# Georgia's State Implementation Plan

for the Floyd County PM 2.5 

# Nonattainment Area

October 20, 2009

Prepared by:

Georgia Department of Natural Resources

Environmental Protection Division

Air Protection BranchThis page was intentionally left blankPM2.5 Attainment SIP – Floyd County, GA

Preface

This document is Georgia’s State Implementatio n Plan (SIP) for attainment of the Federal National Ambient Air Quality Standard (NAAQS) for PM 2.5 in the Floyd County nonattainment area. The Floyd County nonatt ainment area includes all of Floyd County, Georgia. Specifically, this SIP demo nstrates attainment of the annual PM 2.5 NAAQS, promulgated in 1997, in the Floyd Count y nonattainment area by April 5, 2010.

TABLE OF CONTENTS

PREFACE........................................................................................................................... 3

TABLE OF CONTENTS.................................................................................................... 3

LIST OF APPENDICES..................................................................................................... 6

LIST OF FIGURES ............................................................................................................ 7

EXECUTIVE SUMMARY .............................................................................................. 14

SECTION 1. INTRODUCTION ..................................................................................... 18

1.1 F INE P ARTICLES ...................................................................................................... 18

1.2 1997 N ATIONAL A MBIENT A IR Q UALITY S TANDARDS FOR PM 2.5 ........................... 19

SECTION 2. FLOYD COUNTY NONATTAINMENT AREA..................................... 20

2.1 N ONATTAINMENT A REA D ESIGNATION ................................................................... 22

2.2 PM 2.5 M ONITORING S TATION .................................................................................. 23

2.3 C ONCEPTUAL D ESCRIPTION OF THE PM2.5 P ROBLEM ............................................. 24

2.3.1 Long-term trends of PM2.5............................................................................. 24

2.3.2 Spatial Trends of PM2.5 in Georgia................................................................ 36

2.3.3 Source Apportionment of PM2.5...................................................................... 39 2.3.4 Meteorology ..................................................................................................... 41

2.3.5 Sensitivities to Pollutant Emissions ................................................................. 45

2.4 PM2.5 S OURCES AND P RECURSORS ........................................................................ 49

2.4.1 Sources of PM2.5............................................................................................ 49

2.4.2 Precursors....................................................................................................... 51

2.4.3 Technical Justification for Reversal of NOx Precursor Presumption ............ 52

SECTION 3. ATTAINMENT DEMONSTRATION METHODS AND INPUTS......... 59

3.1 A NALYSIS M ETHOD ................................................................................................. 59

3.2 M ODEL S ELECTION .................................................................................................. 60 3.2.1 Selection of Air Quality Model ........................................................................ 61 3.2.2 Selection of Meteorological Model.................................................................. 62 3.2.3 Selection of Emissions Processing System....................................................... 64

3.3 S ELECTION OF THE B ASE M ODELING Y EAR ............................................................. 65

3.4 M ODELING D OMAINS ............................................................................................... 66

3.4.1 Horizontal Modeling Domain.......................................................................... 66

3 of 148Table of Contents PM2.5 A ttainment SIP - Floyd County, GA

3.4.2 Vertical Modeling Domain .............................................................................. 68

3.5 B ASELINE E MISSIONS I NVENTORY ........................................................................... 70

3.5.1 Stationary Point Sources.................................................................................. 74

3.5.2 Stationary Area Sources .................................................................................. 76

3.5.3 Off-Road Mobile Sources................................................................................. 78

3.5.4 Highway Mobile Sources ................................................................................. 78 3.5.5 Biogenic Emission Sources.............................................................................. 78

SECTION 4. MODEL PERFORMANCE EVALUATION............................................ 80

4.1 M ETEOROLOGICAL M ODEL P ERFORMANCE ............................................................. 80

4.2 A IR Q UALITY M ODEL P ERFORMANCE ...................................................................... 84

4.2.1 Modeling Performance Goals and Criteria..................................................... 84

4.2.2 Domain-Wide Model Performance.................................................................. 87

4.2.3 Model Performance within Georgia and in the Floyd County nonattainment

area ........................................................................................................................... 89

4.2.3.1 Model performance statistics........................................................................ 92

4.2.3.1.1 Model Performance Statistics for the FRM Sites....................................... 92

4.2.3.1.2 Model Performance Statistics for STN Sites.............................................. 95

4.2.4 Summary of the performance evaluation of the CMAQ modeling................... 98

SECTION 5. CONTROL AND CONTINGENCY MEASURES................................. 100

5.1 F EDERAL C ONTROL M EASURES FOR PM2.5 A TTAINMENT ..................................... 100

5.1.1 Clean Air Interstate Rule ............................................................................... 100

5.1.2 Tier 2 Vehicle Standards................................................................................ 103

5.1.3 Heavy-Duty Gasoline and Diesel Highway Vehicles Standards ................... 104

5.1.4 Large Nonroad Diesel Engines Rule ............................................................. 104

5.1.5 Nonroad Spark-Ignition Engines and Recreational Engines Standard......... 104

5.1.6 NOx SIP Call in Surrounding States.............................................................. 105

5.2 S TATE C ONTROL M EASURES FOR PM2.5 A TTAINMENT ......................................... 105

5.2.1 Multipollutant Control for Electric Utility Steam Generating Units, GA Rule 391-3-1-.02(2)(sss).................................................................................................. 107

5.2.2 Heavy Duty Diesel Engines Rule (ooo) ......................................................... 108

5.3. S UMMARY OF SO2 E MISSIONS C HANGES ............................................................. 109

5.4. C ONTINGENCY M EASURES ................................................................................... 110

5.4.1 Region for Contingency Measures................................................................. 112

5.4.2 Area of Influence Emission Reductions for Contingency Measures.............. 113

5.5 U NMODELED C ONTROL M EASURES ....................................................................... 116

5.5.1 GA Rule 391-3-1-.02 (2)(5) Open Burning............................................. 117

5.5.2 Switch to Lower Sulfur Coal, Georgia Power Plant Scherer ....................... 117

5.5.3 Multipollutant Rule, Early Implementation of Controls............................... 118

5.6 RACT AND RACM ............................................................................................... 118

SECTION 6. ATTAINMENT DEMONSTRATION.................................................... 121

6.1 M ODELED A TTAINMENT T EST ............................................................................... 121

6.1.1 Determination of Baseline Design Values ..................................................... 121

6.1.2 Relative Response Factor Calculation........................................................... 125

6.1.3. Future Year Quarterly Concentration Calculation ...................................... 127

4 of 148Table of Contents PM2.5 A ttainment SIP - Floyd County, GA

6.1.4. Future Year Annual Average Estimate ......................................................... 127

6.2 S UPPLEMENTAL A NALYSIS ..................................................................................... 128

6.2.1 Additional Air Quality Modeling ................................................................... 128

6.2.2 Air Quality and Emission Trends Analysis .................................................... 132 6.2.3 Supplemental Analysis Conclusions .............................................................. 138

6.3 U NMONITORED A REA A NALYSIS ........................................................................... 138

6.4 D ATA A CCESS ........................................................................................................ 139

SECTION 7. OTHER CLEAN AIR ACT REQUIREMENTS ..................................... 140

7.1 RACT/RACM R EQUIREMENTS ............................................................................. 141

7.2 R EASONABLE F URTHER P ROGRESS ....................................................................... 141

7.3 A CTUAL E MISSIONS I NVENTORY ........................................................................... 141

7.4 P ERIODIC E MISSIONS I NVENTORY ......................................................................... 141

7.5 P ERMIT P ROGRAM R EQUIREMENTS ....................................................................... 141

T 7.6 O THER M EASURES ................................................................................................ 142

7.7 C OMPLIANCE WITH S ECTION 110( A )(2) (I NFRASTRUCTURE E LEMENTS ) ............... 142

7.8 E QUIVALENT T ECHNIQUES .................................................................................... 142

7.9 C ONTINGENCY M EASURES .................................................................................... 142

SECTION 8. 2009 MOTOR VEHICLE EMISSIONS BUDGET................................. 143

SECTION 9. SUMMARY AND CONCLUSION......................................................... 146

SECTION 10. REFERENCES....................................................................................... 148

5 of 148List of Appendices PM2.5 A ttainment SIP - Floyd County, GA

LIST OF APPENDICES

Appendix Title

A Justification for Modification to State Recommendations, PM2.5 Nonattainment Areas, State of Georgia

B PM2.5 Source Apportionment at Georgia STN Sites Using

Positive Matrix Factorization

C PM2.5 Source Apportionment in Georgia

D Characterization of Meteorology and Its Relationships to Fine

Particulate Mass and Visibil ity in the VISTAS Region

E Insignificance of NH 3 , VOCs, and NOx to PM2.5 Attainment in Georgia Nonattainment Areas

F Modeling Protocol For Associati on for Southeastern Integrated Planning (ASIP) Emissions and Ai r Quality Modeling to Address

8-Hour Ozone and PM2.5 Nonattainment in the Southeastern

United States"

G Technical Support Document for Association for Southeastern Integrated Planning (ASIP) Em issions and Air Quality Modeling to Support PM2.5 State Implementation Plans

H Documentation of the Base G2 and Best and Final 2002 Base Year, 2009 and 2018 Emission Inventories for VISTAS

I Emissions Inventories – State of Georgia

J Mobile Source Emissions Modeling for Floyd County PM2.5 Attainment Demonstration - Motor Vehicle Emissions Budgets

K Model Performance Evaluation

L Multipollutant Control for Electric Utility Steam Generating Units [Georgia Rule 391-3-1-.02(2)(sss)]

M Attainment Demonstration Calculations and Results

N CAA Section 110(a)(2) Require ments (SIP Infrastructure Elements): Communications dated 7-23-08 and 9-22-08

6 of 148List of Figures PM2.5 Atta inment SIP - Floyd County, GA

LIST OF FIGURES

Figure 2-1 PM2.5 Nonattainment Areas in Georgia........................................................ 20

Figure 2-2. Floyd County PM2.5 Nonattainment Area ................................................... 21

Figure 2-3. Location of PM2.5 Monitor in the Floyd County Nonattainment Area........ 23

Figure 2-4. Trend of annual mean (arithmetic average of quarterly averages) PM2.5

concentrations at the FRM monitor (13-115-0005) in the Floyd County NAA. .............. 25

Figure 2-5. Trend of PM2.5 Design Values at the FRM monitor (13-115-0005) in the Floyd County NAA........................................................................................................... 27

Figure 2-6. Quarterly averages of PM2.5 concentrations at 13-115-0005 ....................... 28

Figure 2-7. Trend of annual total and speciated PM2.5 concentrations (arithmetic average of daily averages) at the Coosa High School PM2.5 Speciation monitor (13-115-0005). 29

Figure 2-8. Quarterly averages of PM2.5 concentrations at the PM2.5 Speciation site in

the Floyd County NAA (13-115-0005)............................................................................. 30

Figure 2-9. Quarterly averages of SO4 concentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005) .................................................................................. 31

Figure 2-10. Quarterly averages of NO3 concentrations at the PM2.5 Speciation site in

the Floyd County NAA (13-115-0005)............................................................................. 32

Figure 2-11. Quarterly averages of NH4 concentrations at the PM2.5 Speciation site in

the Floyd County NAA (13-115-0005)............................................................................. 33

Figure 2-12. Quarterly averages of OC concentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005) .................................................................................. 34

Figure 2-13. Quarterly averages of EC concentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005) .................................................................................. 35

Figure 2-14: Seasonal patterns in PM 2.5 concentrations and composition in Atlanta (Site

ID 13-089-0002) for 2003-04 (MMO

– Major Metal Oxides; Other

– PM 2.5 other than sulfate, nitrate, ammonium, MMO, elemental carbon and organic carbon)..................... 37

Figure 2-15: Seasonal patterns in PM 2.5 concentrations and composition in Chattanooga (Site ID 47-065-4002) for 2003-04 (MMO

– Major Metal Oxides; Other

– PM 2.5 other

than sulfate, nitrate, ammonium, MMO, elemental carbon and organic carbon). ............ 37

Figure 2-16: Seasonal patterns in PM 2.5 concentrations and composition in Floyd County (Site ID 13-115-0005) for 2003-04 (MMO

– Major Metal Oxides; Other

– PM 2.5 other

than sulfate, nitrate, ammonium, MMO, elemental carbon and organic carbon). ............ 38

Figure 2-17. Seasonal patterns in PM 2.5 concentrations and composition in Macon (Site

ID 13-021-0012) for 2003-04 (MMO

– Major Metal Oxides; Other

– PM 2.5 other than sulfate, nitrate, ammonium, MMO, elemental carbon and organic carbon)..................... 38

Figure 2-18: Average factor contributions for 2003-04 at the Atlanta, Floyd County, and

Macon STN sites using PMF ............................................................................................ 40

7 of 148List of Figures PM2.5 Atta inment SIP - Floyd County, GA

Figure 2-19: Average composition for all key PM2.5 bins in Macon. ............................. 45

Figure 2-20: Sensitivities of PM2.5 by pollutant and source category for the summer episode in Floyd County. ∆ PM2.5 is based upon a 30% reduction of pollutant levels

from 2009 levels. .............................................................................................................. 47

Figure 2-21: Sensitivities of PM2.5 by pollutant and source category for the winter episode in Floyd County. ∆ PM2.5 is based upon a 30% reduction of pollutant levels

from 2009 levels. .............................................................................................................. 47

Figure 2-22: Annual average emission sensitivities by pollutant and source category
based on the average response of the summer and winter episodes in Floyd County...... 48

Figure 2-23: Annual average emission sensitivities by pollutant and source category
based on the CART weighted response of the summer and winter episodes in Floyd County............................................................................................................................... 49

Figure 2-24. SANDWICH Speciated Concentrations of Quarterly and Annual Average

2002 PM2.5 Base Design Values (DVB) averaged over FRM Monitors in each Georgia

PM2.5 Nonattainment Area. ............................................................................................. 53

Figure 2-25. Reductions in EC, OC, and NO3 concentrations between 2002 & 2009 and

2009 & 2018 at Georgia nonattainment monitors............................................................. 55

Figure 2-26. Annual Average PM2.5 Response to GA Statewide 50% NOx Emission

Reduction in 2009 in the Georgia PM2.5 Nonattainment Areas. .................................... 56

Figure 2-27. Annual Average PM2.5 Response to GA Statewide 30% NOx Emission

Reduction in 2009 in the Georgia PM2.5 Nonattainment Areas. ................................... 56

Figure 2-28. Hourly measured and modeled OC concentrations and the difference

between the base and sensitivity concentrations of the four components of OC to 100%

statewide NOx emissions reductions at the Yorkville SEARCH monitor........................ 58

Figure 3-1. The MM5 and CMAQ 36-km Horizontal Domains....................................... 67

Figure 3-2. VISTAS 12-km Modeling Domain................................................................ 67

Figure 4-1: Monthly averaged Bias statistics for 2-m temperature and humidity ............ 82

Figure 4-2. VISTAS STN Soccer Plots ............................................................................ 87

Figure 4-3. VISTAS STN Bugle Plots.............................................................................. 88

Figure 4-4. VISTAS FRM Soccer Plots ........................................................................... 88

Figure 4-5. VISTAS FRM Bugle Plots............................................................................. 89

Figure 4-6. FRM, STN, IMPROVE, CASTNET, NADP, and SEARCH monitoring sites

located in and near the GA PM 2.5 nonattainment areas (left) and the Floyd County PM 2.5 nonattainment area (right)................................................................................................. 91

Figure 4-7. Stacked bar plots of daily PM 2.5 species concentration at 13-115-0005........ 99

Figure 5-1 Floyd County Area of Influence ................................................................... 113

Figure 6-1. Grid cells for which the air quality metrics were applied in the Floyd County

PM2.5 nonattainment area. ............................................................................................. 130

8 of 148List of Figures PM2.5 Atta inment SIP - Floyd County, GA

Figure 6-2. Percentage of Cell-Days in the Floyd County Nonattainment Area within

Concentration Categories for 2002 and 2009. ................................................................ 131

