- 

west virginia department of environmental protection -- -- -- -- - - -- - - 

Executive Office Joe Manch~n 111, Governor 

601 5Th Street SE Randy C Hufhan, Cabinet Secretary 

CharIeston, WV 25304 www wvdep org 

November 4,2009 

Mr. William C. Early 

Acting Regional Administrator 

U.S. EPA, Region I11 (3RA00) 

1650 Arch Street 

Philadelphia, PA 19 103-2029 

Re: Final Charleston, WV PM2,, Attainment 

Demonstration State Implementation Plan 

(SIP) Pursuant to the Federal Clean Air 

Fine Particle Implementation Rule (40 

CFR 5 1, Subpart Z) 

Dear Administrator Early: 

In a letter dated July 16,2009, this agency submitted to the Air Division a proposed revision 

to the State Implementation Plan (SIP) for the State of West Virginia to meet its obligations 

under the Clean Air Act (CAA) and the Federal Clean Air Fine Particle Implementation Rule, for 

the Charleston, WV PM2., nonattainment area (1 997 standard). Based upon comments received 

from EPA, DEP made revisions; reopened the comment period and notified EPA in a letter dated 

September 24,2009. We have now completed the public participation process and are herein 

submitting the final SIP. We certifj7 that the public hearing required by 40 CFR 55 1.102(a) was 

held in accordance with the applicable state laws and the requirements of 40 CFR 55 1.102(d). 

Please be advised that pursuant to 40 CFR 5 1.1 16 (Data Availability), and in consultation 

with EPA Region 3 senior staff, certain detailed data and calculations are being provided in 

electronic form but not in hard copy. The State of West Virginia requests that the EPA approve 

this Charleston attainment demonstration, with a projected attainment date of April 201 0, as a 

revision to the SIP. If you have any questions regarding this submittal or require additional 

information, please contact John A. Benedict, Director of the Division of Air Quality, at (304) 

926-0462. 

-9- Randy C. H an 

Cabinet Secretary 

Enclosure 

cc: Judy Katz, EPA 

John A. Benedict, DEP 

Promoting a healthy environment. 
west virginia department of environmental protection

West Virginia 1997 Fine Particle (PM2.5 ) 

Attainment Demonstration 

and

State Implementation Plan

for the

Charleston, West Virginia 

Nonattainment Area,

Comprising

Kanawha and Putnam Counties 

Final

November 2009

Promoting a healthy environment.
[This page intentionally left blank.]
Table of Contents

List of Tables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page v

List of Figures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page vii

List of Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page ix

Acronyms and Abbreviations .............................................. Page xvi

1.0. INTRODUCTION .................................................. Page 1

1.1. Request ........................................................ Page 1

1.2. Definition of Fine Particle Matter ................................... Page 1

1.3. Health and Environmental Effects ................................... Page 3

1.4. The PM2.5 NAAQS ............................................... Page 4

1.5. Association for Southeastern Integrated Planning (ASIP) ................ Page 9

1.6. Clean Air Act Requirements ...................................... Page 10

2.0. SIGNIFICANCE OF PM2.5 PRECURSOR POLLUTANTS . . . . . . . . . . . . . . . . . Page 11

2.1. Pollutant Contributions in the Charleston Nonattainment Area ........... Page 11

2.2. PM2.5 Component Species Analysis ................................. Page 15

2.3. Attribution of Emissions Sources .................................. Page 23

2.4. Identification of Attainment Plan Pollutants and Precursors .............. Page 27

2.4.a. Direct PM2.5 emissions ........................................ Page 27

2.4.b. SO2 emissions .............................................. Page 28

2.4.c. NOx emissions .............................................. Page 29

2.4.d. VOC emissions ............................................. Page 31

2.4.e. Ammonia emissions .......................................... Page 32

2.5. Transportation Conformity ....................................... Page 35

3.0. ATTAINMENT DEMONSTRATION METHODS AND INPUTS ........... Page 40

3.1. Analysis Method ............................................... Page 40

3.2. Model Selection ................................................ Page 41

3.2.a. Selection of Photochemical Grid Model .......................... Page 41

3.2.a.1. Criteria .............................................. Page 41

3.2.a.2. Overview of CMAQ .................................... Page 42

3.2.b. Selection of Meteorological Model .............................. Page 42

3.2.b.1. Criteria .............................................. Page 42

3.2.b.2. Overview of MM5 ..................................... Page 43

3.2.c. Selection of Emissions Processing System ........................ Page 44

3.2.c.1. Criteria .............................................. Page 44

3.2.c.2. Overview of SMOKE ................................... Page 44

3.3. Selection of the Modeling Year .................................... Page 45

3.4. Modeling Domains .............................................. Page 46

3.4.a. Horizontal Modeling Domain .................................. Page 46

3.4.b. Vertical Modeling Domain .................................... Page 48

FINAL Charleston, WV 1997 PM2.5 SIP Page i
4.0. EMISSION INVENTORY .......................................... Page 49

4.1. Baseline (2002) Emissions Inventory ............................... Page 49

4.1.a. Stationary Sources ........................................... Page 50

4.1.a.1. Stationary Point Sources ................................ Page 50

4.1.a.1.A. Electric Generating Units (EGUs) ...................... Page 50

4.1.a.1.B. Other Industrial Point Sources (NonEGUs) .............. Page 52

4.1.a.2. Stationary Area Sources ................................ Page 52

4.1.b. Mobile Sources ............................................. Page 54

4.1.b.1. NonRoad Mobile Sources ............................... Page 54

4.1.b.2. Onroad Mobile Sources ................................. Page 55

4.1.c. Biogenic Emissions Sources ................................... Page 56

4.1.d. Summary 2002 Baseline Emissions Inventory ..................... Page 57

4.2. Projected 2009 Emissions Inventories ............................... Page 57

4.2.a. Stationary Sources ........................................... Page 57

4.2.a.1. Stationary Point Sources ................................ Page 57

4.2.a.1.A. Electric Generating Units (EGUs) ...................... Page 58

4.2.a.1.B. Other Industrial Point Sources (NonEGUs) .............. Page 59

4.2.a.2. Stationary Area Sources ................................ Page 59

4.2.b. Mobile Sources ............................................. Page 60

4.2.b.1. Nonroad Mobile Sources ................................ Page 61

4.2.b.2. Onroad Mobile Sources ................................. Page 62

4.2.c. Biogenic Sources ............................................ Page 64

4.2.d. Summary of Final Inventories for 2009 ........................... Page 64

4.3. Summary 2002 and 2009 State-wide Emissions Inventories for West Virginia

............................................................. Page 64

4.4. Summary 2009 Region-wide Emissions Inventories for the VISTAS States . Page 65

5.0. MODEL PERFORMANCE EVALUATION ............................ Page 67

5.1. Model Performance Goals, Criteria and Results ....................... Page 69

5.2. VISTAS/ASIP Domain-wide Performance ........................... Page 71

5.3. West Virginia PM2.5 Model Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 73

5.4. Conclusions of Model Performance Evaluation ....................... Page 76

6.0. CONTROL MEASURES ........................................... Page 78

6.1. Point Source Measures ........................................... Page 78

6.1.a. Control Strategies ........................................... Page 78

6.1.a.1. RACT and Regional Transport Requirements (federal and state

regulations) .......................................... Page 78

6.1.a.1.A. RACT ............................................ Page 78

6.1.a.1.B. NOx SIP Call ...................................... Page 78

6.1.a.1.C. Clean Air Interstate Rule (CAIR) ....................... Page 78

6.1.a.1.D. Standards Regarding Fugitive Dust .................... Page 84

6.1.b. Projected Reductions ......................................... Page 84

FINAL Charleston, WV 1997 PM2.5 SIP Page ii
6.2. Area Source Measures ........................................... Page 86

6.2.a. Control Strategy ............................................. Page 86

6.2.a.1. Open Burning Restrictions (state rule) ..................... Page 86

6.2.b. Projected Reductions ......................................... Page 86

6.3. Non-Road Source Measures ...................................... Page 86

6.3.a. Control Strategies ........................................... Page 86

6.3.a.1 Phase I and Phase II Emissions Standards for Gasoline-Powered Nonroad

Utility Engines (federal rule) ............................. Page 86

6.3.a.2. Emissions Standards for Diesel-Powered Nonroad Utility Engines of 50

or More Horsepower (federal rule) ........................ Page 86

6.3.a.3. Emission Standards for Spark-Ignition (SI) Marine Engines (federal rule)

.................................................... Page 87

6.3.a.4. Emission Standards for Large Spark-Ignition (SI) Engines (federal rule)

.................................................... Page 87

6.3.a.5. Standards for Locomotives (federal rule) ................... Page 88

6.3.b. Projected Reductions ......................................... Page 88

6.4. Onroad Source Measures ......................................... Page 90

6.4.a. Control Strategies ........................................... Page 90

6.4.a.1. Federal Tier I new Vehicle Emission and New Federal Evaporative

Emissions Standards (federal regulation) ................... Page 90

6.4.a.2. National Low Emission Vehicle Program (federal regulation) ... Page 90

6.4.a.3. Tier 2 Motor Vehicle Emission Regulations (federal regulation) . Page 91

6.4.a.4. Heavy Duty Diesel Engine Rule (federal regulation) .......... Page 91

6.4.b. Projected Reductions ......................................... Page 92

6.5. Supplemental Control Measures ................................... Page 93

6.6. Schedule of Adopted Control Measures ............................. Page 95

7.0. ATTAINMENT DEMONSTRATION ................................. Page 97

7.1. Attainment Test Introduction ...................................... Page 97

7.1.a. ASIP PM2.5 Projection tool .................................... Page 97

7.1.b. MATS tool ................................................. Page 98

7.2. Attainment Test Results .......................................... Page 99

7.3. Weight of Evidence Analysis ..................................... Page 103

7.3.a. Other Modeling Results ...................................... Page 103

7.3.a.1. EPA’s CAIR Modeling ................................. Page 104

7.3.a.2. Midwest RPO Modeling ................................ Page 105

7.3.b. Trends in Ambient Air Quality and Emissions .................... Page 107

7.4. Unmonitored Area Analysis ..................................... Page 109

8.0. CLEAN AIR ACT SECTION 172(C) REQUIREMENTS ................. Page 115

8.1. Reasonably Available Control Measures ............................ Page 115

8.2. Reasonable Further Progress ..................................... Page 116

8.3. Actual Emissions Inventory ...................................... Page 117

8.4. Periodic Emissions Inventory .................................... Page 117

FINAL Charleston, WV 1997 PM2.5 SIP Page iii
8.5. Permitting Requirements for New and Modified Sources ............... Page 117

8.6. Other Measures ............................................... Page 118

8.7. Compliance with Section 110(a)(2) ................................ Page 118

8.8. Equivalent Techniques .......................................... Page 119

8.9. Contingency Measures .......................................... Page 119

8.9.a. Enforceability Issues ........................................ Page 119

8.9.b. Evaluations/Suggested Reductions ............................. Page 120

8.9.c. Identified Contingency Measures for the Charleston Area ........... Page 121

9.0. REASONABLY AVAILABLE CONTROL MEASURES (RACM), INCLUDING

REASONABLY AVAILABLE CONTROL TECHNOLOGY (RACT) FOR

STATIONARY SOURCES ........................................ Page 130

9.1. Statutory and Regulatory Requirements for RACM Analysis ............ Page 130

9.2. Discussion of Reasonable Control Measures ......................... Page 131

9.3. Discussion of RACT ........................................... Page 131

9.4. Evaluation of RACM for Purposes of Achieving Attainment ............ Page 133

9.5. Summary .................................................... Page 137

9.5.a. RACM Determination ....................................... Page 137

9.5.b. RACT Applicability ......................................... Page 137

10.0. MID-COURSE REVIEW .......................................... Page 138

11.0. PUBLIC PARTICIPATION ........................................ Page 138

12.0 CONCLUSION .................................................. Page 138

FINAL Charleston, WV 1997 PM2.5 SIP Page iv
List of Tables

Table 1.4. Charleston Nonattainment Area Design Values for the 1997 Annual and 24-hr PM2.5

NAAQS ............................................................. Page 6

Table 2.1. PM2.5 Concentrations and Design Values for the FRM monitors1 in the Charleston

PM2.5 Nonattainment Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 11

Table 2.4.a-1. West Virginia Annual PM2.5 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 27

Table 2.4.a-2. Annual PM2.5 Emissions for Kanawha and Putnam Counties . . . . . . . . . . Page 28

Table 2.4.b-1. West Virginia Annual SO2 Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 29

Table 2.4.b-2. Annual SO2 Emissions for Kanawha and Putnam Counties . . . . . . . . . . . Page 29

Table 2.4.c-1. West Virginia Annual NOx Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 30

Table 2.4.c-2. Annual NOx Emissions for Kanawha and Putnam Counties . . . . . . . . . . . Page 30

Table 2.4.d-1. West Virginia Annual VOC Emissions ........................... Page 31

Table 2.4.d-2. Annual VOC Emissions for Kanawha and Putnam Counties .......... Page 31

Table 2.4.e-1. ASIP Ammonia Emissions .................................... Page 33

Table 2.4.e-2. West Virginia Ammonia Emissions ............................. Page 33

Table 2.4.e-3. Ammonia Emissions for Kanawha and Putnam Counties ............. Page 34

Table 2.5-1. Emission Inventory (Tons/Year) ................................. Page 37

Table 2.5-3. Charleston Area PM2.5 Conformity Results . . . . . . . . . . . . . . . . . . . . . . . . . Page 39

Table 4.1.a.1. Comparison of SO2 and NOx Emissions (tons/year) for EGUs from Actual 2002

Inventory and Typical 2002 Inventory .................................... Page 51

Table 4.1.c. West Virginia Biogenic Emissions ................................ Page 56

Table 4.1.d. 2002 Base Year Inventory - Charleston Nonattainment Area ........... Page 57

Table 4.2.d. 2009 Attainment Year Inventory - Charleston Nonattainment Area ...... Page 64

Table 4.3-a. 2002 State-wide Emissions Inventory Summary for West Virginia ...... Page 64

Table 4.3.b. 2009 State-wide Emissions Inventory Summary for West Virginia ....... Page 65

Table 5.1. VISTAS/ASIP Model Performance Goals and Criteria for Components of Fine

Particle Mass . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 70

Table 6.1. Coal-fired EGU Controls (Installed and Under Construction) ............ Page 80

Table 6.2. 2009 Point Source Emission Reductions ............................. Page 85

Table 6.3. 2009 Nonroad Emission Reductions ................................ Page 89

Table 6.4-1. Tier I Standards .............................................. Page 90

Table 6.4-2. Onroad Emission Reductions ................................... Page 92

Table 6.6. West Virginia Schedule of Adopted Control Measures – Charleston Nonattainment

Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 95

Table 7.2-1. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 Using the ASIP

PM2.5 Projection Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 100

Table 7.2-2. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 Using the MATS

PM2.5 Projection Tool . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 101

Table 7.2-3. Comparison of the PM2.5 Mass Estimates for 2009 Using the ASIP and MATS

PM2.5 Projection Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 102

Table 7.3-1. EPA CAIR Modeling Results ................................... Page 104

Table 7.3-2. LADCO - Round 5 - 2009 Results ............................... Page 106

Table 7.3.b-1. Air Monitoring Data for Charleston Area ........................ Page 107

FINAL Charleston, WV 1997 PM2.5 SIP Page v
Table 7.4. VISTAS Regional Scale Modeling Results .......................... Page 110

Table 8.9-1. Contingency Targets for PM and PM Precursors .................... Page 120

Table 8.9-2. Projected 2009 Emissions ..................................... Page 121

Table 8.9-3. Percent Reduction of Projected 2009 Emissions (excluding EGUs) Needed to Meet

Suggested Contingency Targets ......................................... Page 121

Table 8.9-4. DuPont (039-0001) 2009 Projected Emissions Used in Attainment Demonstration

.................................................................. Page 126

Table 8.9-5. Philip Sporn (053-0001) 2009 Projected Emissions Used in Attainment

Demonstration (units 31 and 41), and Expected NOx Reductions due to SNCR . . . Page 126

Table 8.9-6. Contingency Measure Reductions from 2009 Emissions .............. Page 127

Table 8.9-7. Aggregate Emissions in the Charleston Nonattainment Area and Within 200 km of

the Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 128

Table 8.9-8. Projected 2009 Emissions ..................................... Page 128

Table 8.9-9. Percentage Change in Emissions by Sector in the Charleston Area

(2002 to 2009) ...................................................... Page 128

Table 9.3-1. 2002 and 2009 Emissions of Potential RACT Sources in Charleston Area

.................................................................. Page 132

Table 9.4-1. Analysis of Stationary Source Control Measures to Determine Reasonably

Available Control Measures (RACM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 134

FINAL Charleston, WV 1997 PM2.5 SIP Page vi
List of Figures

Figure 1.2. Chemical links between the ozone and PM formation processes. ........ Page 3

Figure 1.4-1. West Virginia PM2.5 Monitoring Network . . . . . . . . . . . . . . . . . . . . . . . . . . Page 7

Figure 1.4-2. Map of West Virginia PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . Page 8

Figure 2.1-1. 2002 sample data for the Charleston PM2.5 monitor . . . . . . . . . . . . . . . . . Page 12

Figure 2.1-2. 2002 sample data for the South Charleston PM2.5 monitor . . . . . . . . . . . . Page 13

Figure 2.1-3. Number of samples per quarter in 2002 at the Charleston monitor (54-039-0010)

with PM2.5 concentrations greater than 15μ/m3. .................... Page 14

Figure 2.1-4. Number of samples per quarter in 2002 at the South Charleston monitor (54-039-

1005) with PM2.5 concentrations greater than 15μ/m3. ............... Page 14

Figure 2.2-1. PM2.5 species contribution in the Charleston area, Charleston monitor (54-039-

0010), based on EPA SMAT data. ............................... Page 16

Figure 2.2-2. PM2.5 species contribution in the Charleston area, at the South Charleston monitor

(54-039-1005), based on EPA SMAT data. ........................ Page 16

Figure 2.2-3. Charleston (54-039-0010) 2009 DVF Quarterly Speciation projection data based

on SMAT tool using 2002 speciation data. Upper left - first quarter (Jan - Mar),

Upper right second quarter (Apr - Jun), bottom left - third quarter (Jul - Sep) and

bottom right - fourth quarter (Oct - Dec). . . . . . . . . . . . . . . . . . . . . . . . . . Page 18

Figure 2.2-4. South Charleston (54-039-1005) 2000-2004 DVB Quarterly Speciation data

based on SMAT tool using 2002 speciation data. Upper left - first quarter (Jan -

Mar), Upper right second quarter (Apr - Jun), bottom left - third quarter (Jul -

Sep) and bottom right - fourth quarter (Oct - Dec). . . . . . . . . . . . . . . . . . Page 19

Figure 2.2-5. CMAQ modeled changes in 2009 PM2.5 mass for the Charleston FRM monitor

from reducing 2002 VISTAS/ASIP Base D emissions by 30% for several

different emissions source categories, for the summer period Jun 1 - Jul 10, 2002.

.......................................................... Page 21

Figure 2.2-6. CMAQ modeled changes in 2009 PM2.5 mass for the Charleston FRM monitor

from reducing 2002 VISTAS/ASIP Base D emissions by 30% for several

different emissions source categories, for the winter period Nov 19 - Dec 19,

2002....................................................... Page 21

Figure 2.2-7. 2002 Monitored Design Values (left) and 2009 base G4 12 km projected DVF

(middle) and 2009 base G4 36 km projected DVF (right) for all FRM monitors in

West Virginia. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 22

Figure 2.3-1. Charleston nonattainment area 2002 SO2 emissions by source sector. . . . Page 24

Figure 2.3-2. 2002 Statewide West Virginia SO2 emissions by source sector. . . . . . . . . Page 25

Figure 2.3-3. Comparison of 2002 total West Virginia SO2 emissions to 2002 SO2 emissions in

the Charleston area. The Charleston SO2 point source emissions account for

approximately 23% of the total state SO2 emissions. . . . . . . . . . . . . . . . . Page 26

Figure 2.4-1. Annual Sensitivities for West Virginia PM2.5 Non-Attainment Areas (VISTAS

Base D emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 32

Figure 2.5-1. Charleston PM2.5 Design Value, 2001-2007 ....................... Page 38

Figure 3.4-1. The MM5 horizontal domain is the outer most, blue grid, with the CMAQ 36-km

domain nested in the MM5 domain . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 47

FINAL Charleston, WV 1997 PM2.5 SIP Page vii
Figure 3.4-2. A more detailed view of the 12-km grid over the VISTAS region ...... Page 48

Figure 4.4-a. Annual SO2 emissions for 2002, 2009, and 2018 in the VISTAS states. . Page 65

Figure 4.4-b. Annual NOx emissions in 2002, 2009 and 2018 in the VISTAS states. . . Page 66

Figure 5-1. IMPROVE, STN, CASTNet, NADP and SEARCH monitoring sites located in the

VISTAS/ASIP region and the VISTAS/ASIP 12 km grid. . . . . . . . . . . . . Page 69

Figure 5.2-1. VISTAS STN Soccer Plots .................................... Page 71

Figure 5.2-2. VISTAS STN Bugle Plots ..................................... Page 72

Figure 5.2-3. VISTAS FRM Soccer Plots .................................... Page 72

Figure 5.2-4. VISTAS FRM Bugle Plots ..................................... Page 73

Figure 5.3-1. Scatter plots of predicted and observed fine particulate mass (PM2.5)

concentrations for January, April, July and October 2002, FRM sites in West

Virginia and the CMAQ 2002 36 and 12 km Base G2 Actual base case simulation.

.......................................................... Page 74

Figure 5.3-2. Soccer plot of monthly fractional bias versus fractional gross error for PM2.5 mass

at FRM monitors in West Virginia for the CMAQ 12 km Base G2 Actual base

case simulation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 75

Figure 7.3.b-1. Chart showing trend in PM2.5 monitoring data in the Charleston area.

...................................................... Page 107

Figure 7.3.b-2. Point source emissions for 1999, 2002 and 2005 in the Charleston Area.

...................................................... Page 108

Figure 7.4-1. 2002 Current-year PM2.5 Design Values (DVC), displaying monitoring sites,

interpolated to 12 km domain by MATS unmonitored area analysis. . . . Page 112

Figure 7.4-2. 2002 Current-year PM2.5 Design Values (DVC), without monitoring sites

displayed, interpolated to 12 km domain by MATS unmonitored area analysis.

......................................................... Page 113

Figure 7.4-3. 2009 projected PM2.5 Design Values (DVF) calculated using MATS unmonitored

area analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 114

Figure 8.9-1. Map of Charleston PM2.5 Nonattainment Area showing 200 km around area,

showing all power plants in the state and sources of contingency measures. 

......................................................... Page 122

Figure 8.9-2. SO2 Area of Influence for Charleston nonattainment area. Green circles indicate

100-km and 200-km radii from the Charleston PM2.5 monitor. Red line perimeter

indicates AoI with a Residence Time $ 10%. Orange line perimeter indicates AoI

with a Residence Time $ 5%. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 124

Figure 8.9-3. SO2 Area of Influence for Charleston nonattainment area, showing county

outlines. Green circles indicate 100-km and 200-km radii from the Charleston

PM2.5 monitor. Red line perimeter indicates AoI with a Residence Time $ 10%.

Orange line perimeter indicates AoI with a Residence Time $ 5%. . . . . Page 125

FINAL Charleston, WV 1997 PM2.5 SIP Page viii
List of Appendices

Appendix A: Air Quality Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page A - 1

Appendix B: Modeling Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page B - 1

Appendix B.1: PM2.5 Conceptual Description: West Virginia PM2.5 Nonattainment Areas . . .

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page B - 5

Appendix B.2: Modeling Protocol for Association for Southeastern Integrated Planning

Emissions and Air Quality Modeling to Address 8-hr Ozone and PM2.5 Nonattainment Areas

in the Southeastern United States . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page B - 39

Appendix C: Emissions Inventory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1

Appendix C.1: Inventory Summaries by Nonattainment Area . . . . . . . . . . . . . . . . Page C - 7

Appendix C.1.a: Charleston Nonattainment Area . . . . . . . . . . . . . . . . . . . . . . Page C - 9

Appendix C.1.b: Huntington Nonattainment Area . . . . . . . . . . . . . . . . . . . . . Page C - 13

Appendix C.1.c: Martinsburg Nonattainment Area . . . . . . . . . . . . . . . . . . . . . Page C -17

Appendix C.1.d: Parkersburg Nonattainment Area . . . . . . . . . . . . . . . . . . . . Page C - 21

Appendix C.1.e: Weirton Nonattainment Area . . . . . . . . . . . . . . . . . . . . . . . . Page C - 25

Appendix C.1.f: Wheeling Nonattainment Area . . . . . . . . . . . . . . . . . . . . . . . Page C - 29

Appendix C.2: West Virginia Point Source Inventories . . . . . . . . . . . . . . . . . . . . Page C - 33

Appendix C.2.a: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 35

Appendix C.2.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 41

Appendix C.3: West Virginia Area Source Inventories . . . . . . . . . . . . . . . . . . . . Page C - 47

Appendix C.3.a: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 49

Appendix C.3.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 209

Appendix C.4: West Virginia Nonroad Inventories . . . . . . . . . . . . . . . . . . . . . . Page C - 369

Appendix C.4.a: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 371

Appendix C.4.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 545

Appendix C.5: West Virginia Onroad Inventories . . . . . . . . . . . . . . . . . . . . . . . Page C - 721

Appendix C.5.a: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 723

Appendix C.5.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 733

Appendix C.6: Ohio Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 743

Appendix C.6.a: Point Source Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 745

Appendix C.6.a.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 747

Appendix C.6.a.2: 2002 NEI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 751

Appendix C.6.a.3: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 755

FINAL Charleston, WV 1997 PM2.5 SIP Page ix
Appendix C.6.b: Area Source Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 759

Appendix C.6.b.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 761

Appendix C.6.b.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 775

Appendix C.6.c: Nonroad Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 789

Appendix C.6.c.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 791

Appendix C.6.c.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 827

Appendix C.6.d: Onroad Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 863

Appendix C.6.d.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 865

Appendix C.6.d.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 885

Appendix C.7: Kentucky Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 905

Appendix C.7.a: Point Source Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 907

Appendix C.7.a.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 909

Appendix C.7.a.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 913

Appendix C.7.b: Area Source Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 917

Appendix C.7.b.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 919

Appendix C.7.b.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 927

Appendix C.7.c: Nonroad Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 935

Appendix C.7.c.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 937

Appendix C.7.c.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 949

Appendix C.7.d: Onroad Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 961

Appendix C.7.d.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 963

Appendix C.7.d.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 969

Appendix C.8: Maryland Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 975

Appendix C.8.a: Point Source Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 977

Appendix C.8.a.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 979

Appendix C.8.a.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 983

Appendix C.8.b: Area Source Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 987

Appendix C.8.b.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 989

Appendix C.8.b.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 995

Appendix C.8.c: Nonroad Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1001

Appendix C.8.c.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1003

Appendix C.8.c.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1011

Appendix C.8.d: Onroad Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1019

Appendix C.8.d.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1021

Appendix C.8.d.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page C - 1027

Appendix D: Emission Inventory Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 1

Appendix D.1: West Virginia Inventory Documentation . . . . . . . . . . . . . . . . . . . . Page D - 5

Appendix D.1.a: Biogenics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 7

Appendix D.1.b: Correspondence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 21

FINAL Charleston, WV 1997 PM2.5 SIP Page x
Appendix D.2: Ohio Inventory Documentation . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 135

Appendix D.2.a: LADCO – Base M Strategy Modeling Emissions (Revised) 

[October 10, 2007] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D- 137

Appendix D.2.b: LADCO IPM Model Parsed File Post Processing Methodology and 

File Preparation (January 2005) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 153

Appendix D.2.c: LADCO Nonroad Emission Inventory Project for Locomotive,

Commercial Marine, and Recreational Marine Emission Sources (December 2004) .....

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 165

Appendix D.2.d: Ohio Partial Nonattainment Counties . . . . . . . . . . . . . . . . Page D - 255

Appendix D.2.e: Correspondence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 259

Appendix D.3: Kentucky Inventory Documentation . . . . . . . . . . . . . . . . . . . . . Page D - 287

Appendix D.4: Maryland Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 291

Appendix D.5: Background Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 311

Appendix D.5.a: Emission Data Collection for 2002 Regional Haze Inventory Area and

Point Sources: Draft Quality Assurance Project Plan (January 2003) ................

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 313

Appendix D.5.b: 2002 Southeast Emission Inventory Development for Onroad Mobile

and Nonroad Mobile Emission Sources (February 3, 2003) . . . . . . . . . . . . . Page D - 340

Appendix D.5.c: Documentation for the Final 1999 National Emission Inventory

(Version 3) for Criteria Air Pollutants and Ammonia: Point Sources (January 31, 2004)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 359

Appendix D.5.d: Development of the VISTAS Draft 2002 Mobile Source Emission

Inventory (February 9, 2004) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 446

Appendix D.5.e: Development of Growth Factors for Future Year Modeling Inventories

(April 30, 2004) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 507

Appendix D.5.f: Quality Assurance Project Plan (Draft) for Visibility Improvement for

State and Tribal Association for the Southeastern States (VISTAS): Emissions and Air

Quality Modeling (November 17, 2004) . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 597

FINAL Charleston, WV 1997 PM2.5 SIP Page xi
Appendix D.5.g: Future Year Electricity Generating Sector Emission Inventory

Development Using the Integrated the Planning Model (IPM®) in Support of Fine

Particle Mass and Visibility in the VISTAS and Midwest RPO Regions (April 2005)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 666

Appendix D.5.h: Inter-RPO IPM Global Parameter Decisions (May 3, 2005)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 710

Appendix D.5.i: Inter-RPO IPM Global Parameter Decisions (May 11, 2005)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 714

Appendix D.5.j: Memorandum from Greg Stella, VISTAS Technical Advisor,

Regarding: EGU Emission Factors and Emission Factor Assignments (June 13, 2005)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 718

Appendix D.5.k: Technical Support Document for VISTAS Emissions and Air Quality

Modeling to Support Regional Haze State Implementation Plans (November 14, 2007)

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D -732

Appendix D.5.l: Technical Memorandum: Control Packet Development and Data

Sources (July 14, 2004) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page D - 1811

Appendix E: Emissions Inventory QAPP . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page E - 1

Appendix F: Emissions Modeling Documentation . . . . . . . . . . . . . . . . . . . . . . . . . Page F - 1

Appendix F.1: Emissions Modeling Documentation . . . . . . . . . . . . . . . . . . . . . . . . Page F - 5

Appendix F.2: Development of Temporal Profiles for Electric Generating Units (EGUs) in

the VISTAS States: Final Technical Memorandum (27 February 2006) . . . . . . . Page F - 15

Appendix F.3: Processing Mobile Emissions in SMOKE: Is it worth simulating everyday

onroad mobile emissions to support 8-hr ozone modeling? . . . . . . . . . . . . . . . . Page F - 203

Appendix F.4: 2002 Fire Emission Inventory for the WRAP Region - Phase II (July 22,

2005) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page F - 227

Appendix G: Meteorological Development Documentation . . . . . . . . . . . . . . . . . . Page G - 1

Appendix G.1: Characterization of Meteorology and Its Relationship to Fine Particle Mass

and Visibility in the VISTAS Region . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page G - 5

FINAL Charleston, WV 1997 PM2.5 SIP Page xii
Appendix G.2: Protocol for Annual MM5 Modeling in Support of VISTAS (Visibility

Improvement – State and Tribal Association) . . . . . . . . . . . . . . . . . . . . . . . . . . . Page G - 327

Appendix H: Model Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page H - 1

Appendix I: Modeling Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page I - 1

Appendix J: Attainment Test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page J - 1

Attainment Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page J - 3

Appendix J.1: Graphical Representations of 2000-2004 Quarterly PM2.5 Component Specific

DVB and 2009 Quarterly Component Specific DVF for Monitors in West Virginia ........

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page J - 83 

Appendix J.2: Procedures for Estimating Future PM2.5 Values for the CAIR Final Rule by

Application of the (Revised) Speciated Modeled Attainment Test (SMAT) Updated- 11/8/04

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page J - 117 

Appendix K: Adopted State Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 1

Appendix K.1: Permitting Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 5

45CSR13 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 7

45CSR 14 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 29

45CSR19 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 79

Appendix K.2: Rules that Require Control of Fugitive Dust . . . . . . . . . . . . . . . Page K - 127

45CSR2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 139

45CSR3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 163

45CSR5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 169

45CSR7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 183

45CSR17 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 201

Appendix K.3: Open Burning Rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 207

45CSR6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 209

Appendix K.4: NOx SIP Call Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 219

45CSR1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 221

45CSR26 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 277

Appendix K.5: CAIR Rules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 321

45CSR39 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 323

45CSR40 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 363

45CSR41 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page K - 413

FINAL Charleston, WV 1997 PM2.5 SIP Page xiii
Appendix L: Contingency Measures Documentation . . . . . . . . . . . . . . . . . . . . . . . . Page L - 1

Contingency Measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page L - 5

1. Enforceability Issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page L - 5

2. Evaluations/Suggested Reductions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page L - 6

3. Identified Contingency Measures for the Charleston Area . . . . . . . . . . . . . Page L - 7

Attachment L.1: FMC (039-0002) Documentation . . . . . . . . . . . . . . . . . . . . . . . . Page L - 19

Attachment L.2: Flexsys (079-0001) Documentation . . . . . . . . . . . . . . . . . . . . . . Page L - 23

Attachment L.3: DuPont (039-0001) SAR Documentation . . . . . . . . . . . . . . . . . . Page L - 29

Attachment L.4: Philip Sporn (053-0001) Documentation . . . . . . . . . . . . . . . . . . Page L - 65

Attachment L.5: Cabot (073-0006) Documentation . . . . . . . . . . . . . . . . . . . . . . . Page L - 73

Attachment L.6: Cytec (073-0003) Documentation . . . . . . . . . . . . . . . . . . . . . . . Page L - 81

Attachment L.7: Emissions in Counties Within 200 km of a Nonattainment Area .........

