#MWmmbtu/hrNSRPermit?PMYearInstalledNOXYearInstalledSO2YearInstalledProjectedControl orStrategy2ProjectedYear toInstall1 71.1 391 Yes FF At start up OFA/SNCRAt startup SDA92%CEAt startup n/a n/aHopewell Power Station10771/510192 71.1 391 Yes FF At start up OFA/SNCRAt startup SDA92%CEAt startup n/a n/a1 69.9 834 Yes FF At startup OFA At startup SDA92%CEAt startup n/a n/aMecklenburg Power Station52007/308612 69.9 834 Yes FF At start up OFA At startup SDA92%CEAt startup n/a n/a1 93 970 No ESP --- LNB 2005 SorbentInj2006 None None2 93 970 No ESP --- LNB 2005 SorbentInj2006 None None3 108 961 No ESP --- LNB/SOFA2004 SorbentInj2006 None None4 108 961 No ESP --- LNB/SOFA2004 SorbentInj2006 None NonePotomac River Generating Station3788/7022875 108 961 No ESP --- LNB/SOFA2004 SorbentInj2006 None None1 71.1 400 Yes FF At start up StagedComb/OFAAt start up SDA92%CEAt start up n/a n/aSouthampton Power Station10774/610932 71.1 400 Yes FF At start up StagedComb/OFAAt start up SDA92%CEAt start up n/a n/a1 173 1,697 No ESP --- ROFA/SNCR2004 None --- FGD 90%CE20108Yorktown Power Station83809/601372 182 1,745 No ESP --- ROFA/SNCR2004 None --- FGD 90%CE201881The Virginia City Hybrid Energy Center, a coal fired power plant currently under construction in Wise County, Virginia, is not included in this listing of existing facilities.2FF=Fabric Filter; ESP=electrostatic precipitator; DLS=dry lime scrubber; FGD=flue gas desulfurization unit; Sorbent inj=sorbent injection; FGR=fluegas recirculation;OFA=over-fire air; SOFA=selectiveover-fire air; ROFA=rotating over-fire air; Staged comb=staged combustion; LNB=low NOXburners; SNCR=selective non-catalyticreaction; SCR=selective catalytic reaction; Meth=methane reburn; SDA=spray dry absorber3No further add on controls are expectedfor Bremo Power Station. However, the July1, 2008, PSD permit for the Virginia CityHybrid Energy Center in Wise County,Virginia, includes a condition requiring that, subject to State Corporation Commission approval, Bremo Power Station switch fuels within two years of the Virginia CityHybrid Energy Center facility commencing commercial operation. This fuel switch will nearly eliminate SO2emissions from the facility. This permit was not yet issued atthe time of the best and final modeling. Therefore, these SO2reductions were not included in the modeling exercise.4A 40% reduction in SO2emissions was estimatedfor the use of low sulfur coal. This value mayfluctuate depending upon the quality and availabilityof low sulfur coal.5A control efficiency of 90% was used in calculating future year SO2emissions estimates, based on the installation of these control devices. Actual SO2control efficiency forthe device controlling unit #6 is 95%. Thedevices that will control units #3, #4, and #5 are also expected to achieve 95% control of SO2.24-Virginia Regional Haze SIP6Both Clinch River and Glen Lyn are part of the AEP Eastern System consent agreement. The agreement requires LNB on Glen Lyn by the date of entry of the consentagreement, which was December 10, 2007. The agreement also requires LNB and SNCR be installed on all three units at Clinch River. The LNB must be installed by thedate 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 tpy SO2starting 1/1/2010 and alimit of 16,300 tpy starting 1/1/2015. Currently it is not known what mechanism will be used byClinch River to achieve compliance with these SO2limitations.7Potomac River Generating Station installed sorbent injection to reduce SO2emissions as part of a plan to comply with the SO2NAAQS. On July 31, 2008, the facilityreceived a state operating permitthat required the use of sorbent injection, required the use of low sulfur (0.9% by weight S)coal, and limited SO2emissions to 3,813 tpy.The permit also limits NOXemissions to 3,700 tpy. At the time of the best and final inventory submittal for the regional haze modeling effort, the emissions reductionsassociated with this permit were not included since the permitwas not yet final when the bestand final inventory was being developed.8Controls for SO2were predicted on units #1 and #2 at Yorktown Power Station.However, due to the remand of CAIR and the vacatur of CAMR, thefinal set of SO2controlsfor these units has not yet been determined by the owner. Virginia expects that some of the regulatory uncertainty currently being experienced by the electric generatingindustry will be alleviated by the time the regional haze periodicreport is due to be submitted to EPA. At that time, the control options assigned tothese units may be betterunderstood, and that information may beprovided 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 individua l emissions are relatively small, but due to the large number of these sour ces, the collective emissions coul d be significant (combustion of fuels for heating, structure fires, service stations, etc.). Emi ssions are estimated by multiplying an emission factor by some known indicator of colle ctive activity, such as fu el usage, number of households, or population. Stationa ry 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 a nd unpaved roads. For the othe r 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 t ypical base year inventor y for all area source categories except for wildland fires. For wildland fires, a typical year inventory was used to
avoid anomalies in wildfire activ ity in 2002 compared to longer te rm averages. Development of a typical year fire inventory provided the capabil ity of using a comparable data set for both the base year and future years. The VISTAS Fire Sp ecial Interest Work Grou p used state records to ratio the number of acres burned over a longer te rm period (three or more years, as available from state records) to 2002. Based on these rati os, 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, supplie d 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 fact or files, then USEPA’s Economic Growth and Analysis System Version 5 growth factors were used. A dditionally, the VISTAS contractor generated, and Virginia staff re viewed, 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 t he majority of the non-road sources, the emissions for 2002 were estimated using the
USEPA’s NONROAD2005c model. For the three source cate gories 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 a ffecting emissions from these sour ce categories. For the largest airports in Virginia, the Federal Aviation Admi nistration’s Terminal Area Forecast was used to26-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 Emissi ons Inventory Technical Support Document (USEPA, 2005). When available, state-specif ic growth factors were used.

4.1.4. Highway Mobile Sources

For on-road vehicles, the newest version of th e USEPA on-road mobile source emission factor model, MOBILE6.2, was used. Key inputs for MOBI LE6.2 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 progr ams). The MOBILE model also takes into consideration federal regulations that affect em issions from this source sector.

The Virginia Department of Motor Vehicles pr ovided statewide vehicle registration data for 2002. These registration data files were used fo r both the 2002 and 2018 analysis years. The Virginia Department of Transportation provi ded 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 inventor ies using input data refl ective of that year.

4.1.5. Biogenic Emission Sources

Biogenic emissions were prepared with th e 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 incl ude use of MM5 data, gridded land use data, and improved emissions characterization. The em ission factors that are used in SMOKE-BEIS3
are the same as the emission factors in UAM-BEI S3. 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 th e USEPA. A separate land classification scheme, based upon satellite (AVHRR, 1 km spatial re solution) and census information, aided in defining the forest, agriculture, and urban por tions 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 emi ssion 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 NO X PM 2.5 PM 10 NH 3 SO 2

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 8,19627-Virginia Regional Haze SIP Table 4.1.6. 2002 Emissions Inventory Summary for Virginia in tpy, continued.

Sector VOC NO X PM 2.5 PM 10 NH 3 SO 2 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 performa nce evaluation, VISTAS has made several improvements to the emissions inventory that, in turn, improved mode l performance. These inventory improvements
are detailed in the VISTAS emissions inve ntory report and Appendix D, and they are
summarized here:

• For electric generating utilities, the Inte grated Planning Model (IPM) was used to provide estimates of future year util ity production and emissions. Continuous emissions monitoring data was used to de fine 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 NH 3 

### emissions from agricultural sources , the Carnegie Mellon University ammonia model was used to impr ove annual and monthly estimates.

• For fires, the VISTAS states provided 2002 fire activity data for wildfires, prescribed fire, land clearing, and agri cultural 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 incr eased 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 shi pping lanes in the Gu lf of Mexico and Atlantic Oceans, ENVIRON created gri dded emissions for the VISTAS modeling domain using inventory da ta newly developed for USEPA by Dr. Corbett at University of Delaware. These emissi ons were incorporat ed in the Base G modeling.

• Updated inventories from the neighbor ing RPOs, Mexico, and Canada were incorporated as available.

4.2. Assessment of Relative Co ntributions from Specifi c Pollutants and Sources Categories

Ammonium sulfate is the largest contributor to visibility impairment at the Virginia Class I areas, and reduction of SO 2 

### emissions would be the most effective means of reducing ammonium28-Virginia Regional Haze SIP 

### sulfate. As illustrated in Figure 4.2-1, 96 percent of SO 2 

### emissions in the VISTAS states are
attributable to electric generating facilitie s and industrial po int sources.

Figure 4.2-1. SO 2 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 eval uation that begins by se lection of the modeling system. VISTAS decided to use the following modeling system:

• Meteorological Model: The Pennsylvania St ate University/National Center for Atmospheric Research (PSU/NCAR) Meso scale Meteorological Model (MM5) is a nonhydrostatic, prognostic meteorological model routinely used for urban- and regional-scale photochemical, fine particul ate matter, and regional haze regulatory modeling studies.

• Emissions Model: The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system is an emissions modeli ng 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-A tmosphere’ photochemical grid model capable of addressing ozone, particulate matte r, 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 Utilities: 76% Industrial: 20% 4.8 Million tons



# VISTAS States SO2 Emissions - 2002

Utilities Industrial On road Non road Other Utilities: 76% Industrial: 20% 4.8 Million tons29-Virginia Regional Haze SIP 

### using the meteorological model. Emission i nventories were also developed for 2002 and processed through the emissions model. These i nputs were used in the air quality model to predict fine particle mass a nd visibility. The model results for 2002 were compared with observed meteorological and air quality data to evaluate m odel performance. Several configurations of the meteor ological and air quality model were evaluated to select a configuration that gave the best overa ll 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 qua lity 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 th is 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 scient ifically appropriate for the intended application and be freely accessible to all stakeholders. “Sci entifically appropriate” means that the models address important physical and chemical phenomen a in sufficient detail, using peer-reviewed methods. “Freely accessible” means that model fo rmulations and coding are freely available for
review and that the models are available to stak eholders, and their consul tants, for execution and
verification at no or low cost.

The following sections outline the criteria for select ing 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 ca ndidate for use in a regional haze SIP, a state needs to show that it meets the same general crit eria as a model for a national ambient air quality standard (NAAQS) attain ment demonstration:

• The model has received a scientific peer review.

• The model can be demonstrated to be a pplicable 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-Atmosphe re” air quality modeling system capable of addressing ozone, fine particul ate matter, visibility, and ac id deposition within a common platform. The original justification for the M odels-3 development emerged from the challenges posed by the 1990 CAAA and USEPA’s desire to develop an advanced modeling framework for
“holistic” environmental modeli ng utilizing state-of-science re presentations of atmospheric processes in a high performance computing envi ronment. The USEPA completed the initial stage of development with Models-3 and rel eased the CMAQ model in mid-1999 as the initial operating science model under the Models-3 framework.

An advantage of choosing CMAQ as the atmosphe ric model is the ability to do one-atmospheric modeling. The same model configuration is being applied for the ozone and PM 2.5 

### attainment demonstrations SIPs, as well as the regional haze SIP. A number of features in CMAQ’s
theoretical formulation and tec hnical implementation make the model well suited for annual PM modeling.

The configuration used for this modeling demonstra tion, 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 objectiv e, diagnostic, or pr ognostic 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 repli cate 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 m odel 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 bou ndary layer heights for AQ modeling

5.2.2.2. Overview of MM5

The non-hydrostatic MM5 model is a three-dime nsional, 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 for31-Virginia Regional Haze SIP 

### more than 20 years and has been used worldw ide 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 re search 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. Th e gridded meteorological fields produced by MM5 are directly compatible with the input requirements of “one atmo sphere” 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 in terpolation, followed by a mass-conservation readjustment.

Distinct planetary boundary layer (PBL) para meterizations are available for air-quality applications, both of which repr esent 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 di agnosing the other key boundary layer terms.

Initial and lateral boundary conditions are specified for r eal-data cases from mesoscale threedimensional analyses performed at 12-hour interv als on the outermost grid mesh selected by the user. Surface fields are analyzed at three-hour in tervals. A Cressman-based technique is used to analyze standard surface and radiosonde observations, usi ng 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 Regi onal Atmospheric Modeling System (RAMS) and the Systems Application International Mesosc ale Model. The MM5 enjoys a far richer application history in regulator y 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 be en found that the MM5 model tends to produce somewhat better photochemical model i nputs than alternative models.

The configuration used for this modeling demonstra tion, as well as a more detailed description of the MM5 model, can be found in the mete orological modeling protocol (Appendix E).

5.2.3. Selection of Emissions Processing System

5.2.3.1. Criteria

The principal criterion for an emissions processi ng system is that it accurately prepares emissions files in a format suitable for the pho tochemical 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 Protot ype was originally developed at the Microcomputing Center of North Carolina. As with most emissions models, SM OKE is principally an emission processing system and not a true em issions 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 em issions rates based on input mobile-source activity data, emission factors, and outputs fr om 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 algor ithms. Indeed, SMOKE is the fastest emissions processing tool currently available to the air quality modeling community. The sparse matrix approach utilized throughout SM OKE permits both rapid a nd flexible processing of emissions data. The processing is rapid because SMOKE utilizes a series of matrix
calculations instead of less effici ent algorithms used in previous systems. The processing is flexible because the processing steps of tem poral projection, controls, chemical speciation, temporal allocation, and spatial allocation have been separated into independent operations wherever possible. The results from these st eps are merged together at a final stage of processing.

SMOKE contains a number of ma jor features that make it an attractive component of the modeling system. The model s upports a variety of input fo rmats from other emissions processing systems and models. It supports bot h gridded and county total land use scheme for biogenic emissions modeling. SMOKE can acco mmodate 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 represente d and so that changes in air quality in response to changes in emissions may be projected. The year 2002 was sele cted 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, PM 2.5 

### , 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 regiona l haze air quality goals. The USEPA recommends that episode
selection be derived from th e following principal criteria:

• Simulate a variety of me teorological conditions.

• Model time periods in which observed con centrations 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 NAAQ S is based on multiple days.

For regional haze modeling, the guidance goes furthe r by suggesting that th e preferred approach is to model a full, representative year. More over, 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 recomm ended 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 meteor ological contractor (BAMS) identified important meteorological characteristics and data sets in the VISTAS region directly rele vant 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 Regre ssion Tree Analyses to evaluate visibility conditions for 2000, 2001, and 2002, the candidate modeling years. The year 2002 was found to be re presentative 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 PM 2.5 

### 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 an alysis, episode characterization analyses, which were colla borative investigations by VISTAS states including North Carolina, Georgia, Florida, inte nsively studied the availability of PM 2.5 

### , meteorological, and emissions data and the relevance of alternative baseline modeling periods from a regulatory sta ndpoint. 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 alre ady chosen calendar year 2002 as the modeling year.

After a lengthy process of integrated studies, th e episode selection process culminated in the selection of calendar year 2002 (January 1 th rough December 31) as the most current, representative, and pragmatic choice for VIST AS regional haze modeling. All of the USEPA criteria for regional haze episode selection were di rectly considered in this process together with many other considerations (e.g., timing of new em issions 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 re commends a 12-km modeling grid resolution for PM 2.5 

### modeling while a 36-km grid is consider ed acceptable for regional haze . For the VISTAS modeling, a coarse 36-km grid resolution wa s 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-wa y nesting is believed to be appropriate for the generally st agnant conditions experienced dur ing Virginia ozone episodes. Two-way nesting was not considered due to numer ical 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 loca tion 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 th e continental United States. This domain was used as the outer grid domain for MM5 mode ling with the CMAQ domain nested within the MM5 domain. Figure 5.4.1-1 shows the MM5 horizo ntal 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 VI STAS 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 doma in for which the RPGs will be assessed.