Figure 6-3. Annual PM2.5 Average Values for the Rome Monitor (13-115-0005) in the Floyd County Nonattainment Area................................................................................. 134

Figure 6-4. PM2.5 monitoring trends 1 in Floyd County (13-115-0005) compared to
statewide EGU SO2 emissions from Georgia and neighboring states............................ 137

Figure 6-5. Modeled 2009 Annual Mean PM2.5 Concentration near the Floyd County

Nonattainment Area on the VISTAS 12km Grid............................................................ 139

9 of 148List of Tables PM2.5 Atta inment SIP - Floyd County, GA

LIST OF TABLES

Table E-1. Projected SO2 emission reductions from new controls on Georgia Power

EGUs in 2008 and 2009.................................................................................................... 16

Table E-2. PM 2.5 2002 Baseline Design Values and 2009 Future (Modeled) Design

Values ............................................................................................................................... 17

Table 2-1. 2001 – 2003 PM2.5 Design Value for Floyd County..................................... 22

Table 2-2. Rome PM 2.5 Data Collection Site................................................................... 24

Table 2-3. Annual mean (arithmetic average of quarterly averages) PM2.5

concentrations at the FRM monitor in the Floyd County NAA........................................ 26

Table 2-4. PM2.5 Design Values at the FRM monitor (13-115-0005) in the Floyd County

NAA............................................................................................................................ ...... 27

Table 2-5. Average PM 2.5 composition during 2003-2004 for the four STN sites in the

non-attainment areas ......................................................................................................... 39

Table 2-6. Estimated primary and secondary percentage of PM 2.5 .................................. 39

Table 2-7 Average factor contributions to PM 2.5 ( μ g/m 3 ) for 2003-04 at the Atlanta, Floyd County, and Macon STN sites using PMF ............................................................. 41

Table 2-8 Summary of average input parameters for each CART classification Category

in Yorkville. ...................................................................................................................... 43

Table 2-9 Summary of average input parameters for key bins for CART classification (Class) categories 3 and 4 in Yorkville............................................................................. 44

Table 2-10. Typical Base Year (2002) Emissions Inventories for Floyd County ........... 50

Table 2-11. Point Sources in the Floyd County Non-Attainment Area That Are Title V Major Sources ................................................................................................................... 51

Table 2-12. Expected Change in NOx Emissions (%) in Georgia PM2.5 Nonattainment

Areas. Reductions are negative........................................................................................ 54

Table 3-1. Vertical Layer Definition For MM5 and CMAQ............................................ 69

Table 3-2. Typical 2002 BaseG2 Annual Emission Summary for Floyd County and State of Georgia ......................................................................................................................... 71

Table 3-3. 2009 BaseG4 Annual Emission Summary for Floyd County and State of Georgia.............................................................................................................................. 72

Table 3-4. 2002 and 2009 Georgia EGU Emissions........................................................ 75

Table 3-5. 2002 and 2009 Floyd County Area Source Emissions of Particulate Matter. 77

Table 4-1: Mathematical Formulation of Statistical Metrics Used for Evaluating

Mesoscale Meteorological Model Performance ............................................................... 81

Table 4-2: Statistical Benchmarks for Mesoscale Meteorological Models ...................... 81

10 of 148List of Tables PM2.5 Atta inment SIP - Floyd County, GA

Table 4-3: Monthly averaged statistics for the region of the 12-km modeling domain in

and around Georgia........................................................................................................... 83

Table 4-4. Established Model Performance Goals and Criteria for thePM2.5 Component Species .............................................................................................................................. 85

Table 4-5 Statistical Metric Calculations.......................................................................... 86

Table 4-6. Ambient monitoring data available in 2002. .................................................. 90

Table 4-7. Annual model performance statistics for PM 2.5 at all FRM monitors in the

State of Georgia and in the Floyd County nonattainment area......................................... 93

Table 4-8. Monthly model performance statistics for PM 2.5 at 13-115-0005................... 94

Table 4-9. Annual model performance statistics for PM 2.5 species and total PM 2.5 at all

STN monitors in the State of Georgia............................................................................... 96

Table 4-10. Annual model performance statistics for PM 2.5 at 13-115-0005. .................. 97

Table 5-1. Federal PM2.5 Control Measures................................................................. 101

Table 5-2. State PM2.5 Control Measures and ContingencyMeasures ........................ 106

Table 5-3. Georgia Multipollutant Rule SO 2 Control Requirements and Construction

Permit Conditions ........................................................................................................... 107

Table 5-4. Changes in SO2 Emissions, 2002 to 2009, Nonattainment Area (tons)....... 109

Table 5-5. Changes in SO2 Emissions, 2002 to 2009, Statewide (tons) ....................... 109

Table 5-6. Predicted changes in SO2 emissions inside the Floyd County Nonattainment Area, 2002 to 2009C....................................................................................................... 111

Table 5-7 Predicted changes in SO2 emissions inside the Floyd County Nonattainment Area, 2009 to 2012.......................................................................................................... 111

Table 5-8. 2002 Baseline SO2 Emissions For Floyd County Area of Influence............ 114

Table 5-9. 2009 SO2 Emissions For Floyd County Area of Influence.......................... 114

Table 5-10. 2012 SO2 Emissions For Floyd County Area of Influence....................... 115

Table 5-11. Total SO2 Emissions For Floyd County Area of Influence ........................ 115

Table 5-12. SO2 emissions reductions expected from control and contingency measures

at coal-fired electric generating units outside the Floyd County Nonattainment Area... 116

Table 5-13. Unmodeled Control Measures.................................................................... 117

Table 5-14 Floyd Co. Nonattainment Area Major Source SO 2 Emissions..................... 119

Table 6-1. Quarterly Average PM2.5 Mass for the FRM Monitor in the Floyd County

Nonattainment Area........................................................................................................ 122

Table 6-2. Observed Quarterly and Annual Mean PM2.5 DVB for Monitor in the Floyd County Nonattainment Area ........................................................................................... 122

Table 6-3. DVB Quarterly Species Fractions (%) from the CAIR SMAT Tool ........... 125

11 of 148List of Tables PM2.5 Atta inment SIP - Floyd County, GA

Table 6-4. Quarterly PM2.5 Component-Specific DVB ( μ g/m 3 ) for Monitor in the Floyd County Nonattainment Area ........................................................................................... 125

Table 6-5. USEPA’s Recommendation for Defining “Near” Cells............................... 126

Table 6-6. Quarterly Component RRFs for Monitor in the Floyd County Nonattainment

Area................................................................................................................................. 127

Table 6-7. Quarterly Component Future Design Values for Monitor in the Floyd County

Nonattainment Area........................................................................................................ 127

Table 6-8. Quarterly Mean PM2.5 Mass estimates for 2009......................................... 127

Table 6-9. Estimated Annual Mean 2009 PM2.5 Mass Compared to the DVB............ 128

Table 6-10. Number of Cell-Days within Concentration Bins. Increases (decreases) in

the number of cell-days (and percent change) within the bins are noted by red (blue)

coloration. ....................................................................................................................... 131

Table 6-11. US EPA CAIR Modeling Results for Floyd County (highest monitor)..... 132

Table 6-12. Annual Average PM2.5 values ( μ g/m 3 ) in Floyd County, 1999 - 2008..... 134

Table 6-13. Three-year Design Values for the Monitor ( 13-115-0005) in the Floyd County

PM2.5 Nonattainment Area. ........................................................................................... 136

Table 6-14. Projected SO2 emission reductions from new controls on Georgia Power

EGUs in 2008 and 2009.................................................................................................. 136

Table 7-1. General Plan Requirements for Nonattainment Areas ................................. 140

Table 8-1. 2009 PM2.5 Motor Vehicle Emissions Budget, Floyd County Nonattainment

Area................................................................................................................................. 144

Table 8-2. Floyd County Nonattainment Area Total Projected 2009 PM2.5 Emissions,

Tons/Year........................................................................................................................ 145

Table 9-1. 2001 – 2003 PM2.5 Design Value for Floyd County Nonattainment Area

Monitor ........................................................................................................................... 146

Table 9-2. PM 2.5 2009 Future (Modeled) Design Values .............................................. 147

12 of 148Acronyms PM2.5 Attainment SIP - Floyd County, GA



## Acronyms

ASIP Association of South eastern Integrated Planning

CAA Clean Air Act

CAIR Clean Air Interstate Rule CMAQ Community Multisc ale Air Quality model

DON Degree of neutralization (of sulfate, in the context of this document)

DVB Baseline design value

DVF Future design value

EC Elemental carbon

EGU Electric generating unit

EI Emissions inventory

EPD Environmental Protection Division

FGD Flue gas desulfurization

FRM Federal Reference Monitor

MM5 Mesoscale Meteorological Model

MVEB Motor vehicle emissions budget

NAA Nonattainment area NAAQS National Ambient Air Quality Standards

OC Organic carbon

OM Organic matter

PBW Particle bound water

PM2.5 Fine particulate matter (2.5 microns or less in diameter)

RACM Reasonably available control measure

RACT Reasonably availa ble control technology

RFP Reasonable further progress
RRF Relative response factor

SANDWICH Sulfate, adjusted nitrate, derived water, inferred carbon hybrid

SCR Selective catalytic reduction

SIP State implementation plan

SMAT Speciated Modeled Attainment Test

SMOKE Sparse Matrix Operator Ke rnel Emissions modeling system

SOA Secondary Organic Aerosols

STN Speciated Trends Network

VISTAS Visibility Improvement State a nd Tribal Association of the Southeast

VOC Volatile organic compound

VMT Vehicle miles traveled

13 of 148Executive Summary PM2.5 Attainment SIP – Floyd County, GA

Executive Summary

This document is Georgia’s state implementatio n plan (SIP) for attainment of the 1997 PM2.5 National Ambient Air Quality Standards in the Floyd County Nonattainment Area (NAA). This SIP meets the requirements of EPA’s fine particle implementation rule, 40 CFR 51 Subpart Z. The Floyd County NAA has been determined to be out of attainment with the annual National Ambient Air Quality Standard (NAAQS) for PM2.5 (particulate

matter with a diameter of 2.5 mi crons or less, also called fi ne particulate matter). The annual air quality standard for PM2.5 is a 3-year annual arithmetic mean concentration of 15.0 micrograms per cubic meter ( μ g/m 3 ) or less. The nonattainment area designation was based upon a 2001 - 2003 design value at the Rome-Coosa High School monitor of

15.7 μ g/m 3 . This document does not address the 24-hour PM2.5 standard promulgated in December 2006, as nonattainment areas and requir ements for this new standard have not

been finalized.

This SIP contains the elements required by 40 CFR 51 Subpart Z, including the following:

• Identification and description of the nonattainment area, including major PM2.5 emissions sources;

• Identification of PM2.5 control measures needed to reach attainment; and

• Description of modeling that demonstrates attainment of the annual standard by April 5, 2010.

These elements are summarized in the following paragraphs.

The nonattainment area is made up of Floyd County. Land utiliza tion in this area includes both urban (City of Ro me) and suburban land uses.

PM2.5 is made up of a number of compone nt species, including the following:

• Elemental carbon

• Organic carbon

• Sulfates

• Nitrates

• Crustal materials

• Ammonia

Sulfates, nitrates, and ammonia are mostly secondary PM2.5. Secondary PM2.5 is not emitted directly into the atmosphere, but rather formed by chemical reactions of precursor species subsequent to their emi ssion. Elemental carbon and crustal materials (soils) are primary PM2.5 which are directly emitted into the atmosphere. Organic carbon can be a mixture of secondary and primary PM2.5.

The largest PM2.5 components m easured in this nonattainmen t area are sulfates and organic carbon. Other components are present in small fractions.

14 of 148Executive Summary PM2.5 Attainment SIP – Floyd County, GA

Sulfate has made up approximately 30 perc ent of the ambient annual PM2.5 measured since 2002 at the Rome-Coosa High School monitor. Sulfates are formed primarily from

sulfur dioxide emissions from coal-fired electric generating units (EGUs), including

EGUs located inside the nonattainment area and other more distant EGUs located both inside and outside of Georgia.

Organic carbon, like sulfates, has comprised approximately 30 percent of the ambient

annual PM2.5 measured since 2002. Atmos pheric organic carbon is produced by vegetation (biogenic sources), emissions of volatile organic chemicals used in commercial and industrial applications, and combustion of wood and fossil fuels. The bulk of organic carbon is believed to be formed from biogenic sources.

The control measures needed to reach attain ment include both state and federal measures and must address both primary PM2.5 and sulfur dioxide (the precursor to sulfate formation). The attainment demonstration may take credit for measures implemented after 2002, the baseline year, and before 2009, th e year in which modeling demonstrates

attainment.

Control measures for attainment focus on control of SO 2 (and therefore sulfates) from EGUs. Biogenic formation of organic carbon is not addressed by contro l measures in this SIP. Significant State measures include Ge orgia Rule 391-3-1-.02(2)(sss), also known as the Multipollutant Rule, and the Heavy-Duty Diesel Engines Rule. The Multipollutant Rule requires significant reductions in SO2 emissions from electric generating units (EGUs) and is the measure that will provide the greatest bene fit toward demonstration of attainment in calendar year 2009. Fede ral measures include the following:

• Clean Air Interstate Rule

• Tier 2 Vehicle Standards

• Heavy-duty Gasoline and Diesel Highway Vehicles Standards

• Ultra-Low Sulfur Diesel Rule

• Large Nonroad Diesel Engines Rule

• Non-road spark ignition Engines an d Recreational Engines Standard

• NOx SIP call in surrounding states

The Clean Air Interstate Rule (CAIR) provi des for reductions of both SO2 and NOx. The other federal measures provide for reduc tions of NOx and direct PM emissions.

Some measures were not modeled but they ar e expected to achieve reductions in ambient

PM fine concentrations. These measures include:

15 of 148Executive Summary PM2.5 Attainment SIP – Floyd County, GA

• Revisions to Georgia’s open burning rule to further restrict open burning in the Floyd County area during May through September;

• Switching of two EGUs at Plant Sc herer to lower sulfur coal; and

• Planned early start-up of SO 2 scrubbers at two EGUs (Bowen Unit 2 and Wansley Unit 2).

These measures are discussed in more deta il in Section 5. They were not modeled because they are voluntary and/or difficult to model.

FOR EACH NONATTAINMENT AREA, THE STATE MUST SUBMIT AN

ATTAINMENT DEMONSTRATION S HOWING ATTAINMENT WITH THE

ANNUAL PM2.5 STANDARD AS EXPEDITIOUSLY AS POSSIBLE. PER 40 CFR 51.1007, THE ATTAINMENT DEMONSTRATION MUST INCLUDE:

• Inventory data

• Modeling results

• Emission reduction analyses

Air quality modeling conducted by Georgia EPD indicates that the nonattainment area will attain the annual NAAQS in 2009. Modeled attainment is based primarily upon projected SO2 emissions reductions from EGU sources within the state. The projected

reductions from EGU sources ar e presented in Table E-1.

Table E-1. Projected SO2 emission reducti ons from new controls on Georgia Power

EGUs in 2008 and 2009.

Facility Unit Control Date 1 2007 SO2

Emissions 2
(tons) Estimated

2008 (tons) Estimated

2009 (tons) 2008
Reductions (tons) 2009
Reductions (tons)

Bowen 1 5/30/2010 42,967.2 42,967.2 42,967.2 0.0 0.0

2 5/30/09 39,888.2 39,888. 2 17,783.5 0.0 22,104.7

3 5/01/08 64,745.5 23,740. 0 3,237.3 41,005.5 61,508.2

4 12/31/08 49,240.0 49,240. 0 2,462.0 0.0 46,778.0

Hammond 1 5/30/08 6,028.2 2, 687.6 301.4 3,340.6 5,726.8

2 5/30/08 6,047.4 2,696. 1 302.4 3,351.3 5,745.0

3 5/30/08 6,147.9 2,740. 9 307.4 3,407.0 5,840.5

4 5/30/08 29,585.3 13,190. 1 1,479.3 16,395.2 28,106.0

Wansley 1 12/31/08 42,739.9 42,739.9 2,137.0 0.0 40,602.9

2 5/30/09 51,105.7 51,105. 7 22,784.6 0.0 28321.1

TOTAL (tons) 338,495.3 270,995.8 93,762.0 67,499.5 244,733.3

(1) Dates prior to 2009 are actual field installation dates. Dates 2009 or later are companyprovided forecast installation dates. (2) Calculated from continuous emissions monitor data.