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page L - 111

Attachment L.8: Area of Influence Methodology . . . . . . . . . . . . . . . . . . . . . . . . Page L - 121

Charleston AoI Plots . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page L - 139

Appendix M: RACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 1

Appendix M.1: EGU RACT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 5

Appendix M.1-1: Federal Consent Decrees . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 119

American Electric Power Service Corp. . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 121

Virginia Electric and Power Company . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 227

Appendix M.1-2: State Consent Orders . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 347

Allegheny Energy - Harrison Power Station . . . . . . . . . . . . . . . . . . . . . . Page M - 349

Allegheny Energy - Pleasants Power Station . . . . . . . . . . . . . . . . . . . . . Page M - 359

Appendix M.2: ICI RACT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 369

Appendix M.3: ICE RACT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 465

Appendix M.4: SAR RACT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page M - 491

FINAL Charleston, WV 1997 PM2.5 SIP Page xiv
Appendix N: ASIP and VISTAS Supporting Documentation . . . . . . . . . . . . . . . . . Page N - 1

Appendix N.1: Documentation of the Base G2 and Best & Final 2002 Base Year, 

2009 and 2018 Emission Inventories for VISTAS . . . . . . . . . . . . . . . . . . . . . . . . . Page N - 5

Appendix N.2: Final Report - Technical Support Document for Association for Southeastern 

Integrated Planning (ASIP) Emissions and Air Quality to Support PM2.5 State

Implementation Plans (March 24, 2009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page N - 343

Appendix N.3: Final Report – Comparison of Particulate Carbon Source Contributions in

the Southeastern U.S. using Photochemical Grid and Receptor Modeling 

(June 30, 2009) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page N - 893

Appendix O: Supporting Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 1

Appendix O.1: LADCO/MRPO Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 5

LADCO Technical Support Document Website . . . . . . . . . . . . . . . . . . . . . . . . Page O - 7

LADCO – Round 5 – 2009 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 13

Regional Air Quality Analyses for Ozone, PM2.5 and Regional Haze: Final Technical

Support Document . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 15

Appendix O.2: EPA CAIR Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 185

CAIR Technical Information Website . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 187

Technical Support Document for the Final Clean Air Interstate Rule - Air Quality

Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page O - 193

Appendix P: RIC Conformity Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page P - 1

Appendix Q: Public Participation Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . Page Q-1

FINAL Charleston, WV 1997 PM2.5 SIP Page xv
Acronyms and Abbreviations

AL Alabama

Antro. Anthropogenic 

AQI Air Quality Index, daily forecast to the public about air quality on

a 24-hour basis

ASIP Association for Southeastern Integrated Planning

BACT best available control technology

BART best available retrofit technology

BCs boundary conditions

Bio. Biogenic

CAAA Clean Air Act Amendments of 1990

CAIR Clean Air Interstate Rule

CAMR Clean Air Mercury Rule

CEN CENRAP

CENRAP Central Regional Air Planning Association

CFR Code of Federal Regulations

CO2 carbon dioxide

CSR Code of State Rules

DAQ WVDEP Division of Air Quality

DEP West Virginia Department of Environmental Protection

EC Elemental carbon

EGU electric generating unit

EPA U.S. Environmental Protection Agency

FL Florida

FR Federal Register

FRM Federal reference method

GA Georgia

KY Kentucky 

LADCO Lake Michigan Air Directors Consortium

LAER lowest achievable emission rate

LRTP Long Range Transportation Plan

lb pound

lb/MMBTU pound per million British thermal units

M-VU MANE-VU

MANE-VU Mid-Atlantic/Northeast Visibility Union

MARAMA Mid-Atlantic Regional Air Management Association

MD Maryland

MMBTU million British thermal units

MMBTU/hr million BTUs per hour

MPO Metropolitan Planning Organization

MRPO Midwest Regional Planning Organization

MS Mississippi

MW megawatt, which equals 1,000,000 watts

FINAL Charleston, WV 1997 PM2.5 SIP Page xvi
MWs megawatts

MY Model Year

N/A not available

N2O nitrous oxide

NAA Nonattainment area

NAAQS National Ambient Air Quality Standard

NACAA National Association of Clean Air Agencies

NARSTO North American Strategy for Tropospheric Ozone. A consortium

for atmospheric research in North America, including the U.S.,

Mexico and Canada.

NC North Carolina

NESCAUM Northeast States for Coordinated Air Use Management

NH3 ammonia

NO nitric oxide

NO2 nitrogen dioxide

nonEGU point sources that are not electrical generating units

NOx oxides of nitrogen; typically, NO and NO2

NSPS New Source Performance Standard

NSR New Source Review

OC Organic carbon

OCM Organic carbon mass

OH Ohio

PBW Particle bound water

PC primary carbon

PM particulate matter

PM10 particulate matter having an aerodynamic diameter or 10 microns

(0.00039 inches) or less

PM10-Primary total mass of PM10 comprising both filterable and condensable

fractions 

PM2.5 particulate matter having an aerodynamic diameter or 2.5 microns

(0.0000975 inches) or less

PM2.5-Primary total mass of PM2.5 comprising both filterable and condensable

fractions 

PM2.5-Secondary PM2.5 created in the atmosphere by the reaction of sulfur dioxide

and nitrogen oxides with other pollutants

PM2.5 Implementation Rule March 29, 2007, Final Rule to Implement the Fine Particle

National Ambient Air Quality Standards (from EPA) 

PSD Prevention of Significant Deterioration

RACM reasonably available control measure

RACT reasonably available control technology

RBLC EPA’s RACT/BACT/LAER Clearinghouse

RFP Reasonable further progress

RIC Regional Intergovernmental Council

RPO regional planning organization

FINAL Charleston, WV 1997 PM2.5 SIP Page xvii
SANDWICH Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbon Hybrid

material balance approach for estimating PM2.5 mass composition

produced by the PM2.5 FRM monitors

SC South Carolina

SESARM Southeastern States Air Resources Managers, Inc.

SIP State Implementation Plan

SMAT Speciated Model Attainment Test

SO2 sulfur dioxide

SO4 sulfate

SOX sulfur oxides

sq. ft. square feet

STN Speciation Trends Network

SUV Sport Utility Vehicle

TIP Transportation Improvement Program

TN Tennessee

TPY tons per year

TSP total suspended particulate

VA Virginia

VISTAS Visibility Improvement State and Territorial Association of the

Southeast

VMT Vehicle miles traveled

VOC Volatile organic compound

WV West Virginia

WVDAQ West Virginia Division of Air Quality

FINAL Charleston, WV 1997 PM2.5 SIP Page xviii
West Virginia

1997 Fine Particle (PM2.5) 

Attainment Demonstration and State Implementation Plan

for the

Charleston, West Virginia Nonattainment Area,

Comprising Kanawha and Putnam Counties 

1.0. INTRODUCTION

The Charleston, WV 1997 PM2.5 nonattainment area is a single-state nonattainment area,

comprising Kanawha and Putnam Counties. The area was designated as nonattainment with the

1997 PM2.5 National Ambient Air Quality Standard (NAAQS) in the January 5, 2005 Federal

Register [70 FR 944], effective April 5, 2005.

1.1. Request

The State of West Virginia is requesting that the United States Environmental Protection Agency

(EPA) approve this attainment demonstration with a projected attainment date of April 2010 as a

revision to the state implementation plan (SIP). The proposed attainment date is within five (5)

years of the date of designation, therefore, pursuant to 40 CFR 51.1009(b) a reasonable further

progress plan is not required. 

1.2. Definition of Fine Particle Matter

Fine particle matter, also known as fine particles and PM2.5, refers to airborne particles less than

or equal to 2.5 micrometers (μm) in diameter, about 1/30th the average width of a human hair.

Fine particles are treated as though they are a single pollutant, however they come from many

different sources and are composed of many different compounds. PM2.5 exposure adversely

affects human health, especially respiratory and cardiovascular systems. Children, people with

heart and lung disease and older adults are particularly sensitive to PM2.5 exposure.

PM2.5 can be liquid, solid or can have a solid core surrounded by liquid. PM2.5 can include

material produced by combustion, photochemical reactions, and can contain salt from sea spray

and soil-like particles. Particles are distinguished based on the method of formation. Primary 

particles are emitted directly into the atmosphere and retain the same chemical composition as

when they are released. Secondary particles are those formed through chemical reactions

involving atmospheric oxygen, water vapor, hydroxyl radicals, nitrates, sulfur dioxide (SO2),

oxides of nitrogen (NOx), and organic gases from natural and anthropogenic sources. PM2.5 can

therefore be composed of varying amounts of different species, including:

FINAL Charleston, WV 1997 PM2.5 SIP Page 1
! Sulfates

! Nitrates (usually found in the form of ammonium nitrate)

! Ammonium

! Particle bound water

! Elemental carbon

! Organic compounds

" Primary organic species (from cooking and combustion)

" Secondary organic compounds

! Crustal material (includes calcium, aluminum, silicon, magnesium and iron)

! Sea salt (generally only found at coastal monitoring sites)

! Transitional metal

! Potassium (generally from wood burning or cooking) 

The most significant sources of PM2.5 and its precursors are coal-fired power plants, industrial

boilers and other combustion sources. These emissions are often transported over large distances.

Other sources of PM2.5 emissions include mobile sources, area sources, biogenic, fires, wind

blown dust and oceans.

Gas-phase precursors SO2, NOx, VOCs and ammonia undergo chemical reactions in the

atmosphere to form secondary PM (see Figure 1.2). Formation of secondary PM depends on

numerous factors including the concentration of precursors; the concentrations of other gaseous

reactive species; atmospheric conditions including solar radiation, temperature and relative

humidity (RH); and the interactions of precursors with pre-existing particles and with cloud or

fog droplets. Several atmospheric aerosol species, such as ammonium nitrate and certain organic

compounds, are semi-volatile and are found in both gas and particle phases. A variety of

meteorological and geographic factors also influence the concentration levels of fine particles,

including both the regional and local distribution of urbanized areas, primary and precursor

emissions sources, and natural features such as oceans and forests. PM2.5 concentrations can

exceed the national ambient air quality standards (NAAQS) at any time of the year. Therefore,

the EPA mandates the year round monitoring of PM2.5 concentrations throughout the country

(40CFR 58, App. D. 4.7).

There were 14 Federal Reference Monitors (FRMs) that sampled PM2.5 in West Virginia, three of

these monitors were located in the Charleston area (See Figure 1.4-1). The FRMs are filter-based

monitors that measure the PM2.5 mass by passing a measured volume of air through a preweighed filter. The purpose of the FRM system is to determine compliance with the PM2.5

NAAQS. Due to budgetary concerns a number of the FRM sites were eliminated, including one

of the monitors in the Charleston area. The FRM monitor at Guthrie was eliminated in the

second quarter of 2007. The Guthrie monitor was co-located with a speciation monitor, which is

still maintained at the site. The Guthrie monitor was never considered the design value monitor,

since it consistently had the lowest readings of the three monitors in the area, and never

monitored a violation of the NAAQS. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 2
Figure 1.2. Chemical links between the ozone and PM formation processes. The major

precursors are shown in green squares. The organic compounds can be gaseous

(always in the gas phase), non-volatile (always in the condensed phase), and

semi-volatile (partitioned between the gas and condensed phase). [Source:

Particulate Matter Science for Policy Makers, A NARSTO Assessment, February

2003.]

1.3. Health and Environmental Effects

The size of particles is directly linked to their potential for causing health problems. Fine

particles less than 2.5 microns in diameter pose the greatest problems because they can lodge

deep in the lungs and some may get into the bloodstream. Therefore, exposure to such particles

can affect both the lungs and heart. Particle pollution may occur all year as opposed to groundlevel ozone, which generally occurs during the summer months. Particle pollution exposure is

linked to a variety of health problems, including increased respiratory symptoms, such as

irritation of the airways, coughing, or difficulty breathing; decreased lung function; aggravated

asthma; development of chronic bronchitis; irregular heartbeat; nonfatal heart attacks; and

premature death in people with heart or lung disease. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 3
Studies have demonstrated a relationship between increased levels of PM2.5 and higher rates of

death and complications from cardiovascular disease. Evidence shows that inhalation of particles

leads to direct vascular injury and atherosclerosis, or hardening of the arteries.

Environmental effects of particle pollution include reduced visibility, environmental damage and

aesthetic damage. PM2.5 is the major cause of reduced visibility (haze) in parts of the United

States, including many of our treasured national parks and wilderness areas. Particles can be

carried over long distances by wind and then settle on ground and water. The effects of this

settling may include making lakes and streams more acidic, changing the nutrient balance in

coastal waters and large river basins, depleting nutrients in soil, damaging sensitive forests and

farm crops, and affecting the diversity of ecosystems. Particle pollution can stain and damage

stone and other materials, including culturally important objects such as statues and monuments.

1.4. The PM2.5 NAAQS

The Clean Air Act (CAA) requires EPA to set National Ambient Area Quality Standards

(NAAQS) for six criteria pollutants, particle pollution (also known as particulate matter (PM)) is

one of these. The CAA established two types of national air quality standards for particulate

matter. Primary standards set limits to protect public health, including the health of “sensitive”

populations, such as asthmatics, children and the elderly. Secondary standards set limits to

protect public welfare, including protection against visibility impairment, damage to animals,

crops, vegetation and buildings. 

The nation’s air quality standards for particulate matter were first established in 1971 and were

not significantly revised until 1987, when EPA changed the indicator of the standards to regulate

inhalable particles less than or equal to 10 microns in diameter (about 1/7th the average width of

a human hair). Ten years later, in 1997, after a lengthy review, EPA revised the PM standards,

setting separate standards for fine particles (PM2.5), equal to or less than 2.5 microns in diameter

(about 1/30th the average width of a human hair), based on their link to serious health problems

ranging from increased symptoms, hospital admissions and emergency room visits for people

with heart and lung disease, to premature death in people with heart or lung disease.

On July 18, 1997, EPA revised the NAAQS for particulate matter and established primary

(health-based) annual and 24-hour standards for PM2.5 [62 FR 38652]. The annual standard is

15.0 micrograms per cubic meter (μg/m3

), based on a 3-year average of annual mean PM2.5

concentrations. The 1997 24-hour standard is 65 μg/m3, based on a 3-year average of the 98th

percentile of 24-hour concentrations. [Percentile is a value on a scale that indicates the percent of

a distribution that is equal to or below it. For example, a concentration value at the 98th percentile

is equal to or greater than 98 percent of the concentration values.] EPA also revised the

secondary standards, making them equal to the primary standards.

The PM2.5 NAAQS were challenged by numerous litigants and in May 1999, the U.S. Court of

Appeals for the D.C. Circuit issued a decision remanding but not vacating, the standards.

American Trucking Assoc. v. EPA, 175 F.3d 1027, 1047-48, on rehearing 195 F.3d 4 (D.C. Cir.

1999). The EPA sought review of two aspects of that decision in the U.S. Supreme Court. The

Supreme Court upheld the PM2.5 standards. EPA v. American Trucking Assoc., 531 U.S. 457

FINAL Charleston, WV 1997 PM2.5 SIP Page 4
(2001). In March 2002, the D.C. Circuit rejected all remaining challenges to the PM2.5 standards,

American Trucking Assoc. v EPA, 283 F.3d 355 (D.C. Cir., 2002). 

The CAA establishes a process for air quality management through the establishment and

implementation of the NAAQS. After the promulgation of a new or revised NAAQS, EPA is

required to designate areas, pursuant to section 107(d)(1) of the CAA, as attainment,

nonattainment or unclassifiable.

On January 5, 2005, EPA issued final rule 40 CFR Part 81 – Air Quality Designations and

Classifications for the Fine Particles (PM2.5) National Ambient Air Quality Standards [70 FR

944], that designated areas across the country for the PM2.5 NAAQS based upon FRM air quality

monitoring data for calendar years 2001-2003. The following areas in West Virginia were

initially designated as nonattainment: 

• Charleston, WV [Kanawha and Putnam Counties]; 

• Huntington-Ashland, WV-KY-OH [Cabell and Wayne Counties, and the Graham Tax

District in Mason County]; 

• Marion County, WV (aka Fairmont CBSA) [Marion County, the Clay Tax District in

Harrison County and the Cass Tax District in Monongalia County]; 

• Martinsburg, WV-Hagerstown, MD [Berkeley County]; 

• Parkersburg-Marietta, WV-OH [Wood County and the Grant Tax District in Pleasants

County];

• Steubenville-Weirton, OH-WV [Brooke and Hancock Counties]; and 

• Wheeling, WV-OH [Marshall and Ohio Counties].

It should be noted that all the areas designated as nonattainment were not in compliance with the

annual standard of 15.0 micrograms per cubic meter (μg/m3

), based on a 3-year average of

annual mean PM2.5 concentrations. However, all areas of West Virginia were found to be

attainment with the co-existing 24-hour standard of 65 μg/m3, based on a 3-year average of the

98th percentile of 24-hour concentrations. The design values for the Charleston nonattainment

area for both the annual and 24-hour standards are presented in Table 1.4. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 5
Table 1.4. Charleston Nonattainment Area Design Values for the 1997 Annual and 24-hr

PM2.5 NAAQS

1997 NAAQS 24 hr 3 yr 98% = 65 1997 Annual NAAQS = 15

FRM

Site

99

-

01

00

-

02

01

-

03

02

-

04

03

-

05

04

-

06

05

-

07

06

-

08

99

-

01

00

-

02

01

-

03

02

-

04

03

-

05

04

-

06

05

-

07

06

-

08

039-

0010

38 36 37 34 34 35 36 34 16.8 16.0 15.5 14.8 15.1 15.0 15.4 14.2

039-

1005

41 40 40 36 36 37 38 36 18.4 17.8 17.1 16.4 16.6 16.4 16.6 15.4

039-

0011

– – – – – 33 31 – – – – – – 13.2 12.2 –

A violation of the annual NAAQS occurs when the annual mean PM2.5 concentration averaged

over three years is greater than 15.0 μg/m3

. This three-year average is termed the design value

for the monitor. The design value for a PM2.5 nonattainment area is the highest monitor’s design

value in the area. A violation of the daily 1997 NAAQS for PM2.5 occurs when the annual 98th

percentile concentration, averaged over three years, is greater than 65 μg/m3.

Reductions in PM2.5 levels which will result in the area attaining the annual PM2.5 standard, will

have the added benefit of lowering the daily monitored values, which will result in a decrease in

the 24-hour design value.

The EPA and State air agencies initiated the monitoring process for the PM2.5 NAAQS in 1999

and deployed the Federal Reference Method (FRM) monitors by January 2001 (see Figure 1-1). 

FINAL Charleston, WV 1997 PM2.5 SIP Page 6
Figure 1.4-1. West Virginia PM2.5 Monitoring Network

EPA based the designations in the January 5, 2005 final rule on air quality monitoring data for

the 3-year period of 2001-2003. Since the designations occurred at the end of 2004, EPA

indicated that they would consider 2004 data where feasible in order to evaluate attainment

status based on data for the 3-year period 2002-2004. EPA explained that they would consider

any complete, quality-assured and certified 2004 PM2.5 data submitted by any State to EPA by

February 22, 2005, if the data indicated that a change in the designation for the entire area would

be appropriate.

In the January 5, 2005 final rule, EPA stated that if EPA agreed that a change in designation was

appropriate based on the inclusion of 2004 data, then EPA would withdraw the initial

designation for the area and issue a designation that reflected the consideration of the new data.

On April 14, 2005, EPA issued final rule 40 CFR Part 81 – Air Quality Designations for the

Fine Particles (PM2.5) National Ambient Air Quality Standards – Supplemental Amendments [70

FR 19844]. In the April 14, 2005 final action EPA withdrew the nonattainment designation for

the Marion County, WV (aka Fairmont CBSA) [Marion County, the Clay Tax District in

Harrison County and the Cass Tax District in Monongalia County] and designated the area as

FINAL Charleston, WV 1997 PM2.5 SIP Page 7
Unclassifiable/ Attainment. [See Figure 1.4-2. Map of WV PM2.5 Nonattainment Areas.] The

PM2.5 standard designations became effective on April 5, 2005, with state implementation plans

due three (3) years later on April 5, 2008.

Figure 1.4-2. Map of West Virginia PM2.5 Nonattainment Areas

States with nonattainment areas are required to submit to EPA by April 5, 2008, an attainment

demonstration with associated air quality modeling, any adopted state regulations to reduce

emissions of PM2.5 and precursors, and other supporting information demonstrating that the area

will attain the standard as expeditiously as practicable, but no later than five (5) years after

designation. EPA will determine the region’s attainment on the basis of air quality data for 2007

- 2009. The West Virginia nonattainment areas, including Charleston, are required to attain the

standard no later than April, 2010.

This document, the West Virginia 1997 Fine Particle (PM2.5) Attainment Demonstration and

State Implementation Plan for the Charleston, West Virginia Nonattainment Area, Comprising

Kanawha and Putnam Counties (Plan), is a plan to demonstrate continued improvement and

compliance with 1997 PM2.5 NAAQS in the Charleston area in 2009. The Plan consists of the

base year inventories for 2002, projection inventories for 2009, an attainment plan, a

demonstration of reasonably available control measures (RACM), including reasonably available

FINAL Charleston, WV 1997 PM2.5 SIP Page 8
control technology (RACT) for point sources, an attainment demonstration, and contingency

plans. 

This Plan has been prepared by the WVDEP in consultation with the Regional Intergovernmental

Council (RIC), the Metropolitan Planning Organization (MPO) responsible for the Charleston

area, to comply with the CAAA of 1990 and with EPA requirements for the Charleston area as

stated in EPA’s 2005 designation of the Charleston area and EPA’s Clean Air Fine Particle

Implementation Rule [72 FR 20586, 25APR2007]. 

1.5. Association for Southeastern Integrated Planning (ASIP)

When EPA promulgated regional haze regulations on July 1, 1999, it offered an optional

approach that groups of states might collaborate in regional analyses of the haze problem. This

option showed promise in allowing more cost-effective analyses and the southeastern states

opted to follow this option. SESARM - Southeastern States Air Resources Managers, Inc. -

accepted responsibility for regional planning organization work tasks on behalf of its member

agencies under this option. The SESARM states – Alabama, Florida, Georgia, Kentucky,

Mississippi, North Carolina, South Carolina and Tennessee – determined that it was appropriate

to expand the collaborative effort for the regional haze program beyond their member boundaries

and invited Virginia and West Virginia to join the group. This effort was named the Visibility

Improvement State and Tribal Association of the Southeast (VISTAS).

In 2005 EPA designated areas in eight (8) of the VISTAS states as nonattainment for PM2.5

and/or 8-hour ozone. 

The nonattainment designations triggered the requirement for State Implementation Plans (SIP)

to be submitted to EPA by April 2008. The guidance from EPA indicated that a significant

requirement of the PM2.5 SIPs will be attainment demonstrations that include modeling analyses

to define control strategies and to confirm attainment.

The VISTAS states concluded that a collaborative process was the most efficient means for the

states to develop information upon which to base their PM2.5 and 8-hour ozone attainment

demonstrations. The local air regulatory agencies for Jefferson County, AL; Jefferson County,

KY; Mecklenburg County, NC; Forsythe County, NC; Knox County, TN; and Shelby County,

TN also joined the collaborative. The name for this collaborative effort is the Association for

Southeastern Integrated Planning (ASIP). ASIP, through its contractors, performed much of the

technical work upon which the Charleston attainment demonstration is based.

FINAL Charleston, WV 1997 PM2.5 SIP Page 9
1.6. Clean Air Act Requirements

Section 172(c) of the Clean Air Act contains the general requirements for nonattainment areas.

These requirements are listed below and are discussed in more detail in Section 8.

Section 172(c) Nonattainment Plan Provisions

(1) Reasonably available control measures (RACM)

(2) Reasonable further progress (RFP)

(3) Actual emissions inventory and periodic emissions inventory

(4) New source review

(5) Permit requirements for new and modified sources

(6) Other measures as may be necessary to provide attainment by specified attainment date

(7) Compliance with Section 110(a)(2)

(8) Equivalent techniques

(9) Contingency measures.

FINAL Charleston, WV 1997 PM2.5 SIP Page 10
2.0. SIGNIFICANCE OF PM2.5 PRECURSOR POLLUTANTS

[40 CFR §51.1002]

2.1. Pollutant Contributions in the Charleston Nonattainment Area

Data from the FRM sites in the Charleston area are displayed below (Figures 2.1-1 and -2).

Table 2.1. contains the quarterly and annual PM2.5 concentrations for the FRM monitors in the

Charleston PM2.5 Nonattainment Area for the three year period used in the nonattainment

designation determination. Table 2.1 presents the 2001-2003 PM2.5 design values for the FRM

monitors based on these quarterly and annual averages. The historic quarterly, yearly and design

value air quality data for the FRM monitors can be found in Appendix A.

Table 2.1. PM2.5 Concentrations and Design Values for the FRM monitors1

 in the

Charleston PM2.5 Nonattainment Area

County FRM

Site

Year 1st

Quarter

2nd

Quarter

3rd

Quarter

4th

Quarter

Annual

Average

Design

Value

Kanawha 54-039-

0010

2001 14.19 17.10 21.00 13.67 16.49

2002 11.76 18.05 21.14 10.59 15.39 15.5

2003 12.74 14.33 20.21 11.15 14.61

Kanawha 54-039-

1005

2001 16.65 16.95 18.02 12.57 16.05

2002 13.08 16.60 20.98 11.81 15.62 15.7

2003 14.50 14.87 20.11 12.11 15.40 1

Note: The Guthrie monitor (54-039-0011) was not installed until 2004.

It was determined that higher PM2.5 concentrations are more likely to occur during the second

and third quarters, or between April and September, with most occurring between June and

September.

FINAL Charleston, WV 1997 PM2.5 SIP Page 11
Figure 2.1-1. 2002 sample data for the Charleston PM2.5 monitor (54-039-0010).

Charleston PM2.5 - 2002 (54-039-0010)

0.05.0

10.015.020.025.030.035.040.045.050.0

1/2/2002 2/2/2002 3/2/2002 4/2/2002 5/2/2002 6/2/2002 7/2/2002 8/2/2002 9/2/2002 10/2/2002 11/2/2002 12

Run Date

PM2.5 Concetration (ug/m3)

FINAL Charleston, WV 1997 PM2.5 SIP 
Figure 2.1-2. 2002 sample data for the South Charleston PM2.5 monitor (54-039-1005).

South Charleston PM2.5 - 2002

(54-039-1005)

0.0

10.020.030.040.050.060.0

1/2/2002

2/2/2002

3/2/2002

4/2/2002

5/2/2002

6/2/2002

7/2/2002

8/2/2002

9/2/2002

10/2/2002

11/2/2002

12

Run Date

PM2.5 Concentration (ug/m3)

FINAL Charleston, WV 1997 PM2.5 SIP 
FRM data was analyzed to determine if there was a seasonal correlation to higher PM2.5 values

(Figures 2.1-3 - 2.1-4).

Figure 2.1-3. Number of samples per quarter in 2002 at the Charleston monitor (54-039-0010)

with PM2.5 concentrations greater than 15μ/m3.

Figure 2.1-4. Number of samples per quarter in 2002 at the South Charleston monitor (54-039-

1005) with PM2.5 concentrations greater than 15μ/m3

.

Charleston PM2.5 Monitor (039-0010)

2002 Samples by Quarter with

PM2.5 Concentrations >15 ug/m3

0

5

10

15

20

25

Q1 Q2 Q3 Q4

2002

Number of Samples

Samples > 15 ug/m3 out of a

total of 113 Samples

South Charleston PM2.5 Monitor (039-1005) 2002 Samples by 

Quarter with PM2.5 Concentrations >15 ug/m3

0

5

10

15

20

25

30

Q1 Q2 Q3 Q4

2002

NUmber of Samples

Samples > 15 ug/m3 out of a

total of 116 Samples

FINAL Charleston, WV 1997 PM2.5 SIP Page 14
2.2. PM2.5 Component Species Analysis

To fully understand the nature of the PM2.5 nonattainment issues in the West Virginia

nonattainment areas, it is important to analyze the percentage contribution of the individual

PM2.5 component species, both from an annual perspective and seasonally throughout the year.

Unfortunately, the FRM monitoring sites only provide a total mass PM2.5 concentration and do

not provide any information concerning the speciated breakdown of the various components. A

separate PM2.5 monitoring network, the Speciated Trends Network (STN), does allow for the

speciation of these components, but the STN PM2.5 concentration data is not directly comparable

to the FRM PM2.5 concentration data due to a slight difference in the monitoring methodology.

This creates an issue in using raw STN PM2.5 data in an attainment demonstration, because it is

not absolutely equivalent to the FRM PM2.5 data on which the nonattainment designation is

based and on which attainment will ultimately be evaluated. 

To address this issue, Neil Frank with the EPA developed an approach to use the raw STN PM2.5

data to appropriately estimate the components of PM2.5 as measured by the FRM monitors. The

approach is termed the “Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbonaceous

material balance approacH” method, or SANDWICH. The SANDWICH approach is discussed

in greater detail in Appendix J.

There were no speciation monitors in West Virginia in 2002, therefore the Speciated Model

Attainment Test (SMAT) (see the ASIP TSD contained in Appendix N.2 for a more detailed

explanation of SMAT) was used to develop speciation profiles for the West Virginia FRM

monitors. Appendix A contains speciation data from the three (3) speciation monitors, one in

South Charleston (54-039-1005), one in Guthrie (54-039-0011) and one in Moundsville (54-051-

1002), that were installed in 2004.

Sources of PM2.5 include all types of combustion activities including motor vehicle emissions,

coal-fired power plants, wood and vegetative burning, and certain industrial processes involving

nitrates and sulfates. EPA uses the SANDWICH method to chemically characterize ambient

PM2.5 speciation data. Figures 2.2-1 and -2 show that a large portion, about 33 - 37%, of annual

averaged PM2.5 composition in the Charleston area consists of ammonium sulfate and ammonium

nitrate, which are products of reactions of ammonia, sulfates and nitrates in the atmosphere in

summer and winter, respectively.

Ammonia from sources such as fertilizer and animal feed operations contribute to the formation

of ammonium sulfates and ammonium nitrates suspended in the atmosphere. The rest originates

from sulfates, carbon and organic compounds from vegetative burning, coal-fired power plants,

geological dust, oil combustion, motor vehicle emissions and diesel emissions. Nitrates usually

originate from vehicle emissions and power generation. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 15
Figure 2.2-1. PM2.5 species contribution in the Charleston area, Charleston monitor (54-039-

0010), based on EPA SMAT data.

Figure 2.2-2. PM2.5 species contribution in the Charleston area, at the South Charleston monitor

(54-039-1005), based on EPA SMAT data.

2000-04 Charleston (Baptist Temple)

PM2.5 Species Percent Contribution

54-039-0010

3% 4%

36%

35%

2%

11%

9%

Crustal

EC

OC

SO4

NO3

NH4

PBW

2000-04 DV = 

15.42 ug/m3

2000-04 South Charleston (Library)

PM2.5 Species Percent Contribution

54-039-1005

3% 4%

42%

31%

2%

10%

8%

Crustal

EC

OC

SO4

NO3

NH4

PBW

2000-04 DV = 

17.11 ug/m3

FINAL Charleston, WV 1997 PM2.5 SIP Page 16
Organic carbon (OC) levels vary across the year (Figures 2.2-3 and -4). A combination of

sources contribute to organic carbon mass, including biogenic, wood burning, vegetative

emissions, and fossil fuel combustion by industrial point sources, on-road vehicles and non-road

engines, and meat cooking. Elevated levels in the winter are likely due to wood burning (from

residential, commercial or industrial wood use, forest fires, prescribed fires, land clearing, or

agricultural burning). Elevated levels in summer are likely due to vegetative carbon emissions.

Contributions from fossil fuel combustion (gasoline and diesel) are greater in urban areas than in

rural areas, but biogenic still dominates.

Ammonium sulfate (SO4) is lowest in the winter and highest in the summer (Figures 2.2-3 and 

-4). Point source SO2 emissions are the predominant precursors of ammonium sulfate.

Ammonium nitrate (NO3) is an insignificant contributor to PM2.5 mass in warmer months and a

somewhat larger contributor in the cooler winter months, but always less important than organic

carbon and ammonium sulfate (Figures 2.2-3 and -4). Ground level (on-road vehicles, non-road

engines, area sources) and point (industrial and electric utility) sources of nitrogen oxides and

agricultural emissions of ammonia are the primary precursors for ammonium nitrate.

Elemental carbon (EC) and fine soil (Crustal) are minor contributors to PM2.5 mass (Figure

Figures 2.2-3 and -4). Fossil fuel combustion and wood burning are the most important

contributors to elemental carbon. Fine soil might be from construction, agricultural activities or

windblown dust.

West Virginia acknowledges that the 2009 projections are modeled projections for 2009 and not

based upon 2009 monitoring data, although we are now in calendar year 2009. Data collection

for 2009 will not be complete until the end of the calendar year, and will not be quality assured

until early 2010.

FINAL Charleston, WV 1997 PM2.5 SIP Page 17
Figure 2.2-3. Charleston (54-039-0010) 2009 DVF Quarterly Speciation projection data based on SMAT tool u

data. Upper left - first quarter (Jan - Mar), Upper right second quarter (Apr - Jun), bottom left - thand bottom right - fourth quarter (Oct - Dec). 

Charleston 2009 DVF Q1

PM2.5 Speciation Percentages

4% 5%

39%

27%

5%

9%

7%

4%

CrustalECOCSO4NO3NH4PBWBlank

2009 Q1 DVF = 

12.12 ug/m3

Charleston 2009 DVF Q2

PM2.5 Speciation Percentages

4% 3%

45%

28%

0%

8%

8%

4%

2009 Q2 DVF = 

13.74 ug/m3

Charleston 2009 DVF Q3

PM2.5 Speciation Percentages

4% 3%

38%

34%

0%

9%

9%

3%

CrustalECOCSO4NO3NH4PBWBlank

2009 Q3 DVF = 

15.73 ug/m3

Charleston 2009 DVF Q4

PM2.5 Speciation Percentages

4% 6%

31%

28%

8%

10%

8%

5%

2009 Q4 DVF = 

11.06 ug/m3

FINAL Charleston, WV 1997 PM2.5 SIP 
Figure 2.2-4. South Charleston (54-039-1005) 2000-2004 DVB Quarterly Speciation data based on SMAT too

speciation data. Upper left - first quarter (Jan - Mar), Upper right second quarter (Apr - Jun), botto(Jul - Sep) and bottom right - fourth quarter (Oct - Dec). 

South Charleston 2000-2004 DVB Q2

PM2.5 Speciation Percentages

3% 3%

43%

30%

0%

9%

9%

3%

2000-2004 Q2 DVB = 

17.28 ug/m3

South Charleston 2000-2004 DVB Q3

PM2.5 Speciation Percentages

3% 2%

34%

38%

0%

11%

10%

2%

CrustalECOCSO4NO3NH4PBWBlank Mass

2000-2004 Q3 DVB = 

21.62 ug/m3

South Charleston 2000-2004 DVB Q1

PM2.5 Speciation Percentages

3% 5%

46%

24%3%

8%

7% 4%

CrustalECOCSO4NO3NH4PBWBlank Mass

2000-2004 Q1 DVB = 

13.95 ug/m3

South Charleston 2000-2004 DVB Q4

PM2.5 Speciation Percentages

3% 6%

40%

25%

6%

9%

7%

4%

2000-2004 Q4 DVB = 

13.61 ug/m3

FINAL Charleston, WV 1997 PM2.5 SIP 
Georgia Tech ran emissions sensitivities in the CMAQ regional air quality model using the

VISTAS 2009 Base D inventory and episodes selected in summer (Jun 1 - Jul 10) and late fall

(Nov 19 - Dec 19) 2002 (Figures 2.2-5 and -6). These model runs indicate that the greatest

reductions in PM2.5 mass would be accomplished by reducing SO2 emissions from electric

utilities and industrial point sources. SO2 reductions in several southeastern states, not just the

Charleston area, would be beneficial in reducing PM2.5 in Charleston.

