west virginia department of environmental protection

West Virginia

Fine Particle (PM2.5)

State Implementation Plan

for the

Parkersburg Nonattainment Area,

Comprising Wood County and the Grant Tax

District of Pleasants County

FINAL

September 2008

Promoting a healthy environment.
[This page intentionally left blank.]
Page i

Table of Contents

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

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

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

Acronyms and Abbreviations ............................................. Page xvii

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 8

1.6. Clean Air Act Requirements ....................................... Page 9

2.0. SIGNIFICANCE OF PM2.5 PRECURSOR POLLUTANTS . . . . . . . . . . . . . . . . . Page 10

2.1. Pollutant Contributions in the Parkersburg Nonattainment Area .......... Page 10

2.2. PM2.5 Component Species Analysis ................................. Page 13

2.3. Attribution of Emissions Sources .................................. Page 19

2.4. Identification of Attainment Plan Pollutants and Precursors .............. Page 23

2.4.a. Direct PM2.5 emissions ........................................ Page 23

2.4.b. SO2 emissions .............................................. Page 23

2.4.c. NOx emissions .............................................. Page 23

2.4.c. VOC emissions ............................................. Page 24

2.4.d. Ammonia emissions .......................................... Page 26

2.5. Transportation Conformity ....................................... Page 28

3.0. ATTAINMENT DEMONSTRATION METHODS AND INPUTS ........... Page 37

3.1. Analysis Method ............................................... Page 37

3.2. Model Selection ................................................ Page 38

3.2.a. Selection of Photochemical Grid Model .......................... Page 38

3.2.a.1. Criteria .............................................. Page 38

3.2.a.2. Overview of CMAQ .................................... Page 39

3.2.b. Selection of Meteorological Model .............................. Page 39

3.2.b.1. Criteria .............................................. Page 39

3.2.b.2. Overview of MM5 ..................................... Page 40

3.2.c. Selection of Emissions Processing System ........................ Page 41

3.2.c.1. Criteria .............................................. Page 41

3.2.c.2. Overview of SMOKE ................................... Page 41

3.3. Selection of the Modeling Year .................................... Page 42

3.4. Modeling Domains .............................................. Page 43

3.4.a. Horizontal Modeling Domain .................................. Page 43

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page ii

3.4.b. Vertical Modeling Domain .................................... Page 45

4.0. EMISSION INVENTORY .......................................... Page 46

4.1. Baseline (2002) Emissions Inventory ............................... Page 46

4.1.a. Stationary Sources ........................................... Page 47

4.1.a.1. Stationary Point Sources ................................ Page 47

4.1.a.1.a. Electric Generating Units (EGUs) ...................... Page 47

4.1.a.1.b. Other Industrial Point Sources (NonEGUs) .............. Page 49

4.1.a.2. Stationary Area Sources ................................ Page 50

4.1.b. Mobile Sources ............................................. Page 51

4.1.b.1. NonRoad Mobile Sources ............................... Page 51

4.1.b.2. Onroad Mobile Sources ................................. Page 53

4.1.c. Biogenic Emissions Sources ................................... Page 53

4.1.d. Summary 2002 Baseline Emissions Inventory for West Virginia ....... Page 54

4.2. Projected 2009 Emissions Inventories ............................... Page 55

4.2.a. Stationary Sources ........................................... Page 56

4.2.a.1. Stationary Point Sources ................................ Page 56

4.2.a.1.a. Electric Generating Units (EGUs) ...................... Page 56

4.2.a.1.b. Other Industrial Point Sources (NonEGUs) .............. Page 57

4.2.a.2. Stationary Area Sources ................................ Page 58

4.2.b. Mobile Sources ............................................. Page 59

4.2.b.1. Nonroad Mobile Sources ................................ Page 60

4.2.b.2. Onroad Mobile Sources ................................. Page 61

4.2.c. Biogenic Sources ............................................ Page 63

4.2.d. Summary of Final Inventories for 2009 ........................... Page 63

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 79

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page iii

6.1.b. Projected Reductions ......................................... Page 80

6.2. Area Source Measures ........................................... Page 81

6.2.a. Control Strategy ............................................. Page 81

6.2.a.1. Open Burning Restrictions (state rule) ..................... Page 81

6.2.b. Projected Reductions ......................................... Page 81

6.3. Non-Road Source Measures ...................................... Page 81

6.3.a. Control Stategies ............................................ Page 81

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

Utility Engines (federal rule) ............................. Page 81

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

or More Horsepower (federal rule) ........................ Page 81

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

.................................................... Page 82

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

.................................................... Page 82

6.3.a.5. Standards for Locomotives (federal rule) ................... Page 83

6.3.b. Projected Reductions ......................................... Page 83

6.4. Onroad Source Measures ......................................... Page 85

6.4.a. Control Strategies ........................................... Page 85

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

Emissions Standards (federal regulation) ................... Page 85

6.4.a.2. National Low Emission Vehicle Program (federal regulation) ... Page 85

6.4.a.3. Tier 2 Motor Vehicle Emission Regulations (federal regulation) . Page 86

6.4.a.4. Heavy Duty Diesel Engine Rule (federal regulation) .......... Page 86

6.4.b. Projected Reductions ......................................... Page 87

6.5. Supplemental Control Measures ................................... Page 88

6.6. Schedule of Adopted Control Measures ............................. Page 90

7.0. ATTAINMENT DEMONSTRATION ................................. Page 92

7.1. Attainment Test Introduction ...................................... Page 92

7.2. Attainment Test Results .......................................... Page 93

7.3. Supplemental Analyses .......................................... Page 94

7.3.a. Other Modeling Results ....................................... Page 95

7.3.a.1. EPA’s CAIR Modeling .................................. Page 95

7.3.a.2. Midwest RPO Modeling ................................. Page 96

7.3.b. Trends in Ambient Air Quality and Emissions .................. Page 98

7.4. Unmonitored Area Analysis ..................................... Page 100

8.0. CLEAN AIR ACT SECTION 172(C) REQUIREMENTS ................. Page 102

8.1. Reasonably Available Control Measures ............................ Page 102

8.2. Reasonable Further Progress ..................................... Page 103

8.3. Actual Emissions Inventory ...................................... Page 103

8.4. Periodic Emissions Inventory .................................... Page 104

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page iv

8.5. Permitting Requirements for New and Modified Sources ............... Page 104

8.6. Other Measures ............................................... Page 105

8.7. Compliance with Section 110(a)(2) ................................ Page 105

8.8. Equivalent Techniques .......................................... Page 105

8.9. Contingency Measures .......................................... Page 106

8.9.a. Enforceability Issues ........................................ Page 106

8.9.b. Evaluations/Required Reductions .............................. Page 106

8.9.c. Equivalency Ratios ......................................... Page 107

8.9.d. Identified Contingency Measures .............................. Page 108

9.0. REASONABLY AVAILABLE CONTROL MEASURES (RACM), INCLUDING

REASONABLY AVAILABLE CONTROL TECHNOLOGY (RACT) FOR

STATIONARY SOURCES ........................................ Page 110

9.1. Statutory and Regulatory Requirements for RACM Analysis ............ Page 110

9.2. Discussion of Reasonable Control Measures ......................... Page 110

9.3. Discussion of RACT ........................................... Page 111

9.3.a. EGU RACT Analysis ........................................ Page 111

9.3.a.1. Background ......................................... Page 111

9.3.a.2. Final Ranking of RACT Candidates ...................... Page 113

9.3.a.3. Why No Additional Controls Will Be Required .............. Page 113

9.3.a.4. Why Controls Implementation Could Be Delayed ............ Page 116

9.3.a.5. Why RACT Selection Is Site Specific and Costs May Be Underestimated

................................................... Page 117

9.3.b. ICI RACT Analysis ......................................... Page 118

9.3.b.1. Background ......................................... Page 119

9.3.b.2. Final Ranking of RACT Candidates ...................... Page 120

9.3.b.3. Why Controls Implementation Could Be Delayed ............ Page 123

9.3.b.4. Why RACT Selection Is Site Specific and Costs May Be Underestimated

................................................... Page 124

9.4. Evaluation of RACM for Purposes of Achieving Attainment ............ Page 125

9.5. Summary .................................................... Page 129

9.5.a. RACM Determination ....................................... Page 129

9.5.b. RACT Applicability ......................................... Page 129

10.0. MID-COURSE REVIEW .......................................... Page 130

11.0. PUBLIC PARTICIPATION ........................................ Page 130

12.0 CONCLUSION .................................................. Page 130

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page v

List of Tables

Table 2.1-1. PM2.5 Concentrations and Design Values for the FRM monitor in the Parkersburg

PM2.5 Nonattainment Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 10

Table 2.4 -1. West Virginia Annual VOC Emissions ............................ Page 24

Table 2.4-2. Annual VOC Emissions for Wood County and the Grant Tax District of Pleasants

County ............................................................. Page 24

Table 2.4-3. ASIP Ammonia Emissions ...................................... Page 26

Table 2.4-4. West Virginia Ammonia Emissions ............................... Page 27

Table 2.4-5. Ammonia Emissions for Wood County and Grant Tax District of Pleasants County

................................................................... Page 27

Table 2.5-1. 2002 Base Year Emission Inventory (Tons/Year) ................... Page 30

Table 2.5-2. VMT for Model Years 2002, 2005, 2009, 2015 and 2025 .............. Page 34

Table 2.5-3. Conformity Results ............................................ Page 35

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

Inventory and Typical 2002 Inventory .................................... Page 49

Table 4.1.c-1. West Virginia Biogenic Emissions .............................. Page 54

Table 4.1.d-1 2002 Base Year Inventory - West Virginia Portion of Nonattainment Area

................................................................... Page 54

Table 4.1.d-2. 2002 Base Year Inventory - Ohio Portion of Nonattainment Area ..... Page 55

Table 4.1.d-3. Summary of 2002 Baseline Emissions Inventory for Parkersburg Nonattainment

Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 55

Table 4.2.d-1. 2009 Attainment Year Inventory - West Virginia Portion of Nonattainment Area

................................................................... Page 63

Table 4.2.d-2. 2009 Attainment Year Inventory - Ohio Portion of Nonattainment Area

................................................................... Page 63

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 64

Table 5.1-1. VISTAS/ASIP Model Performance Goals and Criteria for Components of Fine

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

Table 6.1-1. 2009 Point Source Emission Reductions ........................... Page 80

Table 6.3-1. 2009 Nonroad Emission Reductions ............................. Page 84

Table 6.4-1. Tier I Standards .............................................. Page 85

Table 6.4-2. Onroad Emission Reductions ................................... Page 87

Table 6.6-1. West Virginia Schedule of Adopted Control Measures Parkersburg Nonattainment

Area . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 90

Table 7.2-1. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 .... Page 93

Table 7.3-1. EPA CAIR Modeling Results .................................... Page 95

Table 7.3-2. LADCO - Round 5 - 2009 Results ................................ Page 96

Table 7.3.b-1. Air Monitoring Data for Parkersburg Area ........................ Page 98

Table 7.4-1. VISTAS Regional Scale Modeling Results ........................ Page 101

Table 8.9-1. Contingency Requirement for PM and PM Precursors ............... Page 106

Table 8.9-2. Quarterly Speciated Relative Reduction Factors (RRFs) for Wood County

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

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page vi

Table 8.9-2. Contingency Measure Reductions from 2002 Emissions (tons/year) .... Page 108

Table 8.9-3. Determination of Excess Reductions from Contingency Measures ...... Page 108

Table 9.3.a-1. West Virginia Coal-Fired Power Plants in PM2.5 Nonattainment Areas . Page 112

Table 9.3.a-2. PM10-Primary, PM2.5-Primary, SO2 and NOx from West Virginia 

Coal-Fired Power Plants in PM2.5 Nonattainment Areas, (tpy) . . . . . . . . . . . . . . . . . Page 112

Table 9.3.a-3. Final Ranking of RACT Candidates for Coal-Fired EGUs for PM2.5, NOx and SO2

in PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 114

Table 9.3.b-1. ICI Boilers in the West Virginia Portion of the Parkersburg Nonattainment Area

.................................................................. Page 118

Table 9.3.b-2. Final Ranking of RACT Candidates for PM2.5 from Coal-fired Industrial Boilers

in PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 121

Table 9.3.b-3. Final Ranking of RACT Candidates for PM2.5 from Oil-fired Industrial Boilers in

PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 121

Table 9.3.b-4. Final Ranking of RACT Candidates for SO2 from Coal-fired Industrial Boilers in

PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 122

Table 9.3.b-5. Final Ranking of RACT Candidates for SO2 from Oil-fired Industrial Boilers in

PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 122

Table 9.3.b-6. Final Ranking of RACT Candidates for NOx from Industrial Boilers in PM2.5

Nonattainment Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 123

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

Available Control Measures (RACM) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 126

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page vii

List of Figures

Figure 1.2-1. Chemical links between the ozone and PM formation processes. ........ Page 3

Figure 1.4-1. West Virginia PM2.5 Monitoring Network . . . . . . . . . . . . . . . . . . . . . . . . . . Page 6

Figure 1.4-2. Map of West Virginia PM2.5 Nonattainment Areas . . . . . . . . . . . . . . . . . . . Page 7

Figure 2.1-1. 2002 sample data for the Parkersburg area PM2.5 monitor. . . . . . . . . . . . . Page 11

Figure 2.1-2. Number of samples per quarter in 2002 at the Parkersburg area monitor (54-107-

1002) with PM2.5 concentrations greater than 15μ/m3

. ............... Page 12

Figure 2.2-1. PM2.5 species contribution in the Parkersburg area, based on EPA SMAT data

.......................................................... Page 14

Figure 2.2-2. Parkersburg 2002 Quarterly Speciation data based on SMAT tool. 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 15

Figure 2.2-3. CMAQ modeled changes in PM2.5 mass for Parkersburg FRM monitor from

reducing 2009 VISTAS/ASIP Base D emissions by 30% for several different

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

.......................................................... Page 17

Figure 2.2-4. CMAQ modeled changes in PM2.5 mass for Parkersburg FRM monitor from

reducing 2009 VISTAS/ASIP Base D emissions by 30% for several different

emissions source categories, for the winter period Nov 19 - Dec 19, 2002.