16 of 148Executive Summary PM2.5 Attainment SIP – Floyd County, GA

Since it is performed on the ba sis of individual PM specie s (sulfate, nitrate, organic carbon, etc.), the attainment demonstration test for PM2.5 is referred to as the Speciated Modeled Attainment Test (SMAT). In brief, the air quality model is tested by comparing predicted species concen trations to observed concentrations in the baseline year (2002).

Then a historical baseline emissions inve ntory (based on “typical” emissions and meteorology) and the 2009 projected emissions inventory are input to the model to find PM2.5 species concentrations for both years. The ratio of the future predicted average

annual concentration to the historical base line average annual concentration, known as the relative response factor (RRF), is cal culated for each species. The 2002 observed design value (baseline design value, or DVB) for each species is then multiplied by the species RRF to obtain the 2009 modeled design value (future design value, or DVF) for the species. The modeled values for the indivi dual species are then summed to obtain the overall 2009 modeled design value. This SMAT process is repeated for each federal

reference monitor in the nonattainment area.

The 2009 modeled PM2.5 design value is provi ded in Table E-2. Since the modeled design value is less than 15.0 μg/m 3 , modeled attainment is demonstrated. Supplemental analyses (in addition to SMAT) are presente d that also support the demonstration of

attainment.

Table E-2. PM 2.5 2002 Baseline Design Values and 2009 Future (Modeled) Design

Values

Federal

Reference

Monitor Site ID 2002 Annual Design Value (DVB)
(μg/m 3 ) 2009 Annual Design Value (DVF)
(μg/m 3 )

Rome-Coosa High School 13-115-

0005 15.7 14.0

As required by the EPA Clean Air Fine Par ticle Implementation Ru le, sources of PM2.5 and its precursors within the Floyd County No nattainment Area were evaluated to verify that they were meeting at l east reasonably available control measure (RACM) levels of emission controls. This evaluation and the results of sensitivity modeling that was performed indicate that no additional reductions are available from local sources that would result in advancement of the attainment date by more than one year.

Federal regulations require st ates to submit a Reasonable Further Progress (RFP) plan for any PM2.5 SIP that targets attainment more than five years after the date of NAA designation. The Floyd County Nonattainment Area is targeting atta inment five years after designation, so no RFP plan is required.

17 of 148Executive Summary PM2.5 Attainment SIP – Floyd County, GA

The SIP narrative is organized as follows:

Section 1 Introduction Section 2 Floyd County Nonattainment Area

Section 3 Attainment Demons tration Methods and Inputs

Section 4 Model Performance Evaluation Section 5 Control and Contingency Measures

Section 6 Attainment Demonstration Section 7 Other Clean Air Act Requirements Section 8 2009 Motor Vehicle Emissions Budget Section 9 Summary and Conclusion

Section 10 References

The appendices provide additional mate rial to support th e SIP narrative.

Section 1. Introduction

1.1 Fine Particles

Fine particles in the atmosphere, which ma y be solid or liquid, are comprised of a complex mixture of components. Comm on constituents include: sulfate (SO 4 ); nitrate (NO 3 ); ammonium (NH 4 ); elemental carbon; a great va riety of organic compounds; and inorganic material (including metals, dust, sea salt, and other trace elements) generally

referred to as “crustal” materi al, although it may contain mate rial from other sources. Airborne particles generally less than or equal to 2.5 micrometers in diameter are considered to be “fine particles” (also referred to as PM 2.5 ). 2.5 micrometers is less than one-seventh of the average width of a human hair. “Primary” or “direct” particles are emitted directly into the air as solid or liqui d particles (e.g., elementa l carbon from diesel engines or fire activities, or condensable organic partic les from gasoline engines). “Secondary” particles (e.g., sulfate and nitrate) form in the atmosphere from emissions of gaseous precursors (e.g., SO 2 and NO

x ) that subsequently undergo chemical reactions to form particulate matter. Secondary orga nic aerosols (SOA) are another form of secondary particles that consist of VOCs that have been converted from the gas phase to the particle phase.

The EPA established National Ambient Air Quality Standards (NAAQS) for PM 2.5 based

on evidence from numerous hea lth studies demonstrating that serious health effects are associated with exposures to elevated levels of PM 2.5 . Epidemiological studies have shown statistically significant co rrelations between elevated PM 2.5 levels and premature mortality. Other important effects associated with PM 2.5 exposure include aggravation of respiratory and cardiovascular diseas e, changes in lung function and increased respiratory symptoms, as well as new ev idence for more subtle indicators of

cardiovascular health. Individuals particularly sensitive to PM 2.5 exposure include older

18 of 148Introduction PM2.5 Attainment SIP - Floyd County, GA

adults, people with heart and lung disease, and children. [Source: Preamble to Clean Air Fine Particle Implementation Ru le – Final Rule, April 25, 2007.]

1.2 1997 National Ambient Air Quality Standards for PM 2.5

The 1997 NAAQS for PM2.5 are listed in the following table:

Description Standard ( μ g/m 3 )

Annual arithmetic mean concentration 1 ≤ 15.0 24-hour average concentration, 98 th percentile 1 ≤ 65

(1) determined in accordance with Appendix N of 40 CFR Part 50

These standards were promulgated by U.S. EPA on July 18, 1997 (62 FR 38711 and 40CFR50.7). A monitoring site (or group of spatia lly averaged sites) is in attainment of

the annual PM 2.5 standard when the annual standard design value is less than or equal to 15.0 micrograms per cubic meter ( μ g/m 3 ). The annual standard design value is the 3- year average of the annual mean, which is in turn the averag e of one year’s four calendarquarter averages. A monitoring s ite (or group of spat ially-averaged sites) is in attainment

of the 24-hour PM 2.5 standard when the 24-hour standard design value is less than or equal to 65 μ g/m 3

. The 24-hour standard design value is the three-year average of annual

98 th percentile 24-hour aver ages. The annual 98 th percentile 24-hour average is the 24- hour average PM 2.5 concentration which is higher than 98 percent of the year’s valid 24- hour averages. Therefore, to ach ieve attainment of the 1997 PM 2.5 standards by a given date, the annual and 24-hour standard design va lues calculated from valid data collected for the previous three calendar years must be less than or equal to their respective

standards. For a nonattainment area to achie ve attainment, all monitoring sites in the

nonattainment area must be in attainment. More details on the calculation of design values and the interpretation of the PM 2.5 NAAQS can be found in Appendix N of 40

CFR Part 50.

19 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Section 2. Floyd County Nonattainment Area

There are currently four PM 2.5 nonattainment areas in Georgia: Chattanooga (which also includes parts of Alabama and Tenne ssee), Floyd County, Atlanta, and Macon. Figure 2.1 shows their locations. The Floyd C ounty nonattainment area is located in the northwest portion of the state and south of Georgia’s portion of the Chattanooga

Nonattainment Area.

Figure 2-1 PM2.5 Nonattainment Areas in Georgia

20 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

The geographic boundaries of the Floyd County PM 2.5 nonattainment area are shown in Figure 2.2. Land utilization in the nonattainment area includes both urban and suburban land uses. The population of Floyd Count y was 90,565 in 2000 and is estimated at 95,322 in 2006. The nonattainment area desi gnation, the PM2.5 monitoring station, major PM2.5 sources, PM2.5 precursors, th e conceptual description of the PM2.5 problem, and ambient PM2.5 trends are described in this section.

Figure 2-2. Floyd County PM2.5 Nonattainment Area

21 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

2.1 Nonattainment Area Designation

EPA, based on data submissions from stat es and tribes, designates a county as

attainment/unclassifiable or nonattainment. In addition, a county may be designated as

nonattainment if it is deemed to contain so urces that contribute to the nonattainment status of a county with a nonattaining design value. Nonattainment counties are grouped together into nonattainment areas base d on location within common metropolitan statistical areas (MSAs). EPA made initial designations of the nonattainment areas, including the Floyd County nonattainment area, for the PM 2.5 NAAQS on January 5, 2005 (70FR944), and amended the desi gnations on April 5, 2005 (70FR19844).

The designation of the Floyd County nonatt ainment area was based upon Georgia’s recommendations to EPA and upon EPA’s 9-factor analysis of counties in or adjacent to the Rome, Georgia, Metropolitan Statistical Area. The nine factors are as follows:

• Factor 1: Emissions in areas potentially included versus excluded from the nonattainment area;

• Factor 2: Air quality in potenti ally included vers us excluded areas;

• Factor 3: Population density and degr ee of urbanization in cluding commercial development in potentially included versus excluded areas;

• Factor 4: Traffic and commuting patterns;

• Factor 5: Expected growth;

• Factor 6: Meteorology;

• Factor 7: Geography/topography;

• Factor 8: Jurisdictional boundaries; and

• Factor 9: Level of control of emission sources.

Factors 1 through 5 were the primary criteri a used by EPA in their analysis. The observed PM2.5 design value at the nonattainment area monitor violated the annual standard, as shown in Table 2-1 below. Deta ils of the 9-factor analysis are included as Appendix A of this submittal

.

Table 2-1. 2001 – 2003 PM2.5 Design Value for Floyd County

Site name Monitor ID PM 2.5 Design Value
(μg/m 3 )

Rome-Coosa High School 13-115-0005 15.7

22 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

2.2 PM 2.5 Monitoring Station

There is currently one ambient PM 2.5 monitoring site in the Floyd County nonattainment

area. The location of the Rome-Coosa Hi gh School site is shown in Figure 2-3. Providing adequate coverage of the nonattainment area, data from this site represents a neighborhood scale, which extends up to 4.0 kilo meters from the monitor. The site is considered to be part of the State a nd Local Air Monitoring Stations (SLAMS) monitoring network, with the monitoring obj ective of sampling for population exposure.

Figure 2-3. Location of PM2.5 Monitor in the Floyd County Nonattainment Area

23 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

One PM 2.5 Federal Reference Method (FRM) monitor and one PM 2.5 speciation monitor are located at the Rome-Coosa High School site (13-115-0005). The PM 2.5 FRM monitor was installed in accordance with 40 CFR 58, an d has been collecting data since January 18, 1999 (Table 2-2). Its samp ling schedule was every three days until Ma rch 1, 2007, when it started sampling daily. The PM 2.5 speciation monitor has been collecting data since March 3, 2002. The sampling schedule of the PM 2.5 speciation monitor has been and remains every six days.

Table 2-2. Rome PM 2.5 Data Collection Site

Site Name County Site ID Start Date –

FRM Data

Collection Start Date – Speciation Data

Collection Rome-Coosa High

School Floyd 13-115-

0005 Jan. 18, 1999 March 3, 2002

2.3 Conceptual Description of the PM2.5 Problem

This section evaluates ambient monitoring data obtained from one Federal Reference

Method or FRM monitor and one speciation monitor (both at the same site) located within the Floyd County nonattainme nt area. The evaluations in clude long-term trends of PM2.5 levels obtained from the FRM monitor and the speciation monitor. Both trends in annual averages and quarterly av erages are evaluated. For the speciation monitor, trends in the different PM2.5 species measured are an alyzed and are compared to speciation data

from other PM2.5 nonattainment areas in Ge orgia. Receptor modeling results are presented to provide an insight into the relative amount of am bient PM2.5 attributable to different emission source categories. CART analysis was performed to examine the relationship between meteorology and air qua lity. Lastly, sensitivity modeling was conducted to examine the response in predicte d ambient PM2.5 levels to reductions from different source categories. All of these analyses can be used to identify the key

contributors to PM2.5 levels in the Floyd County area, along w ith recent trends in their impact, and formulate effective control measure approaches for reducing ambient PM2.5

levels.

2.3.1 Long-term trends of PM2.5

Figure 2-4 shows changes of annual PM2.5 c oncentrations (arith metic average of quarterly averages) from 1999 to 2008. Overa ll, PM2.5 concentrations have decreased for this time period.

24 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

The overall trend can be divi ded into three periods. Th e first period (1999 to 2002) shows relatively large decreases with each year. The second period (2003 to 2004)

shows increased PM2.5 concentrations co mpared with 2002. The last period (2005- 2008) shows a small decrease of PM2.5 con centrations through 2007 and a marked

decrease in 2008. The actual values used to cr eate Figure 2-4 are listed in Table 2-3. In 2008, the PM2.5 annual mean concentration dropped to 12.7 μ g/m 3 , which is well below

the 15.0 μ g/m 3 standard.

0 5 10 15 20 25

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

YearConcentration [ug/m3] 13-115-0005

Figure 2-4. Trend of annual mean (arithme tic average of quarterly averages) PM2.5 concentrations at the FRM monitor ( 13-115-0005) in the Floyd County NAA.

25 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 2-3. Annual mean (arithmetic average of quarterly averages) PM2.5 concentrations at the FRM monitor in the Floyd County NAA.

Year Monitor

13-115-0005
( μ g/m 3 )

1999 21.3

2000 17.9

2001 16.2

2002 14.6

2003 16.2

2004 15.6

2005 16.6

2006 15.9

2007 15.6

2008 12.7

Figure 2-5 shows changes of 3- year design values from 2001 to 2008. In general, design values decreased steadily w ith the exception of an incr ease from 2004 to 2005. The actual values used to make Figure 2-5 are listed in Table 2-4.

26 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

0 5 10 15 20 25

99-01 00-02 01-03 02-04 03-05 04-06 05-07 06-08

YearConcentration [μg/m3] 13-115-0005

Figure 2-5. Trend of PM2.5 Design Values at the FRM monitor (13-115-0005) in the Floyd County NAA.

Table 2-4. PM2.5 Design Values at the FRM monitor (13-115-0005) in the Floyd County NAA.

DV Years 13-115-0005
( μ g/m 3 )

99-01 18.5

00-02 16.2

01-03 15.7

02-04 15.5

03-05 16.2

04-06 16.1

05-07 16.0

06-08 14.7

Figure 2-6 shows PM2.5 trends for each qua rter from 1999 to 2007 at 13-115-0005. In general, PM2.5 concentrations were higher in the 2 nd and 3 rd quarters. This is to be expected due to higher temperatures and more photochemistry during th ese quarters.

27 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-6. Quarterly averages of PM2.5 concentrations at 13-115-0005

Figure 2-7 shows changes of annual total and speciated PM2.5 concen trations (arithmetic average of daily averages) from 1999 to 2007 at the Coosa High School PM2.5 Speciation site (13-115-0005). The PM2.5 Sp eciation site started measuring PM2.5 species in 2002. With respect to contri butions of each species to total PM2.5 concentrations, OC (4.8-6.2 μ g/m 3 ) and SO4 (4.5-5.8 μ g/m 3 ) are the major constituents at the monitor. In general, PM2.5 species concentrations were consistent from 2002 to 2007 except for the recent increase of OC concentrat ions and SO4 concentrations from 2006 to
2007. From 2002 to 2007, NH4 con centrations were around 1.5 μ g/m 3 . For the same period, NO3 and EC concentrations were approximately 0.79 μ g/m 3 and 0.53 μ g/m 3

, respectively. It should be noted that the total PM2.5 trends may not necessarily track

with the trends of the summed indivi dual species because the total PM2.5 annual averages are based on measurements taken da ily whereas the speciat ed components were measured every sixth day. Therefore, unusua lly high or low values on a specific day would be weighted more by the individual sp ecies trends than by the total PM2.5 trend. In addition, there is always an unidentified amount of speciated PM2.5 (not shown) that could be increasing or decreasing.

28 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-7. Trend of annual total and speci ated PM2.5 concentrations (arithmetic average of daily averages) at the Coos a High School PM2.5 Speciation monitor (13- 115-0005).