In both summer and winter the model projects some benefits from reducing local sources of

primary carbon from ground sources and from fire emissions. Because biogenic emissions

dominate Volatile Organic Carbon (VOC) emissions, the model indicates little benefit in winter

and no benefit in summer of reducing anthropogenic VOC emissions.

The model projects very little benefit of reducing emissions of nitrogen oxides from either

ground level or point sources in West Virginia. In the southeast, ammonium nitrate levels are

limited by the availability of ammonia, so reducing ammonia emissions would be a more

effective strategy to reduce ammonium nitrate than reducing nitrogen oxide emissions.

Finally, the model shows that SO2 emissions from outside the ASIP 12 km modeling domain

(labeled as “BC” or boundary conditions in Figures 2.2-5 and -6) have a comparable contribution

to PM2.5 as local sources of primary carbon (PC). These results demonstrate the regional

contribution from SO2 point sources located several states away from Charleston, mostly from

the midwest.

In summary, SO2 reductions from electric utilities and industrial point sources are likely to be

most effective in reducing PM2.5 in the Charleston area. From the mobile sector, reductions of

primary carbon from local sources would be more effective than reductions of either VOC or

NOx.

ASIP inventories and air quality modeling indicate that installation of SO2 controls (scrubbers)

for electric utilities under EPA’s Clean Air Interstate Rule (CAIR) will significantly reduce

PM2.5 levels in the Charleston area by 2009 (figure 2.2-7, see Kanawha - 0010, Kanawha - 1005,

middle and right bars).

FINAL Charleston, WV 1997 PM2.5 SIP Page 20
Figure 2.2-5. CMAQ modeled changes in 2009 PM2.5 mass for the Charleston FRM monitor

from reducing 2002 VISTAS/ASIP Base D emissions by 30% for several

different emissions source categories, for the summer period Jun 1 - Jul 10, 2002.

Figure 2.2-6. CMAQ modeled changes in 2009 PM2.5 mass for the Charleston FRM monitor

from reducing 2002 VISTAS/ASIP Base D emissions by 30% for several

different emissions source categories, for the winter period Nov 19 - Dec 19,

2002.

Charleston, WV (540391005) Summer

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

delta PM 2.5 (microgram/m 3

)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Charleston, WV (540391005) Winter

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

delta PM 2.5 (microgram/m 3

)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

FINAL Charleston, WV 1997 PM2.5 SIP Page 21
Figure 2.2-7. 2002 Monitored Design Values (left) and 2009 base G4 12 km projected DVF (middle) and 2009 

projected DVF (right) for all FRM monitors in West Virginia.

West Virginia 2002 Design Value (Left) and

2009 base G4 12km projected DVF (Middle) and

2009 base G4 36km projected DVF (Right)

02468

101214161820

Berkeley-0003

Brooke-0005

Cabell-0006

Hancock-0011

Hancock-1004

Harrison-0003

Kanawha-0010

Kanawha-1005

Marion-0006

Marshall-1002

Mercer-0002

Monongalia-0003

Ohio-0010

Raleigh-0002

Summers-0001

Wood-1002

West Virginia

ug/m3

FINAL Charleston, WV 1997 PM2.5 SIP 
2.3. Attribution of Emissions Sources

Precursor pollutants to PM2.5 can be emitted directly, such as smoke from a fire, or they can form

as a result of chemical reactions among gases such as SO2, nitrogen dioxide and some organics.

Sources of these precursor pollutants include power plants, gasoline and diesel engines, wood

combustion and high-temperature industrial processes such as smelters and steel mills. Other

sources of PM2.5 precursor pollutants include mobile sources, area sources, biogenic, fires, wind

blown dust and oceans.

The speciated analysis of the PM2.5 concentrations in the Charleston PM2.5 nonattainment area

presented above demonstrates that the OC and SO4 components are the most important portions

of the total PM2.5 mass throughout the year. OC is predominately attributed to biogenic VOC

emissions. SO4 is associated with SO2 emissions. NH4 can have a variety of sources including

both industrial and natural processes. What little NO3 is present in the PM2.5 nonattainment area

throughout the year is attributed to NOx from combustion sources. Of all these components and

associated emission sources, SO4 is the only significant PM2.5 component species found

throughout the year that is attributed to a set of emissions sources that are controllable through

regulatory actions by the West Virginia Division of Air Quality.

When evaluated throughout the Charleston nonattainment area and across West Virginia, SO2 is

primarily from the point source sector. Figure 2.3-1 presents the SO2 emissions from the various

source sectors in the Charleston nonattainment area for 2002. The magnitude of the point source

sector emissions completely overshadows the emissions from all other source categories. When

SO2 emissions by source category are evaluated across West Virginia (Figure 2.3-2), the vertical

scale grows 2.4 times larger than the axis scale used for the nonattainment area SO2 emissions

plot (including West Virginia and Ohio emissions). Again, the magnitude of the point source

sector completely masks the SO2 emissions from all other source sectors. Also note that the

Charleston SO2 point source emissions account for approximately 23% of the state SO2

emissions (Figure 2.3-3) in 2002.

FINAL Charleston, WV 1997 PM2.5 SIP Page 23
Figure 2.3-1. Charleston nonattainment area 2002 SO2 emissions by source sector.

Percent Contribution of SO2 Emissions by Sector in the

Charleston Nonattainment Area in 2002

0

20,000

40,000

60,000

80,000

100,000

120,000

140,000

Point

Sta ti ona ry

Area

Sta tiona ry

NonRoad

Mobile

OnRoad

Mobile

Biogenic

Sector

SO2 Emissions (tons/year)

Charleston

Emissions

97.65%

1.87% 0.18% 0.31% 0.00%

FINAL Charleston, WV 1997 PM2.5 SIP Page 24
Figure 2.3-2. 2002 Statewide West Virginia SO2 emissions by source sector. 

West Virginia SO2 Emissions Total

from VISTAS 2002 Data

0

100,000

200,000

300,000

400,000

500,000

600,000

Point Area NonRoad OnRoad

Tons SO2

FINAL Charleston, WV 1997 PM2.5 SIP Page 25
Figure 2.3-3. Comparison of 2002 total West Virginia SO2 emissions to 2002 SO2 emissions in

the Charleston area. The Charleston SO2 point source emissions account for

approximately 23% of the total state SO2 emissions.

570,153 tons

130,109 tons

0

100,000

200,000

300,000

400,000

500,000

600,000

Point

Sta tiona ry

Area

Sta tiona ry

NonRoad

Mobile

OnRoad

Mobile

Biogenic

West Vi rginia SO2 Total

Cha rles ton  Nona ttainment

Area Portion of WV Total SO2

FINAL Charleston, WV 1997 PM2.5 SIP Page 26
2.4. Identification of Attainment Plan Pollutants and Precursors

The EPA’s Clean Air Fine Particulate Implementation Rule [72 FR 20586, 25APR2007],

commonly referred to as the PM2.5 Implementation Rule, guides states as they develop state

implementation plans in response to annual and/or daily PM2.5 nonattainment. It establishes a

hierarchy of precursor pollutants. The significance of each precursor for PM2.5 has been analyzed

and determined by EPA. Based on EPA’s analyses, direct PM2.5, SO2 and NOx were deemed

significant for all nonattainment areas, while NH3 and other precursors were deemed

insignificant at this time. According to the PM2.5 Implementation Rule, sources of direct PM2.5

and SO2 must be evaluated for control measures in all nonattainment areas. Direct PM2.5

emissions include organic carbon, elemental carbon and crustal material. If emissions of a

precursor contribute significantly to PM2.5 concentrations in the area, then the sources of that

precursor should be evaluated for reasonable control measures. EPA found sulfates and carbon to

be the most significant fractions of PM2.5 mass in all nonattainment areas and, therefore,

concluded that reductions in SO2 will lead to a significant net reduction in PM2.5 concentrations

despite a potential slight increase in nitrates. 

2.4.a. Direct PM2.5 emissions

40CFR §51.1002(c) requires States to identify and evaluate sources of direct PM2.5 emissions

with respect to Reasonable further Progress (RFP) and Reasonably Available Control Measures

(RACM), including Reasonably Available Control Technology (RACT) for stationary sources.

West Virginia addresses RFP and RACM/RACT for direct PM2.5 emissions in Sections 8 and 9.

Tables 2.4.a-1 shows the breakdown by sector of the annual state PM2.5 emissions, and Table

2.4.a-2 shows the breakdown by sector of the PM2.5 emissions in Kanawha and Putnam Counties.

As shown, area sources accounted for 57% of the total state PM2.5 emissions, and 70% of the

PM2.5 emissions in Kanawha and Putnam Counties in 2002; and are projected to account for 65%

of the total state PM2.5 emission in 2009, and 70% of the PM2.5 emissions in Kanawha and

Putnam Counties.

Table 2.4.a-1. West Virginia Annual PM2.5 Emissions 

2002

(tons)

2002

(%)

2009

(tons)

2009

(%) 

Area 24,629 57% 23,903 65%

On-road 995 2% 684 2%

Non-Road 1,728 4% 1,528 4%

Point 15,523 36% 10,578 29%

Anthropogenic 42,875 100% 36,692 100%

Biogenic 0 0% 0 0%

Total 42,875 100% 36,692 100%

FINAL Charleston, WV 1997 PM2.5 SIP Page 27
Table 2.4.a-2. Annual PM2.5 Emissions for Kanawha and Putnam Counties

2002 

(tons)

2002 

(%) 

2009

(tons)

2009

(%) 

Area 2,396 70% 2,339 70%

On-road 169 5% 116 3%

Non-Road 213 6% 191 6%

Point 632 19% 710 21%

Anthropogenic 3,410 100% 3,357 100%

Biogenic 0 0% 0 0%

Total 3,410 100% 3,357 100%

2.4.b. SO2 emissions

Sulfate particles are formed in the atmosphere from sulfur dioxide emissions. Sulfate particles

occur as hydrogen sulfate, H2(SO4), ammonium bisulfate, HNH4SO4, and ammonium sulfate,

(NH4)2SO4, depending on the availability of ammonia, NH3, in the atmosphere. 

40CFR §51.1002(c)(1) requires States to address sulfur dioxide (SO2) as a PM2.5 attainment plan

precursor and evaluate sources of SO2 emissions in the State for control measures. West Virginia

addresses RFP and RACM/RACT for SO2 emissions in Sections 8 and 9.

Tables 2.4.b-1 shows the breakdown by sector of the annual state SO2 emissions, and Table

2.4.b-2 shows the breakdown by sector of the SO2 emissions in Kanawha and Putnam Counties.

As shown, point sources accounted for 97% of the total state SO2 emissions, and 98% of the SO2

emissions in Kanawha and Putnam Counties in 2002; and are projected to account for 96% of the

total state SO2 emission in 2009, and 95% of the SO2 emissions in Kanawha and Putnam

Counties.

FINAL Charleston, WV 1997 PM2.5 SIP Page 28
Table 2.4.b-1. West Virginia Annual SO2 Emissions 

2002

(tons)

2002

(%)

2009

(tons)

2009

(%) 

Area 11,707 2% 12,300 4%

On-road 2,464 0% 279 0%

Non-Road 2,112 0% 359 0%

Point 570,153 97% 324,550 96%

Anthropogenic 586,436 100% 337,488 100%

Biogenic 0 0% 0 0%

Total 586,436 100% 337,488 100%

Table 2.4.b-2. Annual SO2 Emissions for Kanawha and Putnam Counties

2002 

(tons)

2002 

(%) 

2009

(tons)

2009

(%) 

Area 2,486 2% 2,664 5%

On-road 411 0% 47 0%

Non-Road 239 0% 40 0%

Point 130,109 98% 52,095 95%

Anthropogenic 133,245 100% 54,846 100%

Biogenic 0 0% 0 0%

Total 133,245 100% 54,846 100%

2.4.c. NOx emissions

Ammonium nitrate, NH4NO3, is formed in the atmosphere by reaction of ammonia and nitrogen

oxides. In the ASIP region, the southeastern United States, nitrate formation is limited by the

availability of ammonia and by temperature. Ammonia preferentially reacts with sulfur dioxide

and sulfate before reacting with nitrogen oxides. Particle nitrate is formed at lower temperatures;

at elevated temperatures nitrates remain in the gaseous form. For this reason, particle nitrate

levels are very low in the summer and a minor contributor to PM2.5 concentrations. Particle

nitrate concentrations are higher on winter days. Modeling data (see Section 2.2) indicate that in

the ASIP region ammonium nitrate formation is limited by ammonia concentrations and suggest

that for winter days control of ammonia sources would be more effective in reducing ammonium

nitrate levels than control of nitrogen oxides.

FINAL Charleston, WV 1997 PM2.5 SIP Page 29
40CFR §51.1002(c)(2) requires States to address NOx as a PM2.5 attainment plan precursor and

evaluate sources of NOx emissions in the State for control measures, unless the State provides an

appropriate technical demonstration for a specific area showing that NOx emissions from sources

in the State do not significantly contribute to PM2.5 concentrations in the nonattainment area, and

EPA concurs. West Virginia addresses RFP and RACM/RACT for NOx emissions in Sections 8

and 9.

Tables 2.4.c-1 shows the breakdown by sector of the annual state NOx emissions, and Table

2.4.c-2 shows the breakdown by sector of the NOx emissions in Kanawha and Putnam Counties.

As shown, point sources accounted for 72% of the total state NOx emissions, and 79% of the

NOx emissions in Kanawha and Putnam Counties in 2002; and are projected to account for 60%

of the total state SO2 emission in 2009, and 62% of the NOx emissions in Kanawha and Putnam

Counties.

Table 2.4.c-1. West Virginia Annual NOx Emissions 

2002

(tons)

2002

(%)

2009

(tons)

2009

(%) 

Area 13,719 4% 14,384 7%

On-road 58,999 15% 35,635 17%

Non-Road 33,239 9% 30,133 15%

Point 277,589 72% 123,499 60%

Anthropogenic 383,546 99% 203,651 99%

Biogenic 2,776 1% 2,776 1%

Total 386,323 100% 206,427 100%

Table 2.4.c-2. Annual NOx Emissions for Kanawha and Putnam Counties

2002 

(tons)

2002 

(%) 

2009

(tons)

2009

(%) 

Area 1,614 2% 1,654 5%

On-road 10,213 13% 6,147 20%

Non-Road 3,957 5% 3,695 12%

Point 60,138 79% 18,929 62%

Anthropogenic 75,922 100% 30,425 100%

Biogenic 0 0% 0 0%

Total 75,922 100% 30,425 100%

FINAL Charleston, WV 1997 PM2.5 SIP Page 30
2.4.d. VOC emissions

In West Virginia anthropogenic emissions of volatile organic compounds (VOCs) are

overwhelmed by the biogenic emissions of VOCs from vegetation. Anthropogenic VOC 

emissions accounted for 28% of the total VOC emissions in the state in 2002, and are projected

to account for 25% in 2009 (see Table 2.4.d-1). In Kanawha and Putnam Counties,

anthropogenic emissions accounted for 57% of the VOC emissions in 2002, and are projected to

account for 46% of the VOC emissions in 2009 (see Table 2.4.d-2). 

Table 2.4.d-1. West Virginia Annual VOC Emissions 

2002

(tons)

2002

(%)

2009

(tons)

2009

(%) 

Area 62,819 13% 57,472 12%

On-road 42,174 8% 24,843 5%

Non-Road 18,566 4% 18,069 4%

Point 15,775 3% 14,404 3%

Anthropogenic 139,334 28% 114,788 24%

Biogenic 357,850 72% 357,850 76%

Total 497,184 100% 472,638 100%

Table 2.4.d-2. Annual VOC Emissions for Kanawha and Putnam Counties

2002 

(tons)

2002 

(%) 

2009

(tons)

2009

(%) 

Area 9,209 23% 8,382 23%

On-road 7,073 17% 4,168 11%

Non-Road 2,828 7% 2,240 6%

Point 3,292 8% 3,326 9%

Anthropogenic 22,402 55% 18,116 50%

Biogenic 18,301 45% 18,301 50%

Total 40,703 100% 36,417 100%

Sensitivity analyses conducted by Georgia Tech for VISTAS, show that reductions of

anthropogenic emissions of VOC would not result in a significant reduction in PM2.5

concentrations in Hancock County (see Figure 2.4-1 below).

FINAL Charleston, WV 1997 PM2.5 SIP Page 31
Figure 2.4-1. Annual Sensitivities for West Virginia PM2.5 Non-Attainment Areas (VISTAS

Base D emissions, from spreadsheet titled

episode_average_so4+no3+nh4+ec+oc_annual_d1_voc_MODIFIED.xls) 

In addition, pursuant to 40CFR §51.1002(c)(3) the State is not required to address VOC as a

PM2.5 attainment plan precursor and evaluate sources of VOC emissions in the State for control

measures. Therefore, West Virginia is not classifying VOC as an attainment plan precursor, and

is not expending further resources on identifying and controlling VOC sources.

2.4.e. Ammonia emissions

West Virginia does not have a large agricultural industry with correspondingly large ammonia

emissions. West Virginia accounts for 1.9 percent of the ammonia emissions in the ASIP region,

which, as shown in Table 2.4.e-1, is the smallest contribution in the region. North Carolina, with

its large agricultural industry, has ammonia emissions which totaled 173,083 tons in 2002

(26.1%), or 13.9 times West Virginia’s total. 

West Virginia Sensitivities: Annual

-0.45

-0.40

-0.35

-0.30

-0.25

-0.20

-0.15

-0.10

-0.05

0.00

Cabell_WV

Berkeley_WV

Hancock_WV

Jefferson_

OH

Charleston_WV

Marshall_WV

Wood_WV

PM2.5 (

g/m

3

)

BVOC

AVOC

FINAL Charleston, WV 1997 PM2.5 SIP Page 32
Table 2.4.e-1. ASIP Ammonia Emissions

State 2002 NH3 Emissions 

(tons)

State Contribution to Total

(%)

Alabama 66,519 10%

Florida 58,602 9%

Georgia 95,936 14%

Kentucky 57,563 9%

Mississippi 63,929 10%

North Carolina 173,084 26%

South Carolina 36,509 6%

Tennessee 43,258 7%

Virginia 55,570 8%

West Virginia 12,461 2%

Total 663,431 100%

Note: All numbers rounded to the nearest ton or whole percentage point.

Nevertheless, as shown in Table 2.4.e-2, the majority (~80%) of the ammonia emissions in the

state are attributable to the area sources sector, with ~90% of those emissions attributable to

Agricultural Livestock Production. Due to the small size of the agricultural industry in West

Virginia and the relatively small amount of ammonia emitted in the state, the West Virginia

Division of Air Quality (WVDAQ) has determined that controls are not warranted on

agricultural sources. For a more detailed area source emissions inventory see Appendix C.

Table 2.4.e-2. West Virginia Ammonia Emissions

Sector 2002 

(tons)

2002

(%)

2009 

(tons)

2009

(%)

Point 453 4% 686 5%

Area 9,993 81% 10,637 79%

NonRoad 9 0% 11 0%

OnRoad 1,908 15% 2,148 16%

Biogenics 0 0% 0 0%

Total 12,364 100% 13,598 100%

Note: All numbers rounded to the nearest ton or whole percentage point.

FINAL Charleston, WV 1997 PM2.5 SIP Page 33
Further, as shown in Table 2.4.e-3, in 2002 Kanawha and Putnam counties account for only 408

tons of ammonia emissions or approximately 3.3% of the ammonia emissions in the state, with

76% of the ammonia emissions attributable to onroad sources.

Table 2.4.e-3. Ammonia Emissions for Kanawha and Putnam Counties1

Sector 2002 

(tons)

2002

(%)

2009 

(tons)

2009

(%)

Point 25 6% 30 7%

Area 70 17% 68 15%

NonRoad 1 0% 2 0%

OnRoad 312 76% 351 78%

Biogenics N/A N/A N/A N/A

Total 408 100% 451 100%

1

Note: All numbers rounded to the nearest ton or whole percentage point.

In addition, pursuant to 40CFR §51.1002(c)(4) the State is not required to address ammonia as a

PM2.5 attainment plan precursor and evaluate sources of ammonia emissions in the State for

control measures. Therefore, West Virginia is not classifying ammonia as an attainment plan

precursor, and is not expending further resources on identifying and controlling ammonia

sources.

FINAL Charleston, WV 1997 PM2.5 SIP Page 34
2.5. Transportation Conformity

Transportation conformity is a way to ensure that Federal funding and approval are given to

those transportation activities which are consistent with air quality goals. It ensures that these

activities do not worsen air quality or interfere with the "purpose" of the SIP, which is to meet

the National Ambient Air Quality Standards (NAAQS). According to the Clean Air Act,

transportation plans, programs, and projects cannot:

1. Create new NAAQS violations; 

2. Increase the frequency or severity of existing NAAQS violations; or 

3. Delay attainment of the NAAQS. 

EPA finalized its first transportation conformity rule in November 1993 (subsequently codified

in 40 CFR 93, subpart A). States were required to submit related SIP revisions to address the rule

provisions by November 1994. The federal rule underwent a series of revisions over the next

decade and beyond, some of which were prompted by court decisions. States are no longer

required to adopt all of the provisions of the entire federal conformity rule. The three required

SIP elements are:

1. Consultation procedures [40 CFR §93.105]; and

2. Procedures for determining regional transportation-related emissions [40 CFR

§93.122(a)(4)(ii)]; and

3. Enforceability of design concept and scope and project-level mitigation and control

measures [93.125(c)].

The federal requirements apply to areas designated as nonattainment for one or more NAAQS, or

which have been redesignated to attainment with federally approved air quality maintenance

plans. EPA published a direct final approval of West Virginia’s most recent transportation

conformity SIP in the May 2, 2008 Federal Register (73 FR 24175). The SIP includes a series of

Memorandums of Understanding (MOU) which detail the various responsibilities for the several

entities involved in the transportation air quality evaluation and approval process. These include

EPA, the Federal Highways Administration (FHWA), the Federal Transit Authority (FTA), state

departments of transportation (DOT), state air agencies and metropolitan planning organizations

(MPO).

The responsible MPO for the Charleston area is the Regional Intergovernmental Council (RIC).

RIC’s transportation study area includes Kanawha and Putnam Counties, West Virginia. RIC

works closely with WVDOT and maintains a Travel Demand Model (TDM) to simulate future

transportation scenarios and evaluate needs. RIC (or their contractor) performs air quality

analyses for the entire nonattainment area using the latest available planning assumptions and

EPA’s most recent approved emission factor program, MOBILE6.2.

For simplicity, the highway planning process may be separated into two parts: 

The Long Range Transportation Plan (LRTP) - an overall long range transportation network

design and implementation process that typically addresses a 20-30 year time frame; and

FINAL Charleston, WV 1997 PM2.5 SIP Page 35
The Transportation Improvement Program (TIP) - a collection of near-term projects that

typically address project implementation for the first 3-5 years of the LRTP and build toward

realization of the LRTP. 

The TDM simulates future traffic activity, taking into account projects which are expected to be

completed by various analysis years. Outputs from the TDM are then used to develop

appropriate inputs for EPA’s MOBILE6.2 emissions factor model. Finally, the activity and

emissions factors are processed to generate overall emissions estimates by analysis year.

The emission estimates are compared to: 

• a base year; or

• no-build scenario (as if the project(s) were not built); or

• emission budgets.

The last only applies if EPA has approved or has found adequate emissions budgets which have

been submitted as a SIP revision. The appropriate test is determined through the consultation

process contained in the MOU, according to the requirements of the federal conformity rule. For

PM2.5, it possible that the pollutant itself and all its various precursors would require analysis.

However, as noted elsewhere in this document, ammonia and volatile organic compounds –

while recognized as such precursors for PM2.5 – are not considered as significant overall to the

nonattainment problem. Therefore, they are not considered as attainment plan precursors for SIP

development purposes under EPA’s PM2.5 implementation rule. Further, other pollutants/

precursors may be considered significant overall but the highway contribution to those emissions

may be insignificant. In that case, the federal Transportation Conformity rule allows such

pollutants/precursors to be exempt from conformity analysis under certain circumstances.

40CFR93.109(k) Areas with insignificant motor vehicle emissions. Notwithstanding the other

paragraphs in this section, an area is not required to satisfy a regional emissions analysis for §93.118

and/or §93.119 for a given pollutant/precursor and NAAQS, if EPA finds through the adequacy or

approval process that a SIP demonstrates that regional motor vehicle emissions are an insignificant

contributor to the air quality problem for that pollutant/precursor and NAAQS. The SIP would have

to demonstrate that it would be unreasonable to expect that such an area would experience enough

motor vehicle emissions growth in that pollutant/precursor for a NAAQS violation to occur. Such

a finding would be based on a number of factors, including the percentage of motor vehicle emissions

in the context of the total SIP inventory, the current state of air quality as determined by monitoring

data for that NAAQS, the absence of SIP motor vehicle control measures, and historical trends and

future projections of the growth of motor vehicle emissions. . . [emphasis added]

For the reasons outlined below, the DEP is herein making a finding that regional highway

emissions of SO2 are an insignificant contributor to the nonattainment problem for the

Charleston area and are exempt from conformity requirements regarding regional emissions

analysis. The finding will become final if EPA concurs and approves this SIP. The original

proposed SIP had also concluded that highway NOx and direct PM emissions were insignificant

as well. This conclusion was based on the limited ability of NOx to form PM and the relative

contribution to the overall equivalent PM emissions. Adverse comments from EPA indicated that

the agency disagreed with our application of New Source Review interpollutant trading ratios for

NOx. The agency also disagreed with our initial finding that a 3.5% contribution of direct

FINAL Charleston, WV 1997 PM2.5 SIP Page 36
highway PM to the overall direct emissions is insignificant under the conformity rule. The DEP

continues to believe that our results for NOx and direct PM are correct, i.e., we still believe that

these pollutants should be exempt from emissions analysis under 40CFR93.109(k) for the

Charleston area. Notwithstanding that belief, we also recognize that such findings have farranging implications and that the EPA must consider the national ramifications for both

interpollutant trading and significance thresholds. Further, we acknowledge that the

Metropolitan Planning Organization, RIC, would likely prefer definitive emissions budgets to

the uncertainty of our taking a position contrary to EPA guidance. Therefore, we are herein

establishing attainment year (2009) MVEBs for NOx and PM2.5.

2009 PM2.5 Motor Vehicle Emissions Budgets

NOx: 6,147 tons per year

PM2.5: 116 tons per year

With respect to SO2, the regional highway pollutant/precursor emissions constitute a relatively

small fraction of the overall emissions as shown in the table below.

Table 2.5-1. Emission Inventory (Tons/Year)

Category County

2002 2009

NOx PM2.5 SO2 NOx PM2.5 SO2

Area

Kanawha 1,416 1,613 2,214 1,453 1,561 2,370

Putnam 197 783 273 202 779 294

Area Subtotal 1,613 2,396 2,487 1,654 2,339 2,664

NonRoad

Kanawha 3,006 172 177 2,805 158 30

Putnam 951 41 62 890 33 10

NonRoad Subtotal 3,957 213 239 3,695 191 40

OnRoad

Kanawha 8,357 138 336 5,027 95 38

Putnam 1,855 32 75 1,120 22 9

OnRoad Subtotal 10,212 170 411 6,147 116 47

Point

Kanawha 15,405 335 21,807 10,796 344 25,104

Putnam 44,733 297 108,302 8,132 366 26,990

Point Subtotal 60,138 632 130,109 18,929 710 52,095

Totals

Nonattainment Area

Total 75,920 3,411 133,246 30,425 3,357 54,846

% OnRoad/ Total 13.5% 5.0% 0.3% 20.2% 3.5% 0.1%

From the above, it can be readily determined that the maximum highway contribution to SO2 is

significantly less than 1% in the attainment year.

FINAL Charleston, WV 1997 PM2.5 SIP Page 37
Second, air quality monitoring for CY2008 measured the PM2.5 concentration at the Charleston

monitor at 12.9 μg/m3

, and at the South Charleston monitor at 14.2 μg/m3; both these monitored

values are well below 15.0 μg/m3. Although the CY2008 annual averages were below 15.0

μg/m3, the three year design values (2006-2008) were 14.22 and 15.44 μg/m3, respectively. The

graph below shows the general improvement of PM2.5 concentrations from the year 2001 to date.

Fluctuations in design values are common and may be attributed to the year to year variability in

PM2.5. Overall, the fine particulate concentrations have significantly improved since the

beginning of the decade. The area is designated as attainment for all other criteria pollutants.

Figure 2.5-1. Charleston PM2.5 Design Value, 2001-2007

Given the relatively small contribution of the highway emissions to the total SIP inventory,

highway emissions are not likely to contribute significantly to the local PM2.5 mass

concentrations. Among other factors, this is largely due to the dominance of sulfates in the

overall PM mass, coupled with the extremely low contribution of highway sources to those

sulfate totals.

Third, historically there have been no West Virginia SIP requirements for motor vehicle control

measures. Kanawha and Putnam Counties are subject to Transportation Conformity for the 8-

hour ozone standard, with SIP-approved, seasonal budgets for NOx and Volatile Organic

FINAL Charleston, WV 1997 PM2.5 SIP Page 38
Compounds (VOC). Further, the nonattainment area is currently subject to Transportation

Conformity for the 1997 PM2.5 standards. Emissions analysis has been mandatory for annual

highway emissions of direct PM and NOx. Upon a positive adequacy review or approval of this

SIP submittal, analysis of direct PM and NOx will continue under the budget test but no highway

emissions analysis of SO2 will be required. Highway analysis of seasonal ozone precursors

would continue to be mandatory under the federally approved 8-hour ozone maintenance plan.

And, PM2.5 hot-spot analyses would continue to apply for required projects under 40CFR93.116

and 93.123(b) of the Transportation Conformity Rule.

Fourth, as required by the Federal Highways Administration, RIC has extensively researched the

area local historical trends and growth patterns to develop the LRTP and support transportation

conformity evaluations. Based upon that research, there is no reason to expect highway motor

vehicle emissions growth that would lead to a PM2.5 NAAQS violation. RIC has estimated

emissions out, at least, to the calendar year 2035 confirming this. The most recently available,

federally approved transportation air quality conformity analysis for the area took into account

all the regional capacity projects, which are scheduled for implementation through the

transportation plan horizon year. Results are shown below.

Table 2.5-3. Charleston Area PM2.5 Conformity Results

Year NOx,

(tons per year)

% Change

from base

PM2.5

(tons per year)

% Change

from base

2002 11,132.5 NA 186.2 NA

2009 6497.0 -41.6% 120.5 -35.3%

2015 3577.0 -67.9% 73.0 -60.8%

2025 2007.5 -82.0% 65.7 -64.7%

2030 1,788.5 -83.9% 62.1 -66.6%

The forecasts clearly show that, despite any anticipated growth in the area, significant decreases

in highway emissions are expected for all analysis years, for both NOx, and direct PM. The

interim conformity tests do not require evaluation of SO2. However, federal heavy duty diesel

engine standards and low sulfur fuel requirements are also expected to yield substantial emission

decreases commensurate with those shown above. Therefore, the DEP reiterates its conclusion

that highway emissions of SO2 are an insignificant contributor to the nonattainment problem for

the Charleston area and are therefore exempt from regional transportation conformity evaluation

under 40CFR93.109(k).

FINAL Charleston, WV 1997 PM2.5 SIP Page 39
3.0. ATTAINMENT DEMONSTRATION METHODS AND INPUTS

[40 CFR §51.1007]

The attainment modeling for the Charleston PM2.5 nonattainment area was performed in

conjunction with the regional haze modeling being done by the Regional Planning Organization

(RPO) for the southeastern states, Visibility Improvement State and Tribal Association of the

Southeast (VISTAS) and the PM2.5 and ozone (O3) modeling being done by the Associated of

Southeastern Integrated Planning (ASIP). VISTAS and ASIP are run by the ten Southeastern

states (Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina,

Tennessee, Virginia and West Virginia). Since the regional haze and PM2.5 modeling both use

annual simulations and the regional haze modeling includes an intermediate year that is the

attainment year required for the Charleston PM2.5 nonattainment area, the WVDAQ decided to

use the modeling for its attainment demonstration. The sections below outline the methods and

inputs used by VISTAS/ASIP for the regional modeling.

3.1. Analysis Method

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

system. VISTAS/ASIP chose the following modeling system:

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

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

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

studies.

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

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

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

photochemical grid models.

• Air Quality Model: EPA’s Models-3/ Community Multiscale Air Quality (CMAQ)

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

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

for periods up to one year.

Additionally, an historical year is selected to model that represents typical meteorological

conditions in the Southeast when high ozone, high PM2.5 and poor visibility are observed

throughout the region. Once the historical year is selected, meteorological inputs are developed

using the meteorological model. Emissions inventories are also developed for the historical year

and processed through the emissions model. These inputs are used in the air quality model to

predict ozone, PM2.5 and visibility, with the results compared to historical data. The model

performance is evaluated by comparing the model predicted data to the historic air quality data.

The EPA’s 2007 Modeling Guidance recommends modeling an entire year or, at a minimum,

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

conditions that contribute to elevated levels of fine particulate matter. ASIP selected the year

FINAL Charleston, WV 1997 PM2.5 SIP Page 40
2002 as the modeling year for this demonstration. Meteorological inputs were developed for

2002 using the meteorological model. Emissions inventories were also developed for 2002 and

processed through the emissions model. These inputs were then used in the air quality model to

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

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

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

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

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

processed through the emissions model. For this demonstration, the baseline year was 2002,

which corresponds to the historic meteorology used in the modeling. The future attainment year

the WVDAQ is using for this demonstration is 2009, since the mandatory attainment date for the

Charleston PM2.5 nonattainment area is April 5, 2010. The attainment date is set prior to the end

of the 2010 calendar year, therefore, attainment of the NAAQS will be required by the end of

2009. The emissions are processed through the air quality model with the meteorological inputs.

The air quality modeling results are used to determine a relative reduction in future PM2.5, which

is used in the attainment.

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

3.2. Model Selection

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

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

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

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

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

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

verification at no or low cost. 

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

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

system used for this modeling attainment demonstration.

3.2.a. Selection of Photochemical Grid Model

3.2.a.1. Criteria

For a photochemical grid model to qualify as a candidate for use in an attainment demonstration,

a State needs to show that it meets several general criteria: 

• The model has received a scientific peer review,

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

• Databases needed to perform the analysis are available and adequate,

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

toward underestimates or overestimates,

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

FINAL Charleston, WV 1997 PM2.5 SIP Page 41
• 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.

3.2.a.2. Overview of CMAQ

The air quality model selected for this study was CMAQ version 4.5, which was the most recent

release at the point that the attainment modeling exercise started. For more than a decade, the

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

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

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

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

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

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

high performance computing environment. The EPA completed the initial stage of development

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

under the Models-3 framework. 

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

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

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

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

modeling.