.......................................................... Page 17

Figure 2.2-5. 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 18

Figure 2.3-1. Parkersburg nonattainment area SO2 emissions by source sector, including West

Virginia and Ohio emissions. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 20

Figure 2.3-2. Statewide West Virginia SO2 emissions by source sector. . . . . . . . . . . . . Page 21

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

in the Parkersburg area. The Parkersburg SO2 point source emissions account for

approximately 12% of the state SO2 emissions. . . . . . . . . . . . . . . . . . . . . Page 22

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

Base D emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page 25

Figure 2.5-1. Parkersburg PM2.5 Design Value, 2001-2007 ...................... Page 31

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 44

Figure 3.4-2. A more detailed view of the 12-km grid over the VISTAS region ...... Page 45

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

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page viii

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 Parkersburg area.

....................................................... Page 98

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

....................................................... Page 99

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page ix

List of Appendices

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

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

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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix 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 Appendix B - 39

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

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

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

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

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

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

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

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

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

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

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

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

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

Appendix C.3.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 95 

Appendix C.4: West Virginia Nonroad Inventories . . . . . . . . . . . . . Page Appendix C - 141 

Appendix C.4.a: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 143 

Appendix C.4.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 317 

Appendix C.5: West Virginia Onroad Inventories . . . . . . . . . . . . . . Page Appendix C - 493 

Appendix C.5.a: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 495 

Appendix C.5.b: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 505 

Appendix C.6: Ohio Inventories . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 515 

Appendix C.6.a: Point Source Inventories . . . . . . . . . . . . . . . . . Page Appendix C - 517 

Appendix C.6.a.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 519 

Appendix C.6.a.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 523 

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page x

Appendix C.6.b: Area Source Inventories . . . . . . . . . . . . . . . . . . Page Appendix C - 527

Appendix C.6.b.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 529

Appendix C.6.b.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 543

Appendix C.6.c: Nonroad Inventories . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 557

Appendix C.6.c.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 559

Appendix C.6.c.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 595

Appendix C.6.d: Onroad Inventories . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 631

Appendix C.6.d.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 633 

Appendix C.6.d.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 653 

Appendix C.7: Kentucky Inventories . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 673 

Appendix C.7.a: Point Source Inventories . . . . . . . . . . . . . . . . . Page Appendix C - 675 

Appendix C.7.a.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 677 

Appendix C.7.a.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 681 

Appendix C.7.b: Area Source Inventories . . . . . . . . . . . . . . . . . Page Appendix C - 685 

Appendix C.7.b.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 687 

Appendix C.7.b.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 695 

Appendix C.7.c: Nonroad Inventories . . . . . . . . . . . . . . . . . . . . Page Appendix C - 703 

Appendix C.7.c.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 705 

Appendix C.7.c.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 717 

Appendix C.7.d: Onroad Inventories . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 729 

Appendix C.7.d.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 731 

Appendix C.7.d.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 737 

Appendix C.8: Maryland Inventories . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 743 

Appendix C.8.a: Point Source Inventories . . . . . . . . . . . . . . . . . Page Appendix C - 745 

Appendix C.8.a.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 747 

Appendix C.8.a.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 751 

Appendix C.8.b: Area Source Inventories . . . . . . . . . . . . . . . . . Page Appendix C - 755 

Appendix C.8.b.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 757 

Appendix C.8.b.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 763 

Appendix C.8.c: Nonroad Inventories . . . . . . . . . . . . . . . . . . . . Page Appendix C - 769 

Appendix C.8.c.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 771 

Appendix C.8.c.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 779 

Appendix C.8.d: Onroad Inventories . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 787 

Appendix C.8.d.1: 2002 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 789 

Appendix C.8.d.2: 2009 . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix C - 795 

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

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

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

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

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xi

Appendix D.2: Ohio Inventory Documentation . . . . . . . . . . . . . . . . . Page Appendix D - 135

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

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

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

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

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

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

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

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

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

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

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

Appendix D.5: Background Documentation . . . . . . . . . . . . . . . . . . . . Page Appendix 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 Appendix D - 313

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

and Nonroad Mobile Emission Sources (February 3, 2003) . . . . . Page Appendix 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 Appendix D - 359

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

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

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

(April 30, 2004) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix 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 Appendix D - 597

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xii

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 Appendix D - 666

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

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

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

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

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

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

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

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

Appendix F.1: Emissions Modeling Documentation . . . . . . . . . . . . . . . . Page Appendix 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 Appendix 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 Appendix F - 203

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

2005) Page Appendix F - 227

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

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

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

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xiii

Appendix G.2: Protocol for Annual MM5 Modeling in Support of VISTAS (Visibility

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

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

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

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

Attainment Demonstration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix 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 Appendix 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 Appendix J - 117 

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xiv

Appendix L: Contingency Measures Documentation . . . . . . . . . . . . . . . . . . . Page Appendix L-1

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

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

2. Evaluations/Required Reductions . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix L - 5

3. Equivalency Ratios . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix L - 7

4. Identified Contingency Measures . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix L - 8

5. Application of Equivalency Ratios to the Parkersburg Area . . . . Page Appendix L - 9

Appendix L.1: Equivalency Ratio Based on Relative Reduction Factors as Generated by the 

Community Multiscale Air Quality (CMAQ) Modeling Results . . . . . Page Appendix L - 11

Appendix L.2: Synopsis of the ASIP PM2.5 Sensitivity Study and SO2/NOx Equivalency

Rations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix L - 17

Appendix L.3: Cytec Industries, Inc. (073-00003) Documentation . . . Page Appendix L - 29

Appendix L.4: Cabot Corporation. (073-00006) Documentation . . . . Page Appendix L - 57

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

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

Appendix M.2: ICI RACT Analysis . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix M - 119

Appendix M.3: Federal Consent Decrees . . . . . . . . . . . . . . . . . . . . . Page Appendix M - 215

American Electric Power Service Corp. . . . . . . . . . . . . . . . . . . . Page Appendix M - 217

Virginia Electric and Power Company . . . . . . . . . . . . . . . . . . . . Page Appendix M - 323

Appendix M.4: State Consent Orders . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix M - 443

Allegheny Energy - Harrison Power Station . . . . . . . . . . . . . . . . Page Appendix M - 445

Allegheny Energy - Pleasants Power Station . . . . . . . . . . . . . . . Page Appendix M - 451

Appendix N: ASIP and VISTAS Supporting Documentation . . . . . . . . . . . . . Page Appendix N-1

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

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

Appendix N.2: Technical Support Document for Association for Southeastern Integrated

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

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix N - 343

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xv

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

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

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

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

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

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

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

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

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

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

Appendix P: Transportation Conformity . . . . . . . . . . . . . . . . . . . . . . . . . . . . Page Appendix P - 1

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

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xvi

[This page intentionally left blank]

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xvii

Acronyms and Abbreviations

AL Alabama

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

CAAA Clean Air Act Amendments of 1990

CAIR Clean Air Interstate Rule

CAMR Clean Air Mercury Rule

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

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

MRPO Midwest Regional Planning Organization

MS Missisippi

MW megawatt, which equals 1,000,000 watts

MWs megawatts

N/A not available

N2O nitrous oxide

NAA Nonattainment area

NAAQS National Ambient Air Quality Standard

NACAA National Association of Clean Air Agencies

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xviii

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

NOX oxides of nitrogen; typically, NO and NO2

NSPS New Source Performance Standard

NSR New Source Review

OC Organic carbon

OH Ohio

PBW Particle bound water

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

RPO regional planning organization

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 Modeling Attainment Test

SO2 sulfur dioxide

SO4 sulfate

SOX sulfur oxides

sq.ft. square feet

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xix

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

WWW Wood-Washington-Wirt Interstate Planning Commission

WV PM2.5 SIP for the Parkersburg Nonattainment Area
Page xx

[This page intentionally left blank.]

WV PM2.5 SIP for the Parkersburg Nonattainment Area
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 1

West Virginia

Fine Particle (PM2.5) State Implementation Plan

for the

Parkersburg Nonattainment Area,

Comprising Wood County and the Grant Tax District of Pleasants County

1.0. INTRODUCTION

The Parkersburg-Marietta, WV-OH PM2.5 nonattainment area is a multi-state nonattainment area,

comprising Wood County and the Grant tax district in Pleasants County, West Virginia, and

Washington County, Ohio. 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:

! Sulfates

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

! Ammonium

! Particle bound water

! Elemental carbon
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 2

! 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 1.2-1). 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 are 14 Federal Reference Monitors (FRMs) that sample PM2.5 in West Virginia, one of

these monitors is located in the Parkersburg 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 3

Figure 1.2-1. 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. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 4

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 standard of 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 5

(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 Parkersburg nonattainment

area for both the annual and 24-hour standards are presented in Table 1.4-1. 

Table 1.4-1. Parkersburg 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

99-

01

00-

02

01-

03

02-

04

03-

05

04-

06

05-

07

107-1002 42 39 37 35 34 35 37 17.6 17.0 16.0 15.2 15.4 15.3 15.4

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 6

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). 

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 7

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

Unclassifiable/ Attainment. [See Figure 1-2. 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 Parkersburg, are required to attain the

standard no later than April, 2010.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 8

This document, the West Virginia Fine Particle (PM2.5) State Implementation Plan for the

Parkersburg Nonattainment Area, Comprising Wood County and the Grant Tax District of

Pleasants County, is a plan to demonstrate continued improvement and compliance with 1997

PM2.5 NAAQS in the Parkersburg 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 control technology (RACT)

for point sources, an attainment demonstration, and contingency plans. 

This Plan has been prepared by the WVDEP in consultation with the Wood-Washington-Wirt

Interstate Planning Commission (WWW) to comply with the CAAA of 1990 and with EPA

requirements for the Parkersburg area as stated in EPA’s 2005 designation of the Parkersburg

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 Parkersburg attainment demonstration is based.
WV PM2.5 SIP for the Parkersburg Nonattainment Area 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 10

2.0. SIGNIFICANCE OF PM2.5 PRECURSOR POLLUTANTS

[40 CFR §51.1002]

2.1. Pollutant Contributions in the Parkersburg Nonattainment Area

Data from the FRM site in the Parkersburg area is displayed below (Figure 2.1-1).

Table 2.1-1 contains the quarterly and annual PM2.5 concentrations for the FRM monitor in the

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

designation determination. Table 2.1-1 also presents the 2001-2003 PM2.5 design value for the

FRM monitor based on these quarterly and annual averages. The historic quarterly, yearly and

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

Table 2.1-1. PM2.5 Concentrations and Design Values for the FRM monitor in the

Parkersburg PM2.5 Nonattainment Area

County FRM

Site

Year 1st

Quarter

2nd

Quarter

3rd

Quarter

4th

Quarter

Annual

Average

Design

Value

Wood 107-1002

2001 15.93 18.58 20.73 14.36 17.40

16.03

2002 12.88 17.32 20.98 11.86 15.76

2003 12.88 14.47 19.78 12.61 14.93

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area 

Figure 2.1-1. 2002 sample data for the Parkersburg area PM2.5 monitor.

Parkersburg PM2.5 - 2002

(54-107-1002)

0.0

15.0

30.045.060.075.0

Run Date

ug/m3
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 12

FRM data was analyzed to determine if there was a seasonal correlation to higher PM2.5 values

(Figure 2.1-2).

Figure 2.1-2. Number of samples per quarter in 2002 at the Parkersburg area monitor (54-107-

1002) with PM2.5 concentrations greater than 15μ/m3.

Parkersburg Area 2002 Samples by Quarter 

with PM2.5 Concentration > 15 ug/m3

6

14

20

8

0

5

10

15

20

25

Q1 Q2 Q3 Q4

2002

Number of Samples

Samples > 15 ug/m3 out of a

total of 116 Samples
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 13

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.