29 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-8 shows quarterly averages of PM 2.5 concentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005). Quarterly average PM2.5 concentration for the first quarter increased from 2006 to 2007. The second quarter values showed almost steady from 2004 to 2007. The third quarter showed noticeable decrease from 2006 to 2007. Contrary to the second quarter, the fourth quarter showed a large decrease

of PM2.5 concentrations from 2005 to 2007. Ov erall, PM2.5 concentrations were higher in the second and third quarters than in th e first and fourth quarters at this site.

Figure 2-8. Quarterly averages of PM2.5 concen trations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005)

30 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-9 shows quarterly aver ages of SO4 concentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005). SO4 concentrations increased from 2006 to 2007, but the first quarter and th e third quarter showed an ove rall decrease from 2002 to 2007. The largest decrease of SO 4 concentrations occurred in the third quarter from 2002 to 2004 and from 2005 to 2006. Compared to the quarterly PM2.5 trends, quarterly SO4 concentrations were relatively higher du ring the second and third quarters than the first and fourth quarter.

Figure 2-9. Quarterly averages of SO4 concen trations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005)

31 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-10 shows quarterly averages of NO3 c oncentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005). Co ntrary to PM2.5 and SO4 trends, NO3

concentrations were low in the second and th ird quarters and high in the first and fourth quarters. From 2006 to 2007, NO3 concentrati ons increased for the first quarter. In terms of absolute values, however, NO3 concentrations did not change significantly.

Figure 2-10. Quarterly averages of NO3 con centrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005)

32 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-11 shows quarterly averages of NH4 c oncentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005). NH4 concentrations increased from 2005 to 2007 in the second and third quarters while it showed decrease from 2002 to 2004 in the third quarter.

Figure 2-11. Quarterly averages of NH4 con centrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005)

33 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-12 shows quarterly aver ages of OC concentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005). In recent years (2004 to 2007), OC

concentrations increase for the first and third quar ters. In 2007, the third quarter ended up showing the highest OC concentrations.

Figure 2-12. Quarterly averages of OC con centrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005)

34 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-13 shows quarterly averages of EC c oncentrations at the PM2.5 Speciation site in the Floyd County NAA (13-115- 0005). Overall, EC concen trations of the fourth quarter from 2004 to 2006 were higher than th ose of other quarters. From 2005 to 2007, EC concentrations largely increased in the thir d quarter. However, EC concentrations did not change dramatically in terms of absolute values.

Figure 2-13. Quarterly averages of EC con centrations at the PM2.5 Speciation site in the Floyd County NAA (13-115-0005)

35 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

2.3.2 Spatial Trends of PM2.5 in Georgia

To analyze spatial patterns in PM 2.5 concentration and composition, GA EPD used 2003- 04 data from the Speciation Trends Networ k (STN) sites in each of the four nonattainment areas: Atlanta (Site ID 13-089-0002), Chattanooga, TN (Site ID 47-065- 4002), Floyd County (Site ID 13-115-0005), and Macon (Site ID 13-021-0007) (Figures 2-14 through 2-17, Table 2-5). All four areas exhibit fairly si milar seasonal trends, with

PM 2.5 peaking in summertime. This peak is mainly due to elevated sulfate (SO4) concentrations, as well as elevated organic ma tter (OM), some of which is classified here under the “Other” category (OC is a measure of organic car bon, while other constituents of organic matter cannot be measured directly , and hence classified as “Other”). Sulfate and OC are by far the two dominant PM 2.5 species, followed by ammonium (NH4), elemental carbon (EC), nitrate (N O3), major metal oxides (MMO = 2.20Al+2.49Si+1.63Ca+2.42Fe+1.94Ti, as defined by the IMPROVE protocol). Nitrate levels are higher during wintertime, when c ooler temperatures favor nitrate particle

formation. Ammonium levels follow those of su lfate and nitrate, as it binds with these anions. The similarities in seasonal patterns and composition of PM 2.5 in these four

nonattainment areas are indications of the regional nature of PM 2.5

.

36 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0

Jan-Mar Apr-Jun Jul-Sep Oct-Decug/m3 Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-14: Seasonal patterns in PM 2.5 concentrations and composition in Atlanta

(Site ID 13-089-0002) for 2003-04 (MMO – Major Metal Oxides; Other – PM 2.5

other than sulfate, nitrate, ammonium, MMO, elemental carbon and organic carbon).

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0

Jan-Mar Apr-Jun Jul-Sep Oct-Decug/m3 Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-15: Seasonal patterns in PM 2.5 concentrations and composition in Chattanooga (Site ID 47-065-4002) for 2003-04 (MMO – Major Me tal Oxides; Other

– PM 2.5 other than sulfate, nitrate, a mmonium, MMO, elemental carbon and organic carbon).

37 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 22.0

Jan-Mar Apr-Jun Jul-Sep Oct-Decug/m3 Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-16: Seasonal patterns in PM 2.5 concentrations and composition in Floyd County (Site ID 13-115-0005) for 2003-04 (M MO – Major Metal Oxides; Other –

PM 2.5 other than sulfate, nitrate, ammoni um, MMO, elemental carbon and organic carbon).

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0

Jan-Mar Apr-Jun Jul-Sep Oct-Decug/m3 Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-17. Seasonal patterns in PM 2.5 concentrations and composition in Macon

(Site ID 13-021-0012) for 2003-04 (MMO – Major Metal Oxides; Other – PM 2.5

other than sulfate, nitrate, ammonium, MMO, elemental carbon and organic carbon).

38 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Assessing the relative contributi on of primary and secondary species is not trivial, since OC is part primary and part secondary. Als o, an assumption needs to be made for the ratio of OM/OC. Assuming an OM/OC ratio of 1.4 and that roughly 50% of the OC is secondary (on an annual basis), it is po ssible to estimate that about 40% of PM 2.5 in the region is primary, with the remaining fraction being secondary (Table 2-6).

Table 2-5. Average PM 2.5 composition during 2003-2004 for the four STN sites in the

non-attainment areas

Site SO4 NO3 NH4 MMO EC OC Other

Atlanta 4.56 0.83 1.35 0.55 0.96 5.16 2.15 Chattanooga 4.96 1.10 1.70 0.62 0.71 4.92 1.13 Floyd County 4.93 0.88 1.46 1.05 0.50 5.01 3.23

Macon 4.50 0.67 1.26 1.47 0.68 5.51 2.34

Table 2-6. Estimated primary and se condary percentage of PM 2.5

Site % primary % secondary

Atlanta 40 60 Chattanooga 32 68 Floyd County 43 57

Macon 44 56

Despite the regional nature of PM 2.5 and the high fraction of secondary components, there is clear evidence of impacts of local sources of primary PM 2.5 at some of the sites. Both the Macon and Floyd County monitors show hi gher levels of crustal elements (MMO, Table 2-5), compared to Chatta nooga and Atlanta (1.47, 1.05, 0.62 and 0.55 μ g/m 3

, respectively). The Floyd County monitor also exhibits higher leve ls of unspecified (“Other”) PM 2.5 , compared to the other three sites. Elemental carbon levels are highest in Atlanta (1.0 μ g/m 3 compared to 0.5-0.7 μ g/m 3 at the other three sites), the largest city of these four areas, and are likely an indicator of emissions from mobile sources and especially diesel traffic. As expected, con centrations of OC (par tially secondary) and secondary ionic PM 2.5 (sulfate, nitrate, ammonium) are fairly similar at all four sites, though the Chattanooga site exhibits somewhat higher levels of ammonium nitrate.

2.3.3 Source Apportionment of PM2.5

Receptor models are useful tools for identif ying the sources contributing to measured levels of pollutants. One of the most r ecently used source-apportionment models in recent years is the Positive Matrix Factorizati on (PMF) model. PMF is a factor analytic method that distinguishes correla tion patterns among speciated PM 2.5 measurements in a given location.

39 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Presented here are source-apportionment re sults for 2003-2004 (Figure 2-18 and Table 2- 7). These once again show the regional nature of PM2.5, given the similarities between the PMF results for the three sites. The majo r impacting factors at all sites are secondary sulfates, secondary nitrates, SOA, mobile sources and biomass burning. The Atlanta area, as expected, has highe r levels of mobile-source PM 2.5, compared to Floyd County and Macon. On the other hand, these latter two site s exhibit higher leve ls of soil dust, and the Macon site exhibits a relatively high contribution of Lime/Minerals PM2.5. This may be due to local sources in the industrial area where the site is located.

These results are also useful for a preliminar y assessment of control strategies. Given the large contributions to PM2.5 from the seconda ry-sulfate factor, it is evident that controlling SO2 emissions (mainly from coal -burning EGUs) would reduce PM2.5 levels throughout the state. Controlling emissions of SOA precursors would also be useful, unfortunately these are not yet well unders tood, and limited available knowledge suggests biogenic sources as the primary SOA precurs ors. Reducing primary PM2.5 may be best achieved by emission reduction measures fo r mobile-source emissions and biomass burning. The efficiency of NOx controls on PM2.5 was addressed via a photochemical modeling study and was found to be inefficient (see Section 2.4.3). Contributions from all other source-categories were small in ge neral, though the Macon and Rome sites seem to be affected by local sources related to lime/minerals processing and soil dust resuspension. More information on source appo rtionment is presented in Appendix B and Appendix C.

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0

Atlanta Floyd county Maconug/m3 Unspec.

SOA

Sec. Nitrate

Sec. Sulfate

Zn-rich

Cu-rich

Road-dust

Oil burning

Na-rich

Lime/Minerals

Soil

Biomass burning

Mobile-sources

Figure 2-18: Average factor contributions for 2003-04 at the At lanta, Floyd County, and Macon STN sites using PMF

40 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 2-7 Average factor contributions to PM 2.5 ( μ g/m 3 ) for 2003-04 at the Atlanta, Floyd County, and Macon STN sites using PMF

Factor Atlanta Floyd County Macon

Mobile-source 2.78 1.61 2.12

Biomass burning 1.06 1.31 1.50

Soil 0.29 0.61 0.67

Lime/Minerals 0.05 0.24 0.59

Na-rich 0.43 0.42 0.33

Oil 0.03 0.04 0.04

Road-dust 0.12 0.13 0.11

Cu-rich 0.07 0.03 0.02

Zn-rich 0.03 0.03 0.03

Sec. Sulfate 4.82 5.10 4.67

Sec. Nitrate 0.99 1.05 0.74

SOA 2.55 3.46 3.81 Unspecified 2.32 2.97 1.81

2.3.4 Meteorology

ICF International performed a meteorological characteriza tion study designed to examine the relationships between meteorology, fine pa rticulates, and regiona l haze at air quality monitoring sites throughout the Southeastern U.S. (Character ization of Meteorology and Its Relationships to Fine Particulate Mass and Visibility in the VISTAS Region, December 5, 2006). This study is one of the technical analyses conducted by VISTAS to support regulatory planning for regional haze and PM2.5 nonattainment issues for the southeastern states. The study is presented as Appendix D.

Classification and Regression Tr ee (CART) statistical analysis was used to examine relationships between meteorology, fine particulates, and visibi lity that are important to atmospheric modeling. Separate CART an alyses were conducted for visibility (as defined by the extinction coefficient) and fi ne particulates [par ticulate matter with a diameter less than 2.5 microns (PM2.5)]. PM2.5 analyses were conducted for the IMPROVE, STN, and SEARCH monitoring sites. CART was applied for each site and was used to classify days for the period 2000- 2004 into groups (or bi ns) with similar air quality (visibility or PM2.5) and meteorologica l characteristics. Cl assification accuracy ranged from approximately 72 to 85 percent fo r visibility and from approximately 75 to 90 percent for PM2.5. In applying the CART technique, ICF International found that good classification for most sites was depe ndent on information about prior day air quality. This indicates that regional buildup and transport of fine particles and related precursor species influences regional visibility and PM2.5 concentrations. They also found that moisture is an important meteorol ogical parameter for good classification for both PM2.5 and visibility and that the more complex role of moisture in determining light extinction—affecting both particle formation and the contribution of sulfate and nitrate

41 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

particle species to light ex tinction—may account for the ove rall better classification accuracy for PM2.5 compared to extinction coefficient.

A CART analysis was not performed for the Ro me monitor. However, a CART analysis was performed for the Yorkville SEARCH mon itor which is located relatively close to the Floyd monitor and can be considered representa tive of the Floyd County nonattainment area. The categorical compar isons for PM2.5 in Yorkville consisted of four categories: <15.0 (Cat egory 1), 15.0-22.5 (Category 2) , 22.5-30.0 (Category 3), and

> 30 (Category 4) μ g/m 3 , respectively. A summary of th e average input parameters for each CART classification category in Yorkville is contained in Table 2-8. From this table, it can be seen that important su rface parameters leading to higher PM2.5 concentrations include higher PM2.5 the da y before in Atlanta, Birmingham, and Yorkville; higher surface temperature; lo wer wind speeds; easterly winds; and lower amounts of rain. In addition, it can be seen that important upper-air meteorological parameters leading to higher PM2.5 concentrations include higher 850 mb temperatures, lower 850 mb wind speeds, northeasterly wi nds, and more stability in Atlanta.

42 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 2-8 Summary of average input para meters for each CART classification Category in Yorkville.

For Yorkville, there are six key bins (gr oup of days with similar meteorological conditions) falling into the Category 3 and Ca tegory 4 concentration range (Table 2-9). Bins 28, 22, and 29 are characterized by high prior-day PM2.5 concentrations in Atlanta and Birmingham (> 35 μ g/m 3 ) and by high prior-day PM2.5 c oncentrations in Yorkville (> 28 μ g/m 3 ). Bins 28 and 29 are characterized by high wind speeds at the surface and aloft. Bins 18, 29, and 15 are characterized by winds from the east or southeast, while the other bins are characterized by winds from the southwest, west, or northwest.

43 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 2-9 Summary of average input paramete rs for key bins for CART classification (Class) categories 3 and 4 in Yorkville.

Figure 2-19 shows the average composition for all key PM2.5 bins in Yorkville. Consider the six key high PM2.5 bins (Class 3 & 4 bins) for Yorkville. On average, all six bins are dominated by sulf ate followed by organic matter.

In summary, high PM2.5 for Yorkville is asso ciated with moderate temperatures, high PM2.5 on previous day (Atlanta, Birmingham, a nd Yorkville), very low wind speeds near the surface and low wind sp eeds aloft, and stable conditions. The high PM2.5 classification categories are associated with higher sulfat e concentrations.

44 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-19: Average composition fo r all key PM2.5 bins in Macon.

2.3.5 Sensitivities to Pollutant Emissions

Georgia Tech performed sensitivity studies to examine the impacts of reductions of emissions of various pollutants on annual PM2.5 concentrations using CMAQv4.4_SOAmods on the VISTAS 12 km modeling domain. A summer episode (June 1 – July 10, 2002) and winter epis ode (November 19 – December 19, 2002) were simulated with VISTAS 2009 BaseD emissions. Each sensitivity consisted of reducing the emissions or boundary conditions by 30%. Most sensitivities were performed on a state-by-state basis or RPO-by-RPO basis. However, sensitivities for ground-level NOx and primary carbon were performed for a spec ific subset of coun ties submitted by each state. Below is a list of the specif ic sensitivities that were performed.

• EGU Point SO2 (10 states + 3 RPOs)

• Non-EGU Point SO2 (10 states + 3 RPOs)

• Boundary SO2 and SO4 (12 km domain)

• Point NOx (10 states + 3 RPOs)

• Ground-level NOx (10 states + 3 RPOs)

• Ground-level Primary Carbon (10 states + 3 RPOs)

• Point Primary Carbon (10 states + 3 RPOs)

• Fire Primary Carbon (10 states + 3 RPOs)

• NH3 (4 RPOs)

• Anthropogenic and Biogenic VOCs (domain-wide)

45 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figures 2-20 and 2-21 contain the sensitivities for each pollutant and source category for the summer and winter episodes, respectivel y. In the summertime, the most important anthropogenic source category in Georgia is EGU SO2 followed by ground-level PC, point PC, and non-EGU SO2. In the winter time, the most important anthropogenic source category is VISTAS NH3 followed by Georgia ground-level PC, Georgia EGU SO2, and domainwide VOCs.