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

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

3.2.b. Selection of Meteorological Model

3.2.b.1. Criteria

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

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

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

both the model’s ability to accurately replicate important meteorological phenomena in the

region of study, and the model's ability to interface with the rest of the modeling systems –

particularly the air quality model. With these issues in mind, the following criteria were

established for the meteorological model to be used in this study:

• Non-Hydrostatic Formulation

• Reasonably current, peer reviewed formulation

• Simulates Cloud Physics

• Publicly available at no or low cost

• Output available in I/O API format 

• Supports Four Dimensional Data Assimilation (FDDA)

• Enhanced treatment of Planetary Boundary Layer heights for air quality modeling

FINAL Charleston, WV 1997 PM2.5 SIP Page 42
3.2.b.2. Overview of MM5

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

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

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

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

mesoscale studies. 

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

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

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

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

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

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

different coordinate systems by performing a vertical interpolation, followed by a massconservation re-adjustment. 

Distinct planetary boundary layer (PBL) parameterizations are available for air-quality

applications, both of which represent sub-grid-scale turbulent fluxes of heat, moisture and

momentum. One scheme uses a first-order eddy diffusivity formulation for stable and neutral

environments and a modified first-order scheme for unstable regimes. The other scheme uses a

prognostic equation for the second-order turbulent kinetic energy, while diagnosing the other key

boundary layer terms. 

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

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

analyze standard surface and radiosonde observations, using the National Meteorological

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

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

Results of detailed performance evaluations of the MM5 modeling system in regulatory air

quality application studies have been widely reported in the literature (e.g., Emery et al., 1999;

Tesche et al., 2000, 2003) and many have involved comparisons with other prognostic models

such as the Regional Atmospheric Modeling System (RAMS) and the Systems Application

International Mesoscale Model. MM5 enjoys a far richer application history in regulatory

modeling studies compared with RAMS or other models. Furthermore, in evaluations of these

models in over 60 recent regional scale air quality application studies since 1995, it has generally

been found that the MM5 model tends to produce somewhat better photochemical model inputs

than alternative models.

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

the MM5 model, can be found in the Modeling Protocol (Appendix B).

FINAL Charleston, WV 1997 PM2.5 SIP Page 43
3.2.c. Selection of Emissions Processing System

3.2.c.1. Criteria

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

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

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

system.

• File System Compatibility with the I/O API

• File Portability

• Ability to grid emissions on a Lambert Conformal projection

• Report Capability

• Graphical Analysis Capability

• MOBILE6 Mobile Source Emissions

• Biogenic Emissions Inventory System (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

3.2.c.2. Overview of SMOKE

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

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

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

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

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

mobile sources, SMOKE actually simulates emissions rates based on input mobile-source

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

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

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

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

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

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

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

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

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

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

processing.

FINAL Charleston, WV 1997 PM2.5 SIP Page 44
SMOKE contains a number of major features that make it an attractive component of the

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

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

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

countries and any pollutant can be processed by the system.

For additional information about the SMOKE model please refer to Modeling Protocol

(Appendix B).

3.3. Selection of the Modeling Year

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

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

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

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

Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze (Attainment Modeling

Guidance) identifies specific goals to consider when selecting one or more episodes for use in

demonstrating attainment with the NAAQS. The EPA recommends that episode selection derive

from the following principal criteria:

• Simulate a variety of meteorological conditions;

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

baseline design value or visibility impairment;

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

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

monitor violating the NAAQS is based on multiple days.

VISTAS adopted a logical, stepwise approach in implementing the Attainment Modeling

Guidance in order to identify the most preferable, representative year for modeling. These steps

include the following:

• Representativeness of Meteorological Conditions: The VISTAS meteorological

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

the VISTAS region directly relevant to the evaluation of candidate annual modeling

episodes.

• Initial Episode Typing: At the time of selection in 2003, meteorological and air quality

data were available for 2002 model inputs and model performance evaluation. VISTAS

used Classification and Regression Tree (CART) analyses to evaluate visibility

conditions for 2000, 2001 and 2002, the candidate modeling years. The year 2002 was

found to be representative of conditions in the other two years. Subsequently, these

analyses were repeated with the meteorological and air quality monitoring data for 2000

to 2004 to evaluate how well the 2002 modeling year represented the full 2000-2004

baseline period. This analysis confirmed that visibility and PM2.5 mass in 2002 were

representative of the five-year baseline period for the VISTAS Class I area. This analysis

is discussed in more detail in the project report in Appendix G.

FINAL Charleston, WV 1997 PM2.5 SIP Page 45
• Data Availability: In parallel with the CART analysis, episode characterization analyses,

collaborative investigations by VISTAS states (e.g., NCDAQ, Georgia DNR, FL DEP)

intensively studied the availability of PM2.5, meteorological, and emissions data and

representativeness of alternative baseline modeling periods from a regulatory standpoint.

Additionally, 2002 was a year that EPA required states to provide emissions inventory

data for the Comprehensive Emissions Reporting Rule (CERR). It made sense to use

2002 as the modeling year to take advantage of the 2002 inventory.

• Years to be used by other RPOs: VISTAS also considered what years other RPOs would

be modeling, and several had already chosen calendar year 2002 as the modeling year.

After a lengthy process of integrated studies, the episode selection process culminated in the

selection of calendar year 2002 (January 1 through December 31) as the most current,

representative and pragmatic choice for modeling. All of the EPA criteria for model year

selection were directly considered in this process together with many other considerations (e.g.,

timing of new emissions or aerometric data deliveries by the EPA or the States to the modeling

teams).

3.4. Modeling Domains

3.4.a. Horizontal Modeling Domain

The EPA’s 2007 modeling guidance recommends a 12-km modeling grid resolution for PM2.5

modeling while a 36-km grid resolution is considered acceptable for regional haze. For the

VISTAS modeling, a coarse 36-km grid resolution was used for modeling the entire United

States and a fine 12-km grid was used to model the eastern United States.

The CMAQ model was run in one-way nested grid mode. This allowed the larger outer domains

to feed concentration data to the inner nested domain. Two-way nesting was not considered due

to numerical and computational uncertainty associated with the technique.

The horizontal coarse grid modeling domain boundaries were determined through a national

effort to develop a common grid projection and boundary. A smaller 12-km grid, modeling

domain was selected in an attempt to balance location of areas of interest, such as ozone and fine

particulate matter nonattainment areas, as well as Class 1 and wilderness areas for regional haze. 

Processing time was also a factor in choosing a smaller 12-km grid, modeling domain.

The coarse 36-km horizontal grid domain covers the continental United States. This domain was

used as the outer grid domain for MM5 modeling with the CMAQ domain nested within the

MM5 domain. Figure 3.4-1 shows the MM5 horizontal domain as the outer most, blue grid with

the CMAQ 36-km domain nested in the MM5 domain.

FINAL Charleston, WV 1997 PM2.5 SIP Page 46
Figure 3.4-1. The MM5 horizontal domain is the outer most, blue grid, with the CMAQ 36-km

domain nested in the MM5 domain

To achieve finer spatial resolution in the VISTAS states, a one-way nested high resolution

(12-km grid resolution) was used. Figure 3.4-2 shows the 12-km grid, modeling domain for the

VISTAS region. This is the modeling domain for which the reasonable progress goals are

assessed. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 47
Figure 3.4-2. A more detailed view of the 12-km grid over the VISTAS region

3.4.b. Vertical Modeling Domain

The vertical grid used in the MM5 modeling primarily defines the CMAQ vertical structure. The

MM5 model employed a terrain following coordinate system defined by pressure, using 34

layers that extend from the surface to the 100 mb level. A layer-averaging scheme was used to

generate 19 vertical layers for CMAQ to reduce the computational costs of the CMAQ

simulations. The effects of layer averaging were evaluated in conjunction with the VISTAS

modeling effort and was found to have a relatively minor effect on the model performance

metrics when both the 34 layer and the 19 layer CMAQ models were compared to ambient

monitoring data.

FINAL Charleston, WV 1997 PM2.5 SIP Page 48
4.0. EMISSION INVENTORY

[40 CFR §51.1008]

4.1. Baseline (2002) Emissions Inventory

Clean Air Act Section 172(c)(3) requires that SIPs include a comprehensive, accurate, current

inventory of actual emissions. The PM2.5 Implementation Rule at 40 CFR §51.1008(b) requires

that the base year for this inventory be the most recent calendar year for which a complete

inventory was required to be submitted to EPA pursuant to Subpart A of 40 CFR Part 51. The

pollutants of concern include volatile organic compounds (VOC), nitrogen oxides (NOx), fine

particulate (PM2.5), coarse particulate (PM10), ammonia (NH3) and sulfur dioxide (SO2). 

The Implementation Rule further states that the baseline emissions inventory for calendar year

2002 or other suitable year shall be used for attainment planning and RFP plans for areas initially

designated nonattainment for the PM2.5 NAAQS between 2004-2005. Therefore, an inventory

was developed for the baseline year 2002 by the WV Department of Environmental Protection,

Division of Air Quality (WVDAQ) and provided to VISTAS’ contractor, MACTEC, for further

development. 

MACTEC performed numerous quality assurance procedures on the data. National Emissions

Inventory (NEI) data were compared with previous year’s data to identify missing sources.

When emissions data were reported as daily values or in terms of pounds, conversions were

made to annual estimates in tons so that annual summaries could be compiled. Pollutant codes

were reviewed and standardized to make them compliant with the NEI Input Format (NIF).

Ammonia estimates submitted by states were compared with the 2002 Toxics Release Inventory.

The results of these and other QA procedures were provided to state and local agencies to review

for reasonableness and accuracy. Finally MACTEC took steps to ensure that point source and

area source emissions were properly allocated and not double-counted or omitted. More detailed

discussion of QA procedures can be found in the MACTEC emissions inventory report

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

Inventories for VISTAS” dated March 24, 2009, which is contained in Appendix N.

There are five emissions inventory sectors: stationary point; stationary area; onroad mobile

(highway); nonroad mobile (off-road); and biogenic sources. Stationary point sources include

those sources that emit greater than a specified tonnage per year, for which the data are compiled

at the process level. Electric generating utilities and industrial sources comprise the major

categories for stationary point sources. Stationary area sources (also known as stationary

nonpoint sources) are those sources whose individual emissions are relatively small, but due to

their large number, the collective emissions can be significant (e.g. dry cleaners, service stations,

agricultural sources, fires, etc.). These types of emissions are estimated on a county level.

Onroad mobile sources are sources that use the roadway system. Examples include cars, trucks,

and motorcycles. The emissions from these sources are estimated by vehicle type and road type

and are summed at the county level. Nonroad mobile sources are equipment that can move but

do not use roadways, e.g., lawn mowers, construction equipment, railroad locomotives, aircraft,

etc. The emissions from these sources are also estimated on a county level. Biogenic sources are

the natural sources like trees, crops, grasses and the natural decay of plants. The emissions from

these sources are estimated on a county level as well.

FINAL Charleston, WV 1997 PM2.5 SIP Page 49
The source sector inventories discussed above form the basis for several types of SIP

inventories. The first type is the actual base year inventory. This inventory reflects the base year

emissions that correspond to the meteorological data used in the modeling effort, in this case,

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

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

actual base year. However, for sources that may have significant emissions changes from year to

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

developed for the electric generating units (EGUS) and the wildfire emissions. The air quality

modeling results, using the typical base year inventory, were used to calculate relative reduction

factors for future years. These relative reduction factors for future years were then used to

demonstrate attainment with the NAAQS. Typical year inventories were also used to develop

future year fire inventories.

4.1.a. Stationary Sources

The stationary source sector consists of two main sub-sectors: point and nonpoint sources. In

addition, the point source category is further divided into two subcategories: EGUS and

nonEGUs. These two inventory types are sometimes reported as separate sectors. Nonpoint

sources have historically been known as area sources. 

4.1.a.1. Stationary Point Sources

Point sources are individual facilities having a fixed location. Generally, these sources must have

permits to operate and their emissions are inventoried on a regular schedule. Major sources

emitting at least 100 tons per year (tpy) of a criteria pollutant, 10 tpy of a single hazardous air

pollutant (HAP), or 25 tpy total HAPS are inventoried annually. State agencies are required to

submit annual point source inventories to the EPA by the Consolidated Emissions Reporting

Rule (CERR). MACTEC obtained the West Virginia base 2002 point source inventory from

EPA’s Central Data Exchange (CDX) site located at http://www.epa.gov/cdx/. Various rounds of

quality assurance initiated by VISTAS have resulted in changes from the original data as

submitted to EPA. 

4.1.a.1.A. Electric Generating Units (EGUs)

EGU source emissions comprise the most significant portion of the SO2 and NOX emissions

inventories in WV nonattainment areas as well as state-wide. They vary daily and seasonally as a

function of energy demand and utilization as well as outage schedules. Therefore, a typical base

year inventory was developed to avoid potential anomalies in future year emissions modeling

that might be created by relying on a single year (2002) to represent future operations. This

approach is consistent with EPA’s modeling guidance. 

The 2002 typical year inventories provide the baseline modeled air quality condition at each unit

against which future year (2009 and 2018) modeling runs were compared to develop relative

response factors (RRFs). The 2002 actual EGU emissions data, on the other hand, were used to

evaluate model performance so that the future year modeling could be performed with an

acceptable level of confidence. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 50
To develop a typical year 2002 emissions inventory for EGU sources, each unit’s average

continuous emission monitor (CEM) heat input for 2000 through 2004 was divided by the 2002

actual heat input to generate a unit-specific normalizing factor. This normalizing factor was then

multiplied by the 2002 actual emissions. The heat inputs for the period 2000 through 2004 were

used since the modeling current design values use monitoring data from this same 5-year period.

If a unit was shut down for an entire year during 2000 through 2004, the average of the years the

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

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

Typical year and the actual year 2002 emissions data were compared, for the entire VISTAS

region. Actual 2002 SO2 emissions were about 0.5 percent higher than the typical year

emissions. The differences on a state-by-state basis ranged from actual emissions being 6.6

percent lower in Florida to 10.9 percent higher in Mississippi. For the entire VISTAS region,

actual 2002 NOx emissions were about 0.1 percent lower than the typical year emissions. The

differences on a state-by-state basis ranged from actual emissions being 9.6 percent lower in

Florida to 6.3 percent higher in Mississippi. For West Virginia typical year emissions were about

3.0% and 3.7% lower for SO2 and NOx respectively than actual emissions. 

Differences in EGU emissions values between actual year and typical year are shown in Table

4.1.a.1-1 below. 

Table 4.1.a.1. Comparison of SO2 and NOx Emissions (tons/year) for EGUs from Actual

2002 Inventory and Typical 2002 Inventory 

SO2 Emissions (tons/year) NOx Emissions (tons/year)

State Actual

2002

Typical

2002

Percentage

Difference

Actual

2002

Typical

2002

Percentage

Difference

AL 447828 423736 5.4 161038 154704 3.9

FL 453631 483590 -6.6 257677 282507 -9.6

GA 514952 517633 -0.5 147517 148126 -0.4

KY 484057 495153 -2.3 198817 201928 -1.6

MS 67429 60086 10.9 43135 40433 6.3

NC 477990 478489 -0.1 151854 148812 2

SC 206399 210272 -1.9 88241 88528 -0.3

TN 334151 320146 4.2 157307 152137 3.3

VA 241204 233691 3.1 86886 85081 2.1

WV 516084 500381 3 230977 222437 3.7

Total 3743725 3683968 1.6 1523449 1497864 1.7

FINAL Charleston, WV 1997 PM2.5 SIP Page 51
For purposes of air quality model validation, actual 2002 calendar year emissions for EGU and

fire activity were used within the VISTAS domain. During strategy and future year

emission runs, “typical year” emissions for these categories were processed.

There are two EGU facilities in the Charleston nonattainment area: Appalachian Power’s John

Amos and Kanawha River Plants. MACTEC used CEM data from EPA’S Clean Air Markets

Division (CAMD) to prepare the actual 2002 inventory for SO2 and NOx for VISTAS states.

CEM data can be found at the CAMD Maps and Data web page at

http://camddataandmaps.epa.gov/gdm/. Hourly CAMD emissions were summed and compared

with state and local agency NEI submittals. This review showed that the CAMD and NEI annual

estimates generally agreed. Minor differences were found to be because facility totals in NEI

data contained additional small or emergency units not included in the CAMD database. 

4.1.a.1.B. Other Industrial Point Sources (NonEGUs)

For nonEGU sources, the same inventory was used for both the actual and typical base year

emissions inventories. The nonEGU category uses annual emissions as reported for the NEI for

the year 2002. West Virginia collected only filterable PM emissions during the 2002 inventory

cycle. Therefore, MACTEC augmented the filterable PM data submitted by West Virginia as

well as for four other VISTAS member states to develop primary PM estimates. Detailed

discussion of how PM data were augmented can be found in the MACTEC emissions inventory

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

Emission Inventories for VISTAS” dated March 24, 2009 (Appendix N). MACTEC’s procedures

for PM augmentation were based on EPA documentation found in Appendix C of

Documentation for the Final 1999 National Emissions Inventory {Version 3} for Criteria Air

Pollutants and Ammonia – Point Sources, January 31, 2004, contained in Appendix D.

Through a request from VISTAS, Midwest Regional Planning Organization (MRPO), provided

nonEGU point source data for their states, including Jefferson County, Ohio. MRPO does not

have a public site available. Their website indicates to call Mark Janssen directly for access. The

data were downloaded from http://www.ladco.org/oldsite/tech/emis/index.html. 

4.1.a.2. Stationary Area Sources

Stationary area sources include sources whose individual emissions are relatively small but due

to their large number, their collective emissions can be significant (e.g., combustion of fuels for

heating, structure fires, service stations, etc.). Emissions are estimated by multiplying an

emission factor by some known indicator of collective activity, such as fuel usage, number of

households or population. Stationary area source emissions are estimated at the county level.

West Virginia used 2002 NEI data developed by the EPA as the starting point for the area source

inventory. West Virginia updated estimates for the Residential Fuel/Wood Combustion

categories for coal, distillate oil, natural gas, and wood from the 2002 preliminary NEI file.

These data were posted to EPA’s CDX site and made available to MACTEC. MACTEC’s

general assumption was that unless determined otherwise, the CERR submittals represented full

and complete inventories. Ammonia, several fugitive dust categories, and wildfires were special

cases. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 52
Ammonia (NH3) emissions were estimated using the Carnegie Mellon University (CMU) model.

CMU updated its NH3 Model after EPA published the 2002 NEI. MACTEC used Version 3.6 of

the CMU NH3 model to calculate NH3 emissions for all the VISTAS states. Prior to inclusion of

the CMU model estimates, MACTEC removed any ammonia records for agricultural livestock or

fertilizer emissions from the VISTAS 2002 initial base year inventory. The CMU model version

3.6 was used in large part because it had recently been updated to include the latest (2002)

Census of Agriculture animal population statistics. The CMU model can be found at

http://www.cmu.edu/ammonia/. 

PM2.5 emissions from several fugitive dust source categories were also updated. During the same

time frame that the final VISTAS inventory was being prepared, the Western Regional Air

Partnership (WRAP) and EPA completed their investigation of the overestimation of the PM2.5 /

PM10 ratio in several fugitive dust categories and EPA was in the process of making revisions to

AP-42. Based on data received from EPA, VISTAS revised the PM2.5 emissions from

construction, paved roads and unpaved road sources. PM2.5 emissions were multiplied by 0.67,

0.6, and 0.67 for construction, paved roads and unpaved roads respectively to produce the values

found in the final VISTAS inventory. No changes were made to PM10, only to PM2.5.

For wildfires, a typical year inventory was generated to avoid anomalies in wildfire activity in

2002 compared to longer term averages. Development of a typical year fire inventory provided

the capability of using a comparable data set for both the base year and future years. Thus, fire

emissions would remain the same for air quality modeling in both the base and future years. The

VISTAS Fire Special Interest Work Group, which included representatives for the Federal Land

Managers (FLMs) and EPA, instructed MACTEC to update fire records to ratio the number of

acres burned over a longer time period (three or more years, as available from state records) to

2002 for each fire type. Based on these ratios, the 2002 acreage was scaled up or down to

develop a typical year inventory.

Typical year fire emissions were developed starting from the actual fire acreage data and

emissions calculated for each VISTAS state. State and federal land managers provided West

Virginia wildfire and prescribed burning data to VISTAS contractors.

MACTEC performed several other global changes on the area source inventory. They removed

stage II emissions from the area source sector and included them in the mobile sector of the

inventory. MACTEC also adjusted fugitive dust PM2.5 emissions and added portable fuel

container emissions. More detailed discussion of how the VISTAS contractor processed the area

source sector inventory can be found in the MACTEC emissions inventory report

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

Inventories for VISTAS” dated March 24, 2009 (Appendix N). 

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

categories, except for wildfires. MRPO area source data for Jefferson County, Ohio were

obtained through communication request from VISTAS. MRPO does not have a public site

available. Their website indicates to call Mark Janssen directly for access. The data were

downloaded from http://www.ladco.org/oldsite/tech/emis/index.html.

FINAL Charleston, WV 1997 PM2.5 SIP Page 53
4.1.b. Mobile Sources

The mobile source sector consists of two sub-sectors, often reported as two distinct sectors:

nonroad and onroad. In general, mobile sources consist of fuel-burning sources that do not have

a fixed location. The sub-sectors are discussed in more detail below.

4.1.b.1. NonRoad Mobile Sources

Nonroad (also known as “off-road”) mobile sources include equipment that can move but do not

use the roadway system. Examples include construction equipment, aircraft, railroad

locomotives, lawn and garden equipment. EPA’s NONROAD model was used to develop

emission estimates for the majority of the nonroad mobile source categories. The NONROAD

model takes into consideration regulations affecting emissions from these source categories and

allows the user to change default assumptions by entering data that reflect local conditions. For

the three source categories not included in the NONROAD model, aircraft engines, railroad

locomotives and commercial marine vessels, traditional methods of estimating emissions were

used. Historically, nonroad sector emissions were calculated using methods similar to those of

the area source sector and the two sectors share the same file format for reporting to the NEI. 

The same nonroad inventory was used for both the actual and typical base year emissions

inventories.

WVDAQ staff review of the Preliminary NEI showed 0.0 tons of emissions from the coal mining

equipment category in several counties where coal mining is prevalent. Further investigation

revealed that the reference source for nonroad activity data, County Business Patterns, often

reports numeric ranges rather than as distinct values. When the NONROAD model encounters

ranges, it interprets them as non-numeric and processes them as 0.0 values. In addition to the

tonnage of underground coal production by county, West Virginia also produced alternative

equipment allocation files indicating the number of employees in air transportation by county,

the number of golf courses and country clubs by county, the number of wholesale establishments

by county, the number of employees in logging operations by county, the number of employees

in landscaping services by county, the number of employees in manufacturing operations by

county, the number of employees in oil and gas drilling and extraction operations by county, and

the number of recreational vehicle parks and campgrounds by county. These updated allocation

files were provided to EPA. The release of the final NONROAD2005c model contained the

corrected allocation files and addressed WVDAQ’s concerns. As a result, the entire VISTAS

region was modeled using the default allocation files provided with NONROAD2005c. 

EPA’s update of the nonroad model occurred while the VISTAS nonroad inventory was being

developed. Updating to the NONROAD2005c version necessitated extensive revisions to the

NONROAD input files. These revisions are documented in the MACTEC emissions inventory

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

Emission Inventories for VISTAS” dated March 24, 2009 (Appendix N). 

An initial 2002 base year emissions inventory for aircraft, locomotives, and commercial marine

vessels (CMV) was prepared for VISTAS in early 2004 based on data contained in the 2002

NEI. Preliminary data in the NEI listed all of the CMV river traffic emissions from several West

Virginia, Ohio and Kentucky counties at the Port of Huntington. Emissions were allocated to the

FINAL Charleston, WV 1997 PM2.5 SIP Page 54
respective counties in the West Virginia correction to the NEI. The NEI data also incorrectly

reported residual oil usage for the CMV category, which was also corrected. Therefore, CMV

emission estimates in the West Virginia portion of the Charleston nonattainment area are more

reflective of actual emissions than appeared in the draft NEI.

Revisions to the initial 2002 emissions inventory were implemented to ensure that the latest state

and local data were incorporated as well as to correct an overestimation of PM emissions from

aircraft. Revisions were actually implemented in two stages. An initial set of revisions was

implemented in the fall of 2004. These were followed by a second set of revisions in 2006,

which constitute the final VISTAS inventory. Briefly, MACTEC determined that PM emissions

from airports were significantly overestimated. The contractor undertook extensive procedures to

identify and correct the error in the data. These procedures are discussed in the MACTEC

emissions inventory report “Documentation of the Base G2 and Best & Final 2002 Base Year,

2009 and 2018 Emission Inventories for VISTAS” dated March 24, 2009 (Appendix N). 

4.1.b.2. Onroad Mobile Sources

For onroad vehicles, the VISTAS emissions inventory contractor did not run MOBILE6 directly.

Instead data files consistent with Mobile Emissions Estimation Model Version 6 (MOBILE6)

were developed and provided to the VISTAS modeling contractor. These input data files were

then run during the VISTAS modeling to generate onroad mobile source emissions using

episodic and meteorological specific conditions configured in the sparse matrix operator kernel

emissions modeling system (SMOKE) emissions processor. The MOBILE6 module of the

SMOKE model was used to develop the onroad mobile source emissions estimates for CO, NOx,

NH3, SO2, PM, and VOC emissions. For West Virginia, the speed, vehicle age and vehicle mix

data are all MOBILE 6.2 defaults. The 2002 vehicle miles traveled (VMT) was obtained from

the West Virginia Department of Transportation (WVDOT) and provided to VISTAS along with

West Virginia-specific temperature data. 

Onroad mobile source emissions were produced using selected weeks (seven days) of each

month and using these days as representative of the entire month. This selection criterion allows

for the representation of day-of-the-week variability in the onroad motor vehicles, and models a

representation of the meteorological variability in each month. The modeled weeks were selected

from mid-month, avoiding inclusion of major holidays. 

MRPO onroad mobile emissions data for Jefferson County, Ohio were obtained through

communication request from VISTAS. MRPO does not have a public site available. Their

website indicates to call Mark Janssen directly for access. The data were downloaded from

http://www.ladco.org/oldsite/tech/emis/index.html.

FINAL Charleston, WV 1997 PM2.5 SIP Page 55
4.1.c. Biogenic Emissions Sources

Natural source emissions can make a significant contribution to total VOC and NOx emissions.

Estimating emissions of VOC and NOx from natural sources is an essential part of preparing an

inventory of ozone precursors. 

In the past, the impacts of biogenic VOCS were not considered when ozone control strategies to

limit emissions of either NOx or VOCS were developed. However, the importance of biogenic

VOC emissions in an ozone inventory is apparent when the biogenic VOC emission estimates

are compared to the anthropogenic VOC emission estimates. 

Calendar year 2002 VOC emission estimates for West Virginia statewide were more than

357,000 tons from biogenic sources compared with less than 16,000 tons from point sources and

about 132,000 tons from all anthropogenic sources combined. The biogenic sector accounted for

73% of all VOC emissions in West Virginia. Isoprene, one of the major constituents of biogenic

emissions, is very photoreactive, making biogenic emissions an even more important source of

VOCS. Because of the interaction between NOx and VOCS in terms of atmospheric ozone levels,

biogenic emissions should be included in any inventory which may be used to predict or monitor

atmospheric ozone levels. Inclusion of biogenic emissions is essential for photochemical air

quality modeling.

Biogenic emissions are included here to provide context with anthropogenic emissions. Biogenic

emissions are assumed to stay constant so projections were not made. Brooke and Hancock

County emissions are summarized below.

Table 4.1.c. West Virginia Biogenic Emissions

State Name County Name FIPS NO (tons/year) VOC (tons/year)

West Virginia Kanawha 54039 45 10,230

West Virginia Putnam 54079 49 8,071

West Virginia biogenic data were downloaded from EPA’s CHIEF website at

http://www.epa.gov/ttn/chief/net/2002inventory.html#biogenic. The biogenic emissions data

were copied from the “BEIS3.12 By county” worksheet.

FINAL Charleston, WV 1997 PM2.5 SIP Page 56
4.1.d. Summary 2002 Baseline Emissions Inventory

Table 4.1.d. is a summary of the 2002 baseline emissions inventory for the Charleston

nonattainment area. The complete inventory is contained in Appendix C.

Table 4.1.d. 2002 Base Year Inventory - Charleston Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 25 60,138 1,134 632 130,109 3,292

Area 70 1,614 10,039 2,396 2,486 9,209

Nonroad 1 3,957 229 213 239 2,828

Onroad 312 10,213 233 632 411 7,073

Biogenic N/A 94 N/A N/A N/A 18,301

Total 407 76,016 11,635 3,410 133,245 40,702

4.2. Projected 2009 Emissions Inventories

The inventory for 2009 accounts for post-2002 emission reductions from promulgated and

proposed federal, state, local and site-specific control programs as of July 1, 2004. In general,

emissions inventories were developed for 2009 using current control information in West

Virginia, and growing the 2002 inventory using the Integrated Planning Model (IPM) for EGUS,

EGAS for nonEGUs, and NONROAD2005 and MOBILE6.2 for nonroad and onroad estimates.

4.2.a. Stationary Sources

As noted previously, the stationary source sector consists of two main sub-sectors: point and

nonpoint sources. In addition, the point source category is further divided into two subcategories:

EGUs and all other point source types, or nonEGUs. Nonpoint sources have historically been

known as area sources. 

4.2.a.1. Stationary Point Sources

For EGUs, VISTAS relied primarily on the Integrated Planning Model (IPM) to project future

generation as well as to calculate the impact of future year control programs. For nonEGUs,

VISTAS used growth and control data consistent with the data used in EPA’s Clean Air

Interstate Rule (CAIR) analyses, and supplemented these data with available S/L agency

knowledge of planned emission controls or other changes at specific nonEGUs and updated fuel

use forecast data for the U.S. Department of Energy. For both sectors, VISTAS generated 2009

and 2018 inventories for a combined on-the-books (OTB) and on-the-way (OTW) control

scenario. The OTB/OTW control scenario accounts for post-2002 emission reductions from

promulgated and proposed nonEGU federal control programs as of July 1, 2004; the final CAIR;

FINAL Charleston, WV 1997 PM2.5 SIP Page 57
and state, local, and site-specific control programs as of October 1, 2007.Section 4.2.a.1.a

discusses the EGU projection inventory development, while Section 4.2.a.1.b discusses the

nonEGU projection inventory development.

4.2.a.1.A. Electric Generating Units (EGUs)

VISTAS and the Midwest Regional Planning Organization (MRPO) jointly agreed to work

together to develop future year emissions based on IPM modeling. In August, 2004 VISTAS

and MRPO contracted with ICF Resources, L.L.C., to run IPM to provide utility forecasts for

2009 and 2018 for the electric generating sector of the contiguous United States. 

IPM is EPA’s preferred model for estimating future year emissions from EGUS. IPM is a

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

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

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

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

electric generation and capacity requirements while complying with specified constraints

including air pollution regulations, transmission bottlenecks, and plant specific operational

constraints. The versatility of IPM allows users to specify which constraints to exercise, and to

populate IPM with their own data sets. The EPA also relies on IPM for regulatory purposes. 

The underlying database in this modeling is EPA’s National Electric Energy Data System

(NEEDS) released with the CAIR Notice of Data Availability (NODA). The NEEDS database

contains the existing and planned/committed unit data in EPA modeling applications of IPM.

NEEDS includes basic geographic, operating, air emissions, and other data on these generating

units. VISTAS states and stakeholders provided changes for:

• NOx post-combustion control on existing units

• SO2 scrubbers on existing units

• SO2 emission limitations

• PM controls on existing units

• Summer net dependable capacity

• Heat rate for existing units

• SO2 and NOx control plans based on state rules or enforcement settlements

Although “typical year” projections for 2009 emissions from EGUS were considered, VISTAS

relied primarily on IPM to project future generation as well as to calculate the impact of future

emission control programs. The years 2009 and 2018 were explicitly modeled.

The IPM modeling runs took into consideration both CAIR implementation as well as other state

and local initiatives and incorporated comments provided by MRPO, CENRAP, and MANE-VU

which included any enforceable actions, such as the Illinois Power NSR settlement. WVDAQ

provided the latest information regarding when and where new SO2 and NOx controls are

planned to come online. WVDAQ also reviewed the IPM results to verify that existing controls

and emission rates were properly reflected in the IPM runs. As directed by WVDAQ,

adjustments to the IPM results were made to specific units with new information that became

available as part of the permitting process or other contact with the industry that indicated which

FINAL Charleston, WV 1997 PM2.5 SIP Page 58
units will install controls as a result of CAIR and when these new controls will come online.

MACTEC was requested to correct the control efficiencies as well as the controlled emission

estimates. The requested changes were made and updates are documented in the MACTEC

emissions inventory report “Documentation of the Base G2 and Best & Final 2002 Base Year,

2009 and 2018 Emission Inventories for VISTAS” dated March 24, 2009 (Appendix N). 

To support PM2.5 CAMX modeling of the future year 2009, VISTAS’ other primary contractor,

Alpine Geophysics, obtained and processed an emission inventory for the 5 MRPO states

(Illinois, Indiana, Michigan, Wisconsin, and Ohio). The technical steps that were made as part of

the conversion of the MRPO BaseM EGU files into IDA format for PM2.5 CAMX modeling of

the future year 2009 are documented in Appendix G of the MACTEC emissions inventory report

referenced above. IPM-generated data, were used for the 2009 modeling. MRPO provided 2009

emissions data for PM10, PM2.5, NOx, SO2 and VOC. 

4.2.a.1.B. Other Industrial Point Sources (NonEGUs)

For nonEGUs, MACTEC started with the final 2002 base year inventory and applied updated

growth and control data consistent with methods used in EPA’s CAIR analysis. The contractors

obtained, reviewed, and applied the most current growth factors developed by EPA, based on

forecasts from an updated Regional Economic Models, Inc. (REMI) model (version 5.5) and the

latest Annual Energy Outlook published by the Department of Energy (DOE). “On-the-books”

and “on-the-way,” control assumptions were obtained, reviewed, and applied to the data.

VISTAS provided initial future year emissions projections as Excel spreadsheets to WVDAQ as

well as to the other member state and local agencies for review and comment.

Information from the agencies regarding sources that have shut down after 2002 was

incorporated and the emissions were set to zero in the projection inventories. There were no

shut-downs modeled for the 2009 projected inventory in the Charleston area. Likewise,

information regarding construction of new sources was requested and where applicable, included

in the 2009 nonEGU inventory. No new sources were identified in the Charleston nonattainment

area. [I don’t know of any. Do you]

To support PM2.5 CAMX modeling of the future year 2009, VISTAS’ other primary contractor,

Alpine Geophysics, obtained and processed into SMOKE format an emission inventory for the 5

MRPO states (Illinois, Indiana, Michigan, Wisconsin, and Ohio). Appendix G of the MACTEC

emissions inventory report “Documentation of the Base G2 and Best & Final 2002 Base Year,

2009 and 2018 Emission Inventories for VISTAS” dated March 24, 2009 (Appendix N) details

the technical steps that were made as part of the conversion of the MRPO BaseM nonEGU files

into IDA format for PM2.5 CAMX modeling of the future year 2009.