Figure 5.4.1-2. Detailed View of the 12 km VISTAS Grid36-Virginia Regional Haze SIP 

### 5.4.2. Vertical Modeling Domain

The CMAQ vertical structure is primarily defined by the vert ical grid used in the MM5 modeling. The MM5 model employed a terrain -following coordinate system defined bypressure, using 34 layers that extend from the surface to the 100 millibar level. A layeraveraging scheme was used to ge nerate 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 a nd the 19 layer CMAQ models were compared to ambient monitoring data.

6. MODEL PERFORMANCE EVALUATION

The initial modeling effort focused on evalua ting previous regional air quality modeling applications and testing candidate model conf igurations for the SMOKE emissions and CMAQ model for the VISTAS 36-km and 12-km modeling do mains. This effort resulted in a report recommending the model configuration for the an nual 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 mode ling 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 Character ization (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 mode l 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 pe rformance as ozone models. VISTAS’ evaluation considered several statistical performance meas ures and displays. Fractional bias and mean fractional error were selected as the most appr opriate metrics to summarize model performance;
other metrics were also calculated and are incl uded 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 pe rformance were prepared, including:

• Scatter plots of predicted and observed c oncentrations and deposition by species, monitoring network, and month.

• Time series plots of predicted and ob served concentrati ons and deposition by species, monitoring site, and month.

• Spatially averaged time series plots.

• Time series plots of monthly fractional bi as 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 pl ots”) that display fractional bias or
error as a function of co ncentration 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, PM 2.5 

### , and Regional Haze (USEPA, 2007). Both soccer plots and bugle plots offer a convenient way to examine model performan ce with respect to set goa ls and criteria. The bugle plots have the added benefit of adjusti ng the goals and criter ia to consider the38-Virginia Regional Haze SIP 

### concentration of the species. Analysis of bugle plots generally suggests that greater emphasis should be placed on performance of those componen ts with the greatest contribution to PM mass and visibility impairment (e.g., sulfate and organi c carbon) and that greater bias and error could be accepted for components with smaller contri butions 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 to tal 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 us ed 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 socce r 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 performan ce statistics for all of the most significant light scattering component species (sulfate, nitrate, a nd 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 perf ormance thresholds. Sulf ates 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 se parate soccer plots for each season. The seasonal plots emphasize poorer nitrate performance in the summer (does not even appear on the plots provide d because performance is off sc ale with other constituents), when observed nitrate is quite lo w and predicted nitrate is even lower. When concentration is factored into performance criteria, nitrate perf ormance improves with respect to mean fractional
bias and mean fractional e rror (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 m onitoring 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 E rror 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 BiasMean 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 BiasMean Fractional Error Sulfate

Nitrate

Organics

Criteria

Goal40-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 ( μ 

### g/m 3 

### )Mean Fractional Error Sulfate

Nitrate

Organics

Criteria

Goal

Figure 6.2-4. Bugle Plot—Mean Fraction Bias41-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 ( μ 

### g/m 3 

### )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 (bextSO 4 

### ).

• Red = light extinction due to nitrates (bextNO 3 

### ).

• 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 orde r 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 simp lified. 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 Virgin ia Class I areas on both 20 percent best days and 20 percent worst days. The bar char ts also suggest that or ganic 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 mo re prominent role in the 20 percent best days than with the 20 percent worst da ys. Also, the species make-up on th e 20 percent best days varies42-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 s how that model performance does improve across the sites. Light extinction due to sulfate predic tion is better, but still falls short on some days. Light extinction due to organic carbon also becomes more importa nt to total light extinction. Much like the sulfate component, the orga nic 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 fa ll within acceptable limit s. Virginia further asserts the one atmosphere modeling performed by the VISTAS contractors is representative of
conditions in the southeastern st ates 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% groupbEXT (1/Mm) bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-1. Stacked Bar Charts for Shenandoah on the 20% Best Days43-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% groupbEXT (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% groupbEXT (1/Mm) bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-3. Stacked Bar Chart for James River Face on the 20% Best Days44-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% groupbEXT (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 regulati on requires states to establish RPGs, expressed in dv, for visibility improvement at each aff ected Class I area covering each (approximately) 10- year period until 2064. This first set of RPGs mu st be met through measures contained in the state’s long-term strategy covering the peri od 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 regiona l haze in the 2000-2004 baseline timeframe were large stationary sources of SO 2 

### 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 VI STAS 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 re alized between the baseline
and 2018?

• Narrowing down further, emissions in what geographic locations are found to have the greatest impact on visibi lity in specific Class I areas?45-Virginia Regional Haze SIP 

### • What types of emissions sources are found in those geographic locations?

• Which specific individual s ources in those geographic lo cations have the greatest visibility impacts at a given Class I area?

• What additional emission controls repres ent 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 im provement, compared to the glidepath, is expected at Class I areas in Vi rginia 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 impl emented between the baseline period and 2018. These programs are describe d in more detail below.

7.2.1. Federal and State Control Requirements

The first phase of CAIR caps emissions of SO 2 

### and NO X 

### from EGUs in the eastern United States beginning in 2010 and 2009, respectively. The se cond phase of CAIR wo uld have reduced SO 2 

### emissions from EGUs in these stat es by more than 70 percent and NO X 

### emissions by more than 60 percent from 2003 levels. CAIR has been rema nded 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 fr om utility boilers by November 16, 2011.

Phase I of the NO X 

### SIP call applies to certain EGUs and large non-EGUs, including large industrial boilers, turbines, and cement kilns. Those states affected by the NO X 

### SIP call in the VISTAS region have developed rules for the control of NO X 

### emissions that have been approved by the USEPA. The NOx SIP Call has re sulted in a 68 percen t reduction in NO X 

### emissions from large stationary com bustion sources. For this analysis, the emissions for NO X 

### 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 pow er plants in North Carolina mu st achieve a 77 percent cut in
NO X 

### emissions by 2009 and a 73 percent cut in SO 2 

### emissions by 2013.

A number of consent agreements also impose sp ecific controls that were included in this inventory development process:

• TECO (US District Court, Middle Distri ct of Florida): Under a settlement agreement, Tampa Electric installed pe rmanent emissions control equipment by2008 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 po llution emission allowances that Tampa46-Virginia Regional Haze SIP 

### Electric or others could use, or sell to others, to emit additional NO X 

### , SO 2 

### , and
PM.

• VEPCO (US District Court, Ea stern 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 SO 2 

### and NO X 

### emissions each year from eight coal-fired electricity generating plants in Virginia and West Virginia.

• Gulf Power (State of Flor ida “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 NO X 

### emission rates by 61 percent at its Crist genera ting plant by 2007, with major reductions beginning in early 2005. The Crist plan t is a significant source of NO X 

### 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 SO 2 

### 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, Virg inia, to control with a wet scrubber the
SO 2 

### emissions from the #8 Power Boiler. This control device will result in reductions of over 3,500 tons of SO 2 

### 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 NO X 

### reductions from specific coal fired power plants and address transportation plans in these cities.

The NC SIP for the Charlott e/Rock Hill/Gastonia nonattainm ent area includes Reasonable Achievable Control Technology (RACT) for NO X 

### for two facilities located in the nonattainment area: Philip Morris USA and Norandal USA.

USEPA set a PM emissions standard for ne w heavy-duty engines of 0.01 grams per brakehorsepower-hour (g/bhp-hr), to take full effect fo r diesel engines in the 2007 model year. This
rule also includes standards for NO X 

### and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/ bhp-hr, re spectively. These NO X 

### 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 technol ogy to be effective on these tr ucks and buses. USEPA required a 97 percent reduction in the sulfur content of high way 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. Manufact urers can produce vehicles with emissions ranging from relatively dirty to very clean, but th e mix of vehicles a manufacturer sells each year must have average NO X 

### 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 NO X 

### , hydrocarbons, and carbon monoxide from several groups of previously unregulated nonroad engines. Includ ed in these are large industrial spark-ignition engines and recreational vehicles. Nonr oad 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 an d industrial applications and include forklifts, electric generators, airport baggage transport ve hicles, and a variety of farm and construction applications. Nonroad recreational vehicles incl ude snowmobiles, off-hi ghway 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 wi ll reduce emissions by more than 90 percent from nonroad diesel equipment and will reduce sulfur le vels by 99 percent from previous levels in nonroad diesel fuel starting in 2007. This step w ill 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 industr ial boiler/process heater/reciprocating internal combustion engines were 4 percent for SO 2 

### and 40 percent for PM 10 

### and PM 2.5 

### . 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 re sult sources that were subject to the rule may need to file applications for permits contai ning MACT limits derived on a case-by-case basis within a time specified by USEPA or Virginia.

The projection inventories do not include the NO X 

### 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 occurr ing prior to 2002 were counted.

Seven localities in Virginia, along with VDEQ a nd 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 NO X 

### RACT on major sources of
NO X 

### emissions, the compacts contained many direct ionally correct programs implemented to
reduce emissions from these areas.

7.2.2. Additional State Program s to Reduce Emissions

In addition to accounting for specific emission re ductions due to ongoing air pollution programs as required under the regional ha ze 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 CF R 51.308(d)(3)(v)(B)) and agricultural and forestry smoke management (40 CFR 51.308(d)(3)(v) (E)). Secti on 7.10 provides more informa tion on these activities.

7.2.3. Projected 2009 and 2018 Base G2 Emissions Inventories

The Base G inventories for 2009 and 2018 acc ount 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 us ing 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. Thes e 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 know n state level Stage I controls on gasoline dispensing facilities and open burni ng 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 underl ying the 2002 baseline inventory (vehicle emission inspection, Stage II vapor recovery, anti-tampering, etc.) with changes based on specific state input. Non-road control da ta and projections for 1996, 2010, 2015, and 2020 were
obtained from The Clean Air Interstate Rule Emissions Inventory Tech nical Support Document (USEPA, 2005), and straight li ne projections were used to estimate 2009 and 2018 levels.

The following bar charts show expected decreases in emissions of SO 2 

### and NO X 

### across the VISTAS states from 2002 through 2018. (Similar ch arts for other visibility impairing pollutants are contained in Appendix H). Note that for SO 2 

### emissions in particular , which are the largest contributors to haze, emissions from electric ge nerating facilities are expected to decrease dramatically (70 percent) be tween 2002 and 2018. However, even after implementation of CAIR, EGU emissions are projected to remain th e largest contributor to haze, comprising more than half of remaining SO 2 

### emissions in every state.

The tables below summarize the 2009 and 2018 Ba se G2 emissions inve ntory. The complete inventory and discussion of the me thodology is containe d in Appendix D.49-Virginia Regional Haze SIP Figure 7.2.3-1. Base G2 Annual SO 2 for 2002, 2009, and 2018 VISTAS States

Figure 7.2.3-2. Base G2 Annual NO X for 2002, 2009, and 2018 VISTAS States W e s t V

i r g i n i a

A

l a b

a m

a
F l o r i d

a

K e n t u c k

y
G

e o r g i a

M i s s i s s i p p i

S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a

T e n n e s s e e V i r g i n i a 

### 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous

Nonroad
Onroad

Industrial
Other Fuel Combustion

EGU 2 0

0

2

2 0 0

9

2 0

1 8

W e s t V

i r g i n i a

A

l a b

a m

a
F l o r i d

a

K e n t u c k

y
G

e o r g i a

M i s s i s s i p p i

S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a

T e n n e s s e e V i r g i n i a 

### 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous

Nonroad
Onroad

Industrial
Other Fuel Combustion

EGU 2 0

0

2

2 0 0

9

2 0

1 8

A

l a b

a m

a
F l o r i d

a

K e n t u c k

y
G

e o r g i a

M i s s i s s i p p i

S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a

T e n n e s s e e V i r g i n i a 

### 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous

Nonroad
Onroad

Industrial
Other Fuel Combustion

EGU Miscellaneous

Nonroad
Onroad

Industrial
Other Fuel Combustion

EGU 2 0

0

2

2 0 0

9

2 0

1 8

0 100 200 300 400 500 600 700 800 900 1,000

A l a bama Flo rida

G eo

rgia

K e ntuc k

y

M i ssissippi North Carol in

a

Sou t h Carolina

Te

n nessee Virginia

W e st VirginiaAnnual NOx (Thousand Tons) 

### Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2 0 0

2

2 0 0

9

2 0

1 8

0 100 200 300 400 500 600 700 800 900 1,000

A l a bama Flo rida

G eo

rgia

K e ntuc k

y

M i ssissippi North Carol in

a

Sou t h Carolina

Te

n nessee Virginia

W e st VirginiaAnnual NOx (Thousand Tons) 

### Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2 0 0

2

2 0 0

9

2 0

1 850-Virginia Regional Haze SIP Table 7.2.3-1. 2009 Virginia Base G2 Emissions Summary, tpy

Sector VOC NO X PM 2.5 PM 10 NH 3 SO 2
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 NO X PM 2.5 PM 10 NH 3 SO 2

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, th e 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 va lue for the worst days.

Figures 7.2.4-1 and 7.2.4-2 illustrate the predic ted visibility improvement by 2018 resulting from the Base G2 inventory that represents implementation of existing federa l and state regulations, compared to the Uniform Rate of Progress glid epath for Shenandoah and James River Face. The red lines show the target na tural condition in 2064 for the 20 percent worst days, and the incremental dv changes resulting from a uniform rate of progress betwee n current and natural conditions in 2064, for average 20 percent worst visi bility 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 l ong term strategy. Method 1 predicti on 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 uni form rate of progress glidepath by 2018. In fact, as illustrated in Figure 7.2.4-3, visibility improve ments 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 percen t greater than the uniform rate of progress by 2018.

The expected change in visibility at Shen andoah 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 illustra ted in Figures 7.2.4-4 and 7.2.4-5

In addition to improving visibility on the 20 percen t worst visibility days, states are also required to protect visibility on the 20 percent best days at the Cla ss I areas. Figures 7.2.4-6 and 7.2.4-7 show graphically the progress expe cted on the 20 percent best vi sibility 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 Cl ass 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 ch ange, 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
YearHaziness 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 Days52-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
YearHaziness Index (Deciviews)

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

Figure 7.2.4-2. Uniform Rate of Progre ss 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%COHUDOSOGRSMJARILIGOMACASHENSHROSIPSCHASEVEROKEFROMASAMASWANBRETBRIGCACRHEGLMINGUPBUPercent 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% 140% 160% 180% 200%COHUDOSOGRSMJARILIGOMACASHENSHROSIPSCHASEVEROKEFROMASAMASWANBRETBRIGCACRHEGLMINGUPBUPercent of target reduction achieved

VISTAS non-VISTAS CMAQ New IMPROVE Algorithm
CMAQ Old IMPROVE Algorithm

0% 20% 40% 60% 80% 100% 120% 140% 160% 180% 200%COHUDOSOGRSMJARILIGOMACASHENSHROSIPSCHASEVEROKEFROMASAMASWANBRETBRIGCACRHEGLMINGUPBUPercent of target reduction achieved

VISTAS non-VISTAS CMAQ New IMPROVE Algorithm
CMAQ Old IMPROVE Algorithm53-Virginia Regional Haze SIP Figure7.2.4-4. Shenandoah 20% Worst Visibility Days and Natural Conditions Visual Images54-Virginia Regional Haze SIP Figure7.2.4-5. James River Face 20% Worst Visib ility Days and Natural Conditions Visual Images55-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
YearHaziness 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
YearHaziness Index (Deciviews)

Baseline Condition (Best Days) Observation Method 1 Prediction Baseline = 14.2 dV

Figure 7.2.4-7. 20% Best Days Ra te of Progress for James River Face56-Virginia Regional Haze SIP Figure 7.2.4-8. Visibility Improvement, 20% Best Days, 2018 Base G2a



### 7.3. Relative Contribution from Internationa l Emissions to Visibility Impairment
in 2018 at VISTAS Class I areas

Emissions from Mexico, Canada, Central Am erica, Asia, and Africa contribute to PM 2.5 

### loadings and visibility impairment at Class I areas in the continental United States. To evaluate the
relative contribution of in ternational emissions to visibility at Class I areas in the southeastern United States, VISTAS used a combination of modeling results fr om the global threedimensional chemical transport model (GEOS-Chem) and CMAQ. VISTAS used the GEOSChem global model to generate initial and boun dary conditions for the CMAQ modeling domain. GEOS-Chem was run for the 2002 modeling year usi ng a 4 x 5 degree horizontal grid resolution and a 3-hour temporal resolution. Because em issions were based on monthly averages, the model does not capture the episod ic variability in emissions. The GEOS-Chem outputs were
used to calculate ini tial and boundary conditions for the na tional CMAQ modeling domain. The national CMAQ domain included po rtions of Canada and Mexico, so emissions for these
countries were included within the national CM AQ modeling domain or as part of the boundary
conditions outside the national modeling domain, as appropriate.