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. Figure 2.2-1 shows that a large portion, about 35%, of annual averaged

PM2.5 composition in the Parkersburg 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. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 14

Figure 2.2-1. PM2.5 species contribution in the Parkersburg area, based on EPA SMAT data

Organic carbon (OC) levels vary across the year (Figure 2.2-2). 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 (Figure 2.2-2). 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 (Figure 2.2-2). 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 2.2-

2). 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.

2000-04 Parkersburg (Vienna Neal School)

PM2.5 Species Percent Contribution

54-107-1002

4%

3%

39%

31%

4%

10%

9%

Crustal

EC

OC

SO4

NO3

NH4

PBW

2000-04 DV = 

16.07 ug/m3
WV PM2.5 SIP for the Parkersburg Nonattainment Area 

Figure 2.2-2. Parkersburg 2002 Quarterly Speciation data based on SMAT tool. Upper left - first quarter (Jan - 

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

3% 3%

44%

29%

0%

9%

9%

3%

Parkersburg 2000-2004 DVB Q2

PM2.5 Speciation Percentages

2000-2004 Q2 DVB = 

16.19 ug/m3

5% 2%

31%

38%

0%

11%

10%

3%

Parkersburg 2000-2004 DVB Q3

PM2.5 Speciation Percentages

CrustalECOCSO4NO3NH4PBWBlank Mass

2000-2004 Q3 DVB = 

20.01 ug/m3

3% 4%

46%

23%

6%

8%

6%

4%

Parkersburg 2000-2004 DVB Q1

PM2.5 Speciation Percentages

CrustalECOCSO4NO3NH4PBWBlank Mass

2000-2004 Q1 DVB = 

13.42 ug/m3

3% 4%

33%

27%

10%

11%

8%

4%

Parkersburg 2000-2004 DVB Q4

PM2.5 Speciation Percentages

2000-2004 Q4 DVB = 

12.68 ug/m3
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 16

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 2.2-3 and -4). 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

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

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 2.2-3 and -4) 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 Parkersburg, 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 Parkersburg 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 Parkersburg area by 2009 (figure 2.2-5, see Wood - 1002, middle and right

bars).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 17

Figure 2.2-3. CMAQ modeled changes in PM2.5 mass for Parkersburg FRM monitor from

reducing 2009 VISTAS/ASIP Base D emissions by 30% for several different

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

Figure 2.2-4. CMAQ modeled changes in PM2.5 mass for Parkersburg FRM monitor from

reducing 2009 VISTAS/ASIP Base D emissions by 30% for several different

emissions source categories, for the winter period Nov 19 - Dec 19, 2002.

Wood, WV (541071002) 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

° PM 2.5 (° g/m3

)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Wood, WV (541071002) Winter

-1.40

-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

° PM 2.5 (° g/m3

)

Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL
WV PM2.5 SIP for the Parkersburg Nonattainment Area 

Figure 2.2-5. 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 19

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 Parkersburg 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 Parkersburg 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 Parkersburg nonattainment area. 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

Parkersburg SO2 point source emissions account for approximately 12% of the state SO2

emissions (Figure 2.3-3).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 20

Figure 2.3-1. Parkersburg nonattainment area SO2 emissions by source sector, including West

Virginia and Ohio emissions.

Parkersburg PM2.5 Nonattainment Area SO2 Emissions in 2002

33%

67%

0

50,000

100,000

150,000

200,000

250,000

Point Stationary Area Stationary Nonroad Mobile Onroad Mobile Biogenics

Annual SO2 (Tons/Year)

Ohio SO2

West Virginia SO2
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 21

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

West Virginia Total SO2 Emissions in 2002

0

100,000

200,000

300,000

400,000

500,000

600,000

Point Stationary Area Stationary Nonroad Mobile Onroad Mobile Biogenics

Annual SO2 (Tons/Year)
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 22

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

in the Parkersburg area. The Parkersburg SO2 point source emissions account for

approximately 12% of the state SO2 emissions.

West Virginia Statewide and West Virginina Portion of Parkersburg 

PM2.5 Nonattainment Area SO2 Emissions in 2002

0

100,000

200,000

300,000

400,000

500,000

600,000

Point Stationary Area Stationary Nonroad Mobile Onroad Mobile Biogenics

Annual SO2 (Tons/Year)

West Virginia Total SO2

WV Portion of Parkersburg

Nonattainment Area SO2
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 23

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.

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.

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 24

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.

2.4.c. 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 2.4-1). In Wood county, anthropogenic emissions

accounted for 44% of the VOC emissions in 2002, and are projected to account for 39% of the

VOC emissions in 2009 (see Table 2.4-2). 

Table 2.4 -1. West Virginia Annual VOC Emissions 

2002

(tons)

2002

(%)

2009

(tons)

2009

(%) 

Area 60,443 12% 57,346 12%

On-road 45,284 9% 26,584 6%

Non-Road 18,566 4% 18,069 4%

Point 15,775 3% 15,171 3%

Anthropogenic 142,070 28% 117,170 25%

Biogenic 357,850 72% 357,850 75%

Total 499,920 100% 475,020 100%

Table 2.4-2. Annual VOC Emissions for Wood County and the Grant Tax District of

Pleasants County 

2002 

(tons)

2002 

(%) 

2009

(tons)

2009

(%) 

Area 3,718 20% 3,397 20%

On-road 2,100 12% 1,300 8%

Non-Road 1,138 6% 1,028 6%

Point 1,017 6% 898 5%

Anthropogenic 7,973 44% 6,623 39%
Table 2.4-2. Annual VOC Emissions for Wood County and the Grant Tax District of

Pleasants County 

2002 

(tons)

2002 

(%) 

2009

(tons)

2009

(%) 

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 25

Biogenic 10,252 56% 10,252 61%

Total 18,225 100% 16,875 100%

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 Wood County (see Figure 2.4-1 below).

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.

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 26

2.4.d. 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 2.4-3, 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. 

Table 2.4-3. 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 2.4-4, 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 WVDAQ has

determined that controls are not warranted on agricultural sources. For a more detailed area

source emissions inventory see Appendix C.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 27

Table 2.4-4. West Virginia Ammonia Emissions

Sector 2002 

(tons)

2002

(%)

2009 

(tons)

2009

(%)

Point 453 4% 671 5%

Area 9,963 80% 10,625 78%

NonRoad 9 0% 11 0%

OnRoad 2,036 16% 2,292 17%

Biogenics N/A N/A N/A N/A

Total 12,461 100% 13,598 100%

Note: All numbers rounded to the nearest ton or whole percentage point.

Further, as shown in Table 2.4-5, Wood county accounts for only 262 tons of ammonia

emissions or approximately 2% of the ammonia emissions in the state, with 45% of the ammonia

emissions attributable to area sources.

Table 2.4-5. Ammonia Emissions for Wood County and Grant Tax District of Pleasants

County 

Sector 2002 

(tons)

2002

(%)

2009 

(tons)

2009

(%)

Point 52 20% 60 21%

Area 117 45% 115 40%

NonRoad 1 0% 1 0%

OnRoad 92 35% 111 39%

Biogenics N/A N/A N/A N/A

Total 262 100% 287 100%

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 28

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

transportation 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 responsible

transportation planning entity for the Parkersburg nonattainment area is the Wood-WashingtonWirt Interstate Planning Commission (WWW).

 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

The Transportation Improvement Program (TIP) - a collection of near-term projects that

typically address the first 3-5 years of the LRTP and build toward realization of the

LRTP. 

WWW has developed a travel demand model (TDM) to simulate 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 29

The emission estimates are compared to: 

• a base year; or

• no-build scenario (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. 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 - 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 PM2.5, NOx and SO2 are insignificant contributors to the nonattainment problem for

the Parkersburg area. The finding will become final if EPA concurs and approves this SIP. 

First, the regional highway pollutant/precursor emissions constitute a relatively small fraction of

the overall emissions as shown in the table below.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 30

Table 2.5-1. 2002 Base Year Emission Inventory (Tons/Year)

Category County NOx PM2.5 SO2

Area Pleasants, WV 171 152 86

Wood, WV 578 987 1,225

WV subtotal 749 1,139 1,311

Washington, OH 188 317 40

Area Subtotal 937 1,456 1,351

NonRoad Pleasants, WV 837 36 41

Wood, WV 1,399 60 112

WV subtotal 2,236 96 153

Washington, OH 1,669 84 92

NonRoad Subtotal 3,905 180 245

OnRoad Pleasants, WV 194 3 9

Wood, WV 2,473 41 102

WV subtotal 2,667 44 111

Washington, OH 2,424 42 112

OnRoad Subtotal 5,091 86 223

Point Pleasants, WV 20,896 853 65,791

Wood, WV 939 215 4,502

WV subtotal 21,835 1,068 70,293

Washington, OH 33,588 681 0

Point Subtotal 55,423 1,749 70,293

% WV OnRoad/ 

WV Subtotal

9.7% 1.9% 0.2%

TOTALS WV Subtotal 27,487 2,347 71,868

Nonattainment

Area Total

65,356 3,471 72,112

% OnRoad/ Total 7.8% 2.5% 0.3%
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 31

From the above, it can be readily determined that the maximum highway contribution to NOx

emissions is less than 10%. This true for West Virginia emissions alone and for the combined

West Virginia and Ohio emissions within the nonattainment area. The highway contribution to

direct PM and SO2 is below 3%. Therefore, the DEP has determined that the regional highway

emissions contribution as a percent of the total SIP inventory is insignificant.

Second, the current air quality (CY 2007) is represented by a design value of 15.4 ug/m3

. This

value is slightly higher than the 15.3 ug/m3 design value upon which the nonattainment

designation is based. The graph below [Figure 2.5-1] shows the general improvement of PM2.5

concentrations from the year 2001 to date. The values dropped from 17.6 μg/m3 in 2001 to 17.0

and 16.0 in 2002 and 2003, respectively. This may be attributed to an overall decrease in sulfates

from SO2 reductions mandated by the Acid Rain Program and preliminary implementation of

controls 

Figure 2.5-1. Parkersburg PM2.5 Design Value, 2001-2007

from the Clean Air Interstate Rule. The design value then fluctuated from 15.2 to 15.4 during the

2004-2007 period. This fluctuation is due to the year to year variability in PM2.5. It is common

to many monitoring sites and, in fact, is much smaller than the year to year variability exhibited

by several other West Virginia sites. Overall, the PM concentrations have improved since the

beginning of the decade. The area is designated as attainment for all other criteria pollutants.

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

Parkersburg PM2.5 Design Value

2001-2007

14.0

14.5

15.0

15.5

16.0

16.5

17.0

17.5

18.0

99-01 00-02 01-03 02-04 03-05 04-06 05-07

Parkersburg PM 2.5 Design Value
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 32

overall PM mass, coupled with the very low contribution of highway sources to those sulfate

totals.

Third, historically there have been no West Virginia SIP requirements for motor vehicle control

measures. The Wood County portion of the area is subject to Transportation Conformity for the

8-hour ozone standard, with SIP-approved, seasonal budgets for NOx and Volatile Organic

Compounds (VOC). Further, the entire nonattainment area is currently subject to Transportation

Conformity for the PM2.5 standard. Emissions analysis has been mandatory for annual highway

emissions of direct PM and NOx. However, upon a positive adequacy review or approval of this

SIP submittal, no highway emissions analysis will be required under the annual PM2.5 standard.

Highway analysis of seasonal ozone precursors would continue to be mandatory. And, PM2.5 hotspot analyses would continue to apply for required projects under 40CFR93.116 and 93.123(b)

of the Transportation Conformity Rule.

Fourth, WWW has extensively researched the area local historical trends and growth patterns to

develop the LRTP and support transportation conformity evaluations. There is no reason to

expect highway motor vehicle emissions growth that would lead to a PM2.5 NAAQS violation.

WWW has estimated emissions out, at least, to the calendar year 2025 confirming this. The

transportation air quality conformity analysis for the WWW area took into account all the

regional capacity projects, which are scheduled for implementation through the transportation

plan horizon year and the four year TIP. The PM conformity tests were performed for calendar

years 2002, 2009, 2015 and 2025, for both the winter and summer representative months

[January for winter and July for summer]. For each of those years, vehicle miles traveled (VMT)

and Speed were developed by the Federal Functional Class codes within Wood County and

Washington County [for both January and July], which are derived from the regional traffic

model assignments that are made for each of those years. Pursuant to the Transportation

Conformity interim tests, NOx and direct PM were evaluated.

The WWW study area covers the Parkersburg-Marietta Metropolitan area and includes two

entire counties: Wood County in West Virginia and Washington County in Ohio. Parkersburg

[WV] along with Marietta and Belpre [OH] are the major urban areas. The metropolitan area has

a population of 151,000, out of which 87,000 are in the urbanized area according to 2000 census.

The study area includes the urban areas of Parkersburg, Marietta and Belpre in addition to all of

Wood County, West Virginia and Washington County, Ohio. The townships of Belpre, Dunham,

Fearing, Marietta, Muskingum, Newport and Warren are included in the study, as part of

Washington County. The transportation plan, on the other hand, is a comprehensive examination

of the future transportation needs for Wood County [WV] and portions of Washington County

[OH]. The study area is 571.6 square miles, with Wood County representing 376.9 square miles,

and the seven Ohio townships representing 194.7 square miles. 