46 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA



## Rome, GA (131150005) Summer

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

S

O

2 _

E

GU SO2_nonEGU

N

O

x _

G

r o

u

n d NOx_Point NH 3 VOCs PC_G r ound

P

C

_Poin t

PC_ F

iresΔPM2.5(μg/m3) Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 2-20: Sensitivities of PM2.5 by pollutant and source category for the summer episode in Floyd County. ∆ PM2.5 is based upon a 30% reduction of pollutant levels from 2009 levels.



## Rome, GA (131150005) Winter

-1.60

-1.40

-1.20

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

S

O

2_

E

GU

S

O

2_no nE

GU
NOx _ Gr

ound NOx _ Point NH3
V O

Cs

P C _

G

round PC_Po i nt

P C _

F iresΔPM2.5(μg/m3) Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 2-21: Sensitivities of PM2.5 by pollutant and source category for the winter episode in Floyd County. ∆ PM2.5 is based upon a 30% reduc tion of pollutant levels

from 2009 levels.

47 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 2-22 contains the annual average sensitivities for each pollutant and source category based on the average response of the summer and winter episodes in Floyd County. Figure 2-23 contains the annual average sensitivities for each pollutant and source category based on the CART weight ed response of the summer and winter episodes in Floyd County. Both of these fi gures indicate that the most important anthropogenic source category is VISTAS NH3 followed by Georgia EGU SO2 and Georgia ground-level PC. However, it should be noted that NH3 and SO2 (both of which are gases at ambient temperatures) react to form ammonium sulfates in the atmosphere (which are fine particulates at ambient temp eratures). Thus, reduction of either NH3 or SO2 emissions should result in a lowering of th e other. Furthermore, there are currently no known cost-effective ways to reduce NH3 emi ssions in Georgia. Therefore, control strategy development should focus on SO2 from EGUs and PC from ground-level

sources.



## Rome, GA (131150005) Annual

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

SO2 _ EGU

SO2 _n

on

EGU

NOx _ Gro un

d NOx_Point NH3 VOCs PC_ Gr

ou

nd

PC_Point PC_ F

i r esΔPM2.5(μg/m3) Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 2-22: Annual average emission sensitivities by pollutant and source category based on the average response of the su mmer and winter episodes in Floyd County.

48 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA



## Rome, GA (131150005) Annual

-2.30

-1.80

-1.30

-0.80

-0.30

0.20

SO2 _ EGU

SO2 _n

on

EGU

NOx _ Gro un

d NOx_Point NH3 VOCs PC_ Gr

ou

nd

PC_Point PC_ F

i r esΔPM2.5(μg/m3) Bio.

Antro.

BCs

MRPO

M-VU

CEN

VISTAS

WV

VA

TN

SC

NC

MS

KY

GA

FL

AL

Figure 2-23: Annual average emission sensitivities by pollutant and source category based on the CART weighted response of the summer and winter episodes in Floyd County.

2.4 PM2.5 Sources and Precursors

This section of the SIP includes a discus sion of sources of PM2.5 emissions and of significant PM2.5 precursors in the Floyd Count y Nonattainment Area. The technical justification is also presented for re versal of the presumption, under the PM Implementation Rule, that NOx is a si gnificant PM2.5 precursor in Georgia.

2.4.1 Sources of PM2.5

Sources of PM2.5 and PM2.5 precursors in th e non-attainment area have been separated into the following five source classifications:

• stationary point sources,

• stationary area sources,

• on-road mobile sources,

• off-road mobile sources, and

• biogenic sources.

49 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 2-10 shows typical base year invent ories of PM2.5 and its precursors for Floyd County. The method for generating the typical base year inventory is explained in

Section 3.5 of this narrative.

Table 2-10. Typical Base Year (2002) Emissions Inventories for Floyd County

Source Type Typical 2002 Emissions (tons/year)*

VOC NOx SO2 PM-2.5 NH3

Point 1835.3 13,053.3 35,245.1 651.0 16.8

Area 4565.0 622.1 979.5 1378.5 575.5

Mobile 3730.9 3058.7 128.1 49.4 106.4

Nonroad 808.2 1100.6 81.2 60.9 0.5

Anthropogenic

subtotal 10,939.4 17,834.7 36,433.9 2139.8 699.2 Biogenic 16,562.4 113.2 NA NA NA

Total 27,501.8 17,947.9 36,433.9 2139.8 699.2

* Source: VISTAS - Typical 2002 Base G2 Annual Emissions Summary for Georgia Counties

Stationary point sources are those sources that emit greater than a specified tonnage (specific to pollutant) per year, with data provided at the facility level. Point sources are responsible for the large majority of NOx a nd SO2 emissions in the non-attainment area. Electric generating units (EGUs) and industrial sources are the major types of stationary point sources.

There is one EGU source, Georgia Po wer’s Plant Hammond, located in the nonattainment area. Plant Hamm ond has four coal-burning EGUs which contribute the majority of the SO2 and NOx emissions in th e non-attainment area. Coal-burning power plants located outside of the non-attainment area but within the Stat e boundaries are also important sources of SO2 emissions that affectambient sulfate levels inside of the nonattainment area. Table 2-11 lists point source s that are Title V major sources of one or more of the following pollutants: NOx, VOC, PM, and SO2.

50 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 2-11. Point Sources in the Floyd Co unty Non-Attainment A rea That Are Title V Major Sources

Facility Facility Type NOx major

source VOC major

source PM major

source SO2 major

source Georgia Power – Plant

Hammond EGU X X X X

Inland Paperboard and Packaging Saw Mill* Pulp and

paper X

Temple Inland Rome (Linerboard Mill)* Pulp and

paper X X X X

Metal Container Corporation Beverage can manufacturing X

Inland Paperboard and Pkg. Corrugated Plant* Pulp and

paper X X X X

Packaging Products Corporation Flexible pkg. printing X

General Shale Brick – Plant 40 Building products X X

* colocated

Stationary area sources are those sources whos e individual emissions are relatively small, but, due to the large number of these sources, the collectiv e emissions from the source category could be significant (i.e ., dry cleaners, service stati ons, agricultural sources, fire emissions, etc.). These types of emissions are estimated on a countywide level. Emissions from large fires that occur in S outh Georgia, outside of the non-attainment area, can also have significant effects on am bient PM levels in the non-attainment area.

On-road mobile sources are automobiles, bus es, trucks, and motorcycles that use the roadway system. The emissions from these sources are estimated by vehicle type and road type, and are summed to the countywide level.

Non-road (or off-road) mobile sources are pieces of equipment that can move but do not use the roadways. Examples are lawn mowers, construction equipment, railroad locomotives, and aircraft. The emissions from these sources, like stationary area sources,

are estimated on a count ywide level.

2.4.2 Precursors

The PM 2.5 SIP must address both direct PM and s econdary PM. As discussed previously, secondary PM is formed from emissions of PM precursors. Therefore, it is critical to identify the precursors that are releva nt to a specific non-attainment area.

51 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

40 CFR 51.1000 defines a “PM 2.5 precursor” as any air polluta nt other than direct PM 2.5 that contributes to the formation of PM 2.5 . Emissions inventories required for attainment

demonstration must include emissions of all PM 2.5 precursors identified for the nonattainment area.

40 CFR 51.1000 defines a “PM 2.5 attainment plan precursor” as SO2 and any other precursor which the State must evaluate for em issions reduction measures in the SIP. 40 CFR 51.1002 states that, for control purposes , NOx is presumed to be a precursor whereas VOCs and ammonia are presumed not to be precursors. The regulation allows any of these presumptions to be reversed by either the State or EPA by means of a technical demonstration. The regulation does not require th e State to address VOCs or ammonia as an attainment plan precursor unless either the State or EPA provides a technical demonstration for a specific area showing that emissions from the State significantly contribute to PM [refer ence 40 CFR 51.1002 (3) and (4)]. 40 CFR 51.1002 (c) implies that all sources of precursors w ithin the State boundaries must be evaluated for emissions reduction measures. However, th e preamble to the final rule, 72 FR 20636, gives EPA’s policies on the geographic ranges to use for evaluation of emissions reduction measures for RFP plans:

• direct PM2.5 - sources inside the non-attainment area only

• SO2 - sources within 200 km

• NOx and VOC- sources within 100 km

• ammonia - no policy

Therefore, it is EPD’s interpretation that sources of SO2 emissi ons throughout the state must be evaluated for potential reduction measures.

Georgia EPD has designated SO2 to be the only attainment plan precursor in the Floyd County SIP. Georgia EPD is not providing a technical demonstrati on to show that VOC or ammonia significantly contri butes to PM to overcome EPA’ s presumption that they are not to be regulated as precursors. Geor gia EPD has determined that NOx is not a significant precursor for PM2.5 formation in the Floyd County non-atta inment area. The technical justification for NOx insignificance is presented in the following subsection.

2.4.3 Technical Justification for Rev ersal of NOx Precursor Presumption

The U.S. EPA, in 72 FR 20586, requires states to “evalua te and consider control strategies for sources of SO 2 , direct PM2.5, and NOx emi ssions in all nonattainment areas.” However, the rule does allow states to make technical dem onstrations to reverse the inclusion of NOx as precursor of PM2.5, or deem the precursor insignificant, based on geographical regions, emissions , etc. This then eliminat es the need to examine NOx control measures for purposes of reduc ing PM2.5 concentrati ons. Georgia EPD’s analysis, summarized below, demonstrates th at NOx is an insignificant PM2.5 precursor

52 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

in each of Georgia’s four nonattainment areas : Atlanta, Macon, Rome, and Chattanooga. The full text of the analysis is presented in Appendix E.

2.4.3.1 Ambient Measurements

Ambient monitoring data in Georgia nonatt ainment areas were evaluated using FRM measurements and speciated data. The “ S ulfate, A djusted N itrate, D erived W ater,

I nferred C arbonaceous mass H ybrid” (“SANDWICH”) material balance approach was used to speciate the FRM to tal PM2.5 mass into its compon ents - SO4, NO3, NH4, PBW, OC, EC, and crustals. Figure 2-24 contains the annual av erage PM2.5 concentrations averaged across all FRM monito rs in each nonattainment area. The measurements show annual average nitrate concentrations (plus a mmonium and PBW associ ated with nitrate)

collected on the FRM filt ers range from 0.27 to 0.33 μ g/m 3 which is only 1.7 to 2.5 percent of the total FRM mass. These are very small compared to sulfate and OC

contributions.

0 2 4 6 8 10 12 14 16 18 20AtlantaMaconRomeChatta.AtlantaMaconRomeChatta.AtlantaMaconRomeChatta.AtlantaMaconRomeChatta.AtlantaMaconRomeChatta.

Quarter 1 Quarter 2 Quarter 3 Quarter 4 Annual Avg.Concentration (μg/m3) Crust.

EC

OC

PBW

NO3

NH4

SO4

Blank

Figure 2-24. SANDWICH Speciated Con centrations of Quarterly and Annual Average 2002 PM2.5 Base Design Values (DVB) averaged over FRM Monitors in each Georgia PM2.5 Nonattainment Area.

2.4.3.2 Future-Year Attainment Modeling

Attainment demonstration modeling using on-the-books, future-year emissions and the Speciated Modeled Attainment Test (SMA T) accounted for statewide NOx emission reductions of 24% between 2002 and 2009 and 30% between 2009 and 2018 (Table 2-12). Despite these large emission reducti ons, the annual average NO3 concentrations are only reduced by 0.00 to 0.03 μ g/m3 across all nonattainment areas in Georgia (Figure 2-25). In addition, there is a reduction in OC . However, much of the reductions in OC

53 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

are due to reductions in primary emissions of OC and not due to reductions of NOx emissions. This is evident by the associated reductions in EC concentrations since primary emissions of OC and EC usually change together (Figure 2-25).

Table 2-12. Expected Change in NO x Emissions (%) in Georgia PM2.5 Nonattainment Areas. Reductions are negative.

Change in NOx emissions (%)

2002 to 2009 Change in NOx emissions (%)

2009 to 2018 Nonattain.

Area Point Nonroad

mobile Area Onroad

mobile Total Point Nonroad

mobile Area Onroad

mobile Total

Atlanta -40.8 -11.4 5.2 -33.7 -30.5 -48.1 -24.3 10.8 -54.3 -40.3

Macon -32.4 -15.1 3.9 -32.0 -30.9 2.7 -27.8 9.4 -48.3 -8.6

Rome -16.8 -15.7 4.1 -28.9 -18.1 -35.2 -26.8 8.2 -46.1 -34.4 Chattanooga -70.9 -12.7 2.7 -34.2 -48.8 5.2 -21.4 7.1 -50.5 -23.7

GA Statewide -24.6 -12.5 3.9 -32.0 -24.1 -15.6 -24.7 6.9 -51.2 -29.8

54 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Georgia Nonattainment Area Concentration Differences: (2002 DV)-(2009 DV) (Left) and (2009 DV)-(2018 DV) (Right)

-0.05 0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45Clayton-0091Cobb-0003Cobb-0004DeKalb-0002DeKalb-2001Fulton-0032Fulton-0039Gwinnett-0002Hall-0003Paulding-0003Bibb-0007Bibb-0012Floyd-0005Hamilton-1011Hamilton-31-1Hamilton-4002Walker-0002

Monitor Locationug/m3 EC

OC

NO3

Figure 2-25. Reductions in EC, OC, a nd NO3 concentrations between 2002 & 2009 and 2009 & 2018 at Georgia nonattainment monitors.

2.4.3.3 Statewide NOx Sensitivities

Sensitivities to statewide NOx emission reduction (30%, 50%, 70%, and 100%) were modeled for 2009 in Georgia. The ma ximum predicted PM2.5 reductions are approximately 1.2 μ g/m 3 for 100% statewide NOx removal, 0.4

 μ g/m 3 for 70% removal,

0.22

 μ g/m 3 for 50% removal (Figure 2-26), and 0.11

 μ g/m 3 for 30% removal (Figure 2- 27).

55 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Statewide 50% NOx Reduction

-0.25

-0.20

-0.15

-0.10

-0.05

0.00DeKalb-2001Fulton-0032Fulton-0039Clayton-0091Hall-0003Gwinnett-0002Cobb-0003DeKalb-0002Paulding-0003Bibb-0007Bibb-0012Floyd-0005Hamilton-4002Walker-0002ΔPM2.5 (μg/m3) Soils

EC

OC

H2O

NO3

NH4

SO4

Figure 2-26. Annual Average PM2.5 Response to GA Statewide 50% NOx Emission Reduction in 2009 in the Georgia PM2.5 Nonattainment Areas.

Statewide 30% NOx Reduction

-0.12

-0.10

-0.08

-0.06

-0.04

-0.02

0.00

0.02

0.04DeKalb-2001Fulton-0032Fulton-0039Clayton-0091Hall-0003Gwinnett-0002Cobb-0003DeKalb-0002Paulding-0003Bibb-0007Bibb-0012Floyd-0005Hamilton-4002Walker-0002ΔPM2.5 (μg/m3) Soils

EC

OC

H2O

NO3

NH4

SO4

Figure 2-27. Annual Average PM2.5 Response to GA Statewide 30% NOx Emission Reduction in 2009 in the Georgia PM2.5 Nonattainment Areas.