Two complementary methods were used to calcul ate the impact of inte rnational emissions at Class I areas. Because the international emissions inventory used in GEOS-CHEM did not distinguish between wildfires a nd anthropogenic fires, all intern ational fire emissions were assumed to be wildfire, and the contributions attr ibutable 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%COHUDOSOGRSMJARILIGOMACASHENSHROSIPSCHASEVEROKEFROMASAMASWANBRETBRIGCACRHEGLMINGUPBUPercent 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%COHUDOSOGRSMJARILIGOMACASHENSHROSIPSCHASEVEROKEFROMASAMASWANBRETBRIGCACRHEGLMINGUPBUPercent of target reduction achieved

VISTAS non-VISTAS CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm57-Virginia Regional Haze SIP 

### • International emissions as the diffe rence 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. Th e difference represen ts 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 contribu tion on 4 x 5 degree grid. Concurrent Harvard modeling for the Electric Powe r Research Institute (EPRI) provided
GEOS-Chem results for 2001 international contribution on a 1 x 1 degree grid
scale.

• International emissions as the differen ce between two CMAQ 36-km simulations, both using 2018 Base F emissions a nd boundary conditions from GEOS-Chem
- International emissions are represente d 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 th e second CMAQ run, only global (United States and international) natural emissi ons are active. Here the impacts of international emissions are compared agai nst 2018 conditions ra ther 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 em issions and boundary conditions on visibility at
Class I areas in 2002.

As illustrated in Figure 7.3-1 for annual averag e contributions to sulfate at VISTAS and neighboring Class I areas, the estim ated international c ontributions 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 internationa l 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 an thropogenic 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 th e future, the incremental contribution from international emissions will become more importa nt. 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 Shena ndoah or James River Face are small compared to
total emissions.

7.4. Relative Contributions to Visibili ty Impairment: Pollutants, Source Categories, and Geographic Areas

An important step toward identi fying 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 differe nt 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 proj ections inventory and consider ed 30 percent reductions from specific pollutants, source categories, and ge ographic areas. Emissions sensitivities were repeated using the 2009 Base D projection inve ntory and two, month-lo ng 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 1.2BRIGHEGLCACRMINGUPBUBRETEVERCHASSAMACOHUOKEFROMASIPSSHROGRSMLIGOMACASWANJARIDOSOSHEN(NH4)2SO4Conc. (μg/m3)



### GEOS_4x5 GEOS_1x1 CMAQ59-Virginia Regional Haze SIP SHENANDOAH Domestic and International Aerosol Mass by Species 20% Worst Days (2002)

0 5 10 15 20 25 30 35 40 45 50DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

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 10/2Mass (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 5 10 15 20 25 30 35 40 45 50DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

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 10/2Mass (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 In ternational Contributions (right)60-Virginia Regional Haze SIP 

### • SO 2 

### from EGU sources in each VISTAS state, other RPOs in the VISTAS 12 km grid, and boundary conditions from outside the 12 km domain.

• SO 2 

### from non-EGU point sources in each VISTAS state, other RPOs, and boundary conditions.

• NO X 

### from ground level (on-road plus non -road plus area) sources in each
VISTAS state and other RPOs.

• NO X 

### from point (EGU plus non-EGU) sources in each VISTAS state and other
RPOs.

• NH 3 

### from all sources in VISTAS and other RPOs.

• VOCs from anthropogenic and biogenic s ources in the 12 km modeling domain.

• Primary carbon from all ground level sour ces 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 th e 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 SO 2 _EGU SO 2 emissions from EGUs

SO 2 _nonEGU SO 2 emissions from non-EGUs NO X _Ground Ground level NO X emissions

NO X _Point NO X emissions from point sources NH 3 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 fires61-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

S O2_EGU SO2_n o nEGU

N Ox

_Gro u n d

N O

x_

P oint NH3 V OCs

PC_Ground PC _ Po

in

t 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

S

O2_ EG

U

S

O2 _ non

E GU NOx _Grou nd NOx_P o int NH3 VOC s

PC

_Gr o und PC_ P oint 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% Reductions62-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 pr ojected to result from further reducing SO 2 

### 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 SO 2 

### reductions from EGUs in several VISTAS states including Alabama, Georgia, Kentucky, North Carolina, South Caroli na, Tennessee, Virginia, and West Virginia.
Contributions from other RPOs and from the bounda ry conditions are comparatively small, and the greatest benefits would likel y be from further EGU reductions within the VISTAS states. Smaller benefits are projected from additional SO 2 

### emission reductions from non-utility, industrial point sources.

Because ammonium nitrate is a small contributor to PM 2.5 

### mass and visibility impairment on the 20 percent worst days at the mountain Cl ass I areas, the benefits of reducing NO X 

### and NH 3 

### 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 bene fit at the Class I areas. Reducing primary carbon from point sources, ground level so urces, or fires is projected to have small to no visibility
benefit. This is consistent w ith the monitoring data that shows that most of measured organic carbon is secondary in origin and that primar y 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 modele d in the sensitivity analyses.

Note that these results from the emission sensitiv ity runs are consistent with the conclusions
drawn from the 2000-2004 baseline monitoring data (see Se ction 2.4). The results indicate that
sulfate is the dominant contribu tor to visibility impairment on the 20 percent worst days at all sites and that ammonium nitrate may be importa nt for sites where the 20 percent worst days occur in the winter. Virgin ia concludes that reducing SO 2 

### emissions from EGU and non-EGU point sources in the VISTAS states would have th e 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 contri buting to visibility impairment at each Class I area have been identified, it is necessary to focus on where the greatest contribu ting sources are
located. SO 2 

### emission reductions from EGU and non-EGU point sources in the VISTAS states have already been established as the greatest contri butors 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 area s that most likely influence visi bility in each Class I area and then to identify the major SO 2 

### point sources located in t hose geographic areas. An SO 2 

### 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 SO 2 

### point
sources within these AoI were identified and ranked by thei r 2018 Base G emissions. The following sections contain a broa d overview of the st eps 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 ba ck trajectories for IMPROVE monitoring sites in Virginia and neighboring Class I areas for the 2000-2004 baseline pe riod. 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 Shen andoah 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 tr ajectories for 20 percen t 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 year s of back trajectories for the 20 percent worst vi sibility days in 2000-2004. Residenc e 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 trajectorie s with 100m and 500m start height s. As illustrated in Figure 7.5.2, winds influencing Shenandoah on the 20 percen t worst days come from all directions and there is no single predominant wind direction influencing the 20 per cent 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. SO 2 

### Areas of Influence

The next step was to develop sulfate extinction- weighted residence time plots to define the geographic area with highest proba bility 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 focu s on the 20 percent worst days that are influenced by sulfate and place less importance on days influe nced by organic carbon from fires. Sulfateweighted back trajectories for th e 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 SO 2 

### 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-w eighted residence time.

7.5.4. Emissions Sources within SO 2 

### Areas of Influence

Residence time plots were then combined with geographically-gridded em issions data based on
the 2002 baseline and 2018 Base G emissions invent ories. 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 tr ansformation of point source emissions along the path of the trajectories, these data were weight ed by 1/d, where d was calcu lated as the distance, in kilometers, between the center of the grid cell in which a source is loca ted and the center of the grid cell in which the IMPROVE monitor is located. The distance-we ighted point source
SO 2 

### emissions are then combined with the gridde d extinction-weighted back-trajectory residence times at a spatial re solution of 36 km.65-Virginia Regional Haze SIP 

### SO2 Area of Influenc e 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 SO 2 AoI for SO 4 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 SO 2 

### emissions were multiplied by the total extinction-weighted back-tra jectory residence times on a grid cell by grid cell basis. These results were then normalized by the domain-wid e total and displayed as a percentage. The analysis was done using both the 200 2 and 2018 base year inventories.

Figure 7.5.4-1 illustrates the result of this fi nal analysis step for the 2002 and 2018 distanceweighted, gridded emissions, sulfate extinction-we ighted, residence time plots for Shenandoah. These maps help visualize where the emissions reductions will be occurring between 2002 and 2018. The change in SO 2 

### 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 SO 2 

### 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 gradie nt than on the 2002 map. Because the total emissions in the domain are smaller in 2018, a s ource 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 SO 2 Distanc- Weighted Emissions, SO 4 Extinction-Weighted
Residence Time Plots.



### Figure 7.5.4-2 illustrates gridded SO 2 

### distance-weighted emissions, sulfate extinction-weighted residence time plots for 2018 emissions for James Ri ver Face. This plot il lustrates the relative importance of Virginia sources of SO 2 

### compared to sources in ne ighboring states. Additional analyses, including 2002 and 2018 distance-weighte d emissions residence time plots for the Class I areas in Virginia and ne ighboring 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 s how, in tabular form, the rela tive contributions of point
source SO 2 

### emissions from nearby states to the Virg inia 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 Cl ass 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 plot s 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

2018 SO2 emissions 2002 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 SO 2 Distance Weighted Emissions, SO 4 Extinction-Weighted
Residence Time Plot



### Table 7.5.4-1. State 2018 SO 2 

### 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 SO 2 

### 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 SO 2 

### 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 SO 2 

### 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 great est impact on visibility in
Shenandoah and James River Face. Lists of SO 2 

### point sources within the AoI for each Class I area were developed using the most current (B aseG) 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 gr eater than five percent. For SO 2 

### sources within each AoI, the following attributes were defined for each individual unit:

• State, county, source (plant), a nd industry identification codes.

• SO 2 

### 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 metr ic 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, st arting with an analysis of the major source categories in each SO 2 

### AoI to determine which major cate gories 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 type s were reviewed. The contributions from major source categories to the 2018 Ba se G2 inventory for the SO 2 

### 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 NO X CO SO 2 PM 10 -Pri PM 2.5 -Pri NH 3

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 So urce Categories, James River Face Area of Influence

Tier VOC NO X CO SO 2 PM 10 -Pri PM 2.5 -Pri NH 3

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 industr ial boilers are the two major sources categories contributing to 2018 SO 2 

### emissions in the AoI. Together these two source categories contribute greater than 80 percent of the 2018 SO 2 

### emissions for the AoI for the Virginia Class I areas.71-Virginia Regional Haze SIP 

### These tables can also be used to evaluate th e major source categories contributing to emissions
of NO X 

### , NH 3 

### , and PM emissions in 2018. For instance, highway vehicles and off road vehicles are major sources of NO X 

### emissions, in addition to electric utilities and industrial boilers. The source category “miscellaneous” (which includes agricultural sources and fires) is the major
contributor to NH 3 

### and primary PM. The emissions sensitivities discusse d in Section 7.4 indicated very small benefits from controlling NO X 

### , NH 3 

### , and primary PM emissions at the Virginia Class I areas, but if these emissions were of concern, different s ource categories would
need to be addressed.

The contributions to SO 2 

### emissions in 2018 from the three hi ghest 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 util ities, all the SO 2 

### emissions are attributable to co al fired power plants. Within industrial boilers, most emissions are attributable to coal fired boilers with lesse r contributions from oil and gas boilers. Commercial and inst itutional coal and oil boilers have smaller
contributions.

Table 7.5.5-3. Annual 2018 SO 2 Emissions Percentage with in 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 c onsider what additional control measures for
electric utilities and industrial boilers are reasonable. The lists of individual sources are also being used to determine if indi vidual sources in other sources categories are major contributors
to SO 2 

### emissions in the AoI.72-Virginia Regional Haze SIP 

### 7.6. Evaluating the Four Statutory Factors for Specific SO 2 

### Emissions Sources in
Each Area of Influence

The next step was to identify emission reductions th at have already occurred within each source category and at specific units. Unit-level tables of emission comp arisons from 2002 to 2018 were developed, allowing VISTAS States to re view existing emission re ductions. These tables assigned future year control technology from IPM forecasting, from state modifications made to EGU assumptions, and from control efficien cy 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 feasib ly be available and to assign costs to those
control measures.

For EGUs, the 2018 IPM file used by VISTAS fo r 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 sour ce types did not duplic ate existing base case assumptions.

For non-EGUs, VISTAS used USEPA’s AirContro lNET database, modified for the VISTAS
emission inventories. The core of AirControlN ET 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 appli cability, 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 identifi ed above, VISTAS ran every available SO 2 

### control strategy in AirControlNET against the EGU and non-EGU point source inventories to develop a
master list of incremental control strate gies 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 co sts 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 201 8 residual emissions and distance (Q/d) or squared distance (Q/d 2 

### ), and the normalized 2018 SO 2 

### 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 reas onable further progress.

The regional haze regulation requires that states consider the following factors and demonstrate
how these factors were taken into considerati on in selecting the reas onable progress goal:

• the costs of compliance,

• the time necessary for compliance,

• the energy and non-air quality environm ental 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-fir ed electric utilities and coal-fired industrial boilers were the largest source categories contributing to SO 2 

### in 2018 in the AoI defined for the Virginia Class I areas. Industrial boilers using o il and commercial and institutional boilers using coal or oil had
small contributions to SO 2 

### in 2018.

Emissions of SO 2 

### from utility, industrial, commercial, or institutional boilers can be controlled either by switching the fuel source to a lower su lfur 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 cont ent or blending bituminous coals can reduce SO 2 

### emissions with low impact to boiler performance. While sub-bituminous co al has a lower sulfur content than bituminous coal, it al so 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 sulf ur sub-bituminous coal without affecting boiler operations. Costs of boiler modi fications 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, transpor tation costs, and modifica tion 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-combus tion control for coal-fir ed boilers. Flue gas is passed through an absorbent for SO 2 

### (generally limestone or lime) in a wet scrubber, a dry scrubber, or a spray dryer. A calcium sulf ate by-product is produced that may be further processed to produce gypsum as a commercial by -product. Costs of fl ue-gas desulfurization include initial construction costs and ongoing opera tional and maintenance co sts 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 th ere is little precedent
for such installations.