4.2.a.2. Stationary Area Sources

For area sources, MACTEC used two approaches to develop the 2009 and 2018 projection

inventories. For nonagricultural sources the final version of the VISTAS 2002 inventory was

used. The contractors then back-calculated uncontrolled emissions from the 2002 base year

inventory based on existing controls reported in the 2002 base year inventory. Controls

(including control efficiency, rule effectiveness and rule penetration) provided by the states or

FINAL Charleston, WV 1997 PM2.5 SIP Page 59
originally developed for use in estimating projected emissions for EPA’s Heavy Duty Diesel

(HDD) rule-making and used in the CAIR projections were then used to calculate controlled

emissions. 

Growth factors supplied from the states or EPA’s CAIR emission projections were then applied

to project the controlled emissions to 2009. In some cases EGAS Version 5 growth factors were

used if no growth factor was available from either the states or the CAIR growth factor files. In a

few cases, additional growth factors had to be added for source categories that had not initially

been included in the original inventory. These growth factors were obtained from EGAS 5.0.

Finally updates to growth factors from EGAS 5.0 were made for fuel fired emission sources. The

updated growth factors reflected the most recent data from the Department of Energy’s Annual

Energy Outlook (AEO). These data were used to reflect changes in energy efficiency resulting

from new or updated fuel firing technologies. Area source controls were estimated using known

state-level Stage I controls on gasoline dispensing facilities and open burning estimates. 

The general approach used to calculate projected emissions for agricultural area sources

(predominantly NH3 emission sources) was to use the 2002 base year inventory, which was in

turn based on the CMU (Carnegie Mellon University) Ammonia Model version 3.6. Since the

base year emissions were uncontrolled, and no future controls for these sources were identified,

MACTEC projected the agricultural emissions using state-specific growth if available, otherwise

EPA’s Interstate Air Quality Transport Rule (IAQTR)/Ammonia inventory was used to develop

the growth factors used to project the revised 2002 base year inventory to 2009 or 2018. Since

the IAQTR inventory was only used to construct growth factors rather than using the emissions

directly, no updated growth factors were prepared from the CAIR inventory values.

Fire emissions were recognized to be inadequately represented in previous inventory efforts.

Early in the fire inventory development process, representatives from the Fish and Wildlife

Service (FWS) and the national Forest Service (FS) were invited to participate. As a result of

their collaboration “typical” values were developed to reflect future year fire emissions. 

More detailed discussion of procedures used by VISTAS to prepare the 2009 area source

inventory can be found in the MACTEC emissions inventory report “Documentation of the Base

G2 and Best & Final 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS” dated

March 24, 2009 (Appendix N). 

MRPO area source data for Jefferson County, Ohio were obtained through communication

request from VISTAS. MRPO does not have a public site available. Their website indicates to

call Mark Janssen directly for access. The data were downloaded from

http://www.ladco.org/oldsite/tech/emis/index.html.

4.2.b. Mobile Sources

The general approach for assembling mobile source data was to use as much existing data from

preliminary projections as possible and to supplement them with stakeholder input. Separate

“on-the-books” and “on-the-way” emission forecasts were developed initially for the mobile

source sector. For the final inventories, “on-the-books” and “on-the-way” were defined with the

FINAL Charleston, WV 1997 PM2.5 SIP Page 60
same strategies and therefore, only a single projection scenario was developed for each forecast

year. 

To ensure consistency across evaluation years, the 2009 and 2018 base case inventories were

developed, to the extent practical, using methodologies the same as those employed in

developing the onroad portion of the revised 2002 VISTAS base year inventory. Any

modifications to the 2002 inventory methods were developed in consultation with VISTAS

state/local stakeholders. Generally, modifications were only made to properly account for actual

changes expected in the intervening period (i.e., between 2002 and 2009 and between 2002 and

2018), but the underlying inventory development methodology was identical, except to the

extent requested by VISTAS state/local stakeholders. Although early versions of the inventory

captured Stage II refueling in the area source inventory, Stage II refueling was moved to the onand nonroad sectors in the final version. West Virginia does not require mobile source controls

other than Stage I vapor recovery in five (5) counties: Kanawha, Putnam, Cabell, Wayne and

Wood. The future year emissions for the nonroad mobile sources included in the EPA

NONROAD model were estimated by running the model for each future year. The future year

onroad mobile source inventories were developed by running the MOBILE6 model.

4.2.b.1. Nonroad Mobile Sources

The paragraphs that follow briefly describe the projection process used to develop 2009 and

2018 nonroad projection estimates for source categories found in the NONROAD model and

those source categories estimated outside of the model (locomotives, airplanes and commercial

marine vessels). MACTEC used NONROAD2005 to develop 2009 and 2018 emission estimates

for the source categories covered by the model. All base year revisions were inherently

incorporated into the associated projection year revisions. 

Other specific updates for the projection years for NONROAD model source categories included

revising the emission inventory year in the model (as well as various output file naming

commands) to be reflective of the projection year. The fuel sulfur content for gasoline and diesel

powered equipment was revised. MACTEC also implemented a limited number of local control

program changes (national control program changes are handled internally within the

NONROAD model, so explicit input file changes are not required). The NONROAD2005 model

is capable of handling separate diesel fuel sulfur inputs for land-based and marine-based nonroad

equipment in a single model execution. Therefore, the differential diesel fuel sulfur values were

assembled into a single NONROAD input file. Other than diesel fuel sulfur content and the year

of the projections, there are no differences in the methodology used to estimate emissions from

NONROAD model sources. All equipment population growth and fleet turnover impacts are also

handled internally within the NONROAD model, so that explicit input file changes are not

required.

For the non-NONROAD model source categories, the 2002 base year emissions inventory for

aircraft, locomotives, and commercial marine vessels (CMV) was used to develop emission

projections for 2009 and 2018. The base year inventory used to prepare the emission forecasts

was the latest available at the time of forecast development. All base year revisions described

earlier in this document were inherently incorporated into the associated projection year

revisions.

FINAL Charleston, WV 1997 PM2.5 SIP Page 61
The methodology used to develop the 2009 emissions forecasts for aircraft, locomotives, and

CMV incorporated “On the Books” and “On the Way” controls. Briefly, the methodology relied

on growth and control factors developed from inventories used in support of EPA rule-makings,

and broadly consists of the following steps:

(a) Begin with the 2002 base year emission estimates for aircraft, locomotive, and CMV as

described above (at the state-county-SCC-pollutant level of detail).

(b) Detailed inventory data (both before and after controls) for these same emission sources

for 1996, 2010, 2015, and 2020 were obtained from the EPA’S Clean Air Interstate Rule

(CAIR) Technical Support Document. Using these data, combined growth and control factors

for the period 2002-2009 and 2002-2018 were estimated using straight line interpolation

between 1996 and 2010 (for 2009) and 2015 and 2020 (for 2018). This was done at the statecounty-SCC-pollutant level of detail.

(c) The EPA growth and control data were matched against the 2002 VISTAS base year data

using state-county-SCC-pollutant as the match key. One-to-one matches were not always 

available so MACTEC developed additional processing steps to develop growth and control

factors. The final default growth and control factors were then applied to the 2002 inventory. 

Projection inventories for 2009 and 2018 for sources in the states of Illinois, Indiana, and Ohio

calculated using the NONROAD model were produced using a methodology identical to that

employed to develop the 2002 base year inventory for those states. This method consists of the

extraction of a complete set of county-level input data applicable to each of the three states from

EPA’s NMIM model. This includes appropriate consideration of all non-default NMIM input

files generated by the Midwest Regional Planning Organization as documented earlier in the

discussion of the 2002 base year inventory. These input data were then assembled into

appropriate input files for the Final NONROAD2005 model and emission estimates were

produced using the same procedure employed for the VISTAS region.

Non-Nonroad sector emissions for Jefferson County, Ohio were developed for the MRPO by one

of their contractors, Environ. The document, “LADCO NONROAD EMISSION INVENTORY

PROJECT FOR LOCOMOTIVE, COMMERCIAL MARINE, AND RECREATIONAL MARINE

EMISSION SOURCES,” can be found at http://www.ladco.org/ladco.php?page=141.

4.2.b.2. Onroad Mobile Sources

MACTEC prepared the 2009 initial inventory for onroad mobile sources using methods identical

to those employed for the 2018 preliminary inventories coupled with any revisions provided by

the states during the review of the revised 2002 base year and the 2018 preliminary inventories.

Therefore, as was the case for 2018, MACTEC obtained from the states any input data revisions,

methodological revisions, and local control program specifications (to the extent that they

differed from 2002/2018).

The methodology used to develop the initial 2009 onroad input files was based on forecasting

the previously developed 2002 base year input files and is identical to that used for the 2018

methodology with a few exceptions: 

FINAL Charleston, WV 1997 PM2.5 SIP Page 62
• The evaluation year was updated to 2009; 

• the diesel fuel sulfur was revised from 500ppm in the 2002 inputs to 29 ppm for 2009 and

11 ppm for 2018; 

• diesel sales fractions were updated identically to 2018 except that the diesel sales

fractions for 2003-2009 were set at the same value as those for 2002 (rather than 2003-

2018);

• VMT mix fractions were updated to 2009 using an identical method to that described for

2018; 

• All other input data were retained at 2002 values, except as otherwise instructed by

individual states (see below). This includes all control program descriptions (I/M, ATP,

Stage II, etc.), all other fuel qualities (RVP, oxy content, etc.), all other vehicle

descriptive data (registration age distributions, etc.), and all scenario descriptive data.

MACTEC also considered expected VMT growth, modeling temperature, vehicle registration

mix, vehicle speed by roadway type, VMT mixes (VMT by vehicle type), diesel sales fractions,

state and local fuel standards, vehicle standards, and other local control options. The contractors

obtained from the states any input data revisions, methodological revisions, and local control

program specifications. For the most part, 2002 assumptions were carried forward for the 2009

MOBILE6 runs.

The basic methodology used to generate the 2009 and 2018 VMT for use in estimating onroad

mobile source emissions was that all estimates start from the final VMT estimates used for the

2002 revised base year inventory. Initial 2009 and 2018 VMT estimates were based on linear

growth rates for each state, county, and vehicle type as derived from the VMT data assembled by

EPA for their most recent HDD rule-making. For states that provided no independent forecast

data, which included West Virginia, the estimates were also the final estimates. Diesel sales

fractions were updated identically to 2018 except that the diesel sales fractions for 2003-2009

were set at the same value as those for 2002 (rather than 2003-2018). VMT mix fractions were

updated to 2009 using an identical method to that used for 2018. All other input data were

retained at 2002 values, except as otherwise instructed by individual states. West Virginia

provided revised VMT input data.

For the development of the final VISTAS 2009 and 2018 inventories and input files, VISTAS

states reviewed earlier version inputs, and provided the following corrections, updates and

supplemental data: Adding Stage II refueling emissions calculations to the SMOKE processing;

revised the HDD compliance; and revised Diesel sulfur values in 2009 to 43 ppm. Diesel sulfur

values for 2018 remained at 11 ppm.

More detailed discussion of procedures and assumptions used for running the MOBILE6 and

NONROAD model are documented in the MACTEC emissions inventory report

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

Inventories for VISTAS” dated March 24, 2009 (Appendix N).

MRPO onroad source data for Jefferson County, Ohio were obtained through communication

request from VISTAS. MRPO does not have a public site available. Their website indicates to

call Mark Janssen directly for access. The data were downloaded from

http://www.ladco.org/oldsite/tech/emis/index.html.

FINAL Charleston, WV 1997 PM2.5 SIP Page 63
4.2.c. Biogenic Sources

It was assumed that 2002 biogenic emissions would be unchanged in 2009. Therefore, no growth

factors were applied. 

4.2.d. Summary of Final Inventories for 2009

Table 4.2.d. is a summary of the 2009 emissions inventory for the Charleston nonattainment

area. The complete inventory and discussion of the methodology is contained in Appendices C,

D and N.

Table 4.2.d. 2009 Attainment Year Inventory - Charleston Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 30 18,929 1,281 710 52,095 3,326

Area 68 1,654 10,165 2,339 2,664 8,382

Nonroad 2 3,695 206 191 40 2,240

Onroad 351 6,147 180 116 47 4,168

Biogenic N/A 94 N/A N/A N/A 18,301

Total 450 30,519 11,731 3,357 54,846 36,417

4.3. Summary 2002 and 2009 State-wide Emissions Inventories for West Virginia

State-wide emissions inventory summaries for 2002 and 2009 are shown below to provide

context. Table 4.3-a contains a summary of the 2002 West Virginia state-wide emissions

inventory. Table 4.3-b contains a summary of the 2009 West Virginia state-wide emissions

inventory. 

Table 4.3-a. 2002 State-wide Emissions Inventory Summary for West Virginia

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 453 277,589 22,076 15,523 570,153 15,775

Area 9,993 13,719 119,020 24,629 11,707 62,819

Nonroad 9 33,239 1,850 1,728 2,112 18,566

Onroad 1,908 58,999 1,381 995 2,464 42,174

Biogenic NA 2,776 NA NA NA 357,850

TOTAL 12,364 386,322 144,328 42,875 586,436 497,184

FINAL Charleston, WV 1997 PM2.5 SIP Page 64
Table 4.3.b. 2009 State-wide Emissions Inventory Summary for West Virginia

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 644 123,499 17,539 10,578 324,550 14,404

Area 10,637 14,384 118,365 23,903 12,300 57,472

Nonroad 11 30,133 1,640 1,528 359 18,069

Onroad 2,148 35,635 1,068 684 279 24,843

Biogenic N/A 2,776 N/A N/A N/A 357,850

TOTAL 13,440 206,427 138,612 36,692 337,488 472,639

4.4. Summary 2009 Region-wide Emissions Inventories for the VISTAS States

The following bar charts show expected decreases in emissions of SO2 and NOx across the

VISTAS states from 2002 through 2018. Note that for SO2 emissions in particular, which are the

largest contributor to haze and to PM2.5, emissions from electric generating facilities are expected

to decrease dramatically (70%) between 2002 and 2018, with SO2 reductions of 83% from

EGUS in West Virginia. However, even after implementation of CAIR, EGU emissions are

projected to remain the largest contributor to haze, comprising more than half of the remaining

SO2 emissions in every state.

Figure 4.4-a. Annual SO2 emissions for 2002, 2009, and 2018 in the VISTAS states.

FINAL Charleston, WV 1997 PM2.5 SIP Page 65
Figure 4.4-b. Annual NOx emissions in 2002, 2009 and 2018 in the VISTAS states.

FINAL Charleston, WV 1997 PM2.5 SIP Page 66
5.0. MODEL PERFORMANCE EVALUATION

The focus of the model performance evaluation is on PM2.5 and its component species in the

urban and PM2.5 nonattainment areas (NAAs). However, the evaluation of the CMAQ 2002 Base

G2 base case simulation was also performed for PM species and visibility primarily at Class I

areas as part of the VISTAS regional haze assessment. The VISTAS model evaluation focused

on the performance of PM component species and visibility at more rural (e.g., IMPROVE)

monitors. ASIP also performed an urban ozone evaluation performance as part of the

development of the southeastern states 8-hour ozone SIPs that were due in June 2007. The

VISTAS regional PM components and visibility and ASIP urban ozone model performance

evaluations are directly relevant to the ASIP PM2.5 evaluation as they share many of the same

precursor and product species and atmospheric processes that produce elevated PM2.5 levels in

the urban and NAAs. The Model Performance Evaluation is contained in Appendix N.2 – 

Technical Support Document for Association for Southeastern Integrated Planning (ASIP)

Emissions and Air Quality Modeling to Support PM2.5 State Implementation Plans (ASIP TSD)

and provides details on the ASIP urban and NAAs PM2.5 mass and PM2.5 component species

model performance evaluation for each ASIP state, the results for West Virginia are summarized

in Section 5.3 below. The Model Performance Evaluation also provides a qualitative evaluation

of the CMAQ base case for PM2.5 components and total mass. [Note: the Model Performance

Evaluation is contained in Chapter 3 of the ASIP TSD, an ENVIRON Report by Ralph Morris,

which is contained in Appendix N.2

In the VISTAS modeling performance evaluation, the CMAQ results were compared with

observational data from the Interagency Monitoring of PROtected Visual Environments

(IMPROVE), Speciated Trends Network (STN), Clean Air Status Trends Network (CASTNet),

Federal Reference Method (FRM) PM2.5 mass, National Acid Deposition Program (NADP) and

South East Aerosol Research and CHaracterization (SEARCH) study monitoring networks. The

VISTAS evaluation focuses primarily on the operational model evaluation of the air quality

model’s performance with respect to individual components of fine particulate matter (PM2.5), as

good model performance of the PM component species will dictate good model performance of

total or reconstituted fine particulate matter from which visibility is based. The FRM network

only collects total PM2.5 mass and so is not as relevant for judging how well the model is

predicting the components of light extinction so was not stressed in the VISTAS evaluation,

however it is an important component of the ASIP PM2.5 evaluation. VISTAS also performed a

diagnostic evaluation analyzing the ability of the model to reproduce gaseous PM precursor (e.g.,

SO2 and NOx) and product (e.g., HNO3) species.

The ASIP model performance evaluation focused on ozone and PM2.5 performance in urban and

nonattainment areas (NAAs). The ASIP ozone model performance evaluation can be found at:

http://pah.cert.ucr.edu/vistas/vistas2/evaluation_results/2002ga2a.mpe/

The ASIP PM2.5 evaluation is summarized in Sections 3.5 and 3.6 of the ASIP TSD with more

details provided in Appendices B and C of the ASIP TSD. In addition, the full display of ASIP

and VISTAS model evaluation products is available on the project website at:

http://pah.cert.ucr.edu/vistas/vistas2/mpe2.shtml

FINAL Charleston, WV 1997 PM2.5 SIP Page 67
A ground-level model evaluation database for 2002 was compiled by the modeling team using

several routine and research-grade databases. The focus of the VISTAS evaluation of the

CMAQ model was on the PM components that can cause visibility impairment, whereas the

ASIP model performance evaluation focus were on PM2.5 mass and its components. The primary

monitoring networks available to evaluate this component of the CMAQ are: 

• Interagency Monitoring of Protected Visual Environments (IMPROVE);

• Clean Air Status and Trends Network (CASTNET); 

• Southeastern Aerosol Research and Characterization (SEARCH); 

• EPA Federal Reference Method (FRM) PM2.5 and PM10 Mass Networks (EPA-FRM);

• EPA Speciation Trends Network (STN) of PM2.5 species; and 

• National Acid Deposition Network (NADP). 

These PM monitoring networks may also provide ozone and other gas phase precursors and

product species, and visibility measurements at some sites. There are also gas-phase criteria

pollutant measures from the EPA’s Air Quality System (AQS) that were used for the urban

ozone evaluation that is discussed elsewhere

(http://pah.cert.ucr.edu/vistas/vistas2/evaluation_results/2002ga2a.mpe/). Figure 5-1 shows the

locations of the monitoring sites for the IMPROVE, STN, CASTNet, NADP and SEARCH

monitoring networks use in the VISTAS and ASIP model evaluation.

FINAL Charleston, WV 1997 PM2.5 SIP Page 68
Figure 5-1. IMPROVE, STN, CASTNet, NADP and SEARCH monitoring sites located in the

VISTAS/ASIP region and the VISTAS/ASIP 12 km grid. 

5.1. Model Performance Goals, Criteria and Results

To quantify model performance, several statistical measures were calculated and evaluated for

all the IMPROVE, STN, CASTNet, SEARCH, FRM and NADP monitors within the

VISTAS/ASIP region or VISTAS/ASIP 12 km domain, individually for each monitor and

individually for each VISTAS/ASIP state. The statistical measures selected were based on the

recommendations outlined in section 18.4 of the EPA’s Guidance On The Use Of Models And

Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and

Regional Haze.

In 2004, VISTAS established model performance goals and criteria for components of fine

particle mass based on previous model performance for ozone and fine particles (see Table 5.1). 

EPA modeling guidance for fine particulate matter at the time noted that PM models might not

be able to achieve the same level of performance as ozone models. The VISTAS and ASIP

model performance evaluation considered several statistical performance measures and displays. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 69
Fractional bias and fractional gross error were selected as the most appropriate metrics to

summarize model performance; other metrics were also calculated and are included in the full

model performance evaluation (see Appendices H and N).

Table 5.1. VISTAS/ASIP Model Performance Goals and Criteria for Components of

Fine Particle Mass

Fractional

Bias

Fractional

Error

Comment

#±15% #±35% Goal for PM model performance based on ozone model

performance, considered excellent performance

#±30% #±50% Goal to PM model performance, considered good performance

#±60% #±75% Criteria for PM model performance, considered average

performance. Exceeding this level of performance indicates

fundamental concerns with the modeling system and triggers

diagnostic evaluation.

Several graphic displays of model performance were prepared including:

1. Scatter plots of predicted and observed concentrations and deposition by species,

monitoring network and month;

2. Time series plots of predicted and observed concentrations and deposition by species,

monitoring site and month;

3. Spatially averaged time series plots;

4. Time series plots of monthly fractional bias and error for a species, region and network;

5. Performance goal plots (“soccer plots”) that summarize model performance by species,

region and season; and

6. Concentration performance plots (“bugle plots”) that display fractional bias or error as a

function of concentration by species, region, monitoring network and month

The “soccer plots” and “bugle plots” are relatively new tools in model performance evaluations,

and have recently been included as model performance evaluation displays in the EPA’s 2007

modeling guidance for Ozone, PM2.5 and Regional Haze. Both “soccer plots” and “bugle plots”

are convenient ways to examine model performance with respect to set goals and criteria. The

bugle plots have the added benefit of adjusting the goals and criteria to consider the

concentration of the species. Analysis of “bugle plots” generally suggests that greater emphasis

should be placed on performance of those components with the greatest contribution to PM mass

and visibility impairment (e.g. sulfate and organic carbon) and that greater bias and error could

be accepted for components with smaller contributions to total PM mas (e.g. elemental carbon,

nitrate and soil). 

Details on the regional model performance evaluation for PM across the VISTAS/ASIP region

36/12 km grid are provided in Chapter 3 and Appendix B of the VISTAS Technical Support

Document that can be found at http://pah.cert.ucr.edu/vistas/vistas2/docs.shtml [also see

Appendix N].

FINAL Charleston, WV 1997 PM2.5 SIP Page 70
5.2. VISTAS/ASIP Domain-wide Performance

As a summary of model performance, soccer and bugle plots for the all of the VISTAS STN and

FRM monitors are included here. Plots have been developed for the average monthly

concentrations and the performance statistics for all of the PM2.5 component species (SO4, NO3,

NH4, OC, and EC) and reconstructed PM2.5 total mass from the STN monitoring sites (Figures

5.2-1 and 5.2-2), as well as the total FRM PM2.5 mass (Figures 5.2-3 and 5.2-4).

The soccer plots for monthly average component performance for all the VISTAS/ASIP STN

sites shows generally good model performance for most species of PM2.5 and total PM2.5. The

exception is the prediction of NO3 values, which most values fall outside the criteria goal (Figure

5.2-1). There are a few months that fall on the criteria level goal, which is better seen in the

zoomed view presented in the image on the right in Figure 5.2-2. However, when the very low

concentration of NO3 is taken into consideration, as presented in the bugle plots (Figures 5.2-2

and 5.2-4), NO3 performance largely falls within the criteria and goal model performance lines. 

One can still note a general tendency for under prediction in NO3, and other species in right hand

image in Figure 5.2-3, which leads to a slight under prediction in total reconstructed PM2.5.

Monthly total PM2.5 concentration performance at all the VISTAS/ASIP FRM monitors largely

falls within goal level thresholds, with only two months falling just outside goal level

performance (Figure 5.2-3). Figure 5.2-4 suggests a slight negative bias in PM2.5 prediction for

most of the year, with mean fractional error values remaining within goal levels across the year.

Figure 5.2-1. VISTAS STN Soccer Plots

The image on the left is a soccer plot depicting both the mean fractional error and

fractional bias for component concentration for all VISTAS STN monitoring sites. The

image on the right is a zoomed view of the soccer plot on the left to better depict the

area inside the criteria/goal lines. Each point represents a monthly value as compared

to the model performance criteria (red box) and modeling performance goals (green

box).

FINAL Charleston, WV 1997 PM2.5 SIP Page 71
Figure 5.2-2. VISTAS STN Bugle Plots

The image on the left is a bugle plot of the mean fraction bias for particulate matter

and its component concentrations for all VISTAS STN monitoring sites. The image on

the right is a bugle plot of mean fraction error for particulate matter and its

component species for all VISTAS STN monitoring sites. Each point represents a

monthly mean fraction bias value as compared to the model performance criteria (red

lines) and modeling performance goals (green lines).

Figure 5.2-3. VISTAS FRM Soccer Plots

Soccer plots depicting both the mean fractional error and fractional bias for

component concentration for all the VISTAS FRM Monitoring sites. The image on the

right is a zoomed view of the soccer plot on the left to better depict the area inside the

criteria/goal lines. Each point represents a monthly value as compared to the model

performance criteria (red box) and modeling performance goals (green box).

FINAL Charleston, WV 1997 PM2.5 SIP Page 72
Figure 5.2-4. VISTAS FRM Bugle Plots

The image on the left is a bugle plot of the mean fraction bias for particulate matter

and its component species concentrations for all the VISTAS FRM Monitoring sites. 

The image on the right is a bugle plot of mean fraction error for particulate matter and

its component species for all the VISTAS FRM Monitoring sites. Each point represents

a monthly mean fraction bias value as compared to the model performance criteria

(red lines) and modeling performance goals (green lines).

Overall, the general tendency for the model to have some difficulty in predicting NO3, as the

monthly average values tend to fall outside the criteria goals for performance in the soccer plots. 

Part of this under prediction lies in the fact that NO3 are generally found in low concentration

across the southeast, and the model generally has difficulties represented any compound with

low atmospheric concentrations. The bugle plots are more encouraging with NO3 performance,

as these plots take into consideration the concentration of the component when evaluating

performance. The bugle plots show all components and total PM2.5 falling within criteria levels,

if not goals levels, of model performance. The weaker performance of NO3 accounts for the

slight negative bias in the both the total reconstructed PM2.5 mass from STN sites as well as FRM

total PM2.5 data.

5.3. West Virginia PM2.5 Model Performance

There were no speciated PM2.5 STN monitoring sites within West Virginia during the 2002

modeling year, so the PM2.5 model evaluation is limited to the 16 FRM PM2.5 mass monitoring

sites. In January, April and July, CMAQ underestimates PM2.5 mass across the FRM sites in

West Virginia by approximately -30%, -25% and -40% and achieves the PM performance goal in

January and April, but not July (Figure 5.3-1). In October the model has near zero bias and 32%

error so achieves the ozone model performance goal. The Soccer Plot in Figure 5.3-2 below

summarizes the FRM PM2.5 mass performance in West Virginia in each month. Nine of the

months achieve the PM performance goal, with the winter months even achieving or nearly

achieving the ozone model performance goal. As seen for the other states, the underprediction

bias during the May-July summer months results in the bias falling outside of the PM

performance goal, but within the PM performance criteria.

FINAL Charleston, WV 1997 PM2.5 SIP Page 73
Figure 5.3-1. Scatter plots of predicted and observed fine particulate mass (PM2.5)

concentrations for January, April, July and October 2002, FRM sites in West

Virginia and the CMAQ 2002 36 and 12 km Base G2 Actual base case

simulation.

FINAL Charleston, WV 1997 PM2.5 SIP Page 74
Figure 5.3-2. Soccer plot of monthly fractional bias versus fractional gross error for PM2.5 mass

at FRM monitors in West Virginia for the CMAQ 12 km Base G2 Actual base

case simulation.

FINAL Charleston, WV 1997 PM2.5 SIP Page 75
5.4. Conclusions of Model Performance Evaluation

The quarterly average CMAQ PM2.5 component species results near the FRM monitors are used

in the Speciated Model Attainment Test (SMAT) to project the current year PM2.5 Design Values

to the 2009 future year for comparison with the PM2.5 NAAQS. SMAT uses the relative changes

CMAQ 2002 and 2009 modeling results to scale each of the PM2.5 components of the current

year PM2.5 Design Values. These model derived scaling factors are referred to as Relative

Response Factors (RRFs). The results of the SMAT PM2.5 Design Value projections for FRM

monitoring sites in and near the ASIP states are presented in Chapter 4 of the ASIP TSD (see

Appendix N.2) . The results indicate that most of the reductions in the PM2.5 Design Values

between 2002 and 2009 are due to reductions in sulfate concentrations. Thus, performance of

the model for sulfate is of most importance in the model performance evaluation.

The implications of the major findings in the ASIP model performance evaluation are discussed

below in the context of the modeling results used to project future year PM2.5 attainment through

SMAT.

• Nitrate Underprediction Tendency: NO3 is routinely underpredicted during the summer

and adjacent months throughout the ASIP region. This underprediction is due to

modeled NOx concentrations near zero, when observed values are low, but above zero

(typically < 1 μg/m3). However, NO3 is almost always a very minor to insignificant

contributor to total PM2.5 mass at FRM monitors in the ASIP region (see stacked bar

charts in Chapter 4). In fact, the maximum NO3 contribution to a 2009 projected PM2.5

Design Value is 1.0 μg/m3with a median value of 0.2 μg/m3. Thus, the NO3 performance

issues are not considered significant in the PM2.5 projections.

• OCM Underpredictions: The organic carbon mass (OCM) underprediction bias is a

cause for concern since it is a major component of the PM2.5 mass at ASIP FRM

monitoring sites with maximum contributions to the 2009 PM2.5 Design Values of ~8

μg/m3

, minimum values of ~3 μg/m3 and a median value of ~4 μg/m3. The reasons for the

underestimation of OCM are unclear, but the fact that the underpredictions are higher in

the urban than rural areas suggest that there may be missing anthropogenic emission

sources, or possibly the urban OCM emissions are over diluted across the 12 km grid

resolution used in the ASIP modeling. The changes in projected OCM concentrations

between the current and projected PM2.5 Design Values are mostly less than 5% (i.e., 0.95

< RRFOCM < 1.05). Thus, the changes in OCM between the current and future year are

having a minor influence on the projected PM2.5 Design Values.

• EC Performance Issues: The EC underprediction bias at the urban sites is partly due to

over dilution of the urban EC emissions due to the coarse (12 km) grid used. For the

most part, the CMAQ model performed well for EC and the underprediction would not

affect the relative changes in the model response to anthropogenic EC emissions changes. 

Therefore, any EC performance issues are not a cause for concern, although the model

performance for EC was generally good.

FINAL Charleston, WV 1997 PM2.5 SIP Page 76
• Sulfate Underprediction Bias: Although SO4 is performing well, it does have an

underprediction bias that is largest in the summer months. But this underprediction is not

severe and the model appears to be capturing the temporal and spatial variations in the

observed sulfate well and is responding to the SO2 emission reductions between 2002 and

2009 in a manner as expected. Thus the model performance indicates that the modeled

relative changes in SO4 concentrations are likely a valid response.

• Soil Performance Issues: The CMAQ performance for the Soil species is quite poor. 

This Soil component of the 2009 projected PM2.5 Design Value ranges from 0.4 to 1.8

μg/m3. The RRFs for Soil indicate that it is mostly increasing, with summer (Q3) Soil

RRFs typically ranging from 1.0 to 1.3. We address the Soil performance issues in

Chapter 5 weight of evidence analysis where we assumed that the modeled Soil remains

unchanged between 2002 and 2009 which did not significantly affect the projected 2009

PM2.5 Design Values.

SO4 reductions dominate the changes in PM2.5 Design Values between 2002 and 2009. SO4

performance is quite good in the CMAQ 2002 Base G2 Actual base case simulation, almost

always achieving the PM performance goal and frequently also achieving the more stringent

ozone performance goal. These factors provide confidence in the Design Value projections

using the CMAQ Base G modeling results.

FINAL Charleston, WV 1997 PM2.5 SIP Page 77
6.0. CONTROL MEASURES

This section is divided into five sections: Point Source Measures, Area Source Measures, NonRoad Source Measures, On-Road Source Measures and Supplemental Control Measures.

6.1. Point Source Measures

6.1.a. Control Strategies

This section documents credit for emission reductions attributable to federal and state

requirements on point sources. These credits include:

• RACT;

• “NOx SIP Call” to reduce ozone transport in the eastern United States; and

• EPA’s Clean Air Interstate Rule (CAIR).

6.1.a.1. RACT and Regional Transport Requirements (federal and state regulations)

6.1.a.1.A. RACT

For each PM2.5 nonattainment area, 40 CFR §51.1010 notes that a SIP revision demonstrating

that all reasonable available control measures, including RACT for stationary sources, necessary

to demonstrate attainment as expeditiously as practicable, have been adopted. The section of the

implementation rules goes on to state that potential measures that are reasonably available,

considering technical and economic feasibility, must be adopted as Reasonably Available

Control Measures (RACM) if, considered collectively, they would advance the attainment date

by one year or more. As discussed in detail in Section 9, West Virginia determined that there are

no additional control measures that could be adopted by January 1, 2008. Further, existing

measures, and those planned for implementation by 2009, are expected to enable the area to

demonstrate compliance with the 1997 PM2.5 NAAQS by the 2010 attainment date. As such, no

further action on RACT is warranted.

6.1.a.1.B. NOx SIP Call

In late 1998, the EPA adopted a rule commonly referred to as the “NOx, SIP Call” to reduce

ozone transport in the eastern United States. This regional NOx reduction program required 22

states, including West Virginia, to further reduce large point source NOx emissions to EPAidentified state emission budget levels by 2007. State regulation adoption timelines

notwithstanding, the majority of the 22 SIP call states had these regulations in place by

2003/2004.West Virginia has adopted state rules codifying the requirements of the NOx SIP Call,

which has resulted in NOx reductions of 77 percent.

6.1.a.1.C. Clean Air Interstate Rule (CAIR)

On May 12, 2005, the EPA promulgated the Clean Ar Interstate Rule, which requires reductions

in NOx and SO2 from large fossil fuel fired electric generating units. The rule is set up in two

phases with the first phase of NOx reductions required by 2009. The first phase of SO2 reductions

are required by 2010. The rule sets up both annual SO2 and NOx emissions budgets and an ozone

FINAL Charleston, WV 1997 PM2.5 SIP Page 78
season NOx emission budget. The rule requires that units with a nameplate capacity greater than

25 megawatts (MW) emit no more NOx or SO2 than their allocations determined by the state

either through emission controls or banking and trading.

On July 11, 2008, the United States Court of Appeals for the District of Columbia Circuit issued

an order vacating CAIR. On September 24, 2008, EPA and others petitioned the Court for

rehearing or rehearing en banc. On December 23, 2008, upon rehearing the Court remanded

CAIR to EPA without vacatur, directing EPA to remedy CAIR’s flaws in accordance with the

Court’s July 11, 2008 opinion. Therefore, CAIR remains in effect.