56 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

GA EPD feels it is inappropriate to appl y a 100% statewide NOx emission reduction to evaluate the significance of NOx emissions on ambient PM2.5 since this is an unrealistic control scenario leading to unrealistic atmospheric conditio ns. In addition, the CB-IV

chemical mechanism and SOA module used in the CMAQ modeling were developed to accurately predict pollutant concentrations under typical ambient conditions. They were not intended to be used to make pollutant predictions under the unrealistically low oxidizing atmospheric conditions caused by zeroing- out all NOx within a state. Instead, GA EPD feels it is more appropriate to eval uate more realistic, yet aggressive, NOx

reductions from sources across the state. GA EPD conducted a technical analysis looking at potential statewide reducti ons in mobile (on-road and non-road), point, and area sources and has concluded that a very aggressive upper bound on statewide emission

reductions would result in a NOx reduction of approximately 47%. This scenario assumes the installation and operation of a ll possible controls through 2030. In addition, GA EPD evaluated aggressive upper-bound NOx emissions reductions for 2014 since the

latest attainment date for annual PM2.5 nona ttainment areas is 2015. Assuming all the controls listed for 2030 are achievable by 2014 and replacing the 2030 on-road mobile

fleet turnover with 201 4 on-road mobile emissions, results in a 31% statewide reduction in NOx emissions. As a result, GA EPD f eels that a statewide 30% or, at worst, a

statewide 50% NOx reduction r un would be the most appropria te scenario to use in the NOx insignificance demonstration. Modeling results show a maximum impact of 0.11

μ g/m 3 across all nonattainment monitors in the state for a 30% statewide NOx reduction run (monitors in dow ntown Atlanta showed a slight increase in PM2.5 formation) and a maximum impact of 0.22 μ g/m 3 across all nonattainment monito rs in the state for a 50%

statewide NOx reduction run.

2.4.3.4 CMAQ Model Performance for Organic Carbon

OC modeling is still devel oping and does not include many important pathways. Recent smog chamber studies at Caltech have shown that reducing NOx emissions can lead to higher SOA production from isopr ene, monoterpenes, and aromatic VOC. None of these pathways are currently included in the model. Furthermore, it should be noted that the SOA module used in CMAQ wa s developed based on S OA formation rates under ambient atmospheric conditions and that SOA fo rmation rates have not been tested under the artificially low oxidant levels that resu lt from zeroing out all NOx emissions in a large state. This introduces additional uncertain ty in the interpretation of the responses of organic carbon aerosol to large NOx reductions.

In Figure 2-28, it can be seen that the CMAQ model (dark blue and light blue lines) has poor hourly OC model performance when comp ared to OC observati ons (black line). The model predicts unrealistical ly high OC predictions in the early morning hours when the mixing height is low. It is during th ese same hours that the model shows large OC sensitivities to NOx reductions. Note that in Figure 2-30, dSOMA (pink) is the response of anthropogenic secondary organic aerosol s, dSOMB (bold red) is the response of biogenic secondary organic aerosols, dPSOM (green) is the response of polymerized secondary organic aerosols, and dPOM (bold black) is the response of primary organic

57 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

aerosols. Because large dSOMB responses to NOx reductions occur during the same periods that the model is performing poorly, it can be concluded that these responses are likely too high. It should be noted that near the end of the month (06/27-06/30) when the model is performing well, that the OC sensitivity has been reduced by an order of magnitude. As a result, it very likely that the OC responses presented earlier are highly

overestimated and should not be used to quantify the impacts of NOx reductions.

Organic Carbon in June 2002 @ YRK

0 5 10 15 20 25 30 35 406/1/02 0:006/2/02 0:006/3/02 0:006/4/02 0:006/5/02 0:006/6/02 0:006/7/02 0:006/8/02 0:006/9/02 0:006/10/02 0:006/11/02 0:006/12/02 0:006/13/02 0:006/14/02 0:006/15/02 0:006/16/02 0:006/17/02 0:006/18/02 0:006/19/02 0:006/20/02 0:006/21/02 0:006/22/02 0:006/23/02 0:006/24/02 0:006/25/02 0:006/26/02 0:006/27/02 0:006/28/02 0:006/29/02 0:006/30/02 0:00

DateAbs Concentration [ug/m3] -4

-3

-2

-1

0

1

2

3

4Diff Concentration [ug/m3] OC_02_Typical OC_09_Typical OC dSOMA dSOMB dPSOM dPOM

Figure 2-28. Hourly measured and modele d OC concentrations and the difference

between the base and sensitivity concentrat ions of the four components of OC to

100% statewide NOx emissions reductions at the Yorkville SEARCH monitor.

2.4.3.5 Conclusion

An analysis of emission trends, ambient data concentrations, and modeling has lead GA EPD to conclude that NOx is an insigni ficant precursor to PM2.5 in Georgia’s nonattainment areas. GA EPD feels it is inappr opriate to evaluate the impacts of a 100% statewide NOx sensitivity as part of a NOx insignificance demonstration since this level of control is not realistically achievable from a NOx control standpoint. In addition, caution should be used when interpreting th e predicted changes in OC resulting from NOx reductions since the CMAQ modeling syst em does not properly simulate hourly OC temporal variations and wa s not designed to predict co ncentrations under extreme reductions in precursor emi ssions and oxidant levels.

58 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

GA EPD feels that a 30% or, at worst, a 50% statewide NOx reduction scenario would be more appropriate to evaluate the effect of NOx reductions on PM 2.5. Modeling results show a maximum impact of 0.11 μ g/m 3 across all nonattainment monitors in the state for

a 30% statewide NOx reduction scenar io and a maximum impact of 0.22 μ g/m 3 across all

nonattainment monitors in the state for a 50% statewide NOx reduction scenario.

EPA’s CAIR modeling used a significance level of 0.2 mg/m 3 to evaluate interstate impacts (e.g., Georgia emissions impacts on non -Georgia PM2.5 monitors). Therefore, it would seem reasonable to assume that the signi ficance threshold level fo r a state on itself, for the purpose of reversal of the NOx pr ecursor presumption, should be higher than a state on a neighboring state. The proposed Pr evention of Significant Deterioration (PSD) significant impact levels (SIL s) for direct PM2.5 emissions from a single stationary source range from 0.3 to 1.0 μg/m3 on an annual average (70 FR 54154). From this, it would follow that the significance threshold all sources in a state should be even greater than this range. At an absolute minimum, the significance threshol d level should set at 0.3 μg/m 3

.

Since both the 30% statewide NOx reduc tion and 50% statewide NOx reduction modeling scenarios result in a reduction of PM2.5 impact of less 0.3 μg/m 3 , EPD has clearly demonstrated that NOx is insignifi cant as a precursor to PM2.5 in the Georgia

nonattainment areas.

Section 3. Attainment Demons tration Methods and Inputs

The attainment modeling for the Floyd County PM 2.5 nonattainment area was performed in conjunction with the regional haze modeling being done by the Southeast regional planning organization (RPO), Visibility Improvement State and Tribal Association of the Southeast (VISTAS), and the PM 2.5 and ozone (O 3 ) modeling being done by the Association of Southeastern Integrated Pla nning (ASIP). VISTAS and ASIP are run by the ten Southeast states (Alabama, Florid a, Georgia, Kentuc ky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia and West Virginia). Since the regional

haze and PM 2.5 modeling use annual simulations and incl ude an intermediate year that is the attainment year requ ired for the Floyd County PM 2.5 nonattainment area, GA EPD decided to use this 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 decided to use the following modeling system:

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

59 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

• Emissions Model: The Sparse Matrix Operator Kernel Emissions (SMOKE) modeling system is an emissions modeli ng system that generates hourly gridded speciated emission inputs of mobile, nonroad mobile, area, point, fire, and biogenic emission sources for photochemical grid models.

• Air Quality Model: The USEPA’s Models -3/ Community Multiscale Air Quality (CMAQ) modeling system is a “One-A tmosphere” photochemical grid model capable of addressing O 3 , particulate matter, visibi lity, 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 PM 2.5 and poor visibility are observed throughout the region. Once the hi storical year is selected, meteorological inputs are developed using the meteorological model. Emission 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, PM 2.5 and visibility, with the results compared to the historic data. The model performan ce is evaluated by comparing the modeled predicted data to the hi storic air quality data.

Once model performance is deemed adequate, ty pical baseline and future year emissions are processed through the emissions model. For this demonstrati on, the baseline year was 2002, which corresponds with the same year as the historic meteorology used in the modeling. The attainment future year GA EP D is using for this demonstration is 2009, since the mandatory attainment date for the Floyd County PM 2.5 nonattainment area is April 5, 2010. The attainment date is set prior to the completion of the 2010 calendar year; therefore the attainment of the NAAQS would have to be met by the end of 2009. These emissions are processed through the ai r quality model with the meteorological inputs. The air quality modeling results are used to determine a relative reduction in

future PM 2.5 , which is used in the at tainment demonstration.

The complete modeling protocol used for th is analysis can be found in Appendix F.

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 me thods. 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 goa ls. These criteria we re used in selecting the modeling system used for this modeling attainment demonstration.

60 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.2.1 Selection of Air Quality Model

3.2.1.1 Criteria

For an air quality model to qualify as a candida te 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 ev aluations have show n the model is not

biased toward underestimates or overestimates.

• A protocol on methods and procedures to be followed has been established.

• The developer of the model must be willing to make the source code available to users for free or for a reasonable cost, and the model cannot otherwise be proprietary.

3.2.1.2 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 the attainment mo deling exercise started. For more than a decade, the USEPA has been developing the Models-3 CMAQ modeling system with the overarching aim of producing a “One-Atmosphe re” air quality modeling system capable of addressing ozone, fine particulate matter, visibility and acid deposition within a common platform. The original justifica tion for the Models-3 development emerged from the challenges posed by the CAAA and the USEPA’s desire to develop an advanced modeling framework for “holistic” environm ental modeling utilizing state-of-science representations of atmospheric processes in a high performance computing environment. The USEPA completed the initial stage of de velopment with Models-3 and released the CMAQ model in mid-1999 as the initial ope rating science model under the Models-3

framework.

Another reason for choosing CMAQ as the atmo spheric model is the ability to do oneatmospheric modeling. Since GA EPD will be using the same modeling exercise for the

ozone and PM 2.5 attainment demonstration state imple mentation plans (SIPs), as well as the regional haze SIP, having a model that can handle both ozone and particulate matter

is essential. A number of features in CMAQ’s theoretical formulation and technical implementation make the model well suited for annual PM 2.5 modeling.

The configuration used for this modeling de monstration, as well as a more detailed description of the CMAQ model, can be found in Appendix G.

61 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.2.2 Selection of Meteorological Model

3.2.2.1 Criteria

Meteorological models, either through objec tive, diagnostic, or prognostic analysis,

extend available information about the state of the atmosphere to the grid upon which photochemical grid modeling is to be ca rried out. The crite ria for selecting a meteorological model are based on both the model's ability to accurately replicate important meteorological phenomena in the re gion 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 we re 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

• Enhanced treatment of Planetary Bo undary Layer heights for AQ modeling

3.2.2.2 Overview of MM5

The non-hydrostatic MM5 model is a three-di mensional, limited-area, primitive equation, prognostic model that has been us ed 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 an d has been used worldwide by hundreds of scientists for a variety of mesoscale studies.

MM5 uses a terrain-following non-dimensiona lized pressure, or "sigma", vertical

coordinate similar to that used in many operational and re search models. In the nonhydrostatic MM5, the sigma levels are define d according to the initial hydrostatically balanced reference state so that the sigma le vels are also time-invariant. The gridded meteorological fields produced by MM5 ar e directly compatible with the input requirements of “one atmosphere” air-quality models using this coordinate. MM5 fields can be easily used in other re gional air quality mode ls with different coordinate systems by performing a vertical inte rpolation, followed by a mass-conservation readjustment.

Two planetary boundary layer para meterizations are available fo r air-quality applications, both of which represent sub-grid -scale turbulent fluxes of heat, moisture and momentum. One scheme uses a first-order eddy diffusi vity formulation for stable and neutral

environments and a modified first-order sche me 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.

62 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Initial and lateral boundary condi tions are specified for real -data cases from mesoscale three-dimensional analyses performed at 12- hour intervals on the outermost grid mesh selected by the user. Surface fields are analyzed at three- hour intervals. A Cressmanbased 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 us ing a relaxation technique a pplied 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 th e Regional Atmospheric Modeli ng System (RAMS) and the Systems Application International Mesoscal e Model. The MM5 enjoys a far richer application history in regulator y modeling studies compared with RAMS or other models. Furthermore, in evaluations of these models in over 60 recent regional scale air quality application studies since 1995, it has generally been found th at the MM5 model tends to produce somewhat better photochemical m odel inputs than a lternative models.

The configuration used for this modeling de monstration, as well as a more detailed description of the MM5 model, can be found in Appendix G.

63 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.2.3 Selection of Emissions Processing System

3.2.3.1 Criteria

The principal criterion for an emissions proces sing 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 cr iterion 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 Sy stem 3 version 0.9 (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

3.2.3.2 Overview of SMOKE

The Sparse Matrix Operator Kernel Emissions (SMOKE) Modeling System was originally developed at the Mi cro-computing Center of Nort h 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 ex ception of mobile and biogenic sources, its purpose is to provide an effici ent, modern tool for convert ing 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 f actors and estimates of vehicle miles traveled.

SMOKE was originally designed to allow emi ssions data processing methods to utilize emergent high-performance-computing as app lied to sparse-matrix algorithms. Indeed, SMOKE is the fastest emissions processing to ol currently available to the air quality modeling community. The sparse matrix a pproach utilized throughout SMOKE permits both rapid and flexible proces sing of emissions data. The processing is rapid because

SMOKE utilizes a series of matr ix calculations instead of less efficient algorithms used in previous systems. The processing is flexib le because the processing steps of temporal

64 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

projection, controls, chemical speciation, temporal allocation , and spatial allocation have been separated into independent operations wh erever possible. The results from these steps are merged together at a final stage of processing.

SMOKE contains a number of ma jor features that make it an attractive component of the modeling system. The model supports a variet y of input formats from other emissions processing systems and models. It supports both gridded and county total land use scheme for biogenic emissions modeling. SMOKE can accommodate emissions files from up to 10 countries and any pollutant can be processed by the system.

For additional information about the SM OKE model please refer to Appendix G.

3.3 Selection of the Base 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 ch anges in air quality in response to changes in emissions. The USEPA’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 criteria to consider when selecting one or more episodes for modeli ng attainment with air quality standards. The USEPA recommends that episode selecti on derive from four principal criteria:

• Simulate a variety of me teorological conditions

• Model time periods in which observed con centrations are close to the appropriate baseline design value or visibility impairment

• Model periods for which extensive air quality/meteorological databases exist

• Model a sufficient number of days so that the modeled a ttainment 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 pref erable, representative modeling year. 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 releva nt to the evaluation of candidate annual modeling episodes.

• Initial Episode Typing: At the time of selection in 2003, meteorological and air quality data were available for 2002 for model inputs and model performance

evaluation. VISTAS used Cl assification and Regression Tree (CART) analyses to evaluate the candidate modeling year s. The year 2002 was found to be representative of conditions in the other years. Subse quently, 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

65 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

baseline period. This analysis confirmed that visibility and PM 2.5 concentrations in 2002 were representative of the five-yea r baseline period. This analysis is

discussed in more detail in th e project report in Appendix D.

• Data Availability: In parallel with the CART analysis, episode characterization analyses, collaborative investigations by VISTAS states (e.g., NCDAQ, GA EPD, FL DEP) intensively studied the availability of PM 2.5 , meteorological, and emissions data and representativeness of alternative baseline modeling periods from a regulatory standpoint. Additiona lly, because 2002 was the year that the USEPA was requiring 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 a dvantage of the 2002 inventory.

• Years to be used by other RPOs: VISTAS also considered what years other RPOs would be modeling, and several had alr eady 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 (1 January through 31 December) as the most current, representative, and pragmatic choice for modeling. All of the USEPA 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 USEPA or the states to the modeling teams).

3.4 Modeling Domains

3.4.1 Horizontal Modeling Domain

The CMAQ model was run in one-way nested gr id mode. This allowed the larger outer

domains to feed concentration data to the inner nested domain. Th e horizontal coarse grid modeling domain boundaries were determined through a national ef fort 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, su ch as ozone and fine particulate matter nonattainment areas. Pro cessing time was also a factor in choosing a smaller 12-km grid modeling domain.

The coarse 36-km horizontal grid do main covers the continental United States. This domain was used as the outer grid doma in for MM5 modeling with the CMAQ domain nested within the MM5 domain. Figure 3- 1 shows the MM5 horizontal domain as the outermost, blue grid with the CMAQ 36-km domain nested in the MM5 domain.