7.6.2. Time Necessary for Compliance

For fuel switching, the time n ecessary to terminate existing fu el contracts and initiate new
contracts needs to be considere d. 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 priori ties. 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-combus tion 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 add itional non-air environmental impacts such as74-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 im pacts 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 pr ocess 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 determini ng reasonable progress for Virginia sources. For a detailed discussion of the reasonable pr ogress assessments for al l units’ contributions greater than 1 percent to any Cl ass I area in Virginia or in ne ighboring 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 great er than 70 percent of the visibility impairing pollution. The VISTAS states determined that controlling SO 2 

### emissions was the approp riate step in addressing the reasonable progress assessment for 2018. The VISTAS findings were consistent with the findings of SAMI, which confirme d that sulfate partic les account for the great est portion of the haze affecting Class I areas in the Southern A ppalachian region and that these sulfates were produced in large part from coal combustion SO 2 

### emissions.

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

progress

Since SO 2 

### point source emissions in 2018 are projected to represent greater than 95 percent of
the total SO 2 

### emissions inventory, the VISTAS States concluded that the focus should be on EGU and non-EGU point sources of SO 2 

### emissions.

7.7.3. Step 3: Determine if the Clean Air Int erstate Rule (CAIR) is sufficient for reasonable progress for subject EGU’s

The coal-fired EGUs in Virgin ia are expected to reduce SO 2 

### emissions by approximately 50 percent between 2002 and 2018 due to the installation of SO 2 

### controls, the use of very low sulfur fuels, or fuel switching. Projected SO 2 

### emission reductions are the result of CAIR, which relies on trading and the use of banked Title IV allowa nces, and the requirements of the AEP Eastern System Consent Agreement. CAIR emission reductions are not directly enforceable, and
emission reduction estimates are based on inform ation provided by facility owners as well as permit applications and other documents submitted to Virginia. Virginia intends to re-evaluate the IPM predictions of SO 2 

### for CAIR at the time of the firs t required periodic report in 2012 to ensure that the predicted reducti ons are indeed taking place where they are expected and needed.
Based on the confirmed CAIR controls and th e reductions stemming from the AEP Consent Agreement, Virginia believes that these emi ssions 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 sufficient75-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 contri bution from all emission units within the SO 2 

### AoI for a given Class I area and identified the EGUs a nd non-EGUs with a contri bution 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 th e 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 Virg inia 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 Brigantin e, 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 cu toff created a practical listing of facilities to examine for reasonable progress but also addre ssed almost half of the calculated percent visibility contributi on 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 Poin ts 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 li st of facilities subject to a reasonable progress review was necessary to allow at tention to be focused on those un its responsible for the largest portion of calculated visi bility impairment.

Table 7.7.4-2 shows facilities and units in Virginia th at 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 SO 2 

### emissions data. The first set was used as part of the G2 inve ntory and was used to calculate the expected visibility impact. The second set of updated 2018 SO 2 

### emissions data in th is table reflects new information received after the G2 inventory e ffort, including expected BART reductions and limitations imposed due to permitting, shutdowns, and enforcement proceedings76-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. Ta ble 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 n ecessary 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 ma y 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 contro ls. For the purpose of evaluating the cost for the reasonable progress assessment in this first regi onal haze SIP, Virginia believes it is not equitable to require non-EGUs to bear a greate r economic burden than EGUs for a given control strategy. In other words, it is not reasonable to potentiall y subject non-EGUs to control measures that require a higher co st per ton than that which has been found reasonable for EGUs.
In order to determine the cost-effectiveness of SO 2 

### 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 SO 2 

### controls, making it appropriate to consider as a benchmark in determin ing a reasonable costeffectiveness for SO 2 

### control for purposes of the reasonable progress assessment.

In the CAIR preamble, USEPA notes that:

The SO 2 

### annual control costs that were presented in the CAIR NPR (Notice of Proposed Rulemaking) were average cost s of $700 per ton and $800 per ton for years 2010 and 2015, respectively, and marg inal costs of $700 per ton and $1,000 per ton for years 2010 and 2015. In addition, the NPR included the results of sensitivity analyses that examined costs of the proposed SO 2 

### controls based on the Energy Information Administration’s proj ections for electricity growth and natural gas prices. These sensitiv ity analyses showed marginal SO 2 

### control costs of $900 per ton and $1,110 per ton fo r years 2010 and 2015, respectively.77-Virginia Regional Haze SIPTable 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1%Data used for Contribution CalculationUpdated 2018 Emission EstimatesCountyPlant IDPlant NamePoint IDUnit Description2002 SO2tpy2018 SO2tpy%Contribution2018 SO2tpyComment/ExplanationSwanquarterIsle of Wight51-093-00006InternationalPaper Company4#7 Boiler 543 mmbtu/hr burningcoal, #6 oil, wood, and TRS gases3,720 4,299 1.19% 3,814The facility’s emissions in 2002were approximately 8,696 tpy ofSO2. Since 2002, IP has receiveda facility-wide permit limiting SO2emissions from the facility to nomore than 7,980 tpy of SO2.Emissions reductions haveresulted from the shutdown ofpower boiler #8 and theinstallation of a TRS scrubber onthe NCG gases incinerated inPoint ID #4. See Appendix J.Linville GorgeRussell51-167-00003AEP-ClinchRiver1238 MW EGU coal fired usingapproximately 0.8% S coal.8,158 10,014 4%Russell51-167-00003AEP-ClinchRiver2238 MW EGU coal fired usingapproximately 0.8% S coal.8,115 10,131 4%Russell51-167-00003AEP-ClinchRiver3238 MW EGU coal fired usingapproximately 0.8% S coal.8,804 9,911 4%16,300The facility is subject to anemissions cap on SO2of 16,300tpy beginning 2015, based on theAEP consent agreement. SeeTable 4-1 and Section 7.2.1.Dolly SodsCity ofCovington51-580-0003MeadWestvaco 25Combined stack for #6 boiler, 550mmbtu/hr firing coal; #7 boiler,440 mmbtu/hr firing coal, bark, andwood; #8 boiler 580 mmbtu/hrfiring coal, bark, and wood; and #9boiler 807 mmbtu/hr firing coal8,552 9,997 1.1% 6,817Unit #9 is subject to BART. Thestack is equipped with arudimentary scrubber. The BARTdetermination required an upgradeto the scrubber that will reduceemissions from the stack (all 4units) to no more than 8,020 tpy.See Section 7.7.5.2.2 and Table7.8.3-1. A reasonable progressreview was also conducted on thisstack since Units #6, #7, and #8also exhaust through the mainstack with Unit #9. Thereasonable progress reviewdetermined that an additional levelof control was feasible and apermit based on the reasonableprogress information has beendrafted, limiting the emissionsfrom this point to 6,817 tpy SO2.See Section 7.7.5.2.2.78-Virginia Regional Haze SIPTable 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1%Data used for Contribution CalculationUpdated 2018 Emission EstimatesCountyPlant IDPlant NamePoint IDUnit Description2002 SO2tpy2018 SO2tpy%Contribution2018 SO2tpyComment/ExplanationJames River FaceCity ofCovington51-580-0003MeadWestvaco 25Combined stack for #6 boiler, 550mmbtu/hr firing coal; #7 boiler,440 mmbtu/hr firing coal, bark, andwood; #8 boiler 580 mmbtu/hrfiring coal, bark, and wood; and #9boiler 807 mmbtu/hr firing coal8,552 9,997 18.4% 6,817See above.Botetourt51-023-0003RoanokeCementCompany22#5 kiln: 184 tphpreheater/precalciner kiln2,885 3,976 7.3% 3,104Facility is limited by permit to3,104.4 tpy of SO2.Bedford51-019-0003Georgia PacificBig Island1#4 Boiler, 284 mmbtu/hr coal/#2oil fired boiler.1,090 1,223 5.5% 219The BART process results in theinstallation of a FGD unit with acontrol efficiency of at least 90%for SO2emissions. See Section7.7.5.2.4 and Table 7.8.3-1.Rockbridge51-163-0001MohawkIndustries –Lees Carpet7155 mmbtu/hr coal fired boiler witha 1% S content limitation293 291 4% ---No changes expected.Giles51-071-0002AEP-Glyn Lyn 3 238 MW coalfired EGU 7,488 9,981 3.6% ---No changes expected.Giles51-071-0004CelaneseAcetate LLC1Stack consists of Boiler #1, 91mmbtu/hr; Boiler #3, 184mmbtu/hr; Boiler #5, 246mmbtu/hr; Boiler #2, 91 mmbtu/hr;Boiler #4, 184 mmbtu/hr; Boiler #6246 mmbtu/hr; and Boiler #7 322mmbtu/hr burning coal with abouta 1.1% S content.6,560 6,510 2.5% ---No changes expected.Fluvanna51-065-0001Dominion-Bremo2 185 MW coal firedEGU 7,993 6,253 2.2% ---The facility is required, subject toState Corporation Commissionapproval, to switch fuels two yearsafter the Virginia City HybridEnergy Center commencescommercial operation. Thisrequirement is in the July 1, 2008,PSD permit for the Energy Center.A fuel switch would eliminatemost of the SO2emissions fromthis facility. See Table 4-1 andSection 7.2.1.79-Virginia Regional Haze SIPTable 7.7.4-2. Units within Virginia with Visibility Impairment Contributions of at least 1%Data used for Contribution CalculationUpdated 2018 Emission EstimatesCountyPlant IDPlant NamePoint IDUnit Description2002 SO2tpy2018 SO2tpy%Contribution2018 SO2tpyComment/ExplanationBedford51-019-0003Georgia PacificBig Island2#5 Boiler, 339 mmbtu/hr coal,wood, wood/paper waste.251 286 1.3% ---No changes expected. This unit isa BART eligible unit. However,the facility is accepting alimitation on the amount of coal tobe burned in the unit such that theannual capacity factor for coalmay not exceed 10%. See Section7.7.5.2.4 and Table 7.8.3-1. Thefacility will be limited to 374 tpyof SO2from this unit. Growthprojections in the inventory areexpected to be a better indicator offuture SO2emissions from the unitthan is the BART emissionslimitation of 374 tpy.ShenandoahFluvanna51-065-0001Dominion-Bremo2 185 MW coal firedEGU 7,993 6,253 8.9% ---The facility is required, subject toState Corporation Commissionapproval, to switch fuels two yearsafter the Virginia City HybridEnergy Center commencescommercial operation. Thisrequirement is in the July 1, 2008,PSD permit for the Energy Center.A fuel switch would eliminatemost of the SO2emissions fromthis facility. See Table 4-1 andSection 7.2.1.PrinceWilliam51-153-0002DominionPossum Point5786 MW residual oil fired EGUburning 0.7% S oil4,368 6,100 4.9% ---No changes expected.Fluvanna51-065-0001Dominion-Bremo1 69 MW coal firedEGU 4,371 2,614 3.7% ---See above.Chesterfield51-041-0002Dominion-Chesterfield8 694 MW coal firedEGU 38,088 3,633 2.4% ---No changes expected. Dominionhas installed and begun operatinga FGD device and polishingbaghouse for this unit. See Table4-1.Chesterfield51-041-0002Dominion-Chesterfield6 359 MW coal fired EGU 19,129 1,561 1% ---No changes expected. Dominionhas submitted data showing thatthey expect to control this unit by2011 with a FGD device.Construction of this FGD hasbegun. See Table 4-1.80-Virginia Regional Haze SIPTable 7.7.4-3: Units Outside Virginia with Visibility Impairment Contributions of at least 1% Virginia Class I AreasData used for Contribution CalculationUpdated 2018 Emission EstimatesStateCountyPlant IDPlant NamePointIDPlant Description2002 SO2tpy2018 SO2tpy%Contribution2018 SO2tpyComment/ExplanationJames River Face003 39,57010,8211.79%---002 27,6516,6941.11%---WV Putnam54-079-0006Appalachian Power –John E. AmosPlant001Electrical Services30,015 6,613 1.09% ---Scrubbers on Units 2 and 3 areoperational. The scrubber on Unit1 is expected to be tied in duringthe fall of 2010. See Appendix J.NC Rockingham37-157-00015Duke Energy Corporation – DanRiverG-21 Electrical Services 2,637 3,464 1.19% ---No changes expected. Facility issubject to the NC CleanSmokestacks Act. See Appendix J.Shenandoah1 10,1609,6104.14%~961MD Alleghany24-001-0011Westvaco Luke Plant2Paper Mill8,923 8,441 3.64% ---Maryland informed Virginia thatUnit #2 is BART eligible andbelieves that either #1 or #2,depending upon engineeringissues, will be controlled by anSO2scrubber to meet BARTrequirements. See Appendix J.28 1,5062,6521.74%---MD Frederick24-021-0005Eastalco Aluminum29Primary Production ofAl1,506 2,652 1.74% ---This facility iscurrently notoperating. They have maintainedtheir Title V Permit, but MDEcould not determine if the facilitywould operate in the future. Both#28 and #29 are BART eligibleunits. See Appendix J.MD Washington24-043-0005Allegheny-R. Paul Smith Plant 2 Electrical Services 3,770 2,568 1.57% 644This facility is subject to theMaryland Healthy Air Act.COMAR 26.11.27.03 lists the SO2tonnage limit for 2013 and beyondas 644 tpy.14 37,7573,0371.48%---MD Charles24-017-0014Mirant Mid-Atlantic LLC15Electrical Services32,587 2,987 1.45% ---Both units are subject to theMaryland Healthy Air Act andwere equipped with SCR in 2009and will be equipped with ascrubber by 2010. COMAR26.22.2703 lists the SO2tonnagelimit for 2013 as 4,678 and 4,646tpy respectively. Growthassumptions are considered to be abetter estimate of future emissionsthan regulatory limits on PTE.See Appendix J.81-Virginia Regional Haze SIPTable 7.7.4-3: Units Outside Virginia with Visibility Impairment Contributions of at least 1% Virginia Class I AreasData used for Contribution CalculationUpdated 2018 Emission EstimatesStateCountyPlant IDPlant NamePointIDPlant Description2002 SO2tpy2018 SO2tpy%Contribution2018 SO2tpyComment/ExplanationWV Berkeley54-003-0006Capitol Cement Corporation 010 Hydraulic Cement 1,247 1,717 1.28% ---Facility has modernized since2002. PSD netting exercise tookplace for SO2. No additionalreductions are expected. SeeAppendix J.001 8,8173,1911.18%002 9,5723,1911.18%WV Grant54-023-0003Mount Storm Power Plant003Electrical Services2,779 2,923 1.08%---Units are controlled by FGD. SeeAppendix J.001 2,5825,9981.04%002 2,7315,9541.03%WV Harrison54-033-0015Monongahela Power Company-Harrison003Electrical Services3,355 5,908 1.03%---Units are controlled by FGD. SeeAppendix J.82-Virginia Regional Haze SIP 

### USEPA goes on to address the analysis of SO 2 

### emission reduction requirements for the CAIR
final rule.

(I) Reference Lists of Cost-Effective SO 2 

### Controls

For today’s action, EPA updated the referen ce lists of controls included in the NPR of the average and margin al cost per ton of recent SO 2 

### control actions. The EPA systematically developed a list of co st 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 contro l cost information to provide the updated reference list for today’s preamble. Th e updated reference list includes both average and marginal costs of control to which EPA compares the CAIR control costs, and the list represents what regula tory decision makers and/or the public
believes are the control costs.

Table IV-3 provides average costs of SO 2 

### controls. This table includes average costs for recent BACT permitting decisions for SO 2 

### . Under EPA’s New Source Review (NSR) program, if a company is pl anning 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 ad dresses 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 effectivene ss. These decisions are relevant for EPA’s reference list of average costs of SO 2 

### controls, because they represent costeffective controls that have been demonstrated.

TABLE IV-3. – Average Costs per Ton of Annual SO 2 

### Controls

SO 2 

### control action Average cost per ton
Best Available Control Tec hnology (BACT) Determinations 1 

### $400-$2,100 Nonroad Diesel Engines and Fuel 2 

### $800 Proposed Best Available Re trofit Technology (BART) for
Electric Power Sector 3 

### $2,600-$3,400

1 These numbers reflect a range of cost-effectiveness data entered into EPA’s RACT/BACT/LAER Clearinghouse (RBLC)
for add-on SO 2 controls ( www.epa.gov/ttn/catc/ ). We identified actions in the data ba se for large, utility scale, coal-fired
boiler units for which cost eff ectiveness 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 ra nged from 0.1 lb/mmBtu to 0.27 lb/mmBtu. Add-on controls reported for these units are dry or wet scrubbers (in one cas e with added alkali and in one case with a baghouse.) Where the dollar-year was not reported, we assumed 1999 dollars. Th e cost range presented in the NPR was $500-$2,100-today’s range includes additional BACT costs that were ente red 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 l ong-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 SO 2 reduction or 0.1lb/mmBtu rate; except the fi ve state WRAP region for which we did not
model SO 2 controls beyond what is done for the WRAP cap in th e base case modeling). Estimated average costs based on this modeling are $2,600 per ton in 2015 a nd $3,400 per ton in 2020. 1999$ per ton.83-Virginia Regional Haze SIP 

### Table IV-4 provides the marginal cost per ton of recent State and regional
decisions for annual SO 2 

### controls.”

TABLE IV-4. – Marginal Co sts per Ton of Annual SO 2 

### Controls

SO 2 

### control action Marginal cost per ton New Hampshire Rule 1 

### $600 WRAP Regional SO 2 

### Trading Rule 2 

### $1,100-$2,200

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

2 An Assessment of Critical Mass for the Regional SO 2 Trading Program,” prepared for the Western Regional Air Partnership Market Trading Forum by ICF Consulting Group, Se ptember 27, 2002, available in the docket. This analysis looked at the implications of one or more Stat es choosing to opt-out of the WRAP regional SO 2 training program. (1999$ per ton.)