West Virginia has adopted state rules codifying the requirements of CAIR, which is expected to

result in NOx, reductions of 78 percent by 2015, and SO2 reductions of 78 percent by 2015. 

Table 6.1 below, identifies all the coal-fired electric generating units (EGUs) in West Virginia

and the controls currently installed along with the date of installation; and the controls currently

under construction along with the scheduled dates of operation of the controls.

FINAL Charleston, WV 1997 PM2.5 SIP Page 79
Table 6.1. Coal-fired EGU Controls (Installed and Under Construction)

County ID Plant Unit MW SO2

Controls

Year SO2

Controls

Installed

NOx

Controls

Year NOx

Controls

Installed

Preston 077-0001 Albright

1 73 – – LNB 1999 2 73 – – LNB 2005 3 137 – – LNB 1995 

Monongalia 061-0001 Ft. Martin

1 552 FGD 2010 SNCR Trim 2004 SN

coCPuC

2 555 FGD 2010 SNCR Trim 2004

Marion 049-0026 Grant Town – 84

CFB

Limestone

Injection

1992 SNCR 2003

SNcoC

Harrison 033-0015 Harrison

1 640 FGD 1994 SCR 2002 St

reopbe

2 640 FGD 1994 SCR 20033 640 FGD 1994 SCR 2003

FINAL Charleston, WV 1997 PM2.5 SIP 
Table 6.1. Coal-fired EGU Controls (Installed and Under Construction)

County ID Plant Unit MW SO2

Controls

Year SO2

Controls

Installed

NOx

Controls

Year NOx

Controls

Installed

Putnam 079-0006 John Amos

1 800 FGD 3/2010 SCR 2005

AroSCbeun1/un12by 

2 800 FGD 12/2010 SCR 20043 1300 FGD 3/2009 SCR 2003

Marshall 051-0006 Kammer

1 210 – – OFA 2000

ARof R12at thUCTan

2 210 – – OFA 19993 210 – – OFA 2000

Kanawha 039-0006 Kanawha River 1 200 – – OFA 1999 

2 200 – – OFA 2000 

FINAL Charleston, WV 1997 PM2.5 SIP 
Table 6.1. Coal-fired EGU Controls (Installed and Under Construction)

County ID Plant Unit MW SO2

Controls

Year SO2

Controls

Installed

NOx

Controls

Year NOx

Controls

Installed

Marshall 051-0005 Mitchell

1 800 FGD 2007 SCR 2007 A

roSC1/12

2 800 FGD 2007 SCR 2007

Monongalia 061-0027 MEA – 60

CFB

Limestone

Injection

1991 LNB 1991 

Mason 053-0009 Mountaineer – 1300 FGD 2007 SCR 2003

AroSC1/12

Grant 023-0003 Mt. Storm

1 533 FGD 2002 SCR 2003 V

mre0.N0.

2 533 FGD 2001 SCR 20033 521 FGD 1994 SCR 2004

Grant 023-0014 North Branch

1A

84

CFB

Limestone

Injection

1992 LNB 1992 

1B

CFB

Limestone

Injection

1992 LNB 1992 

FINAL Charleston, WV 1997 PM2.5 SIP 
Table 6.1. Coal-fired EGU Controls (Installed and Under Construction)

County ID Plant Unit MW SO2

Controls

Year SO2

Controls

Installed

NOx

Controls

Year NOx

Controls

Installed

Mason 053-0001 Philip Sporn

1 150 – – LNB 1997 A

Rof R12at thUCTan

2 150 – – LNB 19973 150 – – LNB + SNCR 1/2009

4 150 – – LNB + SNCR 1/20095 450 – – LNB 1999

Pleasants 073-0005 Pleasants

1 650 FGD 1979 SCR 2003 St

reopbe

2 650 FGD 1980 SCR 2003

Marion 049-0009 Rivesville

7 46 – – – – 8 91 – – – – 

Pleasants 073-0004 Willow Island 1 54 – – OFA 2001 

2 181 – – OFA 2001 

FINAL Charleston, WV 1997 PM2.5 SIP 
6.1.a.1.D. Standards Regarding Fugitive Dust

This section documents credits for emission reductions attributable to federal and state

requirements on point sources. These credits include visibility standards for existing and

modified stationary sources.

The WVDAQ has several rules in place that require the control of fugitive dust within plant

boundaries, these include 45CSR2 – To Prevent and Control Particulate Air Pollution from

Combustion of Fuel in Indirect Heat Exchangers; 45CSR3 – To Prevent and Control Air

Pollution from the Operation of Hot Mix Asphalt Plants; 45CSR5 – To Prevent and Control Air

Pollution from the Operation of Coal Preparation Plants, Coal Handling Operations and Coal

Refuse Disposal Areas; and 45CSR7 – To Prevent and Control Particulate Matter Air Pollution

from Manufacturing Processes and Associated Operations. In addition, 45CSR17 - To Prevent

and Control Particulate Matter Air Pollution from Materials handling, Preparation, Storage and

Other Sources of Fugitive Particulate Matter prohibits the discharge of fugitive particulate matter

beyond the boundary lines of property on which the discharge originates or at any public or

residential location, which causes or contributes to statutory air pollution. Copies of these rules

are included in Appendix K.

West Virginia also has rules in place to regulate emissions from new sources, including

45CSR13 – Permits for Construction, Modification, Relocation And Operation of Stationary

Sources of Air Pollutants, Notification Requirements, Administrative Updates, Temporary

Permits, General Permits, and Procedures for Evaluation (minor source NSR); 45CSR14 –

Permits for Construction and Major Modification of Major Stationary Sources of Air Pollution

for the Prevention of Significant Deterioration (PSD); and 45CSR19 – Permits for Construction

and Major Modification of Major Stationary Sources of Air Pollution which Cause or Contribute

to Nonattainment (nonattainment NSR). The rules identified above have all been approved by

EPA as part of the State Implementation Plan. 

The West Virginia nonattainment NSR and PSD regulations address emissions from new major

sources that may locate in, or near, a nonattainment area, or increase emissions from major

modifications to existing sources located in, or near, a nonattainment area. 

The benefits from the control of fugitive dust are reflected in the 2002 baseline inventory and the

2009 projections thereof. Additional reductions from this measure are not expected.

6.1.b. Projected Reductions

The point source NOx, SO2 and PM2.5 Direct controls are a phased approach to controlling

emissions from power plants and other large fuel combustion sources. The following programs

result in emission reductions from point sources that demonstrate progress toward attaining the

PM2.5 standard:

• NOx SIP Call Rule

• EPA’s CAIR

FINAL Charleston, WV 1997 PM2.5 SIP Page 84
In West Virginia, the expected emission reductions for 2009 from electric generating utilities

were calculated using knowledge of historical emission rates, adjusted by the expected control

efficiencies achieved from various control devices that have been installed.

See Appendix D for further point source documentation.

Emission reductions resulting from the point source controls, in the Charleston area, are

presented in the table below.

Table 6.2. 2009 Point Source Emission Reductions

Charleston Area Emission Reductions1

 (tons/year)

NOx Reductions 39,399

SO2 Reductions 78,234

PM2.5 Direct Reductions -75 1

Note: Negative values indicate an increase in emissions

FINAL Charleston, WV 1997 PM2.5 SIP Page 85
6.2. Area Source Measures

6.2.a. Control Strategy

6.2.a.1. Open Burning Restrictions (state rule)

45CSR5 - To Prevent and Control Air Pollution from Combustion of Refuse - prohibits the open

burning of refuse with limited exceptions.

6.2.b. Projected Reductions

The benefits from this program are reflected in the 2002 baseline inventory and the 2009

projections thereof. Additional reductions from this measure are not expected.

6.3. Non-Road Source Measures

6.3.a. Control Strategies

6.3.a.1 Phase I and Phase II Emissions Standards for Gasoline-Powered Nonroad Utility

Engines (federal rule)

This measure takes credit for emissions reductions attributable to emissions standards

promulgated by the EPA for small non-road, spark-ignition (SI) (i.e., gasoline-powered) utility

engines, as authorized under 42 U.S.C. §7547. The measure affects gasoline-powered (or other

SI) lawn and garden equipment, construction equipment, chain saws, and other such utility

equipment as chippers and stump grinders, wood splitters, etc., rated at or below 19 kilowatts

(kW) [an equivalent of 25 or fewer horsepower (hp)]. Phase II of the rule applied further controls

on handheld and nonhandheld outdoor equipment.

Federal emissions standards promulgated under §7547(a) apply to SI nonroad utility engines.

The EPA’s Phase I Spark Ignition Final Rule on such emissions standards was published in 60

Federal Register 34581 (July 3, 1995) and was effective beginning August 2, 1995. Compliance

was required by the 1997 model year. The Phase II final rule for handheld nonroad equipment

was published in 65 Federal Register 24267 (April 25, 2000). The Phase II final rule for

nonhandheld equipment was published in 64 Federal Register 15207 (March 30, 1999).

This program is implemented by the EPA, under 42 U.S.C. §7547(a).

6.3.a.2. Emissions Standards for Diesel-Powered Nonroad Utility Engines of 50 or More

Horsepower (federal rule)

This measure takes credit for emissions reductions attributable to emissions standards

promulgated by the EPA for nonroad, compression-ignition (i.e., diesel-powered) utility engines,

as authorized under 42 U.S.C. §7547. The measure affects diesel-powered (or other

compression-ignition) construction equipment, industrial equipment, etc., rated at or above 37

kW (37 kW is approximately equal to 50 horsepower).

FINAL Charleston, WV 1997 PM2.5 SIP Page 86
Federal emissions standards applicable to compression-ignition nonroad utility engines are

promulgated under §7547(a).

EPA’s first rule on such emissions standards was published in 59 Federal Register 31306 (June

17, 1994) and was effective on July 18, 1994.

Tier 2 and Tier 3 Emission Standards were promulgated in 1998. This program includes the first

set of standards for nonroad diesel engines less than 37 kW (phase in between 1999 and 2000),

including marine engines in this size range. It also phases in more stringent Tier 2 emission

standards from 2001 to 2006 for all engine sizes and adds yet more stringent Tier 3 standards for

engines between 37 and 560 kW (50 and 750 hp) from 2006 to 2008.

EPA adopted a comprehensive national program to greatly reduce emissions from nonroad diesel

engines by integrating engine and fuel controls as a system to gain the greatest air quality

benefits. This rule was published June 29, 2004. The requirement to reduce sulfur levels in

nonroad diesel fuel by more than 99 percent will allow, for the first time, advanced emission

control systems to be used on engines used in construction, agricultural, industrial and airport

service equipment.

This program is implemented by the EPA, under 42 U.S.C. §7547(a).

6.3.a.3. Emission Standards for Spark-Ignition (SI) Marine Engines (federal rule)

This EPA measure controls exhaust NOx emissions from new spark-ignition (SI) gasoline marine

engines, including outboard engines, personal watercraft engines and jet boat engines.

EPA is imposing emission standards for two-stroke technology, outboard and personal watercraft

engines. This involves increasingly stringent control over the course of a 9-year phase-in period

which began in model year 1998. By the end of the phase-in, each manufacturer is required to

meet a NOx emission standard.

This program is implemented by the EPA under 42 U.S.C. §7547(a).

6.3.a.4. Emission Standards for Large Spark-Ignition (SI) Engines (federal rule)

This EPA measure controls emissions from several groups of previously unregulated nonroad

engines, including large industrial SI engines.

The EPA requirements vary depending upon the type of engine or vehicle, taking into account

environmental impacts, usage rates, the need for high performance models, costs, and other

factors. The emission standards apply to all new engines sold in the United States and any

imported engines manufactured after these standards began.

Controls on the category of large industrial SI engines were first required in 2004. Controls on

the other engine categories began in years after 2005. Large industrial SI engines are those rated

over 19 kW used in a variety of commercial applications; most use liquified petroleum gas, with

others operating on gasoline or natural gas.

FINAL Charleston, WV 1997 PM2.5 SIP Page 87
EPA adopted two tiers of emission standards for large SI engines. The first tier of standards,

which started in 2004, are based in a simple laboratory measurement using steady-state

procedures. The Tier I standards are the same as those adopted earlier by the California Air

Resources Board for engines used in California. Tier 2 standards became effective in 2007.

The program is implemented by the EPA under 42 U.S.C. §7547(a).

6.3.a.5. Standards for Locomotives (federal rule)

This measure sets NOx Standards for locomotive engines manufactured and remanufactured after

2001.

This program includes all locomotives originally manufactured from 2002 through 2004. It also

applies to the remanufacture of all engines built since 1973. Regulation of the remanufacturing

process is critical because locomotives are generally remanufactured five to ten times during

their total service lives, which are typically 40 years or more.

Three separate sets of emission standards have been adopted, with the applicability of the

standards dependent on the date a locomotive is first manufactured. The first set of standards

(Tier 0) applies to locomotives and locomotive engine originally manufactured from 1973

through 2001, any time they are manufactured or remanufactured. The second set of standards

(Tier 1) applies to locomotives and locomotive engines originally manufactured from 2002 to

2004. These locomotives are required to meet the Tier 1 standards at the time of manufacture

and at each subsequent remanufacture. The final set of standards (Tier 2) applies to locomotives

and locomotive engines originally manufactured in 2005 and later. Electric locomotives, historic

steam-powered locomotives and locomotives manufactured before 1973 do not significantly

contribute to the emissions problem and, therefore, are not included in the regulation.

This program is implemented by the EPA under the Final Emission Standards for Locomotives

(EPA420-F-97-048) published in December 1997.

6.3.b. Projected Reductions

The following nonroad emission reduction measures, discussed above, are calculated using the

NONROAD2005 model:

• EPA Nonroad Gasoline Engines Rule

• EPA Nonroad Diesel Engines Rule

• Emissions Standards for Spark-Ignition Marine Engines

• Emission Standards for Large Spark-ignition Engines

Emission Standards for Locomotives are calculated using the Area Source spreadsheet, but

emission benefits are included in the nonroad sector totals. Emission benefits are based on EPA

guidance on emission factors for locomotives. In 2009, the reductions are 32.35 percent for NOx

and 15 percent for PM2.5.

NONROAD2005, the current nonroad emissions model approved for use by the EPA, is not

designed to calculate the benefits of each of the above control measures individually. As a result,

FINAL Charleston, WV 1997 PM2.5 SIP Page 88
this and future SIP revisions will not enumerate the benefits of individual nonroad control

measures. The Table below summarizes the combined benefits from the above control measures

on the Charleston area.

Table 6.3. 2009 Nonroad Emission Reductions 

Charleston Area Emission Reductions (tons/year)

NOx Reductions 262

SO2 Reductions 198

PM2.5 Direct Reductions 22

FINAL Charleston, WV 1997 PM2.5 SIP Page 89
6.4. Onroad Source Measures

6.4.a. Control Strategies

6.4.a.1. Federal Tier I new Vehicle Emission and New Federal Evaporative Emissions

Standards (federal regulation)

Under 42 U.S.C. §7521, EPA issued a new and cleaner set of federal motor vehicle emission

standards (Tier I standards), which were phased in begging with model year 1994.

The benefits of this program are reflected in the 2002 baseline inventory and the 2009

projections thereof.

These federally implemented programs affect light-duty vehicles and light-duty trucks (LDT).

The Federal Motor Vehicle Control Program requires more stringent exhaust emission standards,

as well as a uniform level of evaporative emission controls, demonstrated through the new

federal evaporative test procedures. Under 42 U.S.S. §7521(g), all post-1995 model year cars

must achieve the Tier I (or Phase I) exhaust standards, which are as follows (emissions are in

grams/mile and are related to durability timeframes of 5 yrs/50,ooo miles and 10 yrs/100,000

miles):

Table 6.4-1. Tier I Standards 

Vehicle Type 5 yrs/50,000 miles 10 yrs/100,000 miles

VOCs CO NOx VOCs CO NOx

Light-duty vehicles; light-duty trucks

(load weight 3,750 lbs)

0.25 3.4 0.4a 0.31 4.2 0.6a

Light-duty trucks (load weight 3,751

to 5,750)

0.32 4.4 0.7b 0.4 5.5 0.97b

a

For diesel-fueled light-duty vehicles and for LDTs at 3,750, before model year 2004, the applicable NOx standards

shall be 1.0 at 5 yrs/50,000 miles and 1.25 at 10 yrs/100,000 miles.

b

This NOx standard does not apply to diesel-fueled trucks of 3,751 to 5,750 lbs.

6.4.a.2. National Low Emission Vehicle Program (federal regulation)

Under the National Low-Emission Vehicle (LEV) program, auto manufacturers have agreed to

comply with tailpipe standards that are more stringent than EPA can mandate prior to model year

(MY) 2004. Once manufacturers committed to the program, the standards became enforceable in

the same manner in which other federal motor vehicle emissions control requirements are

enforceable. The program was in place nationwide for MY 2001.

The benefits of this program are reflected in the 2002 baseline inventory and the 2009

projections thereof.

FINAL Charleston, WV 1997 PM2.5 SIP Page 90
These federally implemented programs affect light-duty vehicles and trucks.

The National Low Emission Vehicle Program requires more stringent exhaust emission

standards than the Federal Motor Vehicle Control Program Tier I (or Phase I) exhaust standards.

6.4.a.3. Tier 2 Motor Vehicle Emission Regulations (federal regulation)

The US EPA promulgated a rule on February 10, 2000, requiring more stringent tailpipe

emissions standards for all passenger vehicles, including sport utility vehicles (SUVs), minivans,

vans and pick-up trucks. These regulations also require lower levels of sulfur in gasoline, which

will ensure the effectiveness of low emission-control technologies in vehicles and reduce

harmful air pollution.

These federally implemented programs affect all passenger vehicles, including sport utility

vehicles (SUVs), minivans, vans and pick-up trucks.

The new tailpipe and sulfur standards require passenger vehicles to be 77 to 95 percent cleaner

than those built before the rule was promulgated and will reduce the sulfur content of gasoline by

up to 90 percent. The new tailpipe standards are set at an average standard of 0.07 grams/mile

for NOx for all classes of passenger vehicles beginning in 2004. This includes all light-duty

trucks, as well as the largest SUVs. Vehicles weighing less than 6000 pounds are being phasedin to this standard between 2004 and 2007.

Beginning in 2004, the refiners and importers of gasoline have the flexibility to manufacture

gasoline with a range of sulfur levels as long as all of their production is capped at 300 parts per

million (ppm) and their annual corporate average sulfur levels are 120 ppm. In 2005, the refinery

average was set at 30 ppm, with a corporate average of 90 ppm and a cap of 300 ppm. Finally, in

2006, refiners met a 30 ppm average sulfur level with a maximum cap of 80 ppm.

As newer, cleaner cars enter the national fleet, the new tailpipe standards will significantly

reduce emissions of nitrogen oxides from vehicles by about 74 percent by 2030.

6.4.a.4. Heavy Duty Diesel Engine Rule (federal regulation)

Under the Heavy-Duty Diesel Engine Rule, truck manufacturers must comply with more

stringent tailpipe standards by 2004 and 2007. These standards are enforceable in the same

manner that other federal motor vehicle emissions control requirements are enforceable.

These federally implemented programs affect heavy-duty diesel engines used in trucks.

The Heavy Diesel Engine Rule requires more stringent exhaust emission standards. The rule also

mandates use of ultra-low sulfur diesel fuel. Sulfur in diesel must be lowered to enable modern

pollution-control technology to be effective on these trucks and buses. US EPA requires a 97

percent reduction in the sulfur content of highway diesel fuel from its former level of 500 ppm

(low sulfur diesel, or LSD) to 15 ppm (ultra-low sulfur diesel, or ULSD). Refiners began

producing the cleaner-burning diesel fuel, ULSD, for use in highway vehicles beginning June 1,

2006.

FINAL Charleston, WV 1997 PM2.5 SIP Page 91
6.4.b. Projected Reductions

The following onroad emission reduction measures, discussed in greater detail above, are

calculated using the MOBILE6 model:

• Federal Tier 1 Vehicle Standards, see Section 6.4.a.

• National Low Emission Vehicle Standards, see Section 6.4.b.

• Federal Tier 2 Vehicle Standards, see Section 6.4.c.

• Heavy Duty Diesel Engine Rule, see Section 6.4.d.

MOBILE5b, the mobile emissions model used in previous SIPs, was designed to calculate the

benefits of each of the above control measures individually. In the update to MOBILE6.2,

changes were made to the model, creating synergistic effects between the mobile control

measures listed above. These effects make it difficult to calculate incremental benefits from

implementation of individual control measures. As a result, this and future SIP revisions will not

enumerate the benefits of individual mobile control measures. The table below summarizes the

combined benefits from the above control measures in the Charleston area. See Appendix D for

documentation of the MOBILE 6.2 modeling process.

Table 6.4-2. Onroad Emission Reductions 

Charleston Area Emission Reductions (tons/year)

NOx Reductions 45,497

SO2 Reductions 78,399

PM2.5 Direct Reductions 53

FINAL Charleston, WV 1997 PM2.5 SIP Page 92
6.5. Supplemental Control Measures

EPA’s voluntary measures policy, “Guidance on Incorporating Voluntary Mobile Source

Emission Reductions Programs in State Implementation Plans,” establishes criteria under which

emission reductions from voluntary programs are creditable in a SIP. This policy permits states

to develop and implement innovative programs that partner with local jurisdictions, businesses

and private citizens to implement emission-reducing behaviors at the local level.

Inclusion of the following programs in the control measures portion of this attainment plan is not

intended to create an enforceable commitment by the state to implement the programs or to

achieve any specific emission reductions projected as a result of implementation of the

programs, and the state does not make any such commitment. In addition, the state does not rely

on any emission reductions projected as a result of implementation of these programs to

demonstrate attainment. While the emission reductions from these programs could be substantial

and could lead to significant air quality benefits, actual air quality benefits remain unquantified.

Consequently, projected emission reductions from these programs are not included in the

emission inventory, the attainment modeling, the reasonable further progress calculations, or any

other area of the SIP where specific projected emission reductions are identified.

In 2007 the West Virginia Legislature enacted the West Virginia Energy Policy and

Development Act of 2007 which created the West Virginia Division of Energy to “. . . provide

leadership for developing energy policies emphasizing the increased efficiency of energy use,

(and) the increased development and production of new and existing domestic energy sources.”

The West Virginia Division of Energy (WVDOE) is responsible for the formulation and

implementation of fossil, renewable and energy efficiency initiatives designed to advance energy

resource development opportunities and provide energy services to businesses, communities and

homeowners in West Virginia. A primary goal of the WVDOE is the development of a state

energy plan (http://www.energywv.org/community/eep.html).

The WVDOE sponsors a number of programs, including:

• Ride Share Program (http://www.energywv.org/community/rideshare.html). Due to the

rising gasoline costs and the number of state employees who commute each day, the Ride

Share Program, offered through the Energy Efficiency Program, serves as a means of

financial savings to participating riders, conservation of fuel, and the reduction of air

pollution.

• The ENERGY STAR® Change a Light, Change the World Campaign

(http://www.energystar.gov/index.cfm?c=lighting.pr_lighting). A national challenge to

encourage every American to help change the world – one light, one step at a time. The

campaign culminates in the fall around ENERGY STAR® Change a Light Day (the first

Wednesday in October) with promotions running locally and nationally from October 1

through November 30. If every West Virginia household replaced just one 75-watt

incandescent light with a 20-watt compact fluorescent lamp (CFL), the US EPA estimates

we could save more than $5 million annually in energy costs.

• Clean Air Forum (http://www.energywv.org/community/cleanairforum.html). The Clean

Air Forum newsletter offers energy information from around the state.

FINAL Charleston, WV 1997 PM2.5 SIP Page 93
• Alternative Fuels Program( http://www.energywv.org/community/fuels.html). The West

Virginia Clean State Program, working closely with the US DOE Clean Cities Program,

promotes alternate fuel vehicles.

• West Virginia Friends of Biodiesel Conference

(http://www.energywv.org/community/WVFOBPresentations.html). Sponsored by the

WVDOE in October 2007, the conference brought together current and potential

biodiesel users to spread the knowledge about this renewable fuel.

• Building Professional Energy Training Program

(http://www.energywv.org/community/code.html). The West Virginia Energy Efficiency

Program Sponsors building code seminars to teach the latest codes and building

technologies to local government officials and private-sector building professionals.

• Industrial assessment Program (http://www.energywv.org/community/ia.html). Provides

industrial assessments to industries that participate in the Industries of the Future-West

Virginia (IOF-WV).

• Industries of the Future-West Virginia

(http://www.energywv.org/community/iofwv.html). IOF-WV is a state-level technical

assistance initiative, interacts with the US Department of Energy Industries of the Future

Program to provide assistance to energy-intensive industries. Teams from university

engineering programs provide technical assistance through the Glass Industry Assistance

and the Wood Industry Initiative Program.

• Lighting Grants Program (http://www.energywv.org/community/lgp.html). This program

has provided more than $400,000 for lighting improvements in schools, local

governments and nonprofit hospitals. The 464 audits performed have identified $2.5

million in potential annual savings. 

• Recycling Program (http://www.energywv.org/community/recycling.html). The West

Virginia Recycling Directory is updated annually and lists over 500 West Virginia

recyclers.

• Renewable Energy Program (http://www.energywv.org/community/renewable.html).

Solar energy (http://www.energywv.org/community/solar.cfm) represents conceivably

the single largest source of energy. Solar energy opportunity has been estimated at 1.5

million barrels of oil energy per year for every square kilometer. The biofuels program

(http://www.energywv.org/community/biofuels.html) is looking at energy uses for wood

and other biomass resources. The wind program

(http://www.energywv.org/community/wind.html) has supported the development of a

detailed map of West Virginia wind resources and the promotion of this resource.

• Saving Energy in Public Schools Program

(http://www.energywv.org/community/schoolenergy.html). Developing a systematic

approach to reducing energy use in West Virginia public schools.

• West Virginia ENERGY STAR® Program

(http://www.energywv.org/community/energystar.html). ENERGY STAR® is a

government backed program helping businesses and individuals protect the environment

through superior energy efficiency. 

FINAL Charleston, WV 1997 PM2.5 SIP Page 94
6.6. Schedule of Adopted Control Measures

Table 6.6. West Virginia Schedule of Adopted Control Measures – Charleston

Nonattainment Area

Ref. No. Control Measure Mandate Regulation

Number

Effective Date

Point Source Measures

6.1.a.1.

6.1.a.1.B.

6.1.a.1.C.

RACT and Regional

Transport Requirements

NOx SIP Call - nonEGUs

NOx SIP Call - EGUs 

CAIR - Annual NOx

CAIR - Ozone Season NOx

CAIR - Annual SO2

Federal

45CSR1

45CSR26

45CSR39

45CSR40

45CSR41

10/25/20001

Amended: 5/1/2006

5/1/20022

Amended: 6/1/2003

5/1/20063

Amended: 5/1/08

5/1/20063

Amended: 5/1/08

5/1/20063

Amended: 5/1/08

6.1.a.1.D. Standards Regarding

Fugitive Dust

Indirect Heat Exchangers

Asphalt Plants

Coal Handling &

Preparation

Manufacturing Process

Materials Handling

Federal

Federal

Federal

Federal

State

45CSR2

45CSR3

45CSR5

45CSR7

45CSR17

3/15/19724

Amended: 8/31/2000

10/01/19665

Amended: 8/31/2000

9/01/19686

Amended: 8/31/2000

7/1/19697

Amended: 8/31/2000

4/8/1980

Amended: 8/31/2000

Area Source Measures

6.2.a.1. Open Burning Restrictions State 45CSR6 9/1/19698

Amended: 7/1/2001

FINAL Charleston, WV 1997 PM2.5 SIP Page 95
Table 6.6. West Virginia Schedule of Adopted Control Measures – Charleston

Nonattainment Area

Ref. No. Control Measure Mandate Regulation

Number

Effective Date

Nonroad Measures

6.3.a.1. EPA Nonroad Gasoline

Engine Rule

Federal 40 CFR Parts

90, 91

12/3/96

6.3.a.2. EPA Nonroad Diesel

Engines Rule

Federal 40 CFR Part 9

et al.

Model Year 2000-

2008 depending on

engine size

6.3.a.3. EPA Nonroad SparkIgnition Marine Engine

Rule

Federal 40 CFR Parts

89, 90,91

Model Year 1998

6.3.a.4. EPA Large Spark-Ignition

Engine Rule

Federal 40 CFR Parts

89, 90, 91, 94,

1048,1051,

1065, 1068

11/8/02

6.3.a.5. Standards for Locomotives Federal 63 FR 18998 6/15/98

Onroad Measures

6.4.a.1. Federal Tier I Vehicle

Standards and New Car

Evaporative Standards

Federal 40 CFR Part

86

Model Year 1994-

1996; Evap. Stds.

1996

6.4.a.2. Nation Low Emissions

Vehicle Program

Federal 40 CFR Part

86

Model Year 2001

6.4.a.3. Tier 2 Motor Vehicle

Emission Standards

Federal 65 FR 6698 2/10/00

6.4.a.4. Heavy-Duty Diesel Engine

Rule

Federal 63 FR 54694 12/22/97

Notes: 1Effective date provided is state effective date; federal effective date is 11/27/2006 [71 FR 56881].

2Effective date provided is state effective date; federal effective date is 7/9/2002 [67 FR 31733]. 3

Effective date provided is state effective date; original federal effective date was 12/18/07 [72FR71576],

CAIR SIP revision submitted 4/22/08 . 

4

Effective date provided is state effective date; original federal effective date was 5/31/1972 [37 FR 10902];

federal effective date for most recent amendment is 10/10/2003 [68FR 47473].

5

Effective date provided is state effective date; original federal effective date was 5/31/1972 [37 FR 10902];

federal effective date for most recent amendment is 12/10/2002 [67 FR 63270].

6

Effective date provided is state effective date; original federal effective date was 5/31/1972 [37 FR 10902];

federal effective date for most recent amendment is 12/6/2002 [67 FR 62379].

7

Effective date provided is state effective date; original federal effective date was 5/31/1972 [37 FR 10902];

federal effective date for most recent amendment is 8/4/2003 [68 FR 33010].

8

Effective date provided is state effective date; original federal effective date was 5/31/1972 [37 FR

10902];federal effective date is 4/11/2003 [68 FR 6627].

FINAL Charleston, WV 1997 PM2.5 SIP Page 96
7.0. ATTAINMENT DEMONSTRATION

An attainment demonstration consists of (a) analyses that estimate whether selected emissions

reductions will result in ambient concentrations that meet the NAAQS, and (b) an identified set

of control measures which will result in the required emissions reductions. The necessary

emission reductions for both of these attainment demonstration components may be determined

by relying on results obtained with air quality models.

Section 3.0 of the Attainment Modeling Guidance recommends applying both a modeled

attainment test and a subsequent screening test (or unmonitored area analysis) to the air quality

modeling results to determine if the annual PM2.5 NAAQS will be met. Additional technical or

corroboratory analyses may also be used as part of a “supplemental analysis” or a more stringent

“weight of evidence” determination to supplement the modeled attainment test and to further

support a demonstration of attainment of the NAAQS.

7.1. Attainment Test Introduction

EPA has developed a PC-based software tool entitled the Modeled Attainment Test Software

(MATS) that includes the FRM PM2.5 mass and STN/IMPROVE speciated PM2.5 concentrations

processed by the SANDWICH method. The Speciated Model Attainment Test (SMAT)

presented in EPA’s modeling guidance is codified in MATS. Several beta versions of MATS

have been released with the annual PM2.5 projection SMAT method first becoming available with

the latest release of MATS (Version 1.1.2) in January 2008. For the ASIP modeling performed in

2006-2007, the MATS tool with a PM2.5 projection capability was not available. Therefore, ASIP

developed their own PM2.5 projection tool. The ASIP PM2.5 projection tool is based on STN PM

speciation data, processed using SANDWICH, that are assigned to nearby FRM sites. The

SMAT projection procedure was performed using Excel spreadsheets.

The ASIP projection procedures are presented in section 7.1.a below, with details presented in

Chapter 5 of the ASIP TSD (dated March 24, 2009, contained in Appendix N.2). The MATS

projection procedures are presented in section 7.1.b below, with details presented in Chapter 4 of

the ASIP TSD (Appendix N.2). The final 2009 PM2.5 projections presented were made using

Version 2.01 of EPA’s Modeled Attainment Test Software (MATS) and are presented in Section

7.2, along with the ASIP projections. The ASIP projections are used to corroborate the MATS

projections. 

7.1.a. ASIP PM2.5 Projection tool

The purpose of a modeling assessment is to determine if control strategies currently being

implemented (“on the books”) and proposed control strategies will lead to attainment of the

NAAQS for PM2.5 by the attainment year of 2009. The modeling is applied in a relative sense,

similar to the 8-hour ozone attainment test. However, the PM2.5 attainment test is more

complicated and reflects the fact that PM2.5 is a mixture. In the test, ambient PM2.5 is divided into

major components, with a separate relative response factor (RRF) and future design value (DVF)

calculated for each of the PM2.5 components. Since the attainment test is calculated on a per

species basis, the attainment test for PM2.5 is referred to as the Speciated Modeled Attainment

Test (SMAT). In it entirety, SMAT consists of four basic steps.

FINAL Charleston, WV 1997 PM2.5 SIP Page 97
First, the observed quarterly mean PM2.5 and quarterly mean composition for each monitor is

calculated. This is achieved by multiplying the monitored quarterly mean concentration of PM2.5

from FRM monitors by the monitored fractional composition of PM2.5 species for each quarter

(e.g., (20% sulfate) x (15.0 μg/m3 PM2.5 mass) = 3.0 μg/m3 sulfate mass).

The monitored quarterly mean concentration of PM2.5 from FRM monitors are 5 year baseline

design values (DVB) that are the result of averaging 3 current design values (DVC) that straddle

the modeling base year. The fractional composition of PM2.5 species is derived from STN

monitoring site data that has been processed by the “sulfate, adjusted nitrate, derived water,

inferred carbonaceous material balance approach,” or SANDWICH method, so STN and FRM

masses are equivalent. The mean composition derived from the SANDWICH method includes

the percent of PM2.5 that can be attributed to SO4, NO3, OC, EC, other primary inorganic

particulates (or crustal materials), NH4, and particle bound water (PBW).

The second step is to use model results to derive component specific RRF for each monitor for

each quarter. The RRF is basically the ratio of the model’s future projections to the baseline

current projections. The RRF for each component is the future year modeled quarterly mean

concentration predicted near the monitoring site divided by the base year modeled quarterly

mean concentration predicted near the monitoring site.

For the third step, the component specific RRFs are applied to the observe air quality

concentrations to projected quarterly species estimates. For each quarter, the current quarterly

mean component concentrations (step 1) are multiplied by the component-specific RRF obtained

in step 2. This leads to an estimated future quarterly mean concentration for each component.