WWW models future highway network activity using the QRS-2 Version 6.0 software package

developed by AJH Associates. Advanced General Network Editor [GNE] version 7.0 was used

to edit the base year model network. The WWW QRS-2 traffic model is a 24-hour traffic

analysis model with three internal trip purposes: home-based work, home-based non-work, and

non-home based; internal to external trips; through trips; and truck trips developed based on

roadway functional classes. The model base year is 2000, and the model future year for the Long

Range Multimodal Transportation Plan [LRTP] is 2025. In this model, both QRS-2 default
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 33

parameters [national averages] and the location-specific parameters derived from the 2002

WWW household survey were used. The Wood-Washington-Wirt [WWW] Travel Demand

Model Technical Report outlined the tasks and activities in the base year model calibration and

validation process. The four major model development tasks are listed as follows: 

1. Developing Highway Network System and Related Attributes. 

2. Developing Traffic Analysis Zone [TAZ] System and Related Attributes. 

3. Deriving Internal-Internal, External-Internal and External-External Trips. 

4. Model Calibration and Validation. 

The regional travel demand model for the base year was executed to obtain the total VMT for the

region. The base year estimates of VMT output by the model must be adjusted to match the

HPMS VMT estimates on roadway class-specific bases, resulting in HPMS-adjusted VMT

estimates for each roadway class. Then the VMT factors with facility class [which are developed

as an average of HPMS and those derived from the local vehicle distribution factors] were used

to calculate the VMT for each facility class. The output by the regional travel demand model was

input to the MOBILE6.2 emissions model for developing the roadway class-specific emission

factors for the base year. These emissions factors were combined with the HPMS-adjusted VMT

estimates to compute onroad emissions for each roadway class. The resulting emissions

estimates are then summed to compute total regional emissions from onroad motor vehicles. 

For each future year of interest (i.e., analysis year), the regional travel model must first be used

to develop roadway-class specific VMT estimates. These estimates are then compared to the

base year VMT estimates output by the travel model, to develop roadway-class specific growth

rates. The base year HPMS-adjusted VMT estimates above are then multiplied by these growth

rates to compute future year HPMS-adjusted VMT estimates. 

Similar to the base year computation methodology, congested speeds output by the model were

input to MOBILE to develop roadway class-specific emissions factors. The HPMS-adjusted

VMT estimates for each roadway class were then multiplied by the emissions factors output by

MOBILE, and the resulting emissions estimates summed across all roadway classes to compute

total regional on-road emissions. The process was followed for each selected analysis year. The

above example provides one approach to computing HPMS-adjusted VMT estimates for each

analysis year and scenario. There are, however, a number of other variations that could be

pursued depending on the robustness of the available data and desired level of analysis. 

Table 2.5-2 shows the VMT for the model area for the years 2002, 2005, 2009, 2015 and 2025.

Appendix A [of the report] lists the VMT by facility type for all the above-listed years. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 34

Table 2.5-2. VMT for Model Years 2002, 2005, 2009, 2015 and 2025

County Name Year Winter VMT Summer VMT

Wood 2002 2,295,840 2,604,982 

Washington 2002 2,061,782 2,353,125 

2002 Total 4,357,622 4,958,107

Wood 2009 2,658,148 3,015,859 

Washington 2009 2,224,337 2,538,645 

2009 Total 4,882,485 5,554,504

Wood 2015 2,854,781 3,240,181 

Washington 2015 2,569,827 2,932,187 

2015 Total 5,424,608 6,172,368

Wood 2025 3,111,562 3,531,210 

Washington 2025 2,835,467 3,236,821 

2025 Total 5,947,029 6,768,031

In June 2005, EPA clarified how transportation conformity was determined in noncontiguous

PM2.5 nonattainment areas. EPA’s clarification was as follows: 

Noncontiguous PM2.5 nonattainment areas (NNAs) are areas that contain “satellite

portions” that are not contiguous with the main portion of the nonattainment area.

These satellite areas are designated as part of the overall nonattainment area because

they have a point source which contributes, via transport, to the air quality problems

of the main geographic portion of the PM2.5 nonattainment area. We believe that the

satellite portions of NNAs best fit the definition of a donut area for transportation

conformity purposes. Section 93.101 of the conformity rule defines “donut areas” as

“geographic areas outside a metropolitan planning area boundary, but inside the

boundary of a nonattainment or maintenance area that contains any part of a

metropolitan area(s). These areas are not isolated rural nonattainment and

maintenance areas.” [http://fhwa.dot.gov/environment/conformity/faqs.htm#pm25;

question #7]

The conformity guidance for “donut” areas was entitled Companion Guidance for the July 1,

2004, Final Transportation Conformity Rule: Conformity Implementation in Multi-jurisdictional
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 35

Nonattainment and Maintenance Areas for Existing and New Air Quality Standards. The partial

county of Pleasants is thus considered a “doughnut area” for planning purposes. As part of the

PM2.5 Air Quality analysis, a small portion of Pleasants County [WV] was added to the Wood

County area as a “donut”. In this “donut” area there are roads with different classifications. The

WVDOT provided WWW with the VMT on these roads [in the “donut area”] for the year 2004.

Based upon the advice of the WVDAQ, the modeling area’s growth factor was used to calculate

the donut area VMT [with respect to functional class] for the years 2002, 2009, 2015 and 2025.

This donut area VMT was added to the Wood County VMT and the Air Quality results were

determined based upon that information.

Input files were developed for modeling mobile emissions with the Mobile6.2 software by using

the VMT split by functional class. The area type parameters were established by the West

Virginia Division of Air Quality (WVDAQ) for Wood County. The assumptions related to the

derivation of model inputs were developed as part of an interagency consultation process

involving the following agencies: 

• West Virginia Division of Air Quality. 

• West Virginia Department of Transportation. 

• Wood-Washington-Wirt Interstate Planning Commission. 

• Federal Highway Administration. 

• Ohio Department of Transportation. 

• U.S. EPA. 

• Ohio EPA. 

The results of the Mobile6.2 analysis yields mobile emission rates that can be used along with

the VMT by functional class of roadway to derive estimates of total mobile source emissions for

NOx and PM2.5. The conformity results are represented in Table 2.5-3. The conformity rule

required the region’s LRTP to conform to the SIP before FHWA approves the funding of future

projects. The conformity evaluation is determined by the processes outlined in the conformity

rule. The WWW PM2.5 nonattainment area has demonstrated conformity with the PM2.5

transportation conformity rule using the base year interim emissions test.

Table 2.5-3. Conformity Results

Year NOx,

(tpd)

NOx,

(Annual)

% Change

from base

PM2.5

(tpd)

PM2.5

(Annual)

% Change

from base

2002 6.54 2,388.50 na 0.13 46.26 Na

2009 4.23 1,543.31 -35.4% 0.08 30.64 -33.8%

2015 2.44 890.96 -62.7% 0.06 21.48 -53.6%

2025 1.37 499.97 -79.1% 0.05 18.01 -61.1%

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 36

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 PM2.5, NOx, and SO2 are insignificant contributors to the

nonattainment problem for the Parkersburg area and are therefore exempt from transportation

conformity evaluation under 40CFR93.109(k).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 37

3.0. ATTAINMENT DEMONSTRATION METHODS AND INPUTS

[40 CFR §51.1007]

The attainment modeling for the Parkersburg 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 Parkersburg 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 38

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

Parkersburg 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 39

• 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 40

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).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 41

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.

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 42

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.

• Data Availability: In parallel with the CART analysis, episode characterization analyses,

collaborative investigations by VISTAS states (e.g., NCDAQ, Georgia DNR, FL DEP)
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 43

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 44

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. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 45

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 46

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

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 14, 2008, 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 47

In addition to the various source sectors, there are various types of emissions inventories. The

first 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. 

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. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 48

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.

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. Outside of the

VISTAS region, 2002 emissions obtained from the non-VISTAS regional planning organizations

(RPOs) were used in an “as-is” format with no modification made for actual or typical operation.

Through a request from VISTAS, Midwest Regional Planning Organization (MRPO) provided

EGU data for their states, including Washington County, Ohio. MRPO data for Washington

County did not contain SO2 emissions values. Therefore, SO2 from EGUs in Washington County

was not modeled in any processing for 2002. Emissions data were provided for other pollutants,

however. MRPO does not have a public site available. Their website advises to call Mark

Janssen directly for access. The data were downloaded from

http://www.ladco.org/oldsite/tech/emis/index.html.

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 usually 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. 

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 49

Table 4.1.a.1-1 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 447,828 423,736 5.4 161,038 154,704 3.9

FL 453,631 483,590 -6.6 257,677 282,507 -9.6

GA 514,952 517,633 -0.5 147,517 148,126 -0.4

KY 484,057 495,153 -2.3 198,817 201,928 -1.6

MS 67,429 60,086 10.9 43,135 40,433 6.3

NC 477,990 478,489 -0.1 151,854 148,812 2.0

SC 206,399 210,272 -1.9 88,241 88,528 -0.3

TN 334,151 320,146 4.2 157,307 152,137 3.3

VA 241,204 233,691 3.1 86,886 85,081 2.1

WV 516,084 500,381 3.0 230,977 222,437 3.7

Total 3,743,725 3,683,968 1.6 1,523,449 1,497,864 1.7

4.1.a.1.b. Other Industrial Point Sources (NonEGUs)

For nonEGU sources, the same inventory is 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 14, 2008 (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 Washington County, Ohio. MRPO data for

Washington County did not contain SO2 emissions values. Therefore, SO2 from nonEGUs was

not modeled in any processing for 2002. Emissions data were provided other pollutants,

however. MRPO does not have a public site available. Their website indicates to call Mark
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 50

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. 

Carnegie Mellon University (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 had 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 decided to revise 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 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 51

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 14, 2008 (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 Washington 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.

4.1.b. Mobile Sources

The mobile source sector consists of two sub-sectors, usually 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.

WV DEP 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 52

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 WV DEP’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 14, 2008 (Appendix N). 

NONROAD2005 runs were also performed by MACTEC for Washington County, Ohio using

the same procedure as used for the VISTAS region.

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

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. 

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 14, 2008 (Appendix N). 

Nonroad sector emissions of the categories calculated outside of the NONROAD Model for

Washington 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. MRPO aircraft emissions data for

Washington 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 53

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 Washington 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.

4.1.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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 54

Biogenic emissions are included here to provide context with anthropogenic emissions. Biogenic

emissions are assumed to stay constant so projections were not made. Pleasants and Wood

County emissions are summarized below.

Table 4.1.c-1. West Virginia Biogenic Emissions

State Name County Name FIPS NO (tons/year) VOC (tons/year)

West Virginia Pleasants 073 32 4,165

West Virginia Wood 107 67 6,087

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.

4.1.d. Summary 2002 Baseline Emissions Inventory for West Virginia

Table 4.1.d-1 is a summary of the 2002 baseline emissions inventory for the West Virginia

portion of the Parkersburg nonattainment area. Table 4.1.d-2 summarizes the 2002 baseline

emissions inventory for the Washington County, Ohio portion. Table 4.1.d-3 summarizes the

combined inventories for sources from entire Parkersburg nonattainment area. The complete

inventory is contained in Appendix C. The emissions summaries for the other VISTAS/ASIP

states and Ohio can also be found in Appendix C. See Tables 4.2.d-1 through 4.2.d-3 for the

2009 baseline emissions inventory. The complete inventory is contained in Appendix C.

Table 4.1.d-1 2002 Base Year Inventory - West Virginia Portion of Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 52 21,835 1,769 1,068 70,293 1,162

Area 117 749 5,005 1,139 1,311 3,859

Nonroad 1 2,506 130 120 134 1,138

Onroad 86 2,667 62 44 111 1,956

Biogenic N/A 99 N/A N/A N/A 10,252

Total 255 27,856 6,966 2,372 71,849 18,368
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 55

Table 4.1.d-2. 2002 Base Year Inventory - Ohio Portion of Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 608 33,588 1,612 681 01 767

Area 656 188 1,261 317 40 846

Nonroad 1 1,399 64 60 112 502

Onroad 73 2,424 57 42 112 1,577

Biogenic N/A 90 N/A N/A N/A 5,926

Total 1,338 37,690 2,994 1,100 2641 9,618

1

Note: MRPO did not provide to VISTAS SO2 point source emissions for Washington County, Ohio.

Table 4.1.d-3. Summary of 2002 Baseline Emissions Inventory for Parkersburg

Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 660 55,424 3,381 1,749 70,293 1,929

Area 773 937 6,266 1,455 1,351 4,705

Nonroad 2 3,906 194 181 246 1,641

Onroad 159 5,091 119 87 222 3,533

Biogenic N/A 189 N/A N/A N/A 16,178

TOTAL 1,593 65,546 9,960 3,472 72,113 27,985

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,

EGAS6 for nonEGUs, and NONROAD2005 and MOBILE6.2 for nonroad and onroad estimates.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 56

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 ;

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:
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 57

• 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 MANEVU which included any enforceable actions, such as the Illinois Power NSR settlement. WV

DEP provided the latest information regarding when and where new SO2 and NOx controls are

planned to come online. WV DEP also reviewed the IPM results to verify that existing controls

and emission rates were properly reflected in the IPM runs. As directed by WV DEP,

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

units will install controls as a result of CAIR and when these new controls will come online.