### (II) Cost Effectiveness of the CAIR Annual SO 2 

### Reductions

. . .Table IV-5 provides the averag e and marginal costs of annual SO 2 

### 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 differentia ted from other IPM analyses such as sensitivity runs used to examine the imp acts of varying assump tions about natural gas price and electric growth.)

TABLE IV-5. – Estimated Costs per Tons of SO 2 

### Controlled Under CAIR, Cap Levels Beginning in 2010 and 2015 1


### Type of cost effectiveness 2010 2015 Average Cost – Main Case $500 $700 Marginal Cost – Main Case $700 $1,000 Sensitivity Analysis: marginal Cost Using EIA Growth and
Natural Gas Prices $800 $1,200

1 The EPA IPM modeling 2004, available in the docket, 1999$ per ton.



### These estimated SO 2 

### control costs under the CAIR reflect annual EGU SO 2 

### caps of 3.6 million tons in 2010 and 2.5 million tons in 2015 within the CAIR region....

(IV) Cost Effectiveness: Marginal Cost Curves for SO 2 

### Control

. . .Figure IV-1 shows that the “knee” in the 2010 marginal cost-effectiveness curve – the point where the co sts of controlling a ton of SO 2 

### from EGUs is increasing at a noticeably higher rate – a ppears to occur at about $2,000 per ton of
SO 2 

### . Figure IV-2 shows that the “knee” in the 2015 marginal cost-effectiveness curve also appears to occu r at about $2,000 per ton of SO 2



### . . .84-Virginia Regional Haze SIP 

### After review of USEPA’s CAIR cost analys es, Virginia determined that the CAIR SO 2 

### control costs vary by year of analysis (2010 vs. 2015) and may range from $400 to $3,400 per ton SO 2 

### removed. Ultimately, USEPA found a consistent ma rginal cost for both years at $2,000 per ton. These values establish benchmarks against wh ich 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 Progre ss Goals Under the Regional Haze Program (USEPA, 2007). This document makes the following points regarding setting reas onable 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 re views 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-dec iview 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 SO 2 

### . As noted above, currently CAIR requirements are considered adequate for reasonable progress toward visibility improvements. However, s hould data from IMPROVE monitors indicate that the expected visibility improvements are not being achieved either at Virgin ia 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, fo r 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 in formation, 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 factor s of time necessary for comp liance, 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 co st 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 Ao I as having a visibility impairment contribution of 1.19 percent in 2018, based on an estimat ed 2018 emissions rate of 4,299 tpy SO 2 

### . Point ID #4 is the facility’s #7 power bo iler, 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 co al burned generally has a sulfur (S) content of 0.8 percent by weight. The inci neration of TRS gases creates much of the SO 2 

### emitted from this unit.

Since 2002, the facility has in stalled a TRS scrubber on the non-condensable gases being
incinerated in this unit. This TRS scrubber reduces the SO 2 

### emissions associated with incineration by 200-300 tpy. Additionally, the facility has taken a facility-wide SO 2 

### cap of 7,980 tpy, which is significantly beneath the 2002 total facility-wide annual SO 2 

### emissions of 8,693 tpy
and the estimated 2018 SO 2 

### emissions for the entire facil ity of 10,006 tpy. To help reduce emissions beneath this cap, the facility ha s decommissioned boiler #8, Point ID #17, which in86-Virginia Regional Haze SIP 

### 2002 accounted for SO 2 

### emissions of 900 tpy. Based on these facility changes, Virginia currently estimates that 2018 SO 2 

### emissions from Boiler #7 will be on the order of 3,800 tpy.

There were no controls suggested by the VISTAS control cost sp readsheet for boiler #7. Based on the current use of 0.8 percent S coal, requiring the use of lowe r S content coal would not be practical nor would lower S content coal prov ide much reduction. Review of existing data provided by VISTAS for similar sized boilers in dicates a control cost for FGD greater than $10,000 per ton of SO 2 

### removed.

Based on this VISTAS information, additional control of SO 2 

### appears to be more costly than may be currently deemed reasonable. Howeve r, should data from the IMPROVE monitoring
network indicate that additional reductions in SO 2 

### are necessary for Class I areas such as Swanquarter to meet their goals, a more rigor ous 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 burni ng coal, bark and wood pelletized fuel with a heat input of 440 mmbtu/hr; boile r #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 pelleti zed fuel. Boilers #6 and #9 are equipped
with ESPs and low NO X 

### burners. Boilers #7 and #8 are equipped with ESPs and flue gas
recirculation. The stack is equipped with a rudimentary SO 2 

### scrubber designed to allow
emissions from the stack to meet a 3 hour average of 3,300 pounds of SO 2 

### per hour and 9,132.3 tpy. The boilers use coal with approxim ately 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 SO 2 

### 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 reason able progress determination for this round of Regional Haze planning that additi onal upgrades could be made to the existing scrubber system by 2015. These upgrades would reduce annual SO 2 

### emissions to 6,817 tpy. These reductions
were not included in the emissions inventory for the reasonable pr ogress visibility goal since the control technology for the reasonab le progress determination had not yet been determined. See Appendix H for the correspondence regarding this determination.87-Virginia Regional Haze SIPTable 7.7.5.1-1. Virginia EGUs with Visibility Impairment Contributions of at least 1%Data used for ContributionCalculationUpdated 2018 Emission EstimatesCountyPlant IDPlant NamePointIDUnit Description2002SO2tpy2018SO2tpy%contribution2018SO2tpyComments/ExplanationLinville GorgeRussell 51-167-0003AEP-ClinchRiver1238 MW EGU coal fired usingapproximately 0.8% S coal.8,158 10,014 4%Russell 51-167-0003AEP-ClinchRiver2238 MW EGU coal fired usingapproximately 0.8% S coal.8,115 10,131 4%Russell 51-167-0003AEP-ClinchRiver3238 MW EGU coal fired usingapproximately 0.8% S coal.8,804 9,911 4%16,300 The facility is subject to an emissionscap on SO2of 16,300 tpy beginning2015, based on the AEP consentagreement. See Table 4-1 and Section7.2.1.James River FaceGiles 51-071-0002 AEP-GlynLyn 3 238 MW coal fired EGU7,488 9,981 3.6% --- No changesexpected. See Table 4-1.Fluvanna 51-065-0001Dominion-Bremo2 185 MW coal firedEGU 7,993 6,253 2.2% ---The facility is required, subject to StateCorporation Commission approval, toswitch fuels two years after the VirginiaCity Hybrid Energy Center commencescommercial operation. This requirementis in the July 1, 2008, PSD permit forthe Energy Center. A fuel switch wouldeliminate most of the SO2emissionsfrom this facility. See Table 4-1 andSection 7.2.1.ShenandoahFluvanna 51-065-0001Dominion-Bremo2 185 MW coal firedEGU 7,993 6,253 8.9% ---See above.Prince William 51-153-0002Dominion-Possum Point5786 MW residual oil fired EGUburning 0.7% S oil4,368 6,100 4.9% ---No changes expected.Fluvanna 51-065-0001Dominion-Bremo1 69 MW coal firedEGU 4,371 2,614 3.7% ---See above.Chesterfield 51-041-0002Dominion-Chesterfield8 694 MW coal firedEGU 38,088 3,633 2.4% ---No changes expected. Dominion hasinstalled and is operating a FGD deviceand polishing baghouse for this unit.See Table 4-1.Chesterfield 51-041-0002Dominion-Chesterfield6 359 MW coal fired EGU 19,129 1,561 1% ---No changes expected. Dominion hassubmitted data showing that they expectto control this unit by 2010 with a FGDdevice. The FGD is currently underconstruction. See Table 4-1.88-Virginia Regional Haze SIP 

### 7.7.5.2.3. Roanoke Cement Company

Point #22 at Roanoke Cement Company consists of a preheater, pr ecalciner cement kiln. This kiln is subject to the NO X 

### Budget Trading Program as well as Subparts F and LLL of 40 CFR 63. It is controlled by an ESP fo r particulate matter. For SO 2 

### emissions, the kiln has a process lime injection system to assist in meeting the SO 2 

### limitations when one or both of the raw mills are off
line. The S content of the coal burned in the k iln 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 SO 2 

### . Compliance is determined vi a a continuous emissions monitor
located on the main stack.

VISTAS data did not provide any applicable cont rol technologies for review on this facility. However, LADCO created as part of the BART pr ocess 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 SO 2 

### for small, medium, and large prehea ter kilns and for advanced flue gas desulfurization, wet flue gas desulfurization, and dry flue gas desulfurization. Costs per ton of
SO 2 

### removed range from $9,663 per ton of SO 2 

### removed to well above $60,000 per ton of SO 2 

### removed. Based on this information, SO 2 

### controls are not cost effec tive 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 Boile r #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 pro cess by a flue gas desulfurization unit with a design control efficiency of 90 percent. Annual SO 2 

### 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, ba sed on the annual capacity factor. Annual SO 2 

### emissions will be limited to 374 tpy. In the G2 emissions inventory, estimated 2018 SO 2 

### emissions from this unit are approximately 286 tpy. This estimate of future emissions, which is based on past utilization, may better represent fu ture emission from this unit than will the maximum BART limitation. Therefore, Table 7.7.4-2 shows a 2018 SO 2 

### estimated emissions rate from this unit of 286 tpy.

The estimated cost for a cau stic scrubber per ton of SO 2 

### removed was $12,371 for the No. 5 Boiler based on typical fuel sulfur content for less than 10 percent coal an d more than 90 percent waste type fuel (normal mix). Therefore, further controls bey ond BART would not be economically feasible for reasonable progre ss 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, wh ich 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 contro lling this unit with flue gas de sulfurization would cost on the order of $32,000 per ton of SO 2 

### removed. Based on this cost estimate, and the use of relatively low S coal, no economical SO 2 

### control currently exists for th is unit. Therefore, additional controls for reasonable progress are not feasib le 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 controll ed 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 Riley coal boiler #3 184 mmbtu/hr 3BHBL001E1
Riley coal boiler #5 246 mmbtu/hr

Babcox & Wilcox coal boiler #2 91 mmbtu/hr Riley coal boiler #4 184 mmbtu/hr 3BHBL002E1 Riley coal boiler #6 246 mmbtu/hr

3BHBL003E1 Foster Wheeler coal boiler #7 322 mmbtu/hr



### VISTAS data shows that controlli ng all seven coal fired boilers as if they exhausted through one stack would cost approx imately $3,140 per ton of SO 2 

### removed. However, control costs would be higher due to the need to control three stacks.

Based on this VISTAS information, additional control of SO 2 

### 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 SO 2 

### 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 Represen t Best Available Retrofit Technology (BART) for Individual Sources?

Section 169A of the CAA directs States to asse ss certain large, olde r emission sources for
additional controls in order to address visibility impacts. Stat es are directed to conduct BART determinations for such sources in specific so urce categories that c ontribute to visibility impairment in Class I areas. The 1999 regiona l haze regulation includes the BART requirement,
and it directs states to include BART in th eir regional haze SIPs. On July 6, 2005, USEPA90-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 dir ection to states on dete rmining 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 potent ial to emit 250 tons or more of a visibilityimpairing air pollutant, was put in place be tween August 7, 1962 and August 7, 1977, and whose operations fall within one or more of 26 specifi cally 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 c ontribute 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 impact s 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 r easonably 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-eli gible 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 faci lity 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 emi ssion units identified in the previous two bullets were greater than 250 tons or mo re per year of any of these visibilityimpairing pollutants: SO 2 

### , NO X 

### , and PM 10



### .

The BART Guidelines recommend addressing SO 2 

### , NO X 

### , and PM. The BART Guidelines also suggest that states use their best judgment in determining whether to address VOC or NH 3 

### emissions. Virginia addressed SO 2 

### , NO X 

### , and PM 10 

### as an indicator for particulate matter to identify BART-eligible units, as the BART Guid elines recommend. As discussed in detail in Appendix H, VISTAS modeling demonstrated thatVOCs 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 determ inations, with the exception of Honeywell Nylon LLC Hopewell, Registra tion Number 50232. Due to the large quantity of ammonia emitted by this facility, this facility’s ammonia em issions 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 vi sibility impairment in a Class I area. In accordance with the BART guidelines, Virginia c hose to perform source-specific analyses to
determine which sources cause or contribute to visibility impairment using the CALPUFF model. The CALPUFF modeling pr otocol used for determining wh ich 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 summari zed in Table 7.8.2-1. Additional details are available in Appendix H. Faci lities 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 modeli ng protocol and the ne w IMPROVE equation. Virginia proposed to exempt these units in a ppropriate newspapers on or about the week of January 19, 2007. No adverse comments were r eceived during the pub lic comment period. Correspondence dated June 8, 2007, from the Nati onal 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 MOUNTA INS (NC/TN) 0.149

Chemical Lime Company – Kimballton REGISTRATION NUMBER: 20225

SHENANDOAH NATIONAL PARK (VA) 0.218 2

JAMES RIVER FACE WILDERNESS AREA (VA) 0.247 2

DOLLY SODS WILDERNESS AREA (WV) 0.144 2

OTTER CREEK WILDERNESS AREA (WV) 0.150 2

LINVILLE GORGE WILDERNESS AREA (NC) 0.407 1

SHINING ROCK WILDERNESS AREA (NC) 0.319 1

GREAT SMOKY MOUNTA INS (NC/TN) 0.290 1

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 MOUNTA INS (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) 0.12393-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) 0.344 2

JAMES RIVER FACE WILDERNESS AREA (VA) 0.235 2

DOLLY SODS WILDERNESS AREA (WV) 0.211 1

OTTER CREEK WILDERNESS AREA (WV) 0.129 1

SWANQUARTER WILDERNESS AREA (NC) 0.215 2

Dominion – Chesterfield Power St ation 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 threshold94-Virginia Regional Haze SIP 

### Three of Virginia’s BART-eligible sources ar e EGUs, and these sources have four BARTeligible units. These units are Unit #3 at Yo rktown 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 impr oves 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 th rough EEE need not require affected BARTeligible EGU to install, operate, and maintain BART for SO 2 

### or NO X 

### emissions. Given that Virginia is participating in CAIR and accepts USEPA’s overall finding that CAIR “substitutes”
for BART for SO 2 

### and NO X 

### , Virginia’s EGUs were allo wed to submit BART exemption modeling demonstrations for PM emissions only. These EGUs demonstrated that they do not contribute to visibility impa irment 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 wi th selective catalytic reduction (SCR) for NO X 

### control. Unit #6 has been retrofitted with a flue gas desulfurization unit and a polishing baghouse. A flue gas desulfurization un it is under construction to control SO 2 

### emissions from
Unit #5. See Table 4-1.

In total, ten of Virginia’s thirteen BART-eligible sources were able to de monstrate 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 Requiremen ts for Subject-to-BART Sources

Three sources (MeadWestvaco Packaging Reso urce Group, Georgia Pacifi c-Big Island, and O-N Minerals Global Chemstone Operation) were unab le 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 thei r initial proposed BART determ inations in the spring of 2007.