The fourth step sums the quarterly components to get a quarterly mean PM2.5 value. These

quarterly mean values are then averaged to produce a future year annual average PM2.5 estimate,

or future design value (DVF), for each FRM monitoring site. This final value is then compared

to the NAAQS (15.0 μg/m3

) to determine if attainment is reached. For a more detailed discussion

of SMAT and the data sets for each monitor in the nonattainment areas, see Appendix J.

7.1.b. MATS tool

EPA has established the SMAT recommended procedures for projecting future-year PM2.5

Design Values in a software tool known as the Modeled Attainment Test Software (MATS)

[http://www.epa.gov/scram001/modelingapps_mats.htm]. 

The MATS PM2.5 projection procedures use SANDWICH STN and IMPROVE speciated PM2.5

data that have been imported into the MATS tool. The speciated PM2.5 measurements are then

interpolated to the FRM monitoring sites where they are used to speciate FRM PM2.5 mass

measurements. As stated in EPA’s modeling guidance, the starting point for the future-year

PM2.5 Design Value projections (i.e., the current year Design Value, DVC) is the average of the

three years of Design Values straddling the 2002 modeling year. This results in an average of the

PM2.5 Design Values from 2000-2002, 2001-2003 and 2002-2004.

In the SMAT procedure, the RRFs are applied separately to the quarterly average components of

the current year PM2.5 Design Value (DVC). When developing the quarterly PM species

FINAL Charleston, WV 1997 PM2.5 SIP Page 98
components of the monitor DVCs from the FRM PM2.5 mass and SANDWICH PM2.5 speciation,

the 24-hour average concentrations from each sample day are averaged across each quarter.

Conceptually, the biggest difference between the MATS and ASIP PM2.5 projection approaches

is how the SANDWICH PM speciation data are mapped to the FRM monitors. As noted above,

the ASIP approach assigns SANDWICH STN PM speciation data from a nearby STN monitor to

a FRM site so that SMAT can be applied. MATS, on the other hand, interpolates the

SANDWICH speciated PM data and the Degree of Neutralization (DON) from the STN and

IMPROVE sites to the FRM site to speciate the FRM PM2.5 mass. Although how the FRM PM2.5

mass is speciated is the biggest conceptual difference between the ASIP spreadsheet and MATS

PM2.5 projection approaches, in practice several other differences in the two approaches were

found:

• Different methods for assigning SANDWICH PM speciation to FRM sites.

• Differences in the current-year (2000-2004) PM2.5 Design Values that serve as the

starting point for the projections.

• Differences in the STN SANDWICH speciation data used, including use of

STN/IMPROVE data from different years in the ASIP spreadsheet (2002) and MATS

(2002-2004) methods.

• Inclusion of Sea Salt in the MATS SANDWICH PM2.5 speciation.

For a more detailed explanation of MATS see the Chapter 4 of the updated ASIP TSD, dated

March 24, 2009, contained in Appendix N.2.

7.2. Attainment Test Results

The goal of the SMAT process is to sum the quarterly mean PM2.5 components to get annual

mean PM2.5 values. Table 7.2-1 displays the quarterly mean and annual mean PM2.5 estimates for

2009, using the ASIP PM2.5 projection tool, for the FRM sites in West Virginia and in other

states sharing nonattainment areas. Table 7.2-2 displays the quarterly mean and annual mean

PM2.5 estimates for 2009, using the MATS PM2.5 projection tool, for the FRM sites in West

Virginia and in other states sharing nonattainment areas. Table 7.2-3 presents a comparison of

the annual PM2.5 projections using the ASIP and MATS projection tools.

FINAL Charleston, WV 1997 PM2.5 SIP Page 99
Table 7.2-1. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 Using the

ASIP PM2.5 Projection Tool (Base G4)

AIRS ID State County 1st Q

DVF

2nd Q

DVF

3rd Q

DVF

4th Q

DVF

2009 Annual

DVF

Charleston Nonattainment Area

54-039-0010 WV Kanawha 12.12 13.74 15.73 11.06 13.2

54-039-1005 WV Kanawha 13.62 15.21 17.25 13.04 14.8

Huntington Nonattainment Area

54-011-0006 WV Cabell 13.18 14.23 16.77 12.37 14.1

21-019-0017 KY Boyd 11.89 13.09 15.87 10.32 12.8

39-087-0010 OH Lawrence 13.01 13.91 15.88 11.93 13.7

39-145-0013 OH Scioto 15.76 14.20 15.98 13.18 14.8

Martinsburg Nonattainment Area

54-003-0003 WV Berkeley 13.35 12.78 14.98 13.25 13.6

Parkersburg Nonattainment Area

54-107-1002 WV Wood 13.26 14.22 16.18 12.26 14.0

Weirton Nonattainment Area

54-009-0005 WV Brooke 13.39 14.09 15.12 12.52 13.8

54-029-0011 WV Hancock 12.58 13.41 14.56 12.04 13.1

54-029-1004 WV Hancock 13.44 14.38 16.25 12.75 14.2

Wheeling Nonattainment Area

54-051-1002 WV Marshall 13.74 13.39 15.04 11.48 13.4

54-069-0010 WV Ohio 12.28 12.94 14.67 11.00 12.7

Attainment Areas

54-033-0003 WV Harrison 10.33 11.98 14.31 9.88 11.6

54-049-0006 WV Marion 12.31 13.00 15.31 11.26 13.0

54-055-0002 WV Mercer 8.52 11.36 13.01 9.24 10.5

54-061-0003 WV Monongalia 11.34 12.87 15.45 10.18 12.5

54-081-0002 WV Raleigh 8.98 11.80 13.66 9.21 10.9

54-089-0001 WV Summers 5.97 9.67 11.25 6.06 8.2

FINAL Charleston, WV 1997 PM2.5 SIP Page 100
Table 7.2-2. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 Using the MATS

PM2.5 Projection Tool (Base G4)

AIRS ID State County 1st Q

DVF

2nd Q

DVF

3rd Q

DVF

4th Q

DVF

2009 Annual

DVF

Charleston Nonattainment Area

54-039-0010 WV Kanawha 11.76 14.08 15.61 10.97 13.1

54-039-1005 WV Kanawha 13.51 15.32 17.06 12.81 14.7

Huntington Nonattainment Area

54-011-0006 WV Cabell 13.34 14.64 16.93 12.58 14.4

21-019-0017 KY Boyd 11.80 12.92 15.42 10.32 12.6

39-087-0010 OH Lawrence 12.84 14.07 15.93 11.81 13.7

39-145-0013 OH Scioto 15.63 14.23 15.91 13.20 14.7

Martinsburg Nonattainment Area

54-003-0003 WV Berkeley 13.42 12.77 14.74 13.17 13.5

Parkersburg Nonattainment Area

54-107-1002 WV Wood 13.15 13.86 16.02 12.24 13.8

Weirton Nonattainment Area

54-009-0005 WV Brooke 13.37 13.78 15.09 12.25 13.6

54-029-0011 WV Hancock 12.48 13.04 14.47 11.98 13.0

54-029-1004 WV Hancock 13.40 14.09 16.11 12.51 14.0

39-081-0016 OH Jefferson 14.48 14.44 16.30 14.18 14.9

39-081-1001 OH Jefferson 13.57 13.36 16.85 13.32 14.3

Wheeling Nonattainment Area

54-051-1002 WV Marshall 13.67 13.11 14.91 11.26 13.2

54-069-0010 WV Ohio 12.29 12.74 14.70 10.86 12.6

Attainment Areas

54-033-0003 WV Harrison 10.33 11.82 14.31 9.82 11.6

54-049-0006 WV Marion 12.27 12.76 15.21 11.23 12.9

54-055-0002 WV Mercer 8.52 11.30 13.20 9.36 10.6

54-061-0003 WV Monongalia 11.37 12.56 15.27 10.09 12.3

54-081-0002 WV Raleigh 8.96 11.85 13.87 9.24 11.0

54-089-0001 WV Summers 5.99 9.70 11.19 6.18 8.3

FINAL Charleston, WV 1997 PM2.5 SIP Page 101
Table 7.2-3. Comparison of the PM2.5 Mass Estimates for 2009 Using the ASIP and MATS PM2.5

Projection Tools (Base G4)

AIRS ID State County

ASIP tool MATS tool Difference

2002

DVC

2009

DVF

2002

DVC

2009

DVF

2002

DVC

2009

DVF

Charleston Nonattainment Area

54-039-0010 WV Kanawha 15.4 13.2 15.4 13.1 0.0 0.1

54-039-1005 WV Kanawha 17.1 14.8 17.1 14.8 0.0 0.0

Huntington Nonattainment Area

54-011-0006 WV Cabell 16.5 14.1 16.5 14.4 0.0 -0.3

21-019-0017 KY Boyd 14.9 12.8 14.9 12.9 0.0 -0.1

39-087-0010 OH Lawrence 15.7 13.7 15.7 13.3 0.0 0.4

39-145-0013 OH Scioto 17.1 14.8 17.1 14.8 0.0 0.1

Martinsburg Nonattainment Area

54-003-0003 WV Berkeley 16.2 13.6 16.2 13.5 0.0 0.2

Parkersburg Nonattainment Area

54-107-1002 WV Wood 16.1 14.0 16.1 13.9 0.0 0.1

Weirton Nonattainment Area

54-009-0005 WV Brooke 16.7 13.8 16.7 13.6 0.0 0.2

54-029-0011 WV Hancock 15.8 13.1 16.0 13.0 -0.2 0.1

54-029-1004 WV Hancock 17.3 14.2 17.3 14.0 0.0 0.2

Wheeling Nonattainment Area

54-051-1002 WV Marshall 15.6 13.4 15.6 13.2 0.0 0.2

54-069-0010 WV Ohio 15.1 12.7 15.1 12.7 0.0 0.1

Attainment Areas

54-033-0003 WV Harrison 14.0 11.6 14.0 11.5 0.0 0.1

54-049-0006 WV Marion 15.3 13.0 15.3 12.8 0.0 0.3

54-055-0002 WV Mercer 12.7 10.5 12.7 10.6 0.0 -0.1

54-061-0003 WV Monongalia 14.8 12.5 14.8 12.2 0.0 0.3

54-081-0002 WV Raleigh 13.1 10.9 13.1 11.0 0.0 -0.1

54-089-0001 WV Summers 10.1 8.2 10.1 8.3 0.0 0.1

FINAL Charleston, WV 1997 PM2.5 SIP Page 102
These 2009 DVFs are then compared to the NAAQS (15.0 μg/m3

) to determine if the attainment

goals will be reached. Since the values at the FRM sites in the nonattainment areas are less than

15.0 μg/m3, regardless of the projection method used, all areas have passed the attainment test

portion of the attainment demonstration. Indeed, the fact that two similar but different analysis

methods both show attainment, yields a high degree of confidence that attainment will be

achieved.

For a more detailed explanation of these analyses please see Appendices J and N

7.3. Weight of Evidence Analysis

The Attainment Modeling Guidance asserts that all attainment demonstrations should be

accompanied by supplemental analyses that further support the modeling conclusions. This

supplemental analysis can include additional analyses of air quality, emissions and

meteorological data, and consider modeling outputs other than the results of the attainment test.

If the attainment test results fall short of the standard, the results of corroboratory analyses may

be used in a weight of evidence determination (WOE) to show that attainment is likely despite

modeled results, which may be inconclusive.

The Attainment Modeling Guidance defines the guidelines for supplemental analysis/WOE for

the annual PM2.5 standard as follows:

• Sites with a DVF less than 14.5 μg/m3 should submit basic supplemental analysis to

confirm the outcome of the model attainment test.

• Sites with a DVF between 14.5 and 15.5 μg/m3 should submit a weight of evidence

demonstration to aggregate supplemental analyses to support the model attainment

demonstration.

• Sites with a DVF greater than or equal to 15.5 μg/m3 should consider additional control

measures to ensure attainment, as more qualitative analysis is unlikely to demonstrate

attainment.

The Charleston PM2.5 nonattainment area has DVF that falls between 14.5 and 15.5 μg/m3

,

making the following section a weight of evidence demonstration to aggregate supplemental

analyses to support the modeling results.

In Section 7.1 of the Attainment Modeling Guidance EPA recommends three basic types of

analyses to supplement the primary analyses. They are:

1. Additional modeling

2. Analysis of trends in ambient air quality and emissions

3. Observational models and diagnostic analyses. 

7.3.a. Other Modeling Results

In Section 7.1 of the Attainment Modeling Guidance EPA suggests several additional modeling

exercises that can be performed as part of a supplemental/WOE analysis, including the use of

available regional or national scale modeling applications that are suitable for the local area.

Other regional or national scale modeling studies that contain results for West Virginia include

FINAL Charleston, WV 1997 PM2.5 SIP Page 103
modeling done for other RPOs and EPA. Other modeling studies may use different physical and

chemical modeling options for their meteorological and air quality runs, which would provide a

comparison or sensitivity based on these different options.

7.3.a.1. EPA’s CAIR Modeling

One air quality modeling exercise that contains results for West Virginia’s nonattainment areas

is the EPA’s modeling for the CAIR. The Technical Support Document for the CAIR, March

2005, provides modeling results with and without the implementation of the CAIR. Differences

between the EPA’s modeling and the attainment demonstration are:

4. The meteorology was for 2001,

5. The DVB was the weighted design values for the 1999-2003 period, and

6. The modeling results were for 2010.

The DVF was calculated using the CAIR SMAT tool, so methodologies between the CAIR DVF

and the values presented in Section 7.2 are the same. The CAIR modeling results are listed in

Table 7.3-1.

Table 7.3-1. EPA CAIR Modeling Results

State County Average 

99-03

2010

Base

2010

CAIR

2015

Base

2015

CAIR

Charleston Nonattainment Area

WV Kanawha 17.75 17.56 15.27 17.17 14.66

Huntington Nonattainment Area

WV Cabell 17.22 17.03 15.08 16.86 14.64

KY Boyd 15.37 15.23 13.38 15.06 12.95

OH Lawrence 16.26 16.10 14.11 15.92 13.71

OH Scioto 18.26 18.13 15.98 17.92 15.55

Martinsburg Nonattainment Area

WV Berkeley 16.18 15.69 13.43 15.32 12.73

Parkersburg Nonattainment Area

WV Wood 16.88 16.66 14.14 16.69 13.88

Weirton Nonattainment Area

WV Brooke 16.96 16.63 14.42 16.51 14.05

WV Hancock 17.40 17.06 14.89 16.97 14.54

OH Jefferson 18.30 17.94 15.64 17.83 15.26

FINAL Charleston, WV 1997 PM2.5 SIP Page 104
Table 7.3-1. EPA CAIR Modeling Results

State County Average 

99-03

2010

Base

2010

CAIR

2015

Base

2015

CAIR

Wheeling Nonattainment Area

WV Marshall 16.07 15.81 13.46 15.52 12.87

WV Ohio 15.37 15.14 12.81 14.84 12.22

Attainment Areas

WV Harrison 14.40 14.15 11.90 13.82 11.31

WV Marion 15.58 15.32 12.90 14.98 12.23

WV Mercer 12.97 12.52 10.82 12.14 10.16

WV Monongalia 14.96 14.77 12.31 14.37 11.40

WV Raleigh 13.54 13.19 11.33 12.80 10.66

WV Summers 10.46 10.21 8.63 9.89 8.07

The EPA’s results were for the highest monitor in a county where more than one monitor is

located. The EPA’s modeling results predict that the Charleston (Kanawha County)

nonattainment area will be 15.27 μg/m3

 in 2010, which is 0.5 μg/m3 higher than predicted in

2009 by the attainment test (14.8 μg/m3

 at the South Charleston site, 039-1005) . However,

monitoring shows that the South Charleston monitor had an annual PM2.5 concentration in 2008

of 14.19 μg/m3

, which is more consistent with the 14.8 μg/m3 predicted by the attainment test for

2009. It should be noted that the ASIP modeling was performed using a finer grid resolution and

a more refined emissions inventory. Therefore, it should yield more accurate results than the

CAIR modeling. Nevertheless, the relatively close match between the two provides additional

weight of evidence that Charleston should attain the PM2.5 NAAQS by 2009. 

7.3.a.2. Midwest RPO Modeling

Another air quality modeling exercise that contains results for West Virginia’s nonattainment

areas is the Midwest RPO’s modeling for PM2.5. Differences between the Midwest RPO’s

modeling and the attainment demonstration are:

1. The meteorology was for 2005,

2. The base year emission inventory was 2005, and

3. The DVB was the weighted design values for the 2001-2005 period.

4. The CAMx modeling platform was used.

The Midwest RPO modeling results are listed in Table 7.3-2 and are available at 

http://www.ladco.org/reports/technical_support_document/tsd/tsd_version_iv_april_25_2008_fi

nal.pdf.

FINAL Charleston, WV 1997 PM2.5 SIP Page 105
Table 7.3-2. LADCO - Round 5 - 2009 Results

Site ID County 2003-

2005

2004-

2006

2005-

2007

Base

Year

Design

Value

Future

Year

Design

Value

Charleston Nonattainment Area

5403900101 Kanawha 15.1 15.0 15.4 15.2 13.0

5403900111 Kanawha 13.6 13.2 12.2 13.0 11.2

5403910051 Kanawha 16.6 16.4 16.6 16.5 14.4

Huntington Nonattainment Area

5401100061 Cabell 16.3 16.1 16.6 16.3 13.6

390870010 Lawrence, OH 15.0 15.0 15.7 15.2 12.7

391450013 Scioto, OH 14.6 14.5 15.3 14.8 12.2

Parkersburg Nonattainment Area

5410710021 Wood 15.4 15.3 15.4 15.4 12.9

Weirton Nonattainment Area

5400900051 Brooke 16.8 16.4 16.4 16.5 13.5

5402900111 Hancock 16.4 15.7 15.9 16.0 13.0

5402910041 Hancock 16.6 15.4 15.2 15.7 12.8

390810016 Jefferson, OH 16.7 15.4 15.1 15.7 12.5

390811001 Jefferson, OH 17.2 16.3 16.4 16.6 13.4

Wheeling Nonattainment Area

5405110021 Marshall 15.3 15.0 15.2 15.2 12.4

5406900081 Ohio 14.6 14.1 0.0 14.4 11.7

5406900101 Ohio 15.4 14.3 14.6 14.8 12.0

Attainment Areas

5403300031 Harrison 13.9 13.9 14.2 14.0 11.6

5404900061 Marion 15.0 14.9 15.3 15.1 12.7

5405500021 Mercer 12.8 13.3 14.5 13.5 10.7

5406100031 Monongalia 14.5 14.1 14.4 14.3 11.9

5408100021 Raleigh 12.9 12.8 13.0 12.9 10.9

5408900011 Summers 10.6 11.2 12.5 11.4 8.7

FINAL Charleston, WV 1997 PM2.5 SIP Page 106
7.3.b. Trends in Ambient Air Quality and Emissions

Table 7.3.b-1. Air Monitoring Data for Charleston Area

AIRS

ID

County 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

039-0010 Kanawha 17.8 16.1 16.5 15.4 14.6 14.3 16.3 14.3 15.5 12.9

039-1005 Kanawha 19.0 18.1 18.1 17.1 16.1 15.9 17.7 15.6 16.5 14.2

Figure 7.3.b-1. Chart showing trend in PM2.5 monitoring data in the Charleston area.

As shown in Table 7.3.b-1 and Figure 7.3.b-1 the air quality in the Charleston area has been

improving, showing a downward trend in the PM2.5 concentrations. In addition, as shown in

7.3.b.2. the emissions of PM, NOx and SO2 have also been decreasing. Air quality monitoring for

CY2008 measured the PM2.5 concentration at the Charleston monitor at 12.9 μg/m3, and at the

South Charleston monitor at 14.2 μg/m3

; both these monitored values are well below 15.0 μg/m3.

Although the CY2008 annual averages were below 15.0 μg/m3

, the three year design values were

14.22 and 15.44 μg/m3, respectively.

See Appendix J, Section 3 for discussion of additional supplemental analyses, including MATS

modeling, CAMx modeling, and PSAT modeling. The results of all these models support the

conclusion that the Charleston area will attain the standard by the April 2010 deadline.

Charleston

10

11

12

13

14

15

16

17

18

19

20

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

PM2.5 ug/m3)

Annual PM2.5 Standard

Kanawha (54-039-0010)

Kanawha (54-039-1005)

Linear (Annual PM2.5 Standard)

Linear (Kanawha (54-039-0010))

Linear (Kanawha (54-039-1005))

FINAL Charleston, WV 1997 PM2.5 SIP Page 107
Figure 7.3.b-2. Point source emissions for 1999, 2002 and 2005 in the Charleston Area.

Charleston Area - PM10 Filterable

0

500

1,0001,5002,0002,5003,0003,500

1999 2002 2005

tons/year Kanawha, WV Putnam, WV

Charleston Area - PM2.5 Fi

0

200400600800

1,0001,2001,4001,600

1999 2002 

tons/year 

Charleston Area - NOX

0

10,00020,00030,00040,00050,00060,00070,00080,00090,000

1999 2002 2005

tons/year Kanawha, WV Putnam, WV

Charleston Area - SO2

0

20,00040,00060,00080,000

100,000120,000140,000160,000

1999 2002 

tons/year 

FINAL Charleston, WV 1997 PM2.5 SIP 
7.4. Unmonitored Area Analysis

Pursuant to the Guidance on the Use of Models and Other Analyses for Demonstrating

Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze, West Virginia is

including an additional review, termed Unmonitored Area Analysis, as part of the State

Implementation Plan. This review is intended to ensure that a control strategy leads to

reductions in PM2.5 at other locations which could have baseline (and future) design values

exceeding the NAAQS were a monitor located there. The purpose of the analysis is to use a

combination of model output and ambient data to identify areas that might exceed the NAAQS if

monitors were located there. Considering WV’s particular circumstances, however, we believe a

rigorous approach to the unmonitored area analysis is unnecessary as described in terms of actual

monitored values, RRFs, Charleston Area Terrain Features, and sulfates. As such, WV believes

that future year design values will not be greater than the NAAQS in areas that are not

monitored. 

The unmonitored area analysis is intended to be the primary means for identifying high PM2.5

concentrations outside of traditionally monitored locations. The spatial resolution of the

modeling that is the underlying basis of the unmonitored area analysis will determine how well it

addresses primary PM2.5 hotspot issues. The finer the resolution of the grid model, the more

likely primary PM2.5 hotspots will be identified. Based on the monitoring guidance, it is believed

that an unmonitored area analysis conducted at 12km or finer resolution is sufficient to address

unmonitored PM2.5 for the annual NAAQS.

EPA’s PM2.5 projection procedure includes an unmonitored area analysis that has been

established in MATS (Modeled Attainment Test Software). The unmonitored area analysis uses

the future-year annual PM2.5 Design Values projection procedure applied to each grid cell in the

modeling domain. In this procedure, the current-year (2002) annual PM2.5 Design Values (DVC)

are interpolated to each grid cell in the modeling domain. For a more detailed explanation of the

procedure see Section 4.9 of the ASIP TSD contained in Appendix N.2.

Table 7.4 shows the current-year (DVC) and projected future-year (DVF) PM2.5 design values

(μg/m3

) in West Virginia and adjoining areas using the 2002 Base G2 and 2009, 2012 and 2018

Base G4 CMAQ 12 km modeling results.

Figures 7.4-1 and -2 display the DVCs interpolated to the 12 km CMAQ domain using MATS

and the CMAQ 12 km 2002 Base G2 modeling results. The spatial distribution of the gridded

DVCs are displayed with the monitoring site locations in Figure 7.4-1, and without the

monitoring site locations displayed in Figure 7.4-2, so that they don’t obscure any of the

interpolated DVCs.

Figure 7.4-3 displays the MATS unmonitored area analysis projected using 2009 PM2.5 design

values using the CMAQ 12 km modeling results for the 2009 Base G4 emissions scenario.

As expected, the MATS tool indicates higher concentrations (yellow) around the discrete West

Virginian monitors that have violations in 2002. Those potential "hotspots" disappear on the

2009 map because of the modeled air quality improvement. The absence of such hotspots

confirms that the unmonitored areas should also attain the PM2.5 NAAQS.

FINAL Charleston, WV 1997 PM2.5 SIP Page 109
The MATS unmonitored area analysis projections for 2012 and 2018 using the CMAQ 12 km

modeling results are available in Section 4.9 of the ASIP TSD contained in Appendix N.2.

Table 7.4. VISTAS Regional Scale Modeling Results

AIRS ID County

2002

Annual

DVC

Annual Difference

2009 2012 2018 09-02 12-02 18-02

Charleston Nonattainment Areas

54-039-0010 Kanawha 15.4 13.1 12.2 11.7 -2.3 -3.2 -3.7

54-039-1005 Kanawha 17.1 14.7 13.7 13.2 -2.4 -3.4 -3.9

Huntington Nonattainment Area

54-011-0006 Cabell 16.5 14.4 13.7 13.3 -2.2 -2.9 -3.3

21-019-0017 Boyd, KY 14.9 12.6 11.9 11.5 -2.3 -2.9 -3.4

39-087-0010 Lawrence, OH 15.7 13.7 13.1 12.7 -2.0 -2.6 -3.0

39-145-0013 Scioto, OH 17.1 14.7 14.2 13.5 -2.4 -2.9 -3.6

Martinsburg Nonattainment Area

54-003-0003 Berkeley 16.2 13.5 12.9 12.3 -2.7 -3.3 -3.9

Parkersburg Nonattainment Area

54-107-1002 Wood 16.1 13.8 13.4 12.6 -2.3 -2.7 -3.4

Weirton Nonattainment Area

54-009-0005 Brooke 16.7 13.6 13.3 12.6 -3.1 -3.4 -4.1

54-029-0011 Hancock 16.0 13.0 12.6 11.9 -3.0 -3.4 -4.1

54-029-1004 Hancock 17.3 14.0 13.7 13.0 -3.3 -3.6 -4.3

39-081-0016 Jefferson, OH 18.1 14.9 14.5 13.8 -3.2 -3.6 -4.3

39-081-1001 Jefferson, OH 17.5 14.3 13.9 13.2 -3.2 -3.6 -4.3

Wheeling Nonattainment Area

54-051-1002 Marshall 15.6 13.2 12.7 12.1 -2.4 -3.0 -3.5

54-069-0010 Ohio 15.1 12.6 12.1 11.5 -2.4 -3.0 -3.5

FINAL Charleston, WV 1997 PM2.5 SIP Page 110
Table 7.4. VISTAS Regional Scale Modeling Results

AIRS ID County

2002

Annual

DVC

Annual Difference

2009 2012 2018 09-02 12-02 18-02

Attainment Areas

54-033-0003 Harrison 14.0 11.6 10.7 10.4 -2.4 -3.3 -3.6

54-049-0006 Marion 15.3 12.9 12.0 11.6 -2.5 -3.4 -3.7

54-055-0002 Mercer 12.7 10.6 9.7 9.1 -2.1 -3.0 -3.6

54-061-0003 Monongalia 14.8 12.3 11.5 11.0 -2.5 -3.3 -3.8

54-081-0002 Raleigh 13.1 11.0 10.1 9.5 -2.1 -2.9 -3.5

54-089-0001 Summers 10.1 8.3 7.6 7.1 -1.8 -2.5 -3.0

FINAL Charleston, WV 1997 PM2.5 SIP Page 111
Figure 7.4-1. 2002 Current-year PM2.5 Design Values (DVC), displaying monitoring sites,

interpolated to 12 km domain by MATS unmonitored area analysis.

FINAL Charleston, WV 1997 PM2.5 SIP Page 112
Figure 7.4-2. 2002 Current-year PM2.5 Design Values (DVC), without monitoring sites

displayed, interpolated to 12 km domain by MATS unmonitored area analysis.

FINAL Charleston, WV 1997 PM2.5 SIP Page 113
Figure 7.4-3. 2009 projected PM2.5 Design Values (DVF) calculated using MATS unmonitored

area analysis.

FINAL Charleston, WV 1997 PM2.5 SIP Page 114
8.0. CLEAN AIR ACT SECTION 172(C) REQUIREMENTS

Section 172(c) of the Clean Air Act, as amended, contains the general requirements for the

nonattainment areas. These requirements are listed below and are discussed in more detail in this

Section.

Section 172(c) Nonattainment Plan Provisions

(1) Reasonably available control measures (RACM)

(2) Reasonable further progress (RFP)

(3) Actual emissions inventory and periodic emissions inventory

(4) New source review

(5) Permit requirements for new and modified sources

(6) Other measures as may be necessary to provide attainment by specified attainment date

(7) Compliance with Section 110(a)(2)

(8) Equivalent techniques

(9) Contingency measures

8.1. Reasonably Available Control Measures

Section 172(c)(1) of the CAA requires SIPs to provide for the implementation of RACM to

demonstrate attainment as expeditiously as practicable. A subset of RACM is reasonably

available control technology (RACT), which relates specifically to stationary point sources.

In April 2007 the EPA promulgated the PM2.5 Implementation Rule which established the

requirements for RACM and RACT for PM2.5 nonattainment areas. The EPA stated that if a State

projects that an area will attain the standard within 5 years of designation as a result of existing

measures (i.e., projected to have a design value of 14.5 μg/m3 or lower), then the State may

conduct a limited RACT and RACM analysis that does not involve additional modeling.

Additionally, if a State could not achieve significant emissions reductions during 2008 due to the

time required to implement the potential measures or other relevant factors, then the State could

conclude that there are no further RACM for the nonattainment area that would advance the

attainment date by one year or more.

The predicted design value for the Charleston area is 14.8 μg/m3

, below the standard, but not

below the 14.5 μg/m3

 suggested by EPA to allow a limited RACT and RACM analysis.

However, both the Charleston and South Charleston monitors measured below 14.5 μg/m3

 for

CY2008, 12.9 and 14.2 μg/m3

, respectively. Since the monitored values for CY2008 were well

below the annual PM2.5 standard, the WVDAQ determined it was appropriate to conduct a

limited RACT and RACM analysis. A few RACM type measures have already been

implemented by the WVDAQ, including 45CSR6, and 45CSR17, which were discussed in

Section 6.

Additional RACM measures could not be implemented during 2008, even if cost effective

measures were available. It would take at least two years to complete rule making and another

eighteen months to two years for implementation of any new control measures. There are no

other RACM measures available to advance the attainment date. See Section 9 for a detailed

discussion of RACM and RACT.

FINAL Charleston, WV 1997 PM2.5 SIP Page 115
Furthermore, the PM2.5 Implementation Rule includes a presumption that in States that fulfill

their CAIR SO2 emission reduction requirements entirely through EGU emission reductions,

compliance by EGU sources with an EPA-approved CAIR SIP or a CAIR FIP would satisfy their

SO2 RACM/RACT requirements. The PM2.5 Implementation Rule also includes a presumption

that in States that are subject to the CAIR annual NOx emission reduction requirements and

fulfill these requirements entirely through EGU emission reductions, compliance by EGU

sources with an EPA-approved CAIR SIP or a CAIR FIP would satisfy their NOx RACM/RACT

requirement for the PM2.5 NAAQS, provided that sources with existing selective catalytic

reduction (SCR) emission control technology installed on their boilers operate that technology

on a year round basis beginning in 2009. 

West Virginia is subject to the CAIR and has adopted, and submitted for SIP approval, 45CSR39

– Control of Annual Nitrogen Oxide Emissions to Mitigate Interstate Transport of Fine

Particulate Matter and Nitrogen Oxides; and 45CSR41 – Control of Annual Sulfur Dioxide

Emissions to Mitigate Interstate Transport of Fine Particulate Matter and Sulfur Dioxide. Both of

these rules rely entirely on EGU emission reductions to satisfy the annual NOx and SO2 reduction

requirements. West Virginia is subject to the CAIR FIP until EPA approves the CAIR SIP. 

West Virginia has a three utility companies that have units equipped with existing SCRs:

• Virginia Electric and Power Company - Mt. Storm Power Station

• American Electric Power - John Amos, Mountaineer and Mitchell Power Stations

• Allegheny Energy Supply - Harrison and Pleasants Power Stations.

Virginia Electric and Power Company and American Electric Power are both subject to federal

Consent Decrees which require the year round operation of the existing SCRs beginning January

1, 2008. [See Appendix M for copies of the Consent Decrees.]

Allegheny Energy Supply has entered into Consent Orders with the State and agreed to operate

the SCRs on the units at Harrison and Pleasants whenever the units are in operation, except for

periods of required SCR maintenance, beginning January 1, 2009. [See Appendix M for copies

of the Consent Orders.]

Therefore, compliance with the CAIR requirements satisfy the SO2 and NOx RACM/RACT

requirements for electric generating units.

8.2. Reasonable Further Progress

In the PM2.5 Implementation Rule at 40 CFR 51.1009(b), the EPA maintained that an area that

demonstrates attainment by 2010 would be considered to have satisfied the RFP requirement and

need not submit any additional material to satisfy this requirement. The EPA will view the

attainment demonstration as demonstrating that the area is making reasonable progress toward

attainment. Herein, the DEP demonstrates that the Charleston area will attain by 2010.

Therefore, RFP is satisfied and further RFP analysis is unwarranted.

FINAL Charleston, WV 1997 PM2.5 SIP Page 116
8.3. Actual Emissions Inventory

Section 172(c)(3) requires the development of a comprehensive, accurate current inventory of

actual emissions from all sources in the nonattainment area. Such inventory is due two years

after the effective date of the PM2.5 non attainment designations, i.e., April 5, 2007. The

WVDAQ met this requirement through the submittal of the 2002 emission inventories under the

CERR for the West Virginia counties in this nonattainment area.

The WVDAQ submitted statewide emissions for point, area, nonroad mobile and highway

mobile sources. The final 2002 emission inventories used in the attainment demonstration will

go through the public hearing process with the full attainment demonstration, which will include

any updates or revisions that are necessary since the CERR submittal.

8.4. Periodic Emissions Inventory

Section 172(c) of the CAA requires the submittal of periodic emission inventories. The WVDAQ

plans to meet this requirement through the CERR submittals. As such, the WVDAQ submitted

the 2005 emissions inventory June 1, 2007. Similar to the 2002 CERR submittal, the 2005 CERR

submittal included statewide emissions for point, area, nonroad mobile and highway mobile

sources.

8.5. Permitting Requirements for New and Modified Sources

CAA Section 172(c)(5) requires a permit program consistent with the requirements of Section

173. On June 13, 1984, West Virginia requested that EPA approve regulation 45CSR14 "Permits

for the Construction and Major Modification of Major Stationary Sources of Air Pollution for the

Prevention of Significant Deterioration" (PSD) as a revision to the state implementation plan. 