Review of the initial IPM data indicated that control efficiencies for the Pleasants Units 1 and 2

were set at 79.9% while the true control efficiency is 95%. MACTEC were 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 14, 2008 (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. 

As noted in section 4.1.a.1.a, MRPO did not provide SO2 emissions for Washington County,

Ohio with their 2002 data. SO2 emissions were also missing in their 2009 data set. However,

IPM-generated data, which contained SO2 emissions, were used for the 2009 modeling. MRPO

provided 2009 emissions data for PM10, PM2.5, NOx, 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). For programs
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 58

“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 WV

DEP 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 or new start-ups identified for the 2009 projected inventory in the Parkersburg 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

Parkersburg nonattainment area. Washington County, Ohio data were provided to VISTAS

contractors for the inventory. 

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 14, 2008 (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.

As noted in section 4.1.a.1.b, MRPO did not provide SO2 emissions to VISTAS for Washington

County, Ohio with their 2002 data. SO2 emissions were also missing in their 2009 data set.

However, IPM-generated data, which contained SO2 emissions, were used for the 2009

modeling. Although nonEGU SO2 data were not modeled, Muskingum River and Gorsuch power

plants accounted for about 96% of SO2 emissions in Washington County. MRPO provided 2009

emissions data for PM10, PM2.5, NOx, and VOC. 

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

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 59

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 14, 2008 (Appendix N). 

MRPO area source data for Washington 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

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. Although early versions of the inventory captured Stage II

refueling in the area source inventory, Stage II refueling was moved to the on- and nonroad

sectors in the final version. West Virginia does not require mobile source controls other than
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 60

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 sources found in the NONROAD model and those sources

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 sources 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.

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 61

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 Washington 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 crafted 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: 

• 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 62

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 14, 2008 (Appendix N).

MRPO onroad source data for Washington 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area 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-1 is a summary of the 2009 emissions inventory for the West Virginia portion of the

Parkersburg nonattainment area. Table 4.2.d-2 is a summary of the 2009 emissions inventory for

the Ohio portion of the Parkersburg nonattainment area. Table 4.2.d-3 is a summary of the 2009

emissions inventory for the entire Parkersburg nonattainment area. See Tables 4.1.d-1 through

4.1.d-3 for the 2002 baseline emissions inventory. The complete inventory and discussion of the

methodology is contained in Appendices C, D and N.

Table 4.2.d-1. 2009 Attainment Year Inventory - West Virginia Portion of

Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 60 11,172 1,913 1,139 39,204 1,053

Area 115 784 5,057 1,133 1,404 3,538

Nonroad 1 2,318 118 109 22 1,028

Onroad 104 1,664 50 32 13 1,216

Biogenic NA 99 NA NA NA 10,252

Total 280 16,035 7,138 2,413 40,643 17,086

Table 4.2.d-2. 2009 Attainment Year Inventory - Ohio Portion of Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 752 6,295 3,786 2,594 13,9091 836

Area 749 209 1,264 319 64 976

Nonroad 1 1,094 52 49 20 429

Onroad 79 1,405 43 28 11 876

Biogenic NA 90 NA NA NA 5,926

Total 1,580 9,093 5,146 2,990 14,004 9,042 1

Note: MRPO did not provide to VISTAS SO2 point source 2009 emissions for Washington County, Ohio. However,

2009 SO2 emissions data were developed from IPM so that subsequent modeling accounted for EGUS. Although

SO2 emissions from nonEGUs were not modeled, EGU SO2 accounted for 96% of the Washington County, Ohio

point source inventory. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 64

Table 4.2.d-3. 2009 Attainment Year Inventory - Parkersburg Nonattainment Area

Sector NH3

(tons)

NOx

(tons)

PM10

(tons)

PM2.5

(tons)

SO2

(tons)

VOC

(tons)

Point 812 17,466 5,699 3,733 53,113 1,889

Area 864 993 6,322 1,453 1,468 4,514

Nonroad 2 3,412 170 158 42 1,457

Onroad 183 3,068 93 60 24 2,091

Biogenic NA 189 NA NA NA 16,178

Total 1,861 25,128 12,284 5,403 54,647 26,129

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 9,963 12,687 115,346 21,049 11,667 60,443

Nonroad 9 33,239 1,850 1,728 2,112 18,566

Onroad 2,036 63,525 1,481 1,068 2,635 45,284

Biogenic NA 2,776 NA NA NA 357,850

TOTAL 12,461 389,816 140,755 39,369 586,568 497,918

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 644 124,350 17,539 10,578 324,550 14,404

Area 10,625 14,326 118,106 23,680 12,284 57,346

Nonroad 11 30,133 1,640 1,528 359 18,069

Onroad 2,292 38,392 1,145 734 299 26,584
Table 4.3.b. 2009 State-wide Emissions Inventory Summary for West Virginia

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 65

Biogenic N/A 2,776 N/A N/A N/A 357,850

TOTAL 13,572 209,978 138,429 36,520 337,491 474,254

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 66

Figure 4.4-b. Annual NOx emissions in 2002, 2009 and 2018 in the VISTAS states.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 67

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 68

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 69

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 USEPA’s Guidance On The Use Of Models And

Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and

Regional Haze.

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-

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. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 70

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 5.1-1. 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

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].
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 71

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).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 72

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).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 73

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 74

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 75

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 76

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 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.

• 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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 77

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 78

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 79

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. 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. 

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 80

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

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 both the West Virginia and Ohio 

portions of the Parkersburg area, are presented in the table below.

Table 6.1-1. 2009 Point Source Emission Reductions

West Virginia portion of Parkersburg Area Emission Reductions (tons/year)

NOx Reductions 10,664

SO2 Reductions 31,090

PM2.5 Direct Reductions -71

Ohio portion of Parkersburg Area Emission Reductions (tons/year)

NOx Reductions 27,294

SO2 Reductions 132,623

PM2.5 Direct Reductions -1,913
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 81

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 Stategies

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 USEPA 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 USEPA, 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 USEPA 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).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 82

Federal emissions standards applicable to compression-ignition nonroad utility engines are

promulgated under §7547(a).

USEPA’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.

USEPA 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 USEPA, 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 USEPA under 42 U.S.C. §7547(a).

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

This USEPA measure controls emissions from several groups of previously unregulated nonroad

engines, including large industrial SI engines.

The USEPA 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 83

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 USEPA 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 USEPA 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,
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 84

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 both the West Virginia and Ohio portions of the Parkersburg area.

Table 6.3-1. 2009 Nonroad Emission Reductions 

West Virginia portion of Parkersburg Area Emission Reductions (tons/year)

NOx Reductions 189

SO2 Reductions 111

PM2.5 Direct Reductions 11

Ohio portion of Parkersburg Area Emission Reductions (tons/year)

NOx Reductions 305

SO2 Reductions 92

PM2.5 Direct Reductions 11
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 85

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, USEPA 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-dut 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 0.40 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 USEPA 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 86

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 beginnin June 1,

2006.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 87

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 both the West Virginia and Ohio portions

of the Parkersburg area. See Appendix D for documentation of the MOBILE 6.2 modeling

process.

Table 6.4-2. Onroad Emission Reductions 

West Virginia portion of the Parkersburg Area Emission Reductions (tons/year)

NOx Reductions 1,003

SO2 Reductions 98

PM2.5 Direct Reductions 13

Ohio portion of the Parkersburg Area Emission Reductions (tons/year)

NOx Reductions 1,019

SO2 Reductions 101

PM2.5 Direct Reductions 14
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 88

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.wvdo.org/community/EOD.pdf).

The WVDOE sponsors a number of programs, including:

• Ride Share Program (http://www.wvdo.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.wvdo.org/community/cleanairforum-2006.pdf). The Clean

Air Forum newsletter offers energy information from around the state.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 89

• Alternative Fuels Program (http://www.wvdo.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.wvdo.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.wvdo.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.wvdo.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.wvdo.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.wvdo.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.wvdo.org/community/recycling.html). The West

Virginia Recycling Directory is updated annually and lists over 500 West Virginia

recyclers.

• Renewable Energy Program (http://www.wvdo.org/community/renewable.html). Solar

energy (http://www.wvdo.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.wvdo.org/community/biofuels.html) is looking at energy uses for wood and

other biomass resources. The wind program

(http://www.wvdo.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.wvdo.org/community/schoolenergy.html). Developing a systematic

approach to reducing energy use in West Virginia public schools.

• West Virginia ENERGY STAR® Program

(http://www.wvdo.org/community/energystar.html). ENERGY STAR® is a government

backed program helping businesses and individuals protect the environment through

superior energy efficiency. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 90

6.6. Schedule of Adopted Control Measures

Table 6.6-1. West Virginia Schedule of Adopted Control Measures Parkersburg

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

5/1/20063

5/1/20063

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 Federal 45CSR6 9/1/19698

Amended: 7/1/2001

Nonroad Measures

6.3.a.1. EPA Nonroad Gasoline

Engine Rule

Federal 40 CFR Parts

90, 91

12/3/1996

6.3.a.2. EPA Nonroad Diesel

Engines Rule

Federal 40 CFR Part 9

et al.

Model Year 2000-

2008 depending on

engine size
Table 6.6-1. West Virginia Schedule of Adopted Control Measures Parkersburg

Nonattainment Area

Ref. No. Control Measure Mandate Regulation

Number

Effective Date

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 91

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

11/8/2002

6.3.a.5. Standards for Locomotives Federal 63 FR 18998 6/15/1998

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 2/10/2000

6.4.a.4. Heavy-Duty Diesel Engine

Rule

Federal 63 FR 54694 12/22/1997

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. CAIR rules were submitted to EPA as a SIP revision on

6/1/2006. 

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].
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 92

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

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.

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 quaterly mean

concentration predicted near the monitoring site.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 93

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.

7.2. 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 for the FRM sites in the WV PM2.5 nonattainment areas.

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

(Base G4)

AIRS ID State County 1st Q

DVF

2nd Q

DVF

3rd Q

DVF

4th Q

DVF

2009

Annual

DVF

54-003-0003 WV Berkeley 13.3 12.8 15.0 13.2 13.6

54-009-0005 WV Brooke 13.4 14.1 15.1 12.5 13.8

54-011-0006 WV Cabell 13.2 14.2 16.8 12.4 14.1

54-029-0011 WV Hancock 12.6 13.4 14.6 12.0 13.1

54-029-1004 WV Hancock 13.4 14.4 16.3 12.7 14.2

54-033-0003 WV Harrison 10.3 12.0 14.3 9.9 11.6

54-039-0010 WV Kanawha 12.1 13.7 15.7 11.1 13.2

54-039-1005 WV Kanawha 13.6 15.2 17.2 13.0 14.8

54-049-0006 WV Marion 12.3 13.0 15.3 11.3 13.0

54-051-1002 WV Marshall 13.7 13.4 15.0 11.5 13.4

54-055-0002 WV Mercer 8.5 11.4 13.0 9.2 10.5

54-061-0003 WV Monongalia 11.3 12.9 15.4 10.2 12.5

54-069-0010 WV Ohio 12.3 12.9 14.7 11.0 12.7

54-081-0002 WV Raleigh 9.0 11.8 13.7 9.2 10.9

54-089-0001 WV Summers 6.0 9.7 11.3 6.1 8.2
Table 7.2-1. Quarterly Mean and Annual Mean PM2.5 Mass Estimates for 2009 

(Base G4)

AIRS ID State County 1st Q

DVF

2nd Q

DVF

3rd Q

DVF

4th Q

DVF

2009

Annual

DVF

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 94

54-107-1002 WV Wood 13.3 14.2 16.2 12.3 14.0

These 2009 DVFs are the final product of the SMAT process and 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 <15.0 μg/m3

, all areas have passed the attainment

test portion of the attainment demonstration.

7.3. Supplemental Analyses

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.

Five of the six West Virginia PM2.5 nonattainment areas, including Parkersburg, have DVFs

lower than the 14.5 μg/m3

, making the following section an examination of supplemental

analyses to corroborate modeling results, rather than a WOE analysis to show attainment.

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. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 95

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

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:

1. The meteorology was for 2001,

2. The DVB was the weighted design values for the 1999-2003 period, and

3. 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

WV Berkeley 16.18 15.69 13.43 15.32 12.73

WV Brooke 16.96 16.63 14.42 16.51 14.05

WV Cabell 17.22 17.03 15.08 16.86 14.64

WV Hancock 17.40 17.06 14.89 16.97 14.54

WV Harrison 14.40 14.15 11.90 13.82 11.31

WV Kanawha 17.75 17.56 15.27 17.17 14.66

WV Marion 15.58 15.32 12.90 14.98 12.23

WV Marshall 16.07 15.81 13.46 15.52 12.87

WV Mercer 12.97 12.52 10.82 12.14 10.16

WV Monongalia 14.96 14.77 12.31 14.37 11.40
Table 7.3-1. EPA CAIR Modeling Results

State County Average 

99-03

2010

Base

2010

CAIR

2015

Base

2015

CAIR

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 96

WV Ohio 15.37 15.14 12.81 14.84 12.22

WV Raleigh 13.54 13.19 11.33 12.80 10.66

WV Summers 10.46 10.21 8.63 9.89 8.07

WV Wood 16.88 16.66 14.14 16.69 13.88

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 Parkersburg (Wood County) nonattainment

area should be below the annual PM2.5 standard by 2010. Although this is one year later than the

attainment year for the area, the EPA’s 2010 CAIR DVF is 0.14 μg/m3

 higher than the WVDEP

is showing in the attainment demonstration, but still supports that the area will attain the annual

PM2.5 standard by the attainment year of 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://ladco.org/Technical_Support_Document.html. 