Table 7.8.3-1 summarizes the BART determinations for the various BART-elig ible units at these facilities. Each permit also contains a requireme nt that each facility mu st maintain the BART control equipment and establish pr ocedures to ensure that the e quipment is properly operated and
maintained.95-Virginia Regional Haze SIPTable 7.8.3-1. BART DeterminationsGeorgia Pacific – Big Island: Power Boiler #4 (Permitissued 6/12/08, SIP submittal to EPA dated July 17, 2008)Short TermLimitLong TermLimitControlEfficiencyWork Practice orControl DeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO250.0 lbs/hr 219.0 tpy 90.0% *1.8% S coal;*Caustic scrubberScrubber andcoal limitationeffective01/01/12. Shortterm limiteffective 180days afterscrubber startup. Long termlimit effective07/01/13.*Coal S content monitoring & recordkeeping*Liquid flow rate*Air pressure drop*Monitoring of devices/reporting of data*Stack testing*Calculation of emission ratesThe caustic scrubberwill be a new piece ofequipment that needsto be built.NOX169.0 lbs/hr 740.2 tpy --- *LNBAt issuance. *Calculation of emission ratesExisting controlequipment.PM/PM100.07 lbs/mmbtu19.9 lbs/hr87.0 tpy--- *ESPAt issuance. *ESP voltages*Monitoring of devices/reporting of data*Calculation of emission ratesExisting controlequipmentGeorgia Pacific – Big Island: Power Boiler #5 (Permitissued 6/12/08, SIP submittal to EPA dated July 17, 2008)Short TermLimitLong TermLimitControlEfficiencyWork Practice orControl DeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO2485.1 lbs/hr 374.0 tpy --- *1.3% S coal;*Good operationalpractice*Firing coal nomore than 10% ofthe annual capacityfactorHourly limiteffective atissuance.Annual limiteffective 12months afterpermit issuance(06/12/09).Coal S contentlimit effective01/01/12.*Coal S content monitoring & recordkeeping*Records on other fuels fired*Records on capacity*Calculation of emission ratesPermit issued6/12/2008.NOX139.3 lbs/hr 610.1 tpy --- *OFAAt issuance. *Calculation of emission rates*Emissions and capacity calculationsExisting controlequipment.PM/PM100.07 lbs/mmbtu23.7 lbs/hr103.9 tpy --- *ESPAt issuance. *ESP voltages*Monitoring of devices/reporting of data*Calculation of emission ratesExisting controlequipment.96-Virginia Regional Haze SIPTable 7.8.3-1. BART DeterminationsMeadWestvaco Power Boiler # 9 (PWR009) (Permit issued 2/23/09, SIP submittal to EPA dated 3/6/09)Short TermLimitLong TermLimitControlEfficiencyWork Practice orControl DeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO21,831 lbs/hr onan annualaverage8,020 tpy --- *FGD *Liquid flow rates*Air pressure drops*SO2CEMs*Fuel consumption records*Emissions and capacity calculationsThe SO2limitation isfor the combined stackfrom units 6, 7, 8, and9. This stack has anexisting FGD controldevice. As part of theBART process, thecontrol device is beingimproved.NOX242.1 lbs/hr 1,060 tpy --- *LNB*Fuel consumption recordsPM/PM10166.4 lbs/hr0.07 lbs/mmbtu728.9 tpy --- *ESP*At issuance or01/01/09.*ESP voltages*Fuel consumption recordsExisting LNB andESP.MeadWestvaco Power Boiler #10 (PWR010) (Permit issued 2/23/09, SIP submittal to EPA dated 3/6/09)Short TermLimitLong TermLimitControlEfficiencyWork Practice orControl DeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO2--- --- ---*Fuel restriction ofat least 90%natural gasutilization.*Proper operationand maintenance.*Fuel consumption records*Emissions and capacity calculationsNOX66.0 lbs/hr onnatural gas--- ---*Operation at nomore than 50% ofrated capacity onannual basis.*Propermaintenance.*Fuel consumption recordsPM/PM102.51 lbs/hr onnatural gas--- ---*Fuel restriction ofat least 90%natural gasutilization.*Proper operationand maintenance.*At issuance.*Fuel consumption records*Emissions and capacity calculations97-Virginia Regional Haze SIPTable 7.8.3-1. BART DeterminationsMeadWestvaco Power Recovery Furnace #1 (REC001) (Permit issued 2/23/09, SIP submittal to EPA on 3/6/09)Short Term LimitLong TermLimitControlEfficiencyWork Practiceor ControlDeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO2713.7lb/hr --- ---*Proper boileroperation andmaintenanceAt issuance. *Fuel consumption records*Emissions calculationsNOX211.2lb/hr --- ---*Proper boileroperation andmaintenanceAt issuance. *Fuel consumption records*Emissions and capacity calculationsPM/PM100.044 gr/dscf @8%O2PM: 150.0 lb/hrPM: 85.0 lb/hrannual averagePM10: 103.8 lb/hrPM10: 58.8 lb/hrannual averagePM: 350 tpyPM10: 242 tpy--- *ESP At issuance. *ESP voltages*Fuel consumption records*Emissions and capacity calculationsExisting controldevice.MeadWestvaco Smelt Dissolving Tanks (REC002 and REC003) (Permit issued 2/23/09, SIP submittal to EPA on 3/6/09)Short Term LimitLong TermLimitControlEfficiencyWork Practiceor ControlDeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO214.8 lbs/hr 64.8 tpy---NOX--- --- ---PM/PM10PM: 14.1 lbs/hrPM10: 12.6 lbs/hrPM: 58.0 tpyPM10: 51.9tpy---*Venturiscrubber withbasic solutionAt issuance. *Emissions and capacity calculationsExisting controldevice. PM10limit isfor PM10only. PM hasa higher limit.98-Virginia Regional Haze SIPTable 7.8.3-1. BART DeterminationsO-N Minerals (Global Chemstone) Rotary Kiln U5 (Permit issued 12/28/09, SIP submittal to EPA on 01/14/10)Short Term LimitLong TermLimitControlEfficiencyWork Practiceor ControlDeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO214.7 lbs/hr0.29 lbs/tsf--- ---*Inherentprocessscrubbing or wetscrubber*S content offuel no greaterthan 1%09/10/11 or08/01/12Short termemissions limitseffective09/10/10.*Scrubber: liquid flowrate and differentialpressure.*CEM (beginning 09/10/10).*Emission calculations.*BART monitoring plan.*S content records and fuel consumption.*Hours of operation.NOX87.0 lbs/hr1.74 lbs/tsf--- --- *Indirect firing*GoodcombustionpracticesAt issuance. *BART monitoring plan.*Annual combustion apparatus inspectionsfor NOXoptimizations.PM/PM106.0 lbs/hr0.12 lbs/tsf--- ---*Multicyclone*Fabric filterAt 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 LimitLong TermLimitControlEfficiencyWork Practiceor ControlDeviceComplianceDateRecords, Reporting, and MonitoringCommentsSO22.6 lbs/hr0.16 lbs/tsf--- ---*VenturiscrubberAt issuance.*Scrubber liquid flow rate, exit gastemperature, differential pressure.*BART monitoring plan.*Fuel consumption, S content.*Emission calculations.NOX9.8 lbs/hr0.61 lbs/tsf--- ---*GoodcombustionpracticesAt issuance. *BART monitoring plan.*Annual combustion apparatus inspectionsfor NOXoptimization.PM/PM109.6 lbs/hr0.60 lbs/tsf---- --- *Multicyclone*VenturiscrubberAt issuance.*Scrubber liquid flow rate, exit gastemperature, 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 revi ew of CAIR and CAIR Federal Implementation Plans, including their provisions establishing the CAIR NO X 

### annual and
ozone season and SO 2 

### 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 remande d 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. Ther efore, a new rule is expected to be published in July of 2010. The contents of this rule are not know n at this time. In an effort to determine how this remand may affect EGU em issions 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 considera tion reductions in EGU em issions that would be required by state enforceable or federally en forceable mandates. These mandates included emission reductions from programs such as Georgi a’s Multipollutant Control for Electric Utility Steam Generating Units, federal consent orders su ch as those noted in Section 7.2.1 and the AEP consent order as noted in Section 7.10.4, and vari ous permitting actions. However, this scenario
did not consider controls or reductions th at were solely the result of CAIR.

The analysis showed that CAIR in 2018 resulted in significant SO 2 

### emissions reductions for Virginia and in significant SO 2 

### and NO X 

### emission reductions in th e nearby states of West Virginia and Tennessee when compared to the “N o CAIR Legally Enforceable” scenario. North Carolina results for 2018 remain largely unaffect ed due to the mandates of the North Carolina
Clean Smokestacks Act. The CAIR reductions ar e 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 VIST AS Class I areas. After the remanded rule is proposed, the proposal will be examined to determine how the 2018 SO 2 

### emissions inventory in Virginia will be affected. Should the proposed rule prove to engender less emissions reductions than the remanded rule, Virginia will most lik ely provide this information in the form of
comments on the rule to the formal docket. Fi gures 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. SO 2 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. NO X Emissions Comparisons for VISTAS States, CAIR versus No CAIR, Legally Enforceable



### 7.10. What Additional Emissions Controls W ere 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 th e role of fire at Class I areas and the status of state planning for smoke management; the role of dust and fine so il at Class I areas and st atus of state plans to mitigate emissions from construction activities; and the role of NH 3 

### and potential benefits if emissions from agricultural sources were mitigated. A CMAQ modeling run was performed in101-Virginia Regional Haze SIP 

### the fall of 2007 to account for the cumulative be nefits 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 betw een 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, pres cribed wildland fires, and wild fires) is a relatively minor contributor to visibility impairm ent at the Class I areas in Vi rginia. POM may also be an
indicator of fire emissions alt hough significant fire impacts are in frequent at Class I areas in Virginia. The Virginia Department of Forest ry 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 pr escribed burns. Since elemental carbon is a relatively minor contributor to visibility impairment at both Shenandoah
and James River Face and since si gnificant fire impacts are infrequent at Virginia Class I areas, these management practices are adequate visibi lity protection for this SIP submittal period. Future submittals may review and update these fi ndings 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 impair ment at the Class I ar eas in Virginia. The Virginia Department of Trans portation (VDOT) uses the following requirements in all road and bridge construction specifications for contracts. These requiremen ts for dust control and erosion control may be found at Secti on 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 Cl ean Air Act as amended [42 U.S.C. 1857, et seq., as amended by P.L. 91-604], the Federal Water Pollution C ontrol Act as amended [33 U.S.C. 1251 et seq. as amended by P.L. 92-500], and Executive Order 117 38 and regulations in implementation thereof [40 C.F.R., Part 15]) is not listed on the EPA’s List of Vi olating 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 Activitie s, 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 provisio ns of Section 107.01 and the State Air Pollution
Control Law and Rules of the State Air Pollution Co ntrol 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 not102-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 in corporated 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 po rtion thereof that contains friable asbestos...

(c) Forests: The Contractor shall take all reasonable pr ecautions 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 aut hority 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. NH 3 

### 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 evalua te animal feeding operations (AFOs). This document should also help to promote a national c onsensus on estimating
emissions from AFO’s.

Additionally, the treatment, stor age, and land application of sewage sludge, industrial waste (sludge and wastewater), municipal wastewater, a nd animal waste are regulated activities in the Commonwealth of Virginia. A Virginia Pollu tion 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 app lication of industrial wast e or spray irrigation of industrial and municipal wastewater is covered by a Virg inia Pollution Abatement individual permit.

AFOs are covered by a Virginia Pollution Abatem ent individual or general permit. A separate Virginia Pollution Abatement general permit co vers confined poultry feeding operations for poultry waste management. VPDES permits may be required for some AFOs. The general permit and regulations regarding AFOs ma y be found at 9VAC5-25-191. This regulation requires AFOs to implement a Nutrient Manageme nt 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 creat e reasonable progress goals for th is round of regional haze planning,
in the fall of 2007 VISTAS created a best and fina l inventory exercise, identified as Base G4a.103-Virginia Regional Haze SIP 

### In Virginia, Base G4a captured the emission reductions from a vari ety of facilities and programs.
These include:

• SO 2 

### emission reductions from BART determinations for Meadwestvaco and Georgia-Pacific Big Island. Reducti ons 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 NO X 

### and SO 2 

### 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 NO X 

### emissions annually by 2016 and 174,000
tons of SO 2 

### emissions annually by 2018 from sixt een plants located in Indiana, Kentucky, Ohio, Virginia, and West Virginia.

• Facility shutdown information was included in this inventory exer cise so that the list of operating units in the future year inventory was as accurate as possible.

• Emissions from the new Virginia City H ybrid Energy Center, the coal-fired power plant located in Wise County, Virginia, we re 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 de velopment. The final permit contained
emissions limits for SO 2 

### that were significantly smaller than those used in the G4a
best and final inventor y 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 info rmation, and corrections of inventory

errors.

This SO 2 

### inventory exercise reduced Virginia’s 2018 non-EGU emissions from an estimated 69,000 tons SO 2 

### /year to approximately 58,000 tons SO 2 

### /year and Virginia’s 2018 EGU emissions from an estimated 114,000 tons SO 2 

### /year to approximately 99,000 tons SO 2 

### /year. Table 7.4.10-1 and 7.4.10-2 compare the point sour ce Base G2 and Base G4a emissions by state in the VISTAS Region for 2018. Appendix D pr ovides more detail on the G4a inventory changes.104-Virginia Regional Haze SIPTable 7.10.4-1. Base G2 and Base G4a Point Source Emissions Comparison for SO2, NOX, VOC, and COSO2NOXVOC COStateBase G2 Base G4a∆Base G2 Base G4a∆Base G2 Base G4a∆Base G2 Base G4a∆Alabama 249,075 239,154 -9,921 142,676 142,319-357 57,243 57,242 -1 226,136 226,006 -131Florida 213,387 265,838 52,451 126,543 140,60414,061 45,233 45,860 627 150,965 182,933 31,968Georgia 138,778 127,864 -10,914 131,541 125,680-5,861 43,123 43,098 -25 212,379 212,173 -207Kentucky 266,744 262,784 -3,960 105,411105,411 0 57,287 57,287 0 156,580 156,580 0Mississippi 41,824 40,888 -936 71,804 82,787 10,983 46,452 46,609 157 82,140 83,232 1,092North Carolina 161,085 166,480 5,395 100,154 98,912 -1,242 72,220 72,178 -42 82,420 82,067 -352South Carolina 146,851 147,787 935 95,477 95,082 -396 44,562 42,918 -1,644 83,773 83,390 -383Tennessee 189,919 169,354 -20,565 95,168 94,234-934 94,242 93,432 -810 148,665 148,279 -386Virginia 183,164 156,778 -26,386 122,019 120,078-1,941 54,200 54,166 -34 92,562 95,696 3,134West Virginia 168,128 167,901 -227 94,60094,754 154 17,952 16,968 -984 131,293 123,699 -7,5941,758,956 1,744,827 -14,129 1,085,393 1,099,861 14,468 532,513 529,757 -2,756 1,366,914 1,394,056 27,141Table 7.10.4-2. Base G2 and Base G4a Point Source Emissions Comparison for PM10, PM2.5, and NH3PM10PM2.5NH3StateBase 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 0Florida 56,478 59,283 2,805 46,315 48,903 2,588 4,805 4,805 0Georgia 48,182 48,005 -177 36,399 36,297 -102 6,474 6,474 0Kentucky 26,848 26,848 018,172 18,172 0 1,377 1,377 0Mississippi 30,046 30,249 20317,772 17,971 199 1,591 1,591 0North Carolina 53,113 51,012 -2,101 41,616 39,962 -1,654 2,129 2,129 0South Carolina 43,965 42,314 -1,651 36,118 34,493 -1,625 2,396 2,404 8Tennessee 58,221 57,940 -281 46,919 46,680 -239 2,455 2,454 0Virginia 28,944 27,662 -1,282 23,570 22,378 -1,192 4,227 4,210 -17West Virginia 28,084 19,986 -8,098 20,165 12,240 -7,924 593 521 -72411,625 401,010 -10,615 314,412 304,450 -9,962 29,584 29,502 -81105-Virginia Regional Haze SIP 

### 8. REASONABLE PROGRESS GOALS (RPGs)

The regional haze regulation at 40 CFR 51.308(d)(1) re quires states to establish RPGs for each Class I area within the State (expressed in dv) that provide for reas onable progress towards achieving natural visibility. In addition, USEP A 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 visibili ty 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 r easonable progress goals shown below reflect the additional visibility improve ments predicted from the SO 2 

### reductions in the Base G4a emissions inventory. Also shown are the expected 2018 visi bility values calculate d using the Base G2 inventory. To determine the rate of progre ss 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 visi bility conditions by 2064. The RPGs are based on the available Base G4a modeling results a nd represent the best data available at this
time.