66 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Figure 3-1. The MM5 and CMAQ 36-km Horizontal Domains

To achieve finer spatial resolution in th e VISTAS states, a one-way nested high resolution (12-km grid resolution) was use d. Figure 3-2 shows the 12-km grid modeling domain for the VISTAS region. This is the modeling domain on which the attainment

test results are based.

Figure 3-2. VISTAS 12-km Modeling Domain

67 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.4.2 Vertical Modeling Domain

The vertical grid used in the MM5 mode ling primarily defines the CMAQ vertical structure. The MM5 model employed a terra in-following coordinate system defined by pressure, using 34 layers that extend from th e surface to the 100 mb. Table 3-1 lists the layer definitions for both MM5 and for CMAQ. A layer-averaging scheme was used to generate 19 vertical layers for CMAQ to reduce the computational cost of the CMAQ simulations. The effects of layer averagi ng were evaluated in conjunction with the modeling effort and were found to have a relatively minor effect on the model performance metrics when both the 34-la yer and a 19-layer CMAQ models were compared to ambient monitoring data.

68 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 3-1. Vertical Layer Definition For MM5 and CMAQ

MM5 Simulation CMAQ 19 Layers
Layer Sigma Pressure (mb) Height (m) Depth (m) Layer Sigma Pressure (mb) Height (m) Depth (m)

34 0.000 100 14662 1841 19 0.000 100 14662 6536

33 0.050 145 12822 1466 0.050 145

32 0.100 190 11356 1228 0.100 190

31 0.150 235 10127 1062 0.150 235

30 0.200 280 9066 939 0.200 280

29 0.250 325 8127 843 18 0.250 325 8127 2966

28 0.300 370 7284 767 0.300 370

27 0.350 415 6517 704 0.350 415

26 0.400 460 5812 652 0.400 460

25 0.450 505 5160 607 17 0.450 505 5160 1712

24 0.500 550 4553 569 0.500 550

23 0.550 595 3984 536 0.550 595

22 0.600 640 3448 506 16 0.600 640 3448 986

21 0.650 685 2942 480 0.650 685

20 0.700 730 2462 367 15 0.700 730 2462 633

19 0.740 766 2095 266 0.740 766

18 0.770 793 1828 259 14 0.770 793 1828 428

17 0.800 820 1569 169 0.800 820

16 0.820 838 1400 166 13 0.820 838 1400 329

15 0.840 856 1235 163 0.840 856

14 0.860 874 1071 160 12 0.860 874 1071 160

13 0.880 892 911 158 11 0.880 892 911 158

12 0.900 910 753 78 10 0.900 910 753 155

11 0.910 919 675 77 0.910 919

10 0.920 928 598 77 9 0.920 928 598 153

9 0.930 937 521 76 0.930 937

8 0.940 946 445 76 8 0.940 946 445 76

7 0.950 955 369 75 7 0.950 955 369 75

6 0.960 964 294 74 6 0.960 964 294 74

5 0.970 973 220 74 5 0.970 973 220 74

4 0.980 982 146 37 4 0.980 982 146 37

3 0.985 986.5 109 37 3 0.985 986.5 109 37

2 0.990 991 73 36 2 0.990 991 73 36

1 0.995 995.5 36 36 1 0.995 995.5 36 36

0 1.000 1000 0 0 0 1.000 1000 0 0

69 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.5 Baseline Emissions Inventory

The CAA Amendments revised many of the provi sions of the CAA related to attainment of the NAAQS and the protection of visibility in mandatory Federal Class I areas (certain national parks and wilderness areas). These revisions established new emission inventory requirements applicable to certain areas th at were designated nona ttainment for certain pollutants. In the case of particulate matter, the emission inventory provisions are in the general provisions under Section 172(c)(3). An inventory was developed for the baseline year 2002 and projected to 2009. The pollutants inventorie d include volatile organic compounds (VOC), NOx, PM 2.5 , coarse particulate (PM 10 ), ammonia (NH 3 ) and SO 2

. Tables 3-2 and 3-3 show the typical annual em issions from the various source sectors for the Floyd County PM 2.5 nonattainment area for 2002 and 2009. The baseline emissions inventory for 2002 was developed for Geor gia following the methods described in Appendix H. The 2002 BaseG2 and the 2009 Base G4 emission inventories are the latest emission inventories developed by VI STAS for 2002 and 2009, respectively.

70 of 148Attainment Demo Methods and InputsPM2.5 Attainment SIP - Floyd County, GATable 3-2. Typical 2002 BaseG2 Annual EmissionSummary for Floyd County and State of GeorgiaAreaSourceTypeEmissions(tons)VOCNOxSO2PM-10PM-2.5NH3point1835.313,053.335,245.11080.9651.016.8non-road808.21100.681.264.860.90.5area4565.0622.1979.57823.31378.5575.5mobile3730.93058.7128.170.049.4106.4biogenic16,562.4113.2NANANANAFloyd Co.total27,501.817,947.936,433.99,039.02,139.8699.2point34,964.4197,376.8571,410.933,077.322,531.63699.2non-road85,965.497,961.49005.48617.98226.460.4area333,044.849,987.460,370.2757,656.1159,437.883,066.0mobile283,420.6307,731.712,183.57245.95167.810,546.2biogenic1,972,795.424,159.2NANANANAStatetotal2,710,191.0677,216.5652,970.0806,597.2195,363.697,371.871 of 148Attainment Demo Methods and InputsPM2.5 Attainment SIP - Floyd County, GATable 3-3. 2009 BaseG4 Annual Emission Summary for Floyd County and State of GeorgiaAreaSourceTypeEmissions(tons)VOCNOxSO2PM-10PM-2.5NH3point1880.310859.46864.31858.01104.50.0non-road732.1927.513.555.652.10.6Floyd Co.4235.5647.9area981.88763.41463.1631.4mobile2592.92175.715.559.237.1127.7biogenic16,562.4113.2NANANANAtotal26,003.214,723.77875.110,736.22,656.8759.7point36,430.1148,849.7462,666.540,993.629,889.74648.8non-road67,686.185,732.92724.77521.17174.667.5area306,337.351,925.060,604.0840,244.9169,011.491,439.1mobile195,125.2209,349.21585.06072.03840.112,686.9biogenic1,972,795.424,159.2NANANANAStatetotal2,578,374.0520,016.0527,580.2894,831.6209,915.8108,842.372 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

There are five different emission inventory source classifications: stationary point and area sources, off-road and on-road mobile sources, and biogenic sources.

Stationary point sources are those sources th at emit greater than a specified tonnage per year, with data provided at the facility leve l. Electric generating utilities and industrial sources are the major categories for stationary point sources. Stationary area sources are

those sources whose individual emissions ar e relatively small, but due to the large number of these sources, the collective em issions from the source category could be significant (i.e., dry cleaners, se rvice stations, agricultural sour ces, fire emissions, etc.). These types of emissions are es timated on a countywide level.

Non-road (or off-road) mobile sources are equipment that can move but do not use the roadways, i.e., lawn mowers, construction equi pment, railroad locomotives, aircraft, etc. The emissions from these sources, like st ationary area sources, are estimated on a countywide level. On-road mobile sources are automobiles, buses, trucks, and motorcycles that use the roadway system. The emissions from these sources are estimated by vehicle type and road type, an d are summed to the countywide level. Biogenic sources are the natural sources like trees, crops, grasses an d natural decay of plants. The emissions from these sour ces are estimated on a countywide level.

In addition to the various sour ce classifications, there are al so various types of emission inventories. The first is the actual base year inventory. This invent ory is the base year emissions that correspond to the meteorological data used, which for this modeling effort

is data from 2002. These emissions are us ed for evaluating the air quality model performance. The second type of inventory is the typical base year inventory. This inventory is similar to the actual base y ear inventory, except that for sources whose emissions change significantly from year to ye ar, a more typical emission value is used. In this modeling effort, typical emissions were developed for the elec tric generating units (EGUs) and the fire emissions. The air quality modeling runs using th e typical base year inventory are used to calcu late relative response factor s used in the attainment

demonstration test.

The future year base inventory is an invent ory developed for some future year for which attainment of the air quality st andard is needed. Fo r this modeling project, the future year inventory will be 2009, the last co mplete year for which the sta ndard must be attained. It is for the future base year inventory that sens itivities will be evalua ted to determine what additional controls beyond those control meas ures already included in the future year base inventory will need to be implemen ted to attain and maintain the annual PM 2.5 standard.

In the sections that follow, a synopsis of the inventories used for each source

classification is discussed. The detailed discussions of the emissions inventory development can be found in Appendix H and emission summaries by county for the Floyd County nonattainment area, and for all ot her counties in Georgia, are in Appendix

I. Below is an overview of the invent ories used for each source classification.

73 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.5.1 Stationary Point Sources

Point source emissions are emissions from individual sources having a fixed location. Generally, these sources must have permits to operate, and their emissions are inventoried on a regular schedule. Large sour ces emitting at least 100 tons per year (tpy) of a criteria pollutant are inventoried annually. Smalle r sources have been inventoried less frequently. The point source emissions data can be grouped as EGU sources and other industrial point sources, also called non-electric generating units (non-EGUs). Appendix H documents the point source modeli ng inventory development in more detail.

3.5.1.1 Electric Generating Units

The actual base year inventory for the EGU sources used 2002 continuous emissions monitoring (CEM) data reported to the US EPA’s Acid Rain program or 2002 hourly emissions data provided by stakeholders. These data provide hourly emissions profiles

for SO 2 and NOx that can be used in air quality modeling. Emissions profiles are used to estimate emissions of other pollu tants (VOC, carbon monoxide, NH 4 , PM 2.5 , soil) based

on measured emissions of SO 2 and NOx.

Emissions from EGU vary daily and seasonally as a function of variability in energy demand and utilization and outage schedules. Since emission from EGUs represents a significant portion of the emission inventory, a typical base year emissions inventory was developed to avoid anomalies in future year emissions due to vari ability in meteorology, economic and outage factors in 2002. This appr oach is consistent with the Attainment Modeling Guidance. To develop a typica l year 2002 emissions inventory for EGU sources, each unit’s average CEM heat input for 2000 through 2004 was divided by the 2002 actual heat input to generate a unit-sp ecific normalizing factor. This normalizing factor was then multiplied by the 2002 actual emissions. The heat inputs for the period 2000 through 2004 were used because the modeling current design values use monitored data from this same 5-year period. If a unit was shut down for an entire year during the 2000 through 2004 period, the average of the ye ars the unit was operatio nal was used. If a unit was shut down in 2002, but not permanen tly shut down, the emissions and heat inputs from 2001 (or 2000) were used in the normalizing calculations. Table 3-4 shows emissions used in modeling from Georgia EGUs for 2002 and 2009.

As part of the air quality modeling, VISTAS, in cooperation with the other eastern RPOs, contracted with ICF Resources, L.L.C., to ge nerate future year emission inventories for the electric generating sector of the contiguous United St ates using the Integrated Planning Model (IPM). IPM is a dynamic linear optimization model th at can be used to examine air pollution control policies for various pollutant s 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 leas t-cost means of meeting electric generation and capacity requirements while complying with specified cons traints including air pollution regulations, transmission bottlenecks, and plant-specific operational constraints. The versatility of IPM allows users to speci fy which constraints to exercise, and to

74 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

populate IPM with their own datasets. The IPM modeling runs took into consideration both The Clean Air Interstate Rule (CAIR) implementation and Georgia’s Multi-pollutant Rule requirements for Georgia Power.

Table 3-4. 2002 and 2009 Georgia EGU Emissions

Facility Unit 2002

NOx (tons) 2002

SO2 (tons) 2002

PM10 (tons) 2002

PM2.5 (tons) 2009

NOx (tons) 2009

SO2 (tons) 2009

PM10 (tons) 2009

PM2.5 (tons)

SG01 5557 33050 422 183 1944 39036 542 323

SG02 6171 35266 1095 474 1958 39310 1338 797

SG03 12114 42900 1666 721 2484 2469 2034 1212 Georgia Power

–Plant Bowen

SG04 12022 42634 1936 838 2621 2534 2412 1438

SG01 5705 10387 171 74 5131 11901 162 83

SG02 4534 13941 228 99 4476 14408 195 100

SG03 7296 21211 776 336 7055 22293 1221 623 Georgia Power

– Plant Branch

SG04 7762 22342 825 357 6900 21802 1194 610

SG01 1788 3933 139 60 1759 259 394 201

SG02 1917 4092 149 64 1769 260 396 202

SG03 1930 4262 150 65 1751 257 391 200 Georgia Power

– Plant

Hammond

SG04 3488 18089 147 64 1387 1082 200 102

SGM1 2442 13802 165 73 2127 11134 323 192 Georgia Power

– Plant McDonough SGM2 2346 13631 161 70 2191 11469 333 198

SG01 7999 25286 201 87 4758 26264 256 153

SG02 7344 24966 235 102 4724 26075 297 177

SG03 4669 18149 38 16 5024 27735 16 5 Georgia Power

– Plant

Scherer

SG04 8529 20771 153 66 4822 26616 56 18

SG01 10960 38741 445 193 2430 1890 1566 933 Georgia Power

– Plant Wansley SG02 9800 36421 665 288 2342 37848 889 530

SG01 973 233 22 10 1414 663 42 25

SG02 1059 3991 249 108 1415 5938 182 108

SG03 874 3237 206 89 1562 6556 201 119

SG04 1175 4842 111 48 1559 6256 230 137

SG05 1214 5009 114 50 1593 6394 236 141

SG06 2469 15175 51 23 3010 15753 149 89 Georgia Power

– Plant Yates

SG07 2297 14024 34 16 3040 15910 594 354

3.5.1.2 Other Industrial Point Sources

For the non-EGU sources, the same inventory is used for both the actual and typical base year emissions inventories. The non-EGU cat egory uses annual emissions as reported under the CERR for the year 2002. These emissi ons are temporally allocated to month, day, and hour using source category code (SCC)-based allocation factors.

75 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

The general approach for assembling future y ear data was to use recently updated growth and control data consistent with the USEPA’s CAIR analyses. This data was supplemented with state-specific growth factors and stakeholder input on growth assumptions.

3.5.2 Stationary Area Sources

Stationary area sources are sources whose indi vidual emissions are relatively small, but due to the large number of these sources, th e collective emissions could be significant (i.e., 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 house holds, or population. St ationary area source

emissions are estimated at the countywide level.

A portion of the area source 2002 base year in ventory for Georgia was developed by the GA EPD and provided to the VISTAS/ASIP co ntractor. The VISTAS/ASIP contractor calculated the remaining portion of the area so urce inventory. The sources estimated by

the contractor include emissions from anim al husbandry, wildland fires, and particulate matter from paved and unpaved roads. For the other states within the modeling domain, either state-supplied data or data reported under CERR for 2002 was used.

The actual base year inventory will serve as th e typical base year inventory for all area source categories except for wildland fires. Fo r wildland fires, a typical year inventory

was used to avoid anomalies in wildfire activity in 2002 compar ed 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 remain the same for air quality modeling in both the base and any future years. The VISTAS Fire Special Interest Work Group used State records to ratio the number of acres burned over a longer term period (three or more years, as available from stat e records) to 2002. Based on these ratios, the 2002 acreage was then scaled up or down to develop a typical year inventory.

For categories other than wild land fires, the VISTAS/ASIP cont ractor generated the future base year emissions inventory used in the attainment demonstration modeling. Growth factors supplied from the states or the USEPA’s CAIR emission projections were applied to project the controlled emissions to the appropriate year. In some cases, the U.S. EPA’s Economic Growth and Analysis Sy stem Version 5 growth factors were used if no growth factor was available from either th e states or the CAIR growth factor files. Table 3-5 shows the top five categories of area source emissions in Floyd County. Appendix H provides a more detailed di scussion of the area source inventory.