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

5400900051 Brooke 16.8 16.4 16.4 16.5 13.5

5401100061 Cabell 16.3 16.1 16.6 16.3 13.6

5402900111 Hancock 16.4 15.7 15.9 16.0 13.0

5402910041 Hancock 16.6 15.4 15.2 15.7 12.8
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

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 97

5403300031 Harrison 13.9 13.9 14.2 14.0 11.6

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

5404900061 Marion 15.0 14.9 15.3 15.1 12.7

5405110021 Marshall 15.3 15.0 15.2 15.2 12.4

5405500021 Mercer 12.8 13.3 14.5 13.5 10.7

5406100031 Monongalia 14.5 14.1 14.4 14.3 11.9

5406900081 Ohio 14.6 14.1 0.0 14.4 11.7

5406900101 Ohio 15.4 14.3 14.6 14.8 12.0

5408100021 Raleigh 12.9 12.8 13.0 12.9 10.9

5408900011 Summers 10.6 11.2 12.5 11.4 8.7

5410710021 Wood 15.4 15.3 15.4 15.4 12.9
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 98

7.3.b. Trends in Ambient Air Quality and Emissions

Table 7.3.b-1. Air Monitoring Data for Parkersburg Area

AIRS ID County 1999 2000 2001 2002 2003 2004 2005 2006

54-107-1002 Wood 17.7 17.8 17.4 15.8 14.9 14.9 16.4 14.7

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

As shown in Table 7.3.b-1 and Figure 7.3.b-1 the air quality in the Parkersburg area has been

trending downward. In addition, as shown in 7.3.b.2. the emissions of PM, NOx and SO2 have

also been decreasing.

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 Parkersburg area will attain the standard by the April 2010 deadline.

Parkersburg

0

2

4

6

8

10

12

14

16

18

20

1999 2000 2001 2002 2003 2004 2005 2006

PM2.5 (ug/m3)

Annual PM2.5 Standard

Wood (54-107-1002)

Linear (Wood (54-107-

1002))
WV PM2.5 SIP for the Parkersburg Nonattainment Area 

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

Parkersburg Area - PM10-FIL

0

200400600800

100012001400160018002000

1999 2002 2005

tons/year Pleasants, WV Wood, WV

Parkersburg Area PM25-FIL

0

100200300400500600700800900

1000

1999 2002 2

tons/year 

Parkersburg Area - NOx

0

5000

1000015000200002500030000

1999 2002 2005

tons/year Pleasants, WV Wood, WV

Parkersburg Area - SO2

0

1000020000300004000050000600007000080000

1999 2002 2

tons/year 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 100

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, Parkersburg 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.

VISTAS regional scale modeling resulted in a 2009 DVF of 14.0 μg/m3,for Wood County (AIRS

ID 54-107-1002), which is below the NAAQS. VISTAS modeling of future and base year

emissions resulted in a spatial field of relative response factors (RRFs). Table 1. contains the

VISTAS modeling results, including the Parkersburg area (Wood County). For the Parkersburg

area, all RRFs in the spatial field are less than one, indicating a reduction in design values for all

grid cells. Interpolation between these grid cells would result in RRFs of less than one for all

unmonitored areas, thus indicating a reduction in design values for all grid cells, including those

cells that are not monitored. Combining this result with spatial field of monitored values would

lead to expectation that all concentrations in unmonitored areas would not be higher than the

concentration values at actual monitoring sites. 

The Parkersburg area is located in the north-west portion of West Virginia and is characterized

by rolling terrain with moderate differences in elevation. Elevations in Wood County range from

tens of feet to several hundreds of feet. As such, it is not expected that actual concentration

values in unmonitored areas will exceed either the spatial field of monitored values or the spatial

field of RRFs as a result of terrain influences. As a result, terrain influences are not expected to

contribute to future year design values that are greater than the NAAQS in unmonitored areas.

Finally, since sulfates dominate the individual contribution to PM2.5 at the Wood County site and

is a widespread, dominating component at other sites in the region we do not expect significant

PM2.5 gradients in the Wood County non-attainment area, including the unmonitored areas.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 101

Table 7.4-1. VISTAS Regional Scale Modeling Results

AIRS ID County 2002

Annual

DVC

2009 

Annual 

(Base G4a) 

DVF

Difference

(2009 DVF2002 DVC)

Notes

54-003-0003 Berkeley 16.2 13.6 -2.6

54-009-0005 Brooke 16.7 13.8 -2.9

54-011-0006 Cabell 16.5 14.1 -2.4

54-029-0011 Hancock 15.8 13.1 -2.7

54-029-1004 Hancock 17.3 14.2 -3.1

54-033-0003 Harrison 14.0 11.6 -2.4

54-039-0010 Kanawha 15.4 13.2 -2.2

54-039-0011 Kanawha 12.6 Missing SMAT Data

54-039-1005 Kanawha 17.1 14.8 -2.3

54-049-0006 Marion 15.3 13.0 -2.3

54-051-1002 Marshall 15.6 13.4 -2.2

54-055-0002 Mercer 12.7 10.5 -2.2

54-061-0003 Monongalia 14.8 12.5 -2.3

54-069-0010 Ohio 15.1 12.7 -2.4

54-081-0002 Raleigh 13.1 10.9 -2.2

54-089-0001 Summers 10.1 8.2 -1.9

54-107-1002 Wood 16.1 14.0 -2.1
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 102

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 Parkersburg area is 14.0 μg/m3

, well below the annual PM2.5

standard; therefore, the WVDAQ may 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. 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.

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 103

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 Parkersburg area will attain by 2010.

Therefore, RFP is satisfied and further RFP analysis is unwarranted.

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 104

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

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]. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 105

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. By letters dated April 3, 2008 and July

9,2008, WVDAQ certified to EPA Region III that specific elements under Section 110(a)(2)

have previously been 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.

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).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 106

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. 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.

8.9.b. Evaluations/Required Reductions

The contingency measures for the attainment demonstration must total one year of reductions

needed to attain. The inventory is calculated as described in Section 4. Table 8.9-1 shows the

calculation of the necessary reductions.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 107

Table 8.9-1. Contingency Requirement for PM and PM Precursors

PM 

Precursor

PM and PM Precursor Emissions 2002-2009 (tons/year)

2002 2009 2002-2009

Contingency

Requirement

Calculation

(2002-2009)

7

NOx 27,758 15,503 12,255 1,750.7

PM2.5 Direct 2,372 2,387 0 0.0

SO2 71,849 40,648 31,201 4,457.3

8.9.c. Equivalency Ratios

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.

According to EPA guidance, emission reductions from different precursors can be used to meet

the required contingency target. EPA recommended a method to assess equivalent reductions for

different precursors. The recommended approach is to review existing data and sensitivities

performed as part of photochemical modeling to estimate the relative impact of different

precursors on PM2.5 concentrations. Basing an equivalency ratio on relative reduction factors as

generated by the Community Multiscale Air Quality (CMAQ) modeling results in a quarterly 

ratio of 1.1 to 1.3 tons of NOx for each ton of SO2 (see Appendix L.1). Using sensitivity analyses

created by VISTAS and Georgia Tech (see Appendix L.2), gives an equivalency ratio of 4.5 tons

of NOx for each ton of SO2 in the Parkersburg area. 

Table 8.9-2. Quarterly Speciated Relative Reduction Factors (RRFs) for Wood County

Quarter Crustal EC OC SO4 NO3 NO3/SO4

Q1 1.09996 0.86626 0.98344 0.90487 0.96170 1.1

Q2 1.11903 0.82319 0.96604 0.71783 0.77616 1.1

Q3 1.14873 0.85710 0.96181 0.65552 0.83964 1.3

Q4 1.12030 0.82492 0.98609 0.86338 0.97177 1.1
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 108

8.9.d. Identified Contingency Measures

Table 8.9-2 lists the contingency measures identified by West Virginia for the Attainment

Demonstration. These measures deliver a total benefit of 246 tons/year of PM2.5, 1,093 tons/year

of NOx and 9,358 tons/year of SO2. The NOx reductions are 596 tons less than the required

reduction. However the SO2 reductions are 6,120 tons greater than required. The excess SO2

reductions are more than 7 times the required additional NOx reduction, and this ratio is

significantly higher than the equivalency assessments described in Section 8.9.c. The

contingency measures for the Parkersburg attainment plan are well in excess of the equivalency

ratios described in Section 8.9.c and therefore, should be an appropriate backstop for improving

air quality if the monitoring network does not demonstrate compliance with the 1997 PM2.5

NAAQS in 2009.

Table 8.9-2. Contingency Measure Reductions from 2002 Emissions (tons/year) 

Contingency Measure NOx

(tpy)

PM2.5

(tpy) 

SO2

(tpy)

Cabot - Plant Shutdown 782 81 6,961

Cytec - Replacement of Coal-fired boilers with gas fired boilers 311 165 2,397

TOTAL REDUCTIONS from Contingency Measures 1,093 246 9,358

Table 8.9-3. Determination of Excess Reductions from Contingency Measures

NOx

(tpy)

PM2.5

(tpy) 

SO2

(tpy)

Reductions from Contingency Measures 1,093 246 9,358

Required Reductions from Contingency Measures 1,751 0 4,457

Difference (Excess reductions +, additional reductions needed -) -658 246 4,901

NOx equivalence for SO2

(Needed NOx reductions/1.1 equivalency ratio)

(658 tons NOx = 598 tons SO2)

658 – 598

Excess reductions from Contingency Measures 0 246 4,303

In accordance with EPA’s guidance encouraging early implementation of contingency measures

to guard against failure to either meet a milestone or attain, West Virginia has implemented the

contingency measures identified in Table 8.9-2 according to the timetable indicated in Section 6.

EPA’s guidance on early implementation of control measures is as follows:
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 109

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 are surplus, that is, beyond those

contained in the Attainment Demonstration enclosed in this SIP. 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 they choose to implement in advance of the requirement. 
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 110

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 Parkersburg region, the State of West Virginia implements all RACM. to demonstrate

attainment on the earliest date possible with the annual PM2.5 standard.

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 RACT for stationary sources) necessary

to demonstrate attainment as expeditiously as practicable and to meet any RFP

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.

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 Clean Air Interstate Rule (CAIR). 

Modeling data provided in Section 4 demonstrates that continued implementation of these

control measures described in Section 6, along with CAIR, will allow the Parkersburg area to

come into compliance with the 1997 PM2.5 NAAQS on or before April 2010, as required by 40

CFR §51.1004.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 111

9.3. Discussion of RACT

9.3.a. EGU RACT Analysis

Eight coal-fired power plants having a combined total of 20 utility boilers, which also may be

called electricity generating units (EGUs), operate within four of West Virginia’s six nonattainment areas for particulate matter having an aerodynamic diameter of 2.5 microns or less

(PM2.5). Besides PM2.5, these boilers emit two other pollutants of concern: sulfur dioxide (SO2)

and nitrogen oxides (NOx). 

With guidance published by the U.S. Environmental Protection Agency (EPA) and through

technical and economic analyses, the Division of Air Quality (DAQ) of the West Virginia

Department of Environmental Protection determined potential reasonably available control

technology (RACT) candidates for these pollutants from utility boilers. This analysis presents

DAQ’s final ranking of those RACT candidates.

Based on review of EPA guidance, though, DAQ believes no additional controls for the

pollutants of concern will be needed at these power plants’ boilers.

However, if controls were warranted, DAQ foresees at least two obstacles that prevent

implementation that would advance the attainment date. 

1. One is the timing involved in the design/procure/fabricate/install/accept process for

equipment. Based on its analysis, DAQ believes insufficient time exists between now and

2009 for an owner/operator to initiate and then successfully complete the process for

traditional or innovative controls, as well as for major upgrades to existing controls. 

2. The other is the uncertainty of cost-effectiveness data. DAQ believes selection of any ranked

RACT candidate demands site-specific knowledge, including accurate actual cost data,

instead of data estimated through regulatory models. Based on its research, DAQ believes

available data are outdated or do not reflect current supply-demand pressures that have

significantly increased costs in recent years.

9.3.a.1. Background

Depending on the non-attainment areas in which these power plants are located, they may or

may not generate most of stationary-source emissions that contribute directly or indirectly to

PM2.5 non-attainment. Of those emissions, though, direct PM2.5 emissions have more significance

in their ability to directly contribute to non-attainment than SO2, which does so indirectly

through atmospheric or secondary formation of sulfates; or NOx, which does so through

atmospheric formation of nitrates.