Table 8.1-1. Virginia Re asonable 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

11.4 20% WD 29.3 22.1 21.9 ∆ 7.4 dv ∆ 10.8 Shenandoah
National Park 3.1 20% BD 10.9 8.8 8.7 ∆ 2.2 dv ---

11.1 20% WD 29.1 22.6 22.4 ∆ 6.7 dv ∆ 11.0 James River Face
Wilderness Area 4.4 20% BD 14.2 12.5 12.4 ∆ 1.8 dv ---
*WD=Worst Day, BD=Best Day106-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
YearHaziness 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
YearHaziness Index (Deciviews)

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

Figure 8.1-2. 20% Worst Days Reasonable Progress for James River Face107-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
YearHaziness 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
YearHaziness Index (Deciviews)

Observation Method 1 Prediction Baseline = 14.2 dV

Figure 8.1-4. 20 Percent Best Days Rate of Progress for James River Face108-Virginia Regional Haze SIP 

### 8.2. Clean Air Interstate Rule Rema nd and Reasonable Progress Goals

The RPG analysis described in Section 8.1 contai ns 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 ne w regulations are prom ulgated that are as protective or more protectiv e than CAIR, significant SO 2 

### 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 Nati onal 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 pr edicting future emissions very difficult. Both EGU and non-EGU point source SO 2 

### 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 li sting and short description of several of these regulatory actions:

• The 2010 SO 2 

### NAAQS, published on June 2, 2010, set a new 1-hour standard for
SO 2 

### of 75 ppb. This standard is significantly more stringent than the previous primary standard and has a compliance y ear of 2017. EPA is anticipating an approach for implementing the new 1-hour SO 2 

### standard that would use monitoring and refined di spersion modeling of SO 2 

### 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 SO 2 

### emissions.

• The proposed MACT for industrial, comm ercial, and institu tional boilers and process heaters at major sources was pub lished on April 29, 2010. This proposal would reduce emissions of toxic air pollu tants, including mercury, other metals, and organic air toxics, from new and existi ng applicable units. Controls on units to meet limitations for acid gases would ha ve as a co-benefit the reduction of SO 2 

### emissions from these types of units.

• The CAIR replacement regulation, called the Transport Regulation, may provide additional future year SO 2 

### emission reductions that will benefit visibility in Class
I areas.

• The as-yet-unpublished EGU MACT may have reduction of SO 2 

### emissions as a
co-benefit to the cont rol of acid gases that are also HAPs.

Other uncertainties are economic in nature. For inst ance, recent advances in the ability to extract natural gas from geological formations reduced th e cost of natural gas in 2009 as compared to coal. This reduced price for natural gas encour aged the use of cleaner combined cycle EGUs over dirtier coal fired units. In 2009 less polluti on 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 offe red for the purchase of energy efficient home appliances and equipment.

Given these uncertainties, a high level of c onfidence cannot currently be placed on the 2018 EGU point source emissions inventory projections for Base G4a. The Base G4a inventory109-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 th e 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 pr ogress 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 20 08. These encouraging results for 2008 may not necessarily be indicative of th e beginning of a trend, but they do seem to support the modeling results showing that SO 2 

### emission reductions are key for visi bility improvement. Data from
EPA’s Clean Air Markets website for facilities s ubject 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 SO 2 from Acid Rain Progra m Units (Data from CAMD)



### During the mid course review, which is addresse d 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 st rategy for monitoring regi onal haze visibility impairment. Specifically, the regional haze regulation states at 40 CFR 51.308(d)(4):

(4) Monitoring strategy and ot her implementation plan requirements. The State must submit with the implementation plan a mon itoring strategy for measuring, characterizing, and reporting of regional haze visibility impa irment that is representative of all mandatory Class I Federal areas within the State. This monitoring strategy must be
coordinated with the monito ring strategy required in §51.305 for reasonably attributable visibility impairment. Compliance with this requirement may be met through participation in the IMPROVE network. The im plementation plan must also provide for the following: (i) The establishment of any additional m onitoring sites or equipment needed to assess whether reasonable progress goal s to address regional haze for all mandatory Class I Federal areas within the State are being achieved. (ii)-(vi) [Other implementation plan requi rements that pertain to reporting and use of monitoring data and an emission inventory.]

Such monitoring is intended to provide th e data needed to satisfy four objectives:

• Track the expected visibility improvement s resulting from emissions reductions
identified in this SIP.

• Foster better understanding of the atmo spheric processes important to haze.

• Identify chemical species in the ambien t 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 th at IMPROVE monitoring data from 2000-2004 serve as the baseline for the regional haze program, the fu ture regional haze monitoring strategy must necessarily be based on, or be directly comparable to, IMPROVE. The IMPROVE measurements provide the only long-term record av ailable for tracking visibility improvement or degradation. Therefore, Virginia intends to rely on the IMPROVE network for complying with the regional haze monitoring requiremen t 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 Manage rs provides additional insight into progress toward regional haze goals. Such measurements include:

• An ozone monitor and an SO 2 

### monitor are operated by the National Park Service
at Shenandoah National Park. A continuous PM 2.5 

### monitor is operated at Shenandoah National Park by VDEQ.

• An ozone monitor is operate d by the National Forest Service at James River Face.

Additional haze-related measuremen ts 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 PM 2.5 

### mass and visibility. They included continuous monitoring of sulfate, nitrate, and carbon to better understand daily trends in PM 2.5 

### , detailed analyses of carbon collected on filters to identify s ource contributions to carbon, and a dditional analyses of sodium and ammonium on IMPROVE filter samples.

In addition, Virginia ope rates a comprehensive PM 2.5 

### network of the filter based Federal Reference Method samplers, continuous PM 2.5 

### monitors, STN protocol filter based speciated samplers, and the continuous speciated partic ulate monitors described above. These PM 2.5 

### measurements help Virginia characterize air po llution 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 discusse d above to further the understanding of both PM 2.5 

### and visibility formation and trends in Virginia. Virginia will operate the units discussed above as long as funds allow.

The IMPROVE measurements are ce ntral to Virginia’s regional haze monitoring strategy. Any reduction in the scope of the IMPROVE ne twork in Virginia would jeopardize the Commonwealth’s ability to demonstrate reasonable progress toward visibility improvement in its Class I areas. In particular, Virginia’s regiona l haze strategy relies on em ission reductions from programs that occur on different time scales a nd will most likely not be spatially uniform. Monitoring at every Class I area is important to document the diffe rent air quality responses to
the emissions reductions.

Each of the current IMPROVE monitors in Virgin ia 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 reduc ing haze in the affected Class I area. In the event this occurs, Virginia, in consultati on with the USEPA and relevant Federal Land Managers, will develop an alternative appro ach for meeting the tracking goal, perhaps by seeking contingency funding to carry out limited monitoring or by relyin g on data from nearby urban monitoring sites to demons trate trends in speciated PM 2.5 

### mass.

Data produced by the IMPROVE monitoring networ k 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 will112-Virginia Regional Haze SIP 

### continue to process information from its own m easurements 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 VIST AS and the other RPOs to maintain VIEWS or a similar data management system to faci litate 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, SO 2 

### AoI for each Class I area, and methods to prioritize contributions from
individual sources within the AoI. The stat es collectively accept th e conclusions of these analyses.

In December 2006 the VISTAS State Air Directors he ld their first formal consultation meeting to
review the Base G mode ling results and the SO 2 

### AoI analyses. The Air Directors agreed to look
at reasonable control measures fo r sources on the lists for the SO 2 

### AoI. Each state would
consider sources within their st ate and would identify sources in neighboring states that they would like to have that neighbori ng state consider. States acknow ledged 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 Director s met for their second formal interstate
consultation. States shared their lists of sour ces 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 reasonabl e control measures that should be implemented to mitigate impacts in Class I areas in nei ghboring 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 contributin g at least one percent to visibil ity impairment at Class I areas. Consultation correspondence and document ation may be found in Appendix J.

The Mid-Atlantic/Northeast Visibility Uni on (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 A ppendix J. MANE-VU states asked Virginia to participate in further consultation with these stat es, 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 wh ich 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 SO 2 

### emissions from these units by 90 percent. MANE-VU also requested a control st rategy to provide a 28 percent reduction in SO 2 

### emissions from sources, other than EGUs, that would be equivalent to113-Virginia Regional Haze SIP 

### their proposed low sulfur residential fuel oil st rategy. Many of the units and stacks listed in Table 10-1 will have reduced emissions by 90 per cent or more in 2018. Table 10-1 demonstrates that these units are expected to reduce emissi ons from 2002 levels by approximately 82 percent
in 2018. The information in Table 10-1 is base d on federal consent decrees, knowledge of owner control program installation tim elines, and IPM projections.

Virginia’s non-EGUs are predicted to emit 57,790 tons of SO 2 

### 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 reduc tions. Dominion – Bremo Power Station (ORIS 3796) and Mirant Potomac River Generating Station (ORIS 3788) have requirements limiting their SO 2 

### emissions in 2018, and these emission reductions were not included in the reasonable progress modeling exercise that developed the RPGs listed in S ection 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 fo r the Energy Center. The Energy Center is expected to begin commercial ope ration 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 SO 2 

### in 2002 and was expected, prior to the permit requirement for the fuel switch, to emit over 8,800 tons of SO 2 

### 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 SO 2 

### emissions from the facility to 3,813 tpy and requiring the use of so rbent injection for SO 2 

### control. This limit was upheld by the Virginia Supreme Court. In 2002, this facility emitted over 15,000 tons of SO 2 

### . Prior to the implementation of this limit, the facility was expected to emit 12,000 tons of SO 2 

### in 2018. The permit requirements re present an 8,100 tpy reduction in
2018 SO 2 

### emissions from this facility.

These two facilities alone provi de reductions of 16,900 tons of SO 2 

### 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 expe cted to result in over 1,000 tons of SO 2 

### emission reductions by 2018. Additional SO 2 

### reductions in both the EGU and non-EGU point inventories can reasonably be expected due to the renewe d emphasis placed on energy efficiency and renewable energy source developm ent. Based on this analysis, the Commonwealth of Virginia should easily meet the target SO 2 

### reduction set forth in MANE-VU’s request.

MANE-VU’s analysis examined 2002 emissions fr om the 8 stacks and 10 un its in Virginia to determine estimated visibility impacts from thes e units. In contrast, th e analysis conducted by VISTAS, as described in Section 7, focused on 2018 emission estimates and 2018 calculated visibility contribution. Evaluati on 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. Table114-Virginia Regional Haze SIP 

### 10-2 presents this data. Of the top 25 units on this listing, 23 units ar e 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 conc lusion that can be drawn from Table 10-2 is that existing and future air pol lution control programs in Virginia should reduce the already minute expected 2018 SO 2 

### point source impacts from Virginia emissions on Brigantine to even
lower levels.

11. COMPREHENSIVE PERIODIC IMP LEMENTATION 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 thereaf ter. 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) requ ires periodic reports evaluati ng 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 progre ss report will evaluate the prog ress 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 poi nt EGU and point non-EG U 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 revisi ons being made final.

The requirements listed in 40 CFR 51.308(g) include the following:

• Description of the stat us of implementation.