Following State response to EPA identified inconsistencies with federal requirements, EPA

approved the PSD SIP revision in the April 11, 1986 Federal Register [51 FR 12517]. EPA

approved subsequent revisions to the PSD SIP in 1993 [58 FR 34526] and in 1996 [61 FR

54734]. In 2005 West Virginia revised 45CSR14 to incorporate changes required by EPA in the

December 31, 2002 Federal Register [67 FR 80186], with the changes becoming effective June

1, 2005. Subsequent to the changes becoming effective the District of Columbia (DC) Circuit

Court vacated and remanded key provisions of the December 31, 2002 federal rule. On

December 1, 2005 the State requested that EPA approve the revised 45CSR14 as part of the SIP,

and on December 22, 2005 requested that EPA not act on the portions of the rule that correspond

to the provisions of the federal rule that had been vacated. On November 2, 2006 EPA approved

the revisions to 45CSR14 as part of the SIP [see 71 FR 64470].

West Virginia has also implemented as part of its SIP since 1972, 45CSR13 "Permits for

Construction, Modification, or Relocation of Stationary Sources of Air Pollutants, and

Procedures for Registration and Evaluation" requiring construction/modification permits for all

regulated emission sources. EPA approved the most recent revisions to 45CSR13 as a SIP

revision effective April 29, 2003 [68 FR 9559]. 

In 1983 West Virginia enacted rule 45CSR19 “Requirements for Pre-Construction Review,

Determination of Emission Offsets for Proposed New or Modified Stationary Sources of Air

Pollutants and Bubble Concept for Intrasource Pollutants” for permitting of major sources and

FINAL Charleston, WV 1997 PM2.5 SIP Page 117
modifications in designated nonattainment areas pursuant to Clean Air Act requirements. This

rule was made part of the SIP effective August 1, 1985 [see 50 FR 27247]. 

The 1990 CAAA part "D" new source requirements for West Virginia's ozone nonattainment

areas were not due for submission to EPA until November 15, 1992. The West Virginia Air

Pollution Control Commission, however, adopted (November 10, 1992) by Emergency Rule

revisions to existing regulation 45CSR19 "Requirements for Pre-Construction Review,

Determination of Emission Offsets for Proposed New or Modified Stationary Sources of Air

Pollutants and Emission Trading for Intrasource Pollutants" reflecting to the extent possible the

new CAAA part D requirements (i.e. offsets). The 1992 version of 45CSR19 was adopted as a

Legislative Rule on July 7, 1993 and submitted to EPA on August 10, 1993 as a SIP revision.

Subsequently EPA notified the State of deficiencies in the SIP revision. West Virginia revised

45CSR19 to correct the identified deficiencies and to incorporate changes required by EPA in

the December 31, 2002 Federal Register [67 FR 80186], with the changes becoming effective

June 1, 2005 [see Appendix K]. Subsequent to the changes becoming effective the DC Circuit

Court vacated and remanded key provisions of the December 31, 2002 federal rule. On

December 1, 2005 the State requested that EPA approve the revised 45CSR19 as part of the SIP,

and on December 22, 2006 requested that EPA not act on the portions of the rule that correspond

to the provisions of the federal rule that had been vacated. On November 2, 2006 EPA approved

the revisions to 45CSR19 as part of the SIP [see 71 FR 64468]. Therefore, West Virginia has a

nonattainment NSR program which has been approved by EPA.

8.6. Other Measures

Section 172(c)(6) requires the nonattainment SIPs to include enforceable limitations and other

control measures, along with schedules for compliance as needed to demonstrate attainment.

Section 6.0 of this document discusses in detail the Federal and State measures that were

modeled to show attainment. Appendix K contains the rules and compliance schedules.

8.7. Compliance with Section 110(a)(2)

Section 172(c)(7) of the CAA requires nonattainment SIPs to meet the applicable provisions of

Section 110(a)(2). On October 2, 2007, the EPA provided guidance on SIP elements required

under Section 110(a)(1) and (2) for the PM2.5 NAAQS. On April 3, 2008, WVDAQ submitted a

document to EPA Region III which certified that specific elements under Section 110(a)(2) were

satisfied by certain portions of the West Virginia SIP. On May 22, 2008, WVDAQ submitted a

general infrastructure PM2.5 SIP, which covered the remaining elements not previously certified

to be in the SIP.

The only SIP element of concern is 110(1)(2)(G) which relates to emergency episodes and

contingency plans. At this time, EPA has not promulgated standards for significant harm levels.

EPA also has not promulgated standards for emergency episode plans. The states look to EPA to

provide this information in order to adopt the necessary rules that will protect the public health.

Once the EPA has promulgated rules for significant harm levels and emergency episode plans,

the WVDAQ will start the rulemaking process to adopt these standards.

On October 22, 2008, EPA published a finding that West Virginia had submitted a complete

State Implementation Plan (SIP) that provides the basic program elements specified in section

FINAL Charleston, WV 1997 PM2.5 SIP Page 118
110(a)(2) of the Clean Air Act (CAA or Act) necessary to implement the 1997 Fine Particulate

Matter (PM2.5) National Ambient Air Quality Standards (NAAQS) [73 Federal Register

62902/62905].

8.8. Equivalent Techniques

The WVDAQ believes that the procedures for modeling, emissions inventory and planning

follow EPA guidance and is not requesting approval for equivalent techniques, as envisioned

under Section 172(c)(8).

8.9. Contingency Measures

Section 172(c)(9) of the Clean Air Act, as amended, requires that nonattainment area SIPs

provide for the implementation of specific measures, termed contingency measures, if an area

fails to attain the NAAQS in a timely manner or to achieve RFP. Basically, the SIP is the plan to

reach attainment and the contingency measures provide a backup plan if the original plan proves

to be insufficient. Section III(C)(3) of the General Preamble further explains that contingency

measures should consist of other available control measures, beyond those necessary to meet the

core control requirement to implement reasonably available control measures (RACM) [see

Section 172(c)(1) of the Act] and, therefore, beyond those reasonably required to expeditiously

attain the standards (see 57 FR 13543).

Section 172(c)(9) of the Act specifies that contingency measures shall “take effect . . . without

further action by the State, or the [EPA] Administrator.” EPA has interpreted this latter

requirement [in the General Preamble (at 57 FR 13512)] to mean that no further rulemaking

activities by the State or EPA would be needed to effect full implementation of the contingency

measures, to occur within 60 days after EPA notifies the State of its failure to attain the NAAQS

in a timely manner or to achieve RFP.

EPA recognizes that certain actions, such as notification of sources, modifications of permits,

etc., may be needed before some measures could be implemented. However, States must show

that their contingency measures can be implemented with minimal further administrative action

on their part and with no additional rulemaking actions such as public hearings or legislative

review.

8.9.a. Enforceability Issues

All measures and other elements in the SIP must be enforceable by the state/local governments

and/or EPA [see Section 172(c)(6) and 110(a)(2)(A) of the Act and 57 FR 13556].

Nonattainment area plan provisions must also contain a program to provide for enforcement of

control measures and other elements of the SIP [see Section 110(a)(2)(C) of the Act].

The State of West Virginia has the authority to implement and enforce all emission limitations

and control measures adopted by this SIP.

In accordance with EPA’s guidance encouraging early implementation of contingency measures

to guard against failure to either meet a milestone or attain the NAAQS, West Virginia has

FINAL Charleston, WV 1997 PM2.5 SIP Page 119
implemented the contingency measures identified in Section 8.9.c. EPA’s guidance on early

implementation of control measures is as follows:

The EPA encourages the early implementation of required control measures and of

contingency measures as a means of guarding against failures to meet a milestone or

to attain. Any implemented measures (that are not needed for the rate-of-progress

requirements or for the attainment requirements) would need to be backfilled only

to the extent that they are used to meet a milestone.

The reductions from the designated contingency measures exceed those required to demonstrate

attainment. They will not be used to meet that milestone requirement. As a result, the state will

not be required to backfill any contingency measures that we choose to implement in advance of

the requirement. 

8.9.b. Evaluations/Suggested Reductions

The PM2.5 Implementation Rule at 40 CFR §51.1012 [72 FR 20667, 25 APR 2007], consistent

with Section 172(c)(9) of the Clean Air Act, requires that each attainment plan contain

contingency measures to be undertaken if the area fails to attain the standard by its attainment

date. In the preamble to the Implementation Rule [72 FR 20643, 25 APR 2007] EPA suggests

that contingency measures should provide for emission reductions equivalent to about one year

of reductions needed for RFP, based on the overall level of reductions needed to demonstrate

attainment divided by the number of years from the 2002 base year to the attainment year.

However, EPA acknowledged that this level of reductions may be excessive in some cases.

Table 8.9-1 shows the calculation of the suggested reductions for the Charleston area.

Table 8.9-1. Contingency Targets for PM and PM Precursors

PM 

Precursor

PM and PM Precursor Emissions 2002-2009 (tons/year)

2002

(base year)

2009

(modeled

attainment year)

2002-2009

(years)

Contingency 

Calculation

(2002-2009)

7

Charleston Nonattainment Area

NOx 75,922 30,425 45,497 6,500

PM2.5 Direct 3,410 3,357 53 8

SO2 133,245 54,846 78,399 11,200

West Virginia reviewed the SO2, NOx and PM2.5 emissions projected to remain in 2009 in the

nonattainment area, including all sectors except EGUs (see Table 8.9-2). The EPA determined

that CAIR controls are available and cost-effective for EGUs through 2015 but that additional

controls beyond CAIR are infeasible within that time.

FINAL Charleston, WV 1997 PM2.5 SIP Page 120
Table 8.9-2. Projected 2009 Emissions, excluding EGUs

Area SO2 (tons) NOx (tons) PM2.5 (tons)

Charleston 9,786 18,629 2,890

We also considered the required percent reduction of the projected remaining 2009 emissions

(excluding EGUs) for all sectors (see Table 8.9-3).

Table 8.9-3. Percent Reduction of Projected 2009 Emissions (excluding EGUs) Needed

to Meet Suggested Contingency Targets 

Area SO2 NOx PM2.5

Charleston 114.45% 34.89% 0.26%

West Virginia has demonstrated that the target for contingency measures equal to one full year’s

worth of the emission reductions necessary to achieve attainment is excessive within the

Charleston area, since it is unreasonable to expect to achieve a 114% and 35% reduction in SO2

and NOx emissions, respectively, from the remaining point sources, area sources and mobile

sources – both nonroad and onroad – within one year. Therefore, the state extended its analysis

to other areas in the state which impact the designated nonattainment area.

8.9.c. Identified Contingency Measures for the Charleston Area

Contingency reductions must occur on a timetable that is directly related to the attainment SIP

schedule. States have no more than one year after notification by EPA of an attainment failure to

achieve the contingency plan reductions. For a potential attainment failure, notification would be

received in 2010; therefore, the contingency reductions must be achieved no later than 2011.

EPA suggested in the PM2.5 Implementation Rule [72 FR 20636, 25 APR 2007] that for direct

PM2.5 – only emissions from within the nonattainment area could be considered, however for SO2

and NOx states could consider not only all emissions in the nonattainment area, but also

emissions within a distance of up to 200 kilometers from the nonattainment area. Therefore, we

looked at expected emissions reductions both inside and outside the nonattainment area. The

map below (Figure 8.9-1) shows the Charleston nonattainment area and the 200 kilometers

around the area. Table 4 of Appendix L identifies the counties that are located within 200

kilometers of each nonattainment area.

FINAL Charleston, WV 1997 PM2.5 SIP Page 121
Figure 8.9-1. Map of Charleston PM2.5 Nonattainment Area showing 200 km around area, showing all power pl

sources of contingency measures. 

FINAL Charleston, WV 1997 PM2.5 SIP 
To ensure that the contingency measures from outside the nonattainment area actually impact the

area, an SO2 Area of Influence (AoI) was defined for the Charleston area to represent the

geographic area containing sources that would likely have the greatest impact on PM2.5

concentrations in the Charleston area.

The first step was to generate meteorological back trajectories for monitoring sites in West

Virginia. 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.

Trajectories were started at 100 meters and 500 meters above the surface and run backward from

the site for 72 hours.

The next step was to plot residence time for each monitor using five years of back trajectories for

the high PM2.5 days in 2000-2004. Residence time is the frequency that winds pass over a

specific geographic area on the way to a monitor. Separate residence time plots were generated

using trajectories with 100m and 500m start heights.

The next step was to develop sulfate weighted residence time plots to define the geographic area

with the highest probability of influencing the monitor on the high PM2.5 days in 2000-2004 that

were dominated by sulfate. Sulfate weighted back trajectories for the high PM2.5 days were

combined for 5 years of data. The resulting sulfate weighted residence time plots were used to

define the geographic Area of Influence for sources of SO2 emissions. In Figures 8.9-2 and 8.9-3

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 orange.

FINAL Charleston, WV 1997 PM2.5 SIP Page 123
Figure 8.9-2. SO2 Area of Influence for Charleston nonattainment area. Green circles indicate 100-km and 200-

Charleston PM2.5 monitor. Red line perimeter indicates AoI with a Residence Time $ 10%. Orang

indicates AoI with a Residence Time $ 5%. 

FINAL Charleston, WV 1997 PM2.5 SIP 
Figure 8.9-3. SO2 Area of Influence for Charleston nonattainment area, showing county outlines. Green circles 

200-km radii from the Charleston PM2.5 monitor. Red line perimeter indicates AoI with a Residen

Orange line perimeter indicates AoI with a Residence Time $ 5%. 

FINAL Charleston, WV 1997 PM2.5 SIP 
West Virginia is primarily relying on contingency measures which achieve emission reductions

from the shutdown of specific emission units, the replacement of specific coal-fired boilers with

natural gas-fired boilers, and the installation of controls on specific units within 200 kilometers,

that are also within the Area of Influence. These reductions were not included in the modeled

attainment demonstration and are therefore creditable.

There have been two plant shutdowns which occurred after 2002 in Kanawha and Putnam

counties – FMC Steam Plant (039-0002) and Flexsys (079-0001), resulting in emission

reductions (See Attachments 1 and 2 to Appendix L). Additional reductions will be achieved as a

result of the shut down of the Sulfuric Acid Regeneration plant at the DuPont Plant (039-0001)

located in Belle in Kanawha County, the shutdown of which is required no later than April 1,

2010 by Federal Consent Decree, Case 2:09-cv-99999. (See Attachment 3 to Appendix L for

copy of the Consent Decree.) 

Table 8.9-4. DuPont (039-0001) 2009 Projected Emissions Used in Attainment

Demonstration

Unit SO2

(tons)

NOx

(tons)

PM2.5

(tons)

SAR Process 947 43 1

SAR Process Preheater 0 8 0

SAR Conv Preheater 0 1 0

Total SAR Unit 947 52 1

In addition, the Philip Sporn Power Station (053-0001) in Mason County, also located within

200 km of the nonattainment area and within the AoI, installed selective non-catalytic reduction

(SNCR) on Units 31 and 41, which were put in-service in 2009 to comply with the eastern

system-wide annual tonnage limitation for NOx contained in the federal AEP Consent Decree.

(See Appendix M for a copy of the Consent Decree, see Attachment 4 to Appendix L for

documentation of the installation of SNCR at Sporn.) The installation of SNCR on these units is

expected to result in an additional 25 - 50% NOx reduction. Applying a conservative 25%

percentage reduction to the 2009 projected emissions, equates to a 740 ton NOx reduction

beyond that which was modeled. (See Table 8.9-5)

Table 8.9-5. Philip Sporn (053-0001) 2009 Projected Emissions Used in Attainment

Demonstration (units 31 and 41), and Expected NOx Reductions due to SNCR

Unit SO2

(tons)

PM2.5

(tons)

NOx

(tons)

Expected NOx

Reductions (tons)

Unit 31 6,565 18 1,491 373

Unit 41 6,465 18 1,468 367

Total 13,030 36 2,959 740

FINAL Charleston, WV 1997 PM2.5 SIP Page 126
There were additional reductions in Pleasants County, which is within 200 km of the

nonattainment area and also within the AoI. The Cabot (073-0006) carbon black facility was

shutdown in March of 2008, and at Cytec (073-0003) the coal-fired boilers were replaced with

natural gas-fired boilers. (See Attachments 5 and 6 to Appendix L for documentation of the

changes at Cabot and Cytec.) To estimate the reductions resulting from the replacement of the

boilers at Cytec, the permitted allowable emissions were subtracted from the 2009 projected

emissions, resulting in estimated reductions of 2,326 tons of SO2, 364 tons of NOx and 102 tons

of PM2.5. The reductions from the identified contingency measures are shown in Table 8.9-6,

below. (See Appendix L for documentation of contingency measures.)

Table 8.9-6. Contingency Measure Reductions from 2009 Emissions

Contingency Measure

2009

NOx (tons) PM2.5

(tons)

SO2 (tons)

FMC (039-0002) 481 1 822

DuPont (039-0001) 52 1 947

Flexsys (079-0001) 223 6 694

Cabot (073-0006) 896 92 7,975

Cytec (073-0003) 364 102 2,326

Philip Sporn (053-0001) 740 0 0

Total Reductions from Contingency Measures

(within nonattainment area and AoI) 2,756 202 12,764

Based upon historical growth patterns there is no reason to expect significant growth in any

sector for a one year period, therefore, we are looking only at the reductions identified above. 

However, additional emission reductions are still expected to occur as a result of EPA’s nonroad

measures, and EPA’s onroad measures (see Chapter 6). 

As shown in Table 8.9-7 the aggregate emissions in the nonattainment area and the 200

kilometers around the area are decreasing. Therefore, the total reductions estimated above will

not be offset by other increases within the subject areas.

FINAL Charleston, WV 1997 PM2.5 SIP Page 127
Table 8.9-7. Aggregate Emissions in the Charleston Nonattainment Area and Within

200 km of the Area

Area County

2002 2009

SO2 NOx PM2.5 SO2 NOx PM2.5

Charleston

Kanawha 24,534 28,184 2,257 27,543 20,081 2,158

Putnam 108,711 47,738 1,153 27,304 10,344 1,199

within 200 km 448,358 289,740 28,960 278,002 158,513 28,553

Total 581,603 365,662 32,370 332,849 188,938 31,910

While the contingency measures identified above do not fully meet the contingency targets (6500

tons NOx, 8 tons PM2.5 and 11,200 tons SO2) suggested by EPA in the PM2.5 Implementation Rule

(see Table 8.9-1) for NOx and PM2.5, they do account for significant reductions beyond what is

required for attainment. In fact, the reductions resulting from the contingency measures within

the AoI account for 130.4%, 14.8% and 7.0% of the 2009 projected SO2, NOx and PM2.5

emissions, excluding EGU emissions, respectively, in the nonattainment area. (See Table 8.9-8.)

Table 8.9-8. Projected 2009 Emissions, excluding EGUs

Area SO2

(tons)

NOx

(tons)

PM2.5

(tons)

Charleston NAA emissions, excluding EGUs 9,786 18,629 2,890

Contingency Measure Reductions within AoI from 2009

projections

12,763 2,756 202

% of 2009 Charleston NAA Emissions, excluding EGUs 130.4% 14.8% 7.0%

Table 8.9-9. Percentage Change in Emissions by Sector in the Charleston Area

(2002 to 2009) 

Sector NOx PM2.5 SO2

Area 2.5% -2.4% 7.2%

Nonroad -6.6% -10.3% -83.1%

Onroad -39.8% -31.3% -88.6%

Point -68.5% 12.4% -60.0%

Total -59.9% -1.6% -58.8%

Note: Positive values indicated increases, negative values indicate decreases.

FINAL Charleston, WV 1997 PM2.5 SIP Page 128
It is important to realize that the projected 2009 emissions reflect a 59.9% decrease in the 2002

NOx emissions, and 58.8% decrease in the 2002 SO2 emissions in the nonattainment area. Due to

the large reductions being achieved, it is practically impossible to identify additional reductions

in the AoI within West Virginia which could be achieved within one year. 

Furthermore, of the thirty-three (33) point sources in the Charleston nonattainment area, thirteen

(13) contain processes in the four (4) source categories identified for RACT analyses (see section

9.3 below). The emissions from these 13 sources accounted for 99.3% of the NOx, 85.9% of the

PM2.5 and 100% of the SO2 2002 point source emissions in the nonattainment area; and account

for 97.6% of the NOx, 88.0% of the PM2.5 and 100% of the SO2 2009 projected point source

emissions in the nonattainment area. In 2002, point sources accounted for 79.1% of the NOx,

18.5% of PM2.5 and 97.6% of the SO2 total emissions from all sectors (area, nonroad, onroad,

point, and biogenic) in the nonattainment area. 

Therefore, West Virginia has demonstrated that the suggested contingency targets are excessive

for the area due to the large EGU reductions expected, and the State has adopted sufficient

emission reduction measures for the Charleston area to meet the requirements of the 40 CFR

§51.1012.

FINAL Charleston, WV 1997 PM2.5 SIP Page 129
9.0. REASONABLY AVAILABLE CONTROL MEASURES (RACM), INCLUDING

REASONABLY AVAILABLE CONTROL TECHNOLOGY (RACT) FOR

STATIONARY SOURCES 

[40 CFR §51.1010]

Section 172(c)(1) of the Clean Air Act requires state implementation plans (SIPs) to include an

analysis of reasonably available control measures (RACM). This analysis is designed to ensure

that in the Charleston nonattainment area, the state implements all RACM necessary to

demonstrate attainment of the annual PM2.5 standard by the earliest date practical.

However, to effect an improvement in an annual PM2.5 concentration, reductions in emissions

would have to occur in the year prior to the desired attainment date. In other words, to advance

the attainment date by one year, from April 2010 to April 2009, additional controls, or upgrades

to existing controls would have to have been completed and operational during 2008. Given the

PM2.5 Implementation Rule promulgation on April 25, 2007, there was insufficient time to

implement additional reasonably available control measures. Thus, if major sources required

additional controls or substantial upgrades to existing ones, such controls could not have been

installed and become operational by January 2008. Therefore, the WVDAQ found there were no

reasonably available control measures that would have advanced the attainment date by one year.

9.1. Statutory and Regulatory Requirements for RACM Analysis

The statutory RACM requirement can be found in Section 172(c)(1) of the Clean Air Act, which

directs states to “provide for implementation of all reasonably available control measures as

expeditiously as practicable.” 

The regulatory RACM for a PM2.5 SIP revision can be found at 40 CFR §51.1010. This section

requires:

(a) For each PM2.5 nonattainment area, the State shall submit with the attainment

demonstration a SIP revision demonstrating that it has adopted all

reasonably available control measures (including reasonably available

control technology [RACT] for stationary sources) necessary to demonstrate

attainment as expeditiously as practicable and to meet any RFP [reasonable

further progress] requirements. The SIP revision shall contain the list of

potential measures considered by the State, and information and analysis

sufficient to support the State’s judgement that it has adopted all RACM,

including RACT.

(b) In determining whether a particular emission reduction measure or set of

measures must be adopted as RACM under section 172(c)(1) of the Act, the State

must consider the cumulative impact of implementing the available measures.

Potential measures that are reasonably available considering technical and

economic feasibility must be adopted as RACM if, considered collectively, they

would advance the attainment date by one year or more.

FINAL Charleston, WV 1997 PM2.5 SIP Page 130
9.2. Discussion of Reasonable Control Measures

During the period 2002-2005, the state implemented the control measures described in Section 6.

Significant additional control measures have already been adopted and are planned for

implementation in 2009, including the federal Clean Air Interstate Rule (CAIR). 

Modeling data provided in Section 4 demonstrates that continued implementation of the control

measures described in Section 6, along with CAIR, will allow the Charleston area to come into

compliance with the 1997 PM2.5 NAAQS on or before April 2010, as required by 40 CFR

§51.1004.

9.3. Discussion of RACT

Thirteen (13) facilities located in the Charleston nonattainment area are potentially subject to

reasonably available control technology (RACT) requirements, in four (4) source categories:

 • EGUs (Electric Generating Unit)– John Amos and Kanawha River Power stations;

 • ICEs (Internal Combustion Engine)– Bonham, Carbon, Clendenin, Coco, Lanham, and

Cornwell Compressor Stations;

 • ICI (Industrial, Commercial, Institutional) Boiler facilities – Bayer CropScience, DuPont,

FMC, Union Carbide, and Flexsys; and

 • SAR (Sulfuric Acid Recovery) facility – DuPont Belle.

These facilities each had actual emissions in 2002 of more than 50 tons of NOx, PM2.5 or SO2.

The 2002 emissions and 2009 projected emissions are presented in Table 9.3-1, below.

FINAL Charleston, WV 1997 PM2.5 SIP Page 131
Table 9.3-1. 2002 and 2009 Emissions of Potential RACT Sources in Charleston Area

Facility

2002 2009

NOx

(tons)

PM2.5

(tons)

SO2

(tons)

NOx

(tons)

PM2.5

(tons)

SO2

(tons)

John Amos (079-0006) 44,479 271 107,552 7,890 1,337 26,297

Kanawha River (039-0006) 6,139 118 15,691 3,907 129 18,763

Bonham Compressor Station

(039-0046) 113 2 0 123 2 0

Carbon Compressor Station

(039-0050) 119 1 0 108 1 0

Clendenin Compressor Station

(039-0048) 884 0 0 806 0 0

Coco Compressor Station (039-

0049) 278 6 0 252 6 0

Lanham Compressor Station

(039-0047) 1,088 13 0 1,016 15 1

Cornwell Compressor Station

(039-0051) 1,641 0 0 1,456 0 0

Bayer CropScience (039-0007) 2,850 48 3,245 1,408 53 3,553

FMC Steam Plant (039-0002) 479 1 854 481 1 822

Union Carbide (039-0003) 978 35 1,009 398 29 972

Flexsys (079-0001) 238 7 750 224 7 694

DuPont - Belle (039-0001) 411 41 1,006 413 44 992

In accordance with guidance published by EPA, West Virginia conducted detailed RACT

analyses for the four source categories listed above. (See Appendix M for the detailed RACT

analyses.)

WVDAQ determined that there are no potential measures, considering technical and economic

feasibility, that are reasonably available which could have been implemented in time to advance

the attainment date by one year or more.

FINAL Charleston, WV 1997 PM2.5 SIP Page 132
9.4. Evaluation of RACM for Purposes of Achieving Attainment

In accordance with 40 CFR §51.1010, as part of the SIP revision, the state is required to submit a

demonstration that it has adopted all RACM, including RACT, necessary to demonstrate

attainment as expeditiously as practicable and to meet any RFP requirements. 

In evaluating a particular measure or set of measures, that section of the rule directs the state to

consider the cumulative impact of implementing the available measures and potential reasonably

available control measures that, if considered collectively, would advance the attainment date by

one year or more.

The DAQ evaluation of the control measures described in detail in Section 6 demonstrates that

the cumulative impact of these previously adopted and on-going measures is sufficient to

demonstrate, by April 2010, attainment of the 1997 PM2.5 NAAQS. 

Thus, DAQ finds that no additional measures are necessary to demonstrate attainment as

expeditiously as practicable or to meet any RFP requirements. 

Furthermore, the time required to implement new regulatory programs in West Virginia exceeds

one year. DAQ reviewed and analyzed the list of potential control measures identified by EPA in

the PM2.5 Implementation Rule. The summary of the results of the analysis, provided below in

Tables 9.4-1 through 3, shows that there are no additional measures beyond those already on the

books that could be adopted and implemented by January 1, 2008.

For these reasons listed above, DAQ finds there are no potential reasonably available control

measures that would advance the attainment date by one year or more.

FINAL Charleston, WV 1997 PM2.5 SIP Page 133
Table 9.4-1. Analysis of Stationary Source Control Measures to Determine Reasonably

Available Control Measures (RACM)

Stationary Source Measures

Implementation by January 2008?Enforceable?Technologically Feasible?Economically Feasible?Adverse Impacts?Reductions >0.1 tpd?RACM: Yes/No?

Stationary diesel engine retrofit, rebuild or

replacement, with catalyzed particulate filter

No Yes Yes – No – No

New or upgraded emission control requirements for

direct PM2.5 emissions at stationary sources (e.g.,

installation or improved performance of control

devices such as a baghouse or electrostatic

precipitator; revised opacity standard; improved

compliance monitoring methods)

No Yes – – No Yes No

Improved capture of particulate emissions to increase

the amount of PM2.5 ducted to control devices, and to

minimize the amount of PM2.5 emitted to the

atmosphere, for example through roof monitors 

No Yes – – No – No

New or upgraded emission controls for PM2.5

precursors at stationary sources (e.g., SO2 controls

such as wet scrubbers or dry scrubbers, or reduced

sulfur content in fuel; desulfurization of coke oven

gas at coke ovens; improved sulfur recovery at

refineries; increasing the recovery efficiency at

sulfuric acid plants)

No Yes – – – Yes No

Energy efficiency measures to reduce fuel

consumption and associated pollutant emissions

(either from local sources or distant power providers)

No No Yes – No – No

Measures to reduce fugitive dust from industrial sites No Yes Yes – No No No

FINAL Charleston, WV 1997 PM2.5 SIP Page 134
Table 9.4-2. Analysis of Mobile Source Control Measures to Determine

Reasonably Available Control Measures (RACM)

Mobile Source Measures

Implementation by January 2008?Enforceable?Technologically Feasible?Economically Feasible?Adverse Impacts?Reductions >0.1 tpd?RACM: Yes/No?

Onroad diesel engine retrofits for school buses,

trucks, transit buses using EPA-verified technologies

No Yes Yes – No – No

Nonroad diesel engine retrofit, rebuild or

replacement, with catalyzed particle filter

No No Yes – No – No

Diesel idling programs for trucks, locomotive, and

other mobile sources

No No Yes Yes No – No

Transportation control measures (including those

listed in section 108(f) of the CAA, as well as other

TCMs), other transportation demand management

and transportation systems management strategies 

No Yes Yes

VariesVaries

Yes No

Programs to reduce emissions or accelerate

retirement of high emitting vehicles, boats, and lawn

and garden equipment

No No Yes – No – No

Emissions testing and repair/maintenance programs

for onroad vehicles

No Yes Yes – No Yes No

Emissions testing and repair/maintenance programs

for nonroad heavy-duty vehicles and equipment

No No Yes – No – No

Programs to expand use of clean burning fuels No No Yes Yes No – No

Low emissions specifications for equipment or fuel

used for large construction contracts, industrial

facilities, ship yard, airports, and public or private

vehicle fleets

No No Yes – No – No

Opacity or other emissions standards for “grossemitting” diesel equipment or vesselsNo No Yes – No Yes No

FINAL Charleston, WV 1997 PM2.5 SIP Page 135
Table 9.4-3. Analysis of Area Source Control Measures to Determine

 Reasonably Available Control Measures (RACM)

Area Source Measures

Implementation by January 2008?Enforceable?Technologically Feasible?Economically Feasible?Adverse Impacts?Reductions >0.1 tpd?RACM: Yes/No?

New open burning regulations and/or measures to

improve program effectiveness, such as programs to

reduce or eliminate burning of land clearing

vegetation

No Yes Yes Yes No No No

Programs to reduce emissions from woodstoves and

fireplaces, including outreach programs, curtailments

during days with expected high ambient levels of

PM2.5, and programs to encourage replacement of

woodstoves when houses are sold 

No No Yes – No No No

Controls on emissions from charbroiling or other

commercial cooking operations

No No Yes – No – No

Reduced solvent usage or solvent substitution

(particularly for organic compounds with 7 carbon

atoms or more, such as toluene, xylene, and trimethyl

benzene)

No Yes – – No – No

FINAL Charleston, WV 1997 PM2.5 SIP Page 136
9.5. Summary

9.5.a. RACM Determination

West Virginia will continue to implement the RACM already adopted and described in Section

6. 

The analysis given above, which meets the applicable statutory requirements set forth at Section

172(c)(1) of the Clean Air Act and the applicable regulatory requirements set forth at 40 CFR

§51.1010, demonstrates that these measures are sufficient to allow the Charleston area to

demonstrate attainment, by April 2010, of the 1997 PM2.5 NAAQS.

The state also finds that:

• there are no additional measures necessary to demonstrate attainment as expeditiously as

practicable;

• there are no additional measures to meet any RFP requirements; and

• there are no additional and potential measures that, if considered collectively, would

advance the attainment date by one year or more.

9.5.b. RACT Applicability

For each PM2.5 nonattainment area, 40 CFR §51.1010 notes that a state must submit a SIP

revision that demonstrates all RACM, including RACT for stationary sources, have been adopted

that are necessary to demonstrate attainment as expeditiously as practicable.

That section of the PM2.5 Implementation Rule goes on to state that the potential measures that,

considering technical and economic feasibility, are reasonably available must be adopted as

RACM if, considered collectively, those measures would advance the attainment date by one

year or more. 

As discussed in Section 9.3, West Virginia has determined that there are no additional control

measures that could have been adopted by January 1, 2008. 

Further, DAQ expects existing measures and those planned for implementation in 2009 to enable

the Charleston area to demonstrate compliance with the 1997 PM2.5 NAAQS by the April 2010

attainment date. 

Therefore, DAQ finds that no further actions on RACT are warranted.

FINAL Charleston, WV 1997 PM2.5 SIP Page 137
10.0. MID-COURSE REVIEW

[40 CFR §51.1011]

The proposed attainment date is within five (5) years of the date of designation, therefore,

pursuant to 40 CFR 51.1011 no mid-course review is required.

11.0. PUBLIC PARTICIPATION

A public notice was published in the West Virginia State Register, and the Charleston Gazette on

July 17, 2009, announcing the opening of a 30-day public comment period. A public hearing was

held on August 18, 2009 in the Dolly Sods Conference Room at the West Virginia Department

of Environmental Protection Headquarters at 601 57th Street, Charleston, West Virginia 25304,

beginning at 6:00 p.m. to accept oral comments on the proposed SIP revision. Written comments

were also accepted through 6:00 PM on Tuesday, August 18, 2009. One person attended the

public hearing, however no verbal comments were received. The EPA submitted written

comments on the proposed SIP. WVDAQ addresses these comments in Appendix Q.

In response to EPA’s Comment W (see Response to Comments document contained in Appendix

Q)), the WVDAQ established PM2.5 and Nitrogen Oxides (NOx) Motor Vehicle Emissions

Budgets (MVEB) for highway vehicles; and significantly revised the Transportation Conformity

chapter (Chapter 2.5) of the SIP revision. A public notice was published in the West Virginia

State Register, and the Charleston Gazette on September 25, 2009 reopening the comment

period with respect to this chapter of the proposed SIP revision, and subsequently held a public

hearing on October 27, 2009 in the Dolly Sods Conference Room at the West Virginia

Department of Environmental Protection Headquarters to accept oral comments on the proposed

revisions to Chapter 2.5. Written comments were also accepted through 6:00 PM on Tuesday,

October 27, 2009. The public notice, along with a copy of the Proposed SIP, including all

appendices, was posted on the DAQ website at

http://www.wvdep.org/item.cfm?ssid=8&ss1id=376. No one attended the public hearing and no

written comments were received. 

For documentation of the public participation process see Appendix Q.

12.0 CONCLUSION

The State of West Virginia requests that the United States Environmental Protection Agency act

in a timely manner to approve this attainment demonstration for the Charleston Nonattainment

Area, with a projected attainment date of April 2010, as a revision to the state implementation

plan (SIP).

FINAL Charleston, WV 1997 PM2.5 SIP Page 138