Two tables generally describe the plants. 

• Table 9.3.a-1 lists the plants, their respective boilers and sizes, and the non-attainment

area in which each plant is located.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 112

• Table 9.3.a-2 lists the respective, current estimated emissions, in tons per year (tpy), from

each plant for the three principal pollutants of concern: PM2.5-Primary – the sum of

filterable and condensable fractions contained in the stack gas measured by an EPA test

method – as well as SO2 and NOx.

The table also contains data on emissions of PM10-Primary. PM10 is particulate matter with an

aerodynamic diameter of 10 microns or less. PM10-Primary comprises the filterable and

condensable fractions contained in the stack gas measured by an EPA test method. Note that

footnotes for both tables are explained at the bottom of Table 9.3.a-2.

Table 9.3.a-1. West Virginia Coal-Fired Power Plants in PM2.5 Nonattainment Areas

Facility Name Total Boilers Combined Generating

Capacity (MW)

Nonattainment Area

John Amos 3 2,900 Charleston

Kanawha River 2 400 Charleston

Mitchell 2 1,600 Wheeling

Kammer 3 630 Wheeling

Mountaineer 1 1,300 Huntington

Philip Sporn 5 1,050 Huntington

Pleasants 2 1,300 Parkersburg

Willow Island 2 235 Parkersburg

Table 9.3.a-2. PM10-Primary, PM2.5-Primary, SO2 and NOx from West Virginia 

Coal-Fired Power Plants in PM2.5 Nonattainment Areas, (tpy)A

Facility Name PM10-PrimaryB

Emissions (tpy)

PM2.5-PrimaryB

Emissions (tpy)

SO2 Emissions

(tpy)

NOx Emissions

(tpy)

John Amos 552 271 107,552 44,479

Kanawha River 240 118 15,691 6,138

Mitchell 252 123 59,165 31,163

Kammer 78 56 42,064 14,325
Table 9.3.a-2. PM10-Primary, PM2.5-Primary, SO2 and NOx from West Virginia 

Coal-Fired Power Plants in PM2.5 Nonattainment Areas, (tpy)A

Facility Name PM10-PrimaryB

Emissions (tpy)

PM2.5-PrimaryB

Emissions (tpy)

SO2 Emissions

(tpy)

NOx Emissions

(tpy)

WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 113

Mountaineer 279 136 43,008 12,883

Philip Sporn 198 96 41,207 13,611

Pleasants 779 338 41,917 13,718

Willow Island 333 210 14,460 5,948

Notes: AData taken from DEP analysis of 2002 emissions inventory certified data submitted by sources’

owners/operators to EPA’s Clean Air Markets Division as part of the Acid Rain Program. BPrimary means that the data include both filterable and condensable fractions of PM.

9.3.a.2. Final Ranking of RACT Candidates

To determine RACT candidates that might apply to each of the three pollutants of concern

emitted from the EGU category, DAQ followed EPA guidance published in the federal

government’s March 29, 2007, Final Rule to Implement the Fine Particle National Ambient Air

Quality Standards (PM2.5 Implementation Rule).

Among several things, that guidance required evaluations of technical and economic feasibilities

of each candidate technology. For technical feasibility, DAQ compared existing controls at the

West Virginia facilities to those expected or potentially used with any coal-fired utility boiler.

Cost effectiveness of controls, presented as dollars per ton of respective pollutant removed

($/ton), described the principal test for determining if any control, for any pollutant, was

economically feasible. 

Based on the technical and economic analyses recorded in Chapters 4-6 of the EGU RACT

Analysis, Table 9.3.a-3, which DAQ considers to be the summary of its key findings, lists the

DAQ’s final ranking of RACT candidates for electric generating units. The chapters just

mentioned, which are in Appendix M, contain the respective evaluations of potential RACT for

PM2.5, SO2 and NOx. 

9.3.a.3. Why No Additional Controls Will Be Required

Based on EPA statements about controls equivalency or superiority among federal air-qualitymanagement programs, however, DAQ believes that no additional controls are needed on the

utility boilers in the state’s PM2.5 non-attainment areas.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 114

Table 9.3.a-3. Final Ranking of RACT Candidates for Coal-Fired EGUs for PM2.5, NOx

and SO2 in PM2.5 Nonattainment Areas

PollutantA Control

TechnologyB,C,D

Retrofit, Modification or Other Enhancements

PM2.5 ESP/dry Improvements/expansion to existing particulate controls

ESP/wet Gas conditioning

ESP + FF Addition downstream of full-sized FF

Addition downstream of smaller technologies such as COHPAC

Addition of particle agglomerator upstream of ESP or FF

SO2 FGD/wet Improvements to existing unitsE

SDA + FF Coal washing

FSI/furnace

DSI/duct

NOx LNB + OFA Boiler tuningE

Reburn Coal-pulverizer-plus-boiler tuningE

SCR Improved/intelligent soot blowing

SNCR

Notes: APollutants = particulate matter with an aerodynamic diameter of 2.5 microns or less (PM2.5), sulfur dioxide

(SO2) and nitrogen oxides (NOx) BControl equipment for PM = electrostatic precipitator (ESP), fabric filter (FF) or baghouse (BH) CControl equipment for SO2 = wet scrubber or wet flue-gas desulferization (wet FGD), furnace sorbent

injection (FSI), spray dry absorber (SDA) and duct or dry sorbent injection (DSI)

DControl equiment for NOx = selective catalytic reduction (SCR), selective non-catalytic reduction (SNCR),

low-NOx burner (LNB) and overfire air (OFA) E

By themselves, these enhancements might not be considered RACT. However, they or any others that

might give incremental pollutant reduction could be used with each other, as appropriate, as well as NOx

control technologies such as LNB + OFA, reburn, SCR and SNCR; SO2 scrubbers; or boilers controlled

with jucst ESPs, if compatible with existing control configurations. They could also be used in an SCR-wetFGD-ESP or SNCR-wet-FGD-ESP configuration, if the enhancements were compatible.

For example, for its Clean Air Interstate Rule or CAIR program, EPA states in its PM2.5

Implementation Rule that CAIR equals RACT for coal-fired utility boilers:

Specifically, the final rule includes a presumption that in States that fulfill their

CAIR SO2 emission reduction requirements entirely through EGU emission

reductions (i.e. without reductions from non-EGU sources or allowing non-EGU
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 115

sources to opt in to the CAIR SO2 trading program), compliance by EGU sources

with an EPA-approved CAIR SIP [State Implementation Plan] or a CAIR FIP

[Federal Implementation Plan] would satisfy their SO2 RACT/RACM [Reasonably

Available Control Measures] requirements for attaining the fine particle NAAQS

[National Ambient Air Quality Standard]. . . 

For EGUs in the CAIR region, based upon the presumption explained here, States

may define RACT/RACM as the CAIR level of control on the collective group of

sources in the region rather than impose a specific level of control on an individual

source.

And in EPA’s Oct. 2006 Regional Haze Rule—also known as the BART, or best available

retrofit technology, rule—for certain EGUs, that agency states that CAIR-related technologies

were better than BART technologies: 

In the BART rule, EPA presents the results of an analysis showing that controls for

EGUs subject to CAIR will result in more visibility improvement in natural areas

than BART would have provided. Therefore, States which adopt the CAIR cap and

trade program for SO2 and NOx are allowed to apply CAIR controls as a substitute

for controls required under BART because our analysis concluded that CAIR

controls are “better than BART” for EGUs in the states subject to CAIR.

Therefore, since West Virginia remains subject to CAIR and since the state adopted an approach

consistent with EPA’s requirements, DAQ presumes that the state’s CAIR controls for SO2 and

NOx, as well as PM2.5, equal RACT. DAQ also presumes that these controls are better than

BART controls.

If, however, additional PM2.5 reductions were required from utility boilers beyond the CAIRequals-RACT-for-EGUs statement in EPA’s PM2.5 Implementation Rule, then more controls or

modifications/upgrades to existing controls could be considered from the Table 9.3a-3 menu of

potential RACT options. 

DAQ acknowledges, though, that it may be technically feasible for owners/operators to add

more PM controls such as fabric filters or other devices to further polish or cleanse the flue gas

by removing more PM2.5. 

But DAQ believes that owners/operators of facilities that have or will have the SCR/wetFGD/ESP combination likely will not add more SO2 control devices at those facilities.

Enhancements to existing SO2 controls might be an option. However, given the newness of the

scrubbers at those facilities that have or will have them, such enhancements are also unlikely.

DAQ also does not expect owners/operators of utility boilers that already have NOx controls —

i.e., LNB, OFA, LNB + OFA, SNCR or SCR—required through the NOx SIP Call to install

additional controls. DAQ notes that currently existing SCR and SNCR units at larger utility

boilers will operate year-round when CAIR’s NOx Phase I commences. Note that DAQ defines

larger utility boilers as those with generating capacities greater than 450 megawatts (MWs).
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 116

9.3.a.4. Why Controls Implementation Could Be Delayed

If additional controls or major upgrades were required, DAQ believes those could not be

installed and operational by January 2009. Thus, the attainment date could be not advanced by

one year.

At least five major obstacles prevent realistic timely implementation by 2009 of any RACT

candidate involving retrofit of any major air-pollution-control device or major upgrades to any

existing technologies—even if an owner/operator initiated the design/procure/fabricate/install/

accept process immediately.

1. While, in the strictest sense, add-on technologies as well as enhancements or major

upgrades may be technically feasible and/or cost effective, whether any occur depends on

site-specific factors. DAQ believes regulatory estimates cannot accurately or completely

describe these factors for a particular facility, nor the costs owners/operators could incur.

Nor can regulatory estimates reasonably predict the amount of time the entire add-ontechnology/major-upgrade process may take from decision to final acceptance.

2. Because owners/operators compete simultaneously among themselves for those vendors

who have the capacity to supply equipment and services, it is unwise to presume that

equipment vendors can and will accept new capital projects. 

3. Materials and labor such as boilermakers and steelworkers, for example, to install

equipment may not be available. For example, as respondents to a Lake Michigan Air

Directors Consortium/Midwest RPO (LADCO/MRPO) draft RACT document for

industrial boilers said: “Because the ICI boiler owners and operators are competing for

resources (labor and materials) with the EGU category, there are likely to be impacts and

delays in engineering, materials procurement, etc., going forward.” 

4. At least one federal program, CAIR, injects negative impacts and delays. Besides the

competition noted in point 2, above, DAQ believes that because of CAIR and the NOx

SIP Call, costs of some controls have increased significantly in the past few years.

Likely, those costs will not plateau until the CAIR and PM2.5 programs are fully

completed.

5. If vendors can be found who will commit to supplying the equipment, based on the

technical and economic analyses performed in or referred to by this document, it appears

that it could take three to four years, if not five or six—from decision, to procurement, to

design, to fabrication, then installation and through acceptance testing—to implement

major add-on technologies at an existing site. Major upgrades may take less time, though

DAQ has no estimates of how much less.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 117

9.3.a.5. Why RACT Selection Is Site Specific and Costs May Be Underestimated

If any new technology or major upgrade is required, based on technical feasibility and cost

effectiveness, DAQ notes two significant concerns about the ranked RACT candidates,

particularly those requiring significant capital expense, and their selection:

1. Regardless of what candidate measure is selected or combination of measures are

selected, final choice at any facility, for any boiler, depends on site-specific factors.

Primarily, those include available physical space and compatibility with existing airpollution-control technologies. But among other things, site-specific factors also include

combustion processes and conditions, as well as fuels used. 

2. Regardless of the estimated costs presented in the EGU RACT analysis, they may

underestimate the real-world expenditures that could or would occur. Underestimation

could come from out-of-date data that need adjustment for inflation or for increases due

to environmental-regulations-induced supply-demand pressures. Underestimation could

also come from use of regulatory models or other means, rather than actual data, used to

derive these costs. Underestimation may also come from using inadequate retrofit

multipliers when approximating costs.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 118

9.3.b. ICI RACT Analysis

Industrial, commercial and institutional boilers — ICIs — operate within four of the state’s six

non-attainment areas for PM2.5. Besides PM2.5, these boilers emit two other pollutants of concern:

SO2 and NOx. 

Table 9.3.b-1 identifies the ICI boilers in the West Virginia portion of the Parkersburg

nonattainment area that, in 2002, had actual emissions of 50 tons of either direct PM2.5, NOx or

SO2.

Table 9.3.b-1. ICI Boilers in the West Virginia Portion of the Parkersburg

Nonattainment Area

Facility ID 2002 NOx

(tons)

2002 PM2.5

(tons)

2002 SO2

(tons)

DuPont Washington Works 107-00001 771 167 4,485

General Electric 107-00010 121 14 17

Cabot Corporation 073-00006 782 81 6,961

Cytec Industries 073-00003 423 217 2,438

With guidance published by EPA and through technical and economic analyses, DAQ

determined RACT candidates for these pollutants from ICI boilers. This analysis presents DAQ’s

final ranking of those RACT candidates.