• Summary of emission reducti ons achieved thus far, including the status of implementation of the CAIR compliance plans for EGUs compared to the control assumed in the modeling. (Virginia rec ognizes that the 2018 pr ojections 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 co mpliance 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 cond itions 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 SIPTable 10-1. Virginia Electric Generating Units Identified by MANE-VUPlantORIS ID/Inventory IDUnitMW2002 SO2Emissions(tons)SO2controlsControlInstallationDateSO2ControlEfficiency2018ProjectedSO2Emissions(tons)Comments3 185 9,233 Low S coal 2007 40%2,766Dominion –Chesapeake PowerStation380351-550-000264 239 12,505 Low S coal 2007 40% 4,155IPM predicts these units will be controlled byscrubbers in 2018.4 188 9,416 FGD 2010 90%7445 359 19,129 FGD 2010 90%1,561Dominion –Chesterfield PowerStation379751-041-00026 694 38,088 FGD 2008 95% 3,6331 238 8,158 Low S coal --- ---5,430AEP – Clinch River 377551-167-000032 238 8,115 Low S coal --- --- 5,494Based on federal consent decree, the facility(units 1, 2, and 3) has a cap of 16,300 tpybeginning in 2015.1 173 11,551 FGD 2010 90%6522 182 12,426 FGD 2018 90%617Dominion –Yorktown PowerStation380951-199-000013 875 11,498 Predicted by IPM to shutdown in 2018 Oil fired boiler.ESTIMATED EMISSIONS TOTAL:140,119 25, 052Based on federal consent decrees, knowledgeof owner control programestimates, and IPMprojects, these units will reduce emissions byapproximately 82% from 2002 estimates in2018.116-Virginia Regional Haze SIPTable 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to BrigantineFIPSCountyPlant IDPlantPointIDSIC(2002 G)(2018 G)Distance(km)Q/dRTMax**Q/d*RTMaxPercentageComment153 00002 DOMINION - POSSUM POINT5 49114,368 6,100 265.83 22.95 26.98 619.191 0.74%IPM predicts thisunit will shut downprior to 2018.101 00001STONE CONTAINER CORP (D/B/ASMURFIT-STON2 2611 3,562 4,006 296.83 13.50 23.79 321.165 0.38%Unit has beenretrofitted with FGDdue to federalconsent order.093 00006 INTERNATIONAL PAPER COMPANY 42621 3,720 4,299 377.94 11.38 27.29 310.5602 0.37%Facility is currentlyshut down.510 00003POTOMAC RIVER GENERATINGSTATION1 4911 2,245 2,400 235.03 10.21 26.98 275.4658 0.33%510 00003POTOMAC RIVER GENERATINGSTATION2 4911 2,384 2,400 235.03 10.21 26.98 275.4658 0.33%510 00003POTOMAC RIVER GENERATINGSTATION3 4911 3,514 2,400 235.03 10.21 26.98 275.4658 0.33%510 00003POTOMAC RIVER GENERATINGSTATION4 4911 3,669 2,400 235.03 10.21 26.98 275.4658 0.33%510 00003POTOMAC RIVER GENERATINGSTATION5 4911 3,445 2,400 235.03 10.21 26.98 275.4658 0.33%Facility has a permitissued in 2008capping the entirefacility to no morethan 3,813 tons SO2per year.199 00001DOMINION - YORKTOWN POWERSTATION6 4911 11,551 2,775 305.95 9.07 27.29 247.5203 0.30%Expected to becontrolled by FGD.099 ORIS54304 SEI BIRCHWOOD POWER FACILITY1 4911 0 2,789 282.04 9.89 25.00 247.25 0.30%Controlled by FGD.041 00002DOMINION - CHESTERFIELD POWERSTATION8 4911 38,088 3,633 345.27 10.52 19.94 209.7688 0.25%Controlled by FGD.065 00001DOMINION - BREMO POWERSTATION2 4911 7,993 6,253 387.00 16.16 12.92 208.7872 0.25%Expected to switchfuels.670 00055JAMES RIVER COGENERATIONCOMPANY1 4911 2,490 3,221 345.20 9.33 16.45 153.4785 0.18%Controlled by FGD.670 00055JAMES RIVER COGENERATIONCOMPANY2 4911 2,563 3,193 345.20 9.25 16.45 152.1625 0.18%Controlled by FGD.093 00006 INTERNATIONAL PAPER COMPANY 32621 1,679 1,907 377.94 5.04 27.29 137.5416 0.16%Facility is currentlyshut down.199 00004 GIANT YORKTOWN REFINERY262911 984 1,290 306.01 4.21 27.29 114.8909 0.14%670 00058 COGENTRIX HOPEWELL1 4911 282,209 344.54 6.41 16.45 105.4445 0.13%Controlled by FGD.117-Virginia Regional Haze SIPTable 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to BrigantineFIPSCountyPlant IDPlantPointIDSIC(2002 G)(2018 G)Distance(km)Q/dRTMax**Q/d*RTMaxPercentageComment670 00058 COGENTRIX HOPEWELL2 4911 292,209 344.54 6.41 16.45 105.4445 0.13%Controlled by FGD.093 00006 INTERNATIONAL PAPER COMPANY 62621 1,154 1,349 377.94 3.57 27.29 97.4253 0.12%Facility is currentlyshut down.041 00002DOMINION - CHESTERFIELD POWERSTATION6 4911 19,129 1,561 345.27 4.52 19.94 90.1288 0.11%Expected to becontrolled by FGD.740 ORIS10071 COGENTRIX PORTSMOUTH GEN1 4911 0 1,070 333.78 3.20 27.29 87.328 0.10%Controlled by FGD.740 ORIS10071 COGENTRIX PORTSMOUTH GEN2 4911 0 1,070 333.78 3.20 27.29 87.328 0.10%Controlled by FGD.065 00001DOMINION - BREMO POWERSTATION1 4911 4,371 2,614 387.00 6.75 12.92 87.21 0.10%Expected to switchfuels.550 00026 DOMINION - CHESAPEAKE4 491112,505 1,039 340.98 3.05 27.29 83.2345 0.10%Using low S fuel.199 00004 GIANT YORKTOWN REFINERY7 2911 677 820 306.01 2.68 27.29 73.1372 0.09%093 00006 INTERNATIONAL PAPER COMPANY17 2621 900 1,010 377.94 2.67 27.29 72.8643 0.09%Facility is currentlyshut down.041 00078DUPONT DE NEMOURS E I &COMPANY INC JAME2 2819 1,145 1,117 344.34 3.24 19.94 64.6056 0.08%Required by federalconsent decree tolimit annualemissions to 123tons SO2, beginningMarch 2011.670 00003STONE CONTAINER CORPORATIONHOPEWELL2 2631 1,188 1,334 344.26 3.87 16.45 63.6615 0.08%093 00006 INTERNATIONAL PAPER COMPANY7 2621 737 861 377.94 2.28 27.29 62.2212 0.07%Facility is currentlyshut down.041 00081 PHILIP MORRIS USA INC - PARK500 3 2141 1,070 1,062 341.81 3.11 19.94 62.0134 0.07%023 00003 ROANOKE CEMENT COMPANY 223241 2,885 3,976 532.37 7.47 8.12 60.6564 0.07%Limited by permit to3,104 tons SO2/year.199 00001DOMINION - YORKTOWN POWERSTATION5 4911 12,426 652 305.95 2.13 27.29 58.1277 0.07%Expected to becontrolled by FGD.670 00026HONEYWELL NYLON INC-HOPEWELL10C 2869 1,491 1,198 344.48 3.48 16.45 57.246 0.07%550 00026 DOMINION - CHESAPEAKE34911 9,233 692 340.98 2.03 27.29 55.3987 0.07%Using low S fuel.199 00001DOMINION - YORKTOWN POWERSTATION3 4911 11,498 617 305.95 2.02 27.29 55.1258 0.07%IPM predicts unitwill shut down.199 00004 GIANT YORKTOWN REFINERY6 2911 477 579 306.01 1.89 27.29 51.5781 0.06%041 00081 PHILIP MORRIS USA INC - PARK 500 2 2141 823 817 341.81 2.39 19.94 47.6566 0.06%101 00001STONE CONTAINER CORP (D/B/ASMURFIT-STONE)5 2611 504 590 296.83 1.99 23.79 47.3421 0.06%118-Virginia Regional Haze SIPTable 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to BrigantineFIPSCountyPlant IDPlantPointIDSIC(2002 G)(2018 G)Distance(km)Q/dRTMax**Q/d*RTMaxPercentageComment041 00002DOMINION - CHESTERFIELD POWERSTATION4 4911 9,416 744 345.27 2.15 19.94 42.871 0.05%Expected to becontrolled by FGD.085 00042 BEAR ISLAND PAPER COMPANY LLC1 2621 470 528 317.85 1.66 23.79 39.4914 0.05%550 00026 DOMINION - CHESAPEAKE14911 5,261 461 340.98 1.35 27.29 36.8415 0.04%Using low S fuel.670 00003STONE CONTAINER CORPORATIONHOPEWELL1 2631 766 760 344.26 2.21 16.45 36.3545 0.04%670 ORIS10771 LG&E WESTMORELAND HOPEWELL GEN1 4911 0 758 345.55 2.19 16.45 36.0255 0.04%Controlled by FGD.550 00026 DOMINION - CHESAPEAKE24911 5,307 447 340.98 1.31 27.29 35.7499 0.04%Using low S fuel.019 00003GEORGIA PACIFIC CORP BIG ISLANDPLT1 2631 1,090 1,223 478.58 2.56 12.76 32.6656 0.04%BART-will becontrolled by FGD.760 00308PHILIP MORRIS USAMANUFACTURING CENTER1 2111 532 528 341.69 1.54 19.94 30.7076 0.04%550 00038 PERDUE FARMS INCORPORATED5 2075 371 368 337.09 1.09 27.29 29.7461 0.04%101 00001STONE CONTAINER CORP (D/B/ASMURFIT-STON4 2611 315 365 296.83 1.23 23.79 29.2617 0.04%093 00006 INTERNATIONAL PAPER COMPANY5 2621 286 326 377.94 0.86 27.29 23.4694 0.03%Facility is currentlyshut down.760 ORIS54081COGENTRIX OF RICHMONDINCORPORATEDGEN1 4911 0 358 343.41 1.04 19.94 20.7376 0.02%Controlled by FGD.760 ORIS54081COGENTRIX OF RICHMONDINCORPORATEDGEN2 4911 0 358 343.41 1.04 19.94 20.7376 0.02%Controlled by FGD760 ORIS54081COGENTRIX OF RICHMONDINCORPORATEDGEN3 4911 0 358 343.41 1.04 19.94 20.7376 0.02%Controlled by FGD760 ORIS54081COGENTRIX OF RICHMONDINCORPORATEDGEN4 4911 0 358 343.41 1.04 19.94 20.7376 0.02%Controlled by FGD.031 00156DOMINION - ALTAVISTA POWERSTATION1 4911 50 778 495.79 1.57 12.76 20.0332 0.02%Controlled by FGD.083 00046DOMINION - CLOVER POWERSTATION2 4911 1,000 699 471.38 1.48 13.43 19.8764 0.02%Controlled by FGD.083 00046DOMINION - CLOVER POWERSTATION1 4911 982 691 471.38 1.47 13.43 19.7421 0.02%Controlled by FGD.093 00006 INTERNATIONAL PAPER COMPANY8 2621 218 255 377.94 0.67 27.29 18.2843 0.02%Facility is currentlyshut down.095 00022OWENS-BROCKWAY GLASSCONTAINER21 3221 194 256 309.26 0.83 21.72 18.0276 0.02%069 00034GLOBAL STONE CHEMSTONECORPORATION22 3274 263 345 313.98 1.10 15.22 16.742 0.02%117 ORIS52007MECKLENBURG COGENERATIONFACILITYGEN1 4911 0 487 479.28 1.02 13.70 13.974 0.02%Controlled by FGD119-Virginia Regional Haze SIPTable 10-2. Contribution of Virginia 2018 Point Source Sulfate Emissions to BrigantineFIPSCountyPlant IDPlantPointIDSIC(2002 G)(2018 G)Distance(km)Q/dRTMax**Q/d*RTMaxPercentageComment117 ORIS52007MECKLENBURG COGENERATIONFACILITYGEN2 4911 0 487 479.28 1.02 13.70 13.974 0.02%Controlled by FGD.143 00003BURLINGTON INDUSTRIESINCORPORATED HURT1 2262 490 487 500.00 0.97 12.76 12.3772 0.01%081 00002GEORGIA PACIFIC CORP JARRATTPLANT6 2493 303 301 396.69 0.76 15.52 11.7952 0.01%019 00003GEORGIA PACIFIC CORP BIG ISLANDPLT2 2631 251 286 478.58 0.60 12.76 7.656 0.01%BART-Wood fired.143 00100OWENS-BROCKWAY GLASSCONTAINER INC21 3221 215 284 533.04 0.53 12.76 6.7628 0.01%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 discus sion of the implementation process and the most recent IMPROVE monitoring data and VIEWS data.

There are several technical improvements that ar e recommended in the emissions inventory and air quality models that are used to support re gulatory 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 n eeded in the integrated one-atmosphere air quality models that are used to project air qua lity responses to emissions reductions. As the understanding of partitioning between gaseous a nd aerosol phases improves, this understanding needs to be reflected in the models. Improvement s 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 sh ould 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 ve ry low. Additional improvements in seasonal allocation of ammonia emissions would impr ove model estimates of ammonium nitrate formation. Organic carbon is generally underes timated in the summer months. Improvements
are needed in the characteriza tion 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 betwee n rural and urban monitoring networks. To better understand the contribution of fire from natural forest fires, prescribed burning, land clearing, and agricultural burning, states ne ed improved recordk eeping. Additional improvements to international emissions inventor y are also needed, to improve understanding of boundary conditions for modeling domains and of th e 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). Th e findings of the five-y ear progress report will determine which action is appropriate and necessary.121-Virginia Regional Haze SIP 

### • Virginia determines that the existing SI P requires no further substantive revision
in order to achieve estab lished goals. Virginia notif ies 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 stat es which participated in the regional planning process. Virginia notifies th e Administrator and the states that participated in regional planning. Virginia collaborates with states through the regional planning process to a ddress the SIP’s deficiencies.

• Virginia determines that the current SIP may be inadequate to ensure reasonable progress due to emissions from another c ountry. 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 administrat ive 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 Virg inia State Implementation Plan was held in the second floor conference room A, Depar tment of Environmental Quality, 629 East Main Street, Richmond, Virginia, at 10:00 a.m. on September 16, 2010.

In the National Capital Interstate Air Qualit y 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. En vironmental Protection Agency was notified of the hearing, as was each local air pollu tion control agency which will be significantly impacted by the revision and is located in t he 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 require ments 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 Virg inia, 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

### PROO F O F P UB LI CAT IO N 

# • 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, 20 1 0 certify that the notice of:
C l elD AJ r Act

D EQ- Al r Q u a li ty Di visio n 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 1 8,2010
C l ean Air Act
D EQ- A ir Q U ality Di vis i o n

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 .90 3

. 2018 

## w Offi cial Court Doc ument Retain For Your R ecords
DO NOT D I SC ARD**=:~o>uAA~= ~,:~~** **~n::~,= (1IIM1"....1I11** **~($IoI)** ....**~IO'** ___ ._ ...

_ . !IO"I



## ..... '

..**""'~IW'1I'**

### GENERAL NOTICES/ERRATA

AIR POLLUTION CONTROL BOARD

State Implem entatio n Pl a n R evision

- Visibilit y Impairment s in Federal Class I Areas

Notice of action: The [)cpanmenl of Environmenta l Quality (DEQ) is seeking comments and armouncing a public hearing

on a proposed plan to improve**vi~ihility** impairment in
federal C i a$:! I ar<':as

. federa l Cla$$ I arcas arc defined in the
Clean Air Act as nationa l 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 o f 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(Xlnsibili t ies under the
federa l 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 r equirements fo r C<lntmJling
air JXlllutants that reduce visibility in C lassl 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 na t ional goal of a

return 10 naturol visibilily corn.!itioru; by 2064 for each CI95s I

area within the state and for C lass 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 ensu r e no degradation in visib i lity 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 visibili t y**eondition..~** for the most impaired and least impaireJ days. The SIP also contains supporting docwnenta t ion 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 i tations, compliance**s<;;hedule~,** and

other me"""r"" "" ne"""""ry to "chi"v e 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 Co mmonwealth 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 en f orceability 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 t o cause or contribule 10 any impairmenl of visibility in any C la:ss I**are~.** BART-cligib l e 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 f or compliance with

BART for each source s u bject to BART are**includ~d** in the**long~teml** strategy

.

Federal infom J ation : 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 re v ision to tbe Co mmonwea l tb of**Virgini~** SIP under §**110(~)** 3nd § 169A of the federal CM in accordance with 40 C FR
5 1.10

· t. It is planned to submit all provisi= of the propooal

as a r evision to the Commonwealth of Virginia SIP

. C()II.'3 ultation 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 II

IOh.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 b y 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 Regis t er of Regulations Augus/30

, 2010

2901

## General Notices / Errata

with any supporting docwm ::n ts or exhibits. A ll testimony

, e.>JJ ihilS, 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:x t ing

documents an: available on the DEQ Air Pub 1i (; Notices for Plans website (http }/ w\\'w.dell

_ virginia.gov / air / permittingl

p l anolcs

. html )

. The documents may also be ob t .-'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 comme nt period at the fol1owing DEQ locations :

1) Main Street O ffi ce , 8th Floor

, 629 E. Main St

, Richmond VA

, telephone (804) 698- 4 070

, 2) Southwc,:;t Regional Office

, 355 Dcadmorc St

, Abingdon VA

. t ckphonc (540) 6 7 6.4800

, 3) B lue Ridge Regional Office

, ROBnoke LOCBlion. 3019

Peters Creek Rd., Roanoke VA, telephone (540) 562·6700,

4 ) B l ue Ridge Regional Office

, Lynchburg Loca tion

, 1705
Tim berlake Rd

. , Lynchburg VA

, telephone (804) 582 · 5120

, S) Vlliley Regional Office. 4411 Early Rd.

, Hllrrisooburg

VA

, telephone (540) 574 ·78 00

, 6) Piedmont Regional Office, 4 949

· A Cox Rd., Glen Alle n VA, telephone (804) 527-5020,

7)Northern Regional Office

, 13901 Crown Court, Woodbridge VA, telephone (703) 583-3800

, and

8) Tidewater Regio nal Office. 5636 Southern Blvd

., Virginia &ach, VA telephone (757) 518

- 201X.l

.

Contact !nfonnation : Doris A. McLeod, Departmen t of
Enviro nmental Quality, 629**F.a.~t** Main Street, P

. O

. 80.'\ 1105, Richmond, VA 23218

, l\:1cphonc (804) 698

- 4197

, FAX (804)
698-4510

, or emai l**dori.~.l1lc1cod@dcq virginL-l.g<N** **.**

Vo/uroo 26

. Issue 26 V r 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 En vironmental 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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