Even if site-specific cost-effective controls are applicable, however, DAQ foresees at least two

obstacles prevent implementation that would advance the attainment date. 

• One is the timing involved in the design/procure/fabricate/install/accept process for

equipment. Based on its analysis, DAQ believes insufficient time exists between now and

2009 for an owner/operator to initiate and then successfully complete the process for

major traditional or innovative controls, as well as for major upgrades to existing

controls.

• The other is the uncertainty of cost-effectiveness data. DAQ believes that selection of any

ranked RACT candidate demands site-specific knowledge, including accurate actual cost

data, instead of data estimated through regulatory models. Based on its research, DAQ

believes available data are outdated or do not reflect current supply-demand pressures

that have significantly increased costs in recent years.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 119

9.3.b.1. Background

Because of the quantity of emissions from industrial boilers and the potential to maximize

environmental benefit from their control, this RACT analysis focuses only on them. These may

be located at source categories such as petroleum refining, carbon-black production, coal-fired

electricity generation, coal-tar distillation, coking and chemicals production. Some boilers may

combust only coal; some may have the capacity to burn coal; some burn fuel oil—typically, No.

2 low-sulfur distillate; and natural gas; and some burn natural gas as the primary fuel. 

But some industrial boilers may also burn process off-gases, such as refinery waste gas or cokeoven gas. For example, Mountain State Carbon LLC (formerly, Wheeling Pittsburgh Steel

Corp.), in Follansbee, which is in the Weirton-Steubenville interstate PM2.5 non-attainment area,

has four industrial boilers that burn coke-oven gas. Boiler sizes range from 85-92 million British

thermal units per hour (MMBTU/hr). Upstream of the boilers in a separate processing unit, that

fuel is essentially stripped of various organic fractions and sulfur. However, the gaseous feed

would contain traces of organics, hydrogen sulfide and carbonyl sulfide. The boilers also may

burn natural gas, as required. 

In varying quantities, these and all other industrial boilers in the non-attainment areas emit PM2.5,

SO2 and NOx. However, coal is the only fuel that this RACT analysis addresses for all three

pollutants. Several reasons exist why.

• Boilers that combust No. 6 residual fuel oil, which may be associated with coal-fired or

natural-gas-fired industrial boilers, do so infrequently: at startup or doing some

malfunction or limited maintenance period. Thus any PM2.5, SO2 and NOx emissions from

these units would be infrequent, at best. However, because controls might differ for the

particulate and SO2 emissions from those suggested for coal-fired boilers, DAQ did

examine controls for those two pollutants from oil combustion.

• Other oil-fired boilers use No. 2 low-sulfur distillate fuel oil that in most, if not all, cases

has a weight percent of sulfur of 0.25 or less. Because of the fuel characteristics,

required control of SO2 and PM2.5 from these units is highly unlikely. 

If, though, NOx controls were needed for boilers burning this residual fuel oil, options

would include those listed, analyzed and selected in Chap. 6 of the ICI RACT analysis, as

well as shown in Table 9.3b-6. However, DAQ notes that Table 4.4 of a Feb. 2007

technical support document—“Identification and Evaluation of Candidate Control

Measures: Final Technical Support Document. Prepared for Seth Barna, Ozone Transport

Commission (OTC), Washington, D.C. Herndon, Va. Feb. 28.”—lists No. 2 distillate as a

compliance option for boilers having inputs between 25-250 MMBTU/hr. But no

industrial boilers listed in West Virginia’s most recent emissions inventory that fire No. 2

distillate fuel oil as the primary fuel exceed heat-input rates of 250 MMBTU/hr.

• For boilers that fire natural gas primarily, if controls were needed, they would be for

NOx, not PM2.5 and/or SO2 because of the fuel’s characteristics. Therefore, DAQ

examined only NOx controls for such boilers.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 120

• Because of their size and fuel-firing rates, boilers that burn hydrogen or process gas

would not be significant sources of PM2.5, SO2 or NOx. Therefore, DAQ performed no

RACT analyses on these types of units. DAQ notes, though, that the NOx controls

examined in Chap. 6 of the ICI RACT analysis could apply to these boilers.

While all these types of industrial boilers do emit PM2.5, they are not the principal sources of

stationary-source emissions in the non-attainment areas that contribute directly or indirectly to

non-attainment. But regardless of the location of the source of those emissions, direct PM2.5

emissions have more significance in their ability to contribute to non-attainment than SO2, which

does so indirectly through atmospheric or secondary formation of sulfates; or NOx, which does

so through atmospheric formation of nitrates.

9.3.b.2. Final Ranking of RACT Candidates

To determine RACT candidates that might apply to each of the three pollutants of concern

emitted from the EGU category, DAQ followed EPA guidance published in the federal

government’s PM2.5 Implementation Rule.

Among several things, that guidance required evaluations of technical and economic feasibilities

of each candidate technology. For technical feasibility, DAQ compared existing controls at the

West Virginia facilities to those expected or potentially used with any coal-fired or oil-fired

utility boiler. Cost effectiveness of controls, presented as dollars per ton of respective pollutant

removed ($/ton), described the principal test for determining if any control, for any pollutant,

was economically feasible. 

Chapters 4-6 of the ICI RACT analysis contain, respectively, the evaluation of potential RACT

controls for PM2.5, SO2 and NOx. Based on the technical and economic analyses recorded in

those chapters, the following tables, which DAQ considers to be the summary of its key findings,

list the DAQ’s final ranking of RACT candidates for industrial boilers. 

• Table 9.3.b-2, RACT Candidates for Coal-fired Industrial Boilers for PM2.5

• Table 9.3.b-3, RACT Candidates for Oil-fired Industrial Boilers for PM2.5

• Table 9.3.b-4, RACT Candidates for Coal-fired Industrial Boilers for SO2

• Table 9.3.b-5, RACT Candidates for Oil-fired Industrial Boilers for SO2

• Table 9.3.b-6, RACT Candidates for Industrial Boilers for NOx
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 121

Table 9.3.b-2. Final Ranking of RACT Candidates for PM2.5 from Coal-fired Industrial

Boilers in PM2.5 Nonattainment Areas

Control Scenario Control Technology/Enhancement

Pre-combustion Coal washing

Post-combustion FF

ESP / wet or dry

Venturi scrubber

Wet scrubber

Multiclone/variable-throat venturi

Gas conditioningA

Addition downstream of existing control of ESP or FF

Addition downstream of smaller technologies such as COHPACA

Addition of particle agglomerator upstream of ESP or FFA

Notes: ESP = electrostatic precipitator; FF = fabric filter; and COHPAC = compact hybrid particulate collector ASome enhancements might not be considered RACT, if they were the only technology implemented.

Table 9.3.b-3. Final Ranking of RACT Candidates for PM2.5 from Oil-fired Industrial

Boilers in PM2.5 Nonattainment Areas

Control Scenario Control Technology/Enhancement

Pre-combustion Fuel switching from high-sulfur (S) fuel to lower-S fuel

Post-combustion ESP / dry

Venturi scrubber

Wet scrubber
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 122

Table 9.3.b-4. Final Ranking of RACT Candidates for SO2 from Coal-fired Industrial

Boilers in PM2.5 Nonattainment Areas

Control Scenario Control Technology/Enhancement

Pre-combustion Fuel switching: higher-S coal to lower-S coal

Coal washing

Combustion FSI

Improved/intelligent sootblowingA

Post-combustion FGD (wet)

FGD (SDA)

DSI/duct

Notes: S = sulfur; FSI = furnace sorbent injection; FGD = flue gas desulfuization (also known as wet scrubbing) ABy itself, this enhancement cannot be considered RACT. However, it might give an incremental pollutant

reduction that, when combined with other enhancements for either PM or NOx, may give significantly

reduced NOx. The slight increase in SO2 removal is incidental to the primary purpose of

improved/intelligent sootblowing: to reduce boiler generated NOx.

Table 9.3.b-5. Final Ranking of RACT Candidates for SO2 from Oil-fired Industrial

Boilers in PM2.5 Nonattainment Areas

Control Scenario Control Technology/Enhancement

Pre-combustion Fuel switching: higher-S coal to lower-S oil

Post-combustion FGD (wet)
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 123

Table 9.3.b-6. Final Ranking of RACT Candidates for NOx from Industrial Boilers in

PM2.5 Nonattainment Areas

Control Scenario Control Technology/Enhancement

Combustion LNB

WSI

OT + WSI

LNB + OFA

Coal reburn

LNB + FGR

Natural gas reburn

OT/staged combustionB

Boiler tuningB

Improved/intelligent sootblowingB

Low-excess-air firing/oxygen trimB

Switching to lower-fuel-bound-nitrogen fuel

Post-combustion SCR

SNCR

Notes: LNB = low-NOx burner; WSI = water/steam injection; OT = oxygen trim, which may also be known as

staged combustion; OFA = overfire air; SCR = selective catalytic reduction; SNCR = selective noncatalytic reduction

AThese applications may find use with large, medium or small boilers fired with coal, oil or natural gas. BBy themselves, these enhancements cannot be considered RACT. However, they or any others that might

give incremental pollutant reduction are meant to be used with each other, as appropriate, as well as NOx

control technologies such as LNB + OFA, reburn, SCR and SNCR; SO2 scrubbers; or boilers controlled

with just ESPs.

9.3.b.3. Why Controls Implementation Could Be Delayed

If additional controls or major upgrades were warranted, DAQ believes they could not be

installed and operational by January 2009. Thus, the attainment date could be not advanced by

one year.

At least five major obstacles prevent realistic timely implementation by 2009 of any RACT

candidate involving retrofit of any major air-pollution-control device or major upgrades to any

existing technologies—even if an owner/operator initiated the 

design/procure/fabricate/install/accept process immediately.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 124

1. While, in the strictest sense, add-on technologies as well as enhancements or major

upgrades may be technically feasible and/or cost effective, whether any occur depends on

site-specific factors. DAQ believes regulatory estimates cannot accurately or completely

describe these factors for a particular facility, nor the costs owners/operators could incur.

Nor can regulatory estimates reasonably predict the amount of time the entire add-ontechnology/major-upgrade process may take from decision to final acceptance.

2. Because owners/operators compete simultaneously among themselves for those vendors

who have the capacity to supply equipment and services—and they compete against the

power-generation industry and its technology programs (see point 3, which follows), it is

unwise to presume that equipment vendors can and will accept new capital projects. 

3. Materials and labor such as boilermakers and steelworkers, for example, to install

equipment may not be available. For example, as respondents to a LADCO/MRPO draft

RACT document for industrial boilers said: “Because the ICI boiler owners and operators

are competing for resources (labor and materials) with the EGU category, there are likely

to be impacts and delays in engineering, materials procurement, etc., going forward.” 

4. At least one federal program, the Clean Air Interstate Rule or CAIR, injects negative

impacts and delays. Besides the competition noted in point 2, above, DAQ believes that

because of CAIR and the NOx SIP Call, costs of some controls have increased

significantly in the past few years. Likely, those costs will not plateau until the CAIR and

PM2.5 programs are fully completed.

5. If vendors can be found who will commit to supplying the equipment, based on the

technical and economic analyses performed in or referred to by this document, it appears

that it could take several years—from decision, to procurement, to design, to fabrication,

then installation and through acceptance testing—to implement major add-on

technologies at an existing site. Major upgrades may take less time, though DAQ has no

estimates of how much less.

9.3.b.4. Why RACT Selection Is Site Specific and Costs May Be Underestimated

If any new technology or major upgrade is required, based on technical feasibility and cost

effectiveness, DAQ notes two significant concerns about the ranked RACT candidates,

particularly those requiring significant capital expense, and their selection:

1. Regardless of what candidate measure is selected or combination of measures are

selected, final choice at any facility, for any boiler, depends on site-specific factors.

Primarily, those include available physical space and compatibility with existing airpollution-control technologies. But among other things, site-specific factors also include

combustion processes and conditions, as well as fuels used. 

2. Regardless of the estimated costs presented in the ICI RACT Analysis, they may

underestimate the real-world expenditures that could or would occur. Underestimation

could come from out-of-date data that need adjustment for inflation or for increases due
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 125

to environmental-regulations-induced supply-demand pressures. Underestimation could

also come from use of regulatory models or other means, rather than actual data, used to

derive these costs. Underestimation may also come from using inadequate retrofit

multipliers when approximating costs. 

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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 126

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 127

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 128

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
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 129

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 Parkersburg 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 8.1.c., West Virginia has determined that there are no additional control

measures that could be adopted by January 1, 2008. 

Further, DAQ expects existing measures and those planned for implementation in 2009 to enable

the Parkersburg 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.
WV PM2.5 SIP for the Parkersburg Nonattainment Area Page 130

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, the Charleston Gazette, the

Charleston Daily Mail and the Parkersburg News on June 13, 2008, announcing the opening of a

30-day public comment period. The public notice also announced that a Public Hearing will be

held on July 15 at the Wood-Washington-Wirt Interstate Planning Commission, 531 Market

Street in Parkersburg, beginning at 6:00 p.m. 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. 

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 Parkersburg Nonattainment

Area, with a projected attainment date of April 2010, as a revision to the state implementation

plan (SIP).