76 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

Table 3-5. 2002 and 2009 Floyd County Area Source Emissions of Particulate Matter

TIER 1 Name

Area Source 2002

PM10 (tons) 2002

PM2.5 (tons) 2009

PM10 (tons) 2009

PM2.5 (tons)

Fuel Combustion Industrial 137 88 138 89

Fuel Combustion Other 202 202 167 167

Other Industrial Processes 197 46 229 55 Waste Disposal and Recycling 126 112 145 129

Miscellaneous 6947 743 7870 837

Total 7609 1192 8549 1277

77 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

3.5.3 Off-Road Mobile Sources

Off-road (or non-road) mobile sources are eq uipment that can move but do not use the roadways, such as construction equipment, aircraft, railroad locomotives, lawn and garden equipment, etc. For the majority of the non-road mobile sources, the emissions for 2002 were estimated using the USEPA’ s NONROAD2005c model. For the three source categories not included in the NONROAD model, i.e., aircraft engines, railroad locomotives, and commercial marine, more traditional methods of estimating the emissions were used. The same inventory is used for both the actual and typical base year emissions inventories.

For the source categories estimated usi ng the USEPA’s NONROAD model, the model growth assumptions were used to create the 2009 future year inventory. The NONROAD

model takes into considera tion regulations affecting emissions from these source categories. For the commercial marine, railroad locomotives and airport emissions, the VISTAS/ASIP contractor calculated the future growth in emissions using detailed inventory data (both before and after controls) for 1996 and 2010, obtained from the CAIR Technical Support Document. When ava ilable, state-specific growth factors were used. Appendix H provides a detailed di scussion of the nonroad mobile source inventory.

3.5.4 Highway Mobile Sources

For onroad vehicles, the newe st version of the MOBILE m odel, MOBILE6.2, was used. Key inputs for MOBILE include information on the age of ve hicles on the roads, the average speeds on the roads, the mix of vehicles on the roads, any programs in place in

an area to reduce emissions for motor vehicl es (such as emissions inspection programs), and temperature.

The MOBILE model takes into consideration regul ations that affect emissions from this

source sector. The same MOBILE run is used to represent the actual and typical year emissions for onroad vehicles using input da ta reflective of 2002. The MOBILE model is then run for the 2009 inventory using input data reflective of that year. The 2002 vehicle miles traveled (VMT) estimates were obt ained from the Georgia Department of Transportation (GDOT). The VMT for 2009 we re projected by the VISTAS contractors based on linear growth as derived from th e VMT data assembled by the U.S. EPA for their most recent heavy-duty diesel rulemaking. For a detailed discussion about the mobile source inventory development used in the attainment demonstration modeling, please refer to Appendix H. For details on th e mobile source emissions modeling used to

calculate the motor vehicle emissions budget, see Section 8 and Appendix J.

3.5.5 Biogenic Emission Sources

Biogenic emissions were prepared with the SMOKE-BEIS3 (Biogenic Emission Inventory System 3 version 0.9) preprocessor. SMOKE-BEIS3 is a modified version of

78 of 148Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA

the Urban Airshed Model (UAM)-BEIS3 mode l. Modifications include use of MM5 data, gridded land use data, and improved emissions char acterization. The emission

factors that are used in SMOKE-BEIS3 are th e same as the emission factors as in UAMBEIS3. The basis for the gridded land use data used by BEIS3 is the county land use data in the Biogenic Emissions Landcover Data base version 3 (BELD 3) provided by the USEPA. A separate land cl assification scheme, based up on satellite (AVHRR, 1 km spatial resolution) and census information ai ded in defining the forest, agriculture, and urban portions of each county.

79 of 148Model Performance Evaluation PM 2.5 Attainment SIP – Floyd County, GA

Section 4. Model Performance Evaluation

There are many aspects of model performance. This section will focus primarily on the methods and techniques recommended by the US EPA for evaluating the performance of the air quality model. Before th e air quality model can be fully evaluated, the meteorological modeling performance is needed to understand potential biases and errors that may be passed from the meteorological model direct ly into the air quality model. A complete discussion of the meteorological and air quality model performance evaluations for VISTAS, Georgia, and Floyd County can be found in Appendix K.

4.1 Meteorological Model Performance

Generally speaking, the meteorological modelin g performance was quite good at both the 36- km and 12-km grid resolutions. Synoptic featur es were routinely accurately predicted and the meteorological model showed considerable sk ill in replicating the state variables (e.g. temperature, mixing ratio, relative humidity, wind speed and direction, cloud cover, and precipitation). The meteorologi cal modeling performance statistics fell within expected and acceptable ranges of error during the majority of the 2002 modeled year.

The meteorological modeling perf ormance for Georgia was very similar to the performance for the VISTAS/ASIP region for the 12-k m modeling domain. Again, large-scale meteorological patterns were ac curately predicted. The meteor ological model demonstrated

substantial skills thro ughout the entire year and was especially skillful during the summertime season from May through September.

U.S. EPA guidance (EPA, 2007) recognizes the complexity a nd importance of evaluating meteorological modeling results for air quality appl ications. Since MM5 algorithms and modules have undergone si gnificant peer review and testin g, an “operational” evaluation of the modeling system is sufficient to serve as the basis of evaluating if the system is operating with sufficient reliability to be used in support of SIP development. An operational evaluation can be defined as the process of evaluating how accurately a modeling simulation estimates observed quan tities. In the case of a prognostic meteorologi cal model, this amounts to a statistical analysis of model predictions and surface observations.

GA EPD used the software package METSTAT developed by ENVIRON corporation for calculating model performance statistics. METSTAT computes domain wide surface statistics for temperature, wind speed and direction, and humidity. The metrics include: Bias Error (B), Gross Error (E) and Root Mean S quare Error (RMSE), Systematic Root Mean Square Error (RMSE

s ), Unsystematic Root Mean Square Error (RMSE

u ) and Index Of Agreement (IOA). Mathematical formulation of these variables is provided in Table 4-1. The surface meteorological data for this analysis was obtained from the CISL Research Data Archive ( http://dss.ucar.edu/datasets/ds472.0 ).

While reviewing statistics, the reader is cautioned that summary statistics are useful in making only a general assessment about the adequacy of meteorological fields. For example, daily-mean performance statistics are likely to conceal important hour-to-hour variations. Also, the credibility of summary statistics de pend upon the number of observation-prediction pairs and generally improve with larger sampling sizes and longer averaging periods. This is because the sensitivity of these summary statistics to extreme values is high in case of smaller sample sizes. These and other concerns have lead U.S. EPA to recommend that benchmarks proposed in Table 4-2 (Emery et al ., 2001) should not be used in a “pass/fail” test for a model, but only as a means of assessing gene ral confidence in meteor ological model output.

80 of 148Model Performance Evaluation PM 2.5 Attainment SIP – Floyd County, GA

A graphical summary of the daily and hourly me an performance statistic s for the 12-km grid resolution modeling simulation is provided in Appendix K.2. Monthly averaged statistics have also been provided in Figure 4-1 and Tabl e 4-3. Statistics have been computed at monitoring stations that are located in and around Georgia.

Table 4-1: Mathematical Formulation of Statistical Metrics Used for Evaluating Mesoscale Meteorological Model Performance

Metrics Formulation

Bias 

# ( ) ∑∑

= = − = J

j I

i i j i j OP IJ B

1 1 1

Gross Error 

## ∑∑

= = − = J

j I

i i j i j OP IJ E

1 1 1

Root Mean Square Error 

# ( ) 2/1

1 1 2 1 ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

− = 

## ∑∑

= = J

j I

i i j i j OP IJ RMSE

Systematic Root Mean Square Error 

# ( ) 2/1

1 1 2 ˆ 1 ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

− = 

## ∑∑

= = J

j I

i i j i j S OP IJ RMSE

Unsystematic Root Mean Square Error 

# ( ) 2/1

1 1 2 ˆ 1 ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

− = 

## ∑∑

= = J

j I

i i j i j u PP IJ RMSE

Index of Agreement ⎥ ⎥ ⎥ ⎥

⎦ ⎤

⎢ ⎢ ⎢ ⎢

⎣ ⎡

−+− −= 

## ∑∑

= = J

j I

i o i jo i j MOMP

RMSEIJ IOA

1 1 2

. 1

Table 4-2: Statistical Benchmarks fo r Mesoscale Meteorological Models

Statistical Measure Benchmark Wind Speed Bias (m/s) < ± 0.5 Wind Speed Total RMSE (m/s) 2.0 Wind Speed Index of Agreement 0.6 Wind Direction Gross Error (degree) 30.0 Wind Direction Bias (degree) < ± 10.0 Temperature Bias (Kelvin) < ± 0.5 Temperature Gross Error (degree) 2.0 Temperature Index of Agreement 0.8 Humidity Bias (g/kg) < ± 1.0 Humidity Gross Error (g/kg) 2.0 Humidity Index of Agreement 0.6

81 of 148Model Performance Evaluation PM 2.5 Attainment SIP – Floyd County, GA

Monthly Average Temperature Bias

-0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40 0.60

J

anuar y

F ebur a r y March A pril May June J u ly August September October November

D

e cem berBias (degree K)

Monthly Average Humidity Bias

-1.00 -0.80 -0.60 -0.40 -0.20 0.00 0.20 0.40

January

Fe

bura r y Ma r c h Apr i l M ay June J u l y August Septe m

ber Oc t ober Novembe r DecemberBias (g/kg)

Figure 4-1: Monthly average d Bias statistics for 2-m temperature and humidity

82 of 148Model Performance EvaluationPM2.5 Attainment SIP – Floyd County, GATable 4-3: Monthly averaged statisticsfor the region of the 12-km modeling domain in and around Georgia.83 of 148Model Performance Evaluation PM 2.5 Attainment SIP – Floyd County, GA

The MM5 simulation is able to capture mete orological conditions observed during the study period with an adequate level of accuracy. Pe rformance statistics for most days are within the benchmarks proposed by Emery (2001). Monthly average statistics rev eal under prediction in humidity from May through November, and an over prediction in temperature during the summer months (May through September). The si mulation tends to over predict daytime and nighttime temperature, and consistently over-predicts nighttime wind speed. However, the magnitude of these under/over predictions remains sm all. It should also be pointed out that air quality model performance evaluation serves as an additional check on how accurately the meteorological model was able to capture the observed atmosphe ric dynamics during a particular time period. In an unlikely event of unusuall y poor air quality model performance, it is reasonable to further investigate the pe rformance of meteorological model.

Overall, the GA EPD believes that the meteorological model performance is adequate for this modeling exercise and should produce credible inputs for the air quality modeling for the attainment demonstration for the Floyd County PM 2.5 nonattainment area.

4.2 Air Quality Model Performance

The air quality model evaluation mostly focused on the FRM and STN monitors across the state of Georgia, due to the nature of the attainment test. Designations we re based on FRM monitors, and calculations of future design values are based on current design value information from these sites. Thus, model performance for these FRM si tes should be evaluate d. STN data was also utilized as this data is used to speciate th e FRM data so component based relative response

factors can be calculated for each FRM monitoring site. More detailed information on the attainment test process is describe d in Section 6.1 and Appendix G.

Only a brief summary of the model performanc e evaluation for the VISTAS/ASIP 12-km grid

domain will be discussed in the subsections to follow. For the full model performance evaluation for the 12-km grid domai n, please refer to Appendix K.3.

4.2.1 Modeling Performance Goals and Criteria

In 2004, VISTAS/ASIP established model performa nce “goal levels” and “criteria levels” for components of fine particle mass (Table 4-4) based on previous model performance for ozone and fine particles. The Attainment Modeling Gu idance (EPA, 2007) for fine particulate matter at the time noted that PM models might not be able to achieve the same level of performance as

ozone models. VISTAS’ evaluation considered several statistical performance measures and graphical performance measures. Fractional bias and mean fractional error were selected as the most appropriate metrics to summarize model performance (Boylan and Russell, 2006); other

metrics were also calculated and ar e included for FRM and STN monitors.

84 of 148Model Performance Evaluation PM 2.5 Attainment SIP – Floyd County, GA

Table 4-4. Established Model Performance Go als and Criteria for thePM2.5 Component Species

Mean Fractional

Bias Mean Fractional

Error Comment

< 15 percent < 35 percent Goal for PM 2.5 model performance based on ozone model performance, considered “excellent performance”

< 30 percent < 50 percent Goal for PM 2.5 model performance, considered good performance; hereafter, it is called “(performance) goal level”

< 60 percent < 75 percent Criteria for PM 2.5 model performance, considered average performance; hereafter, it is called “(performance) criteria level”. Exceeding this level of performance indicates fundamental concerns with the modeling system and trigge rs diagnostic evaluation.

The statistical measures were calculated for all of the component species of particulate matter. For convenience, these statistical measures or metrics, along with a variety of additional statistical measures, are summarized in Table 4-5.

An additional way to evaluate model performance statistics is to visua lize performance based on

these fractional bias and mean fractional errors via “soccer plots” (e .g. Figure 4-2) and “bugle plots” (Figure 4-3). The soccer plot is so name d because the dotted lines resemble a soccer goal. The soccer plot is useful as both bias and erro r are shown on a single plot. As bias and error approach zero, the points are plot ted closer to or within the “performance criteria level”, the “performance goal level”, and/or the “excellent performance level”, represented here by the

dashed boxes.

The bugle plot, named for the shape formed by the criteria and goal lines. The bugle plots are shaped as such because the goal and criteri a lines are adjusted based on the average concentration of the observed species concentra tions and the modeled species concentrations. As the average concentration becomes smaller, the criteria and goal lines become larger to adjust for the model’s poor ability to predict at low concentrations and for the over-sensitivity of

normalized statistical measures to low concentration cases.

The analysis of bugle plots dem onstrated that greater emphasis should be placed on performance of those components with the greatest contribution to PM 2.5 mass (e.g. SO 4 and OC) and that greater bias and error could be accepted for com ponents with smaller contributions to total PM 2.5 mass (e.g. EC, NO 3 , and SOIL). The soccer plots and bugle plots have been included as suggested in the Attain ment Modeling Guidance.

85 of 148Model Performance Evaluation PM 2.5 Attainment SIP – Floyd County, GA

Table 4-5 Statistical Metric Calculations

Statistical Measure Shorthand

Notation Mathematical Expression Notes

Accuracy of Paired

Peak A p

peak peak
O OP

−

Coefficient of

Determination R 2



# ( ) 

# ( )

∑ ∑ ∑

= = =



### − − ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

−−

N

i N

i i i N

i i i



### OOPP OOPP

1 1 2 2 2

1



### )()( P i = prediction at time and location i;

O i = observation at time and location i;

P = arithmetic average of P i , i = 1, 2, . . ., N;

O = arithmetic average of O i , i = 1, 2, . . ., N;

Normalized Mean

Error NME



## ∑ ∑

=

= −

N

i i N

i ii

O OP

1 1 Reported as %

Root Mean Square

Error RMSE 

## ( ) 2 1

1 2 1 ⎥ ⎦ ⎤ ⎢ ⎣ ⎡

− 

## ∑

= N

i ii OP N Reported as %

Mean Fractional

Error MFE 

## ∑

= + − N

i ii ii OP OP

N 1 2 Reported as %

Mean Absolute

Gross Error MAGE 

# ∑

= − N

i ii OP N 1 1

Mean Normalized

Gross Error MNGE 

# ∑

= − N

i i ii

O OP

N 1 1 Reported as %

Mean Biased MB 

## ( ) 

# ∑

= − N

i ii OP N 1 1 Reported as concentration

Mean Normalized

Bias MNB 

## ( ) 

## ∑

= − N

i i ii

O OP

N 1 1 Reported as %

Mean

Fractionalized Bias (Fractional Bias) MFB 

## ∑

= ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛

+ − N

i ii ii OP OP

N 1 2 Reported as %

Normalized Mean

Bias NMB 

## ( )



# ∑ ∑

=

= −

N

i i N

i ii

O OP

1 1 Reported as %

Bias Factor BF 

## ∑

= ⎟ ⎟ ⎠ ⎞ ⎜ ⎜ ⎝ ⎛ N

i i i O P

N 1 1 Reported as BF:1 or 1:BF or in fractional notation (BF/1 or 1/BF)

86 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

4.2.2 Domain-Wide Model Performance

As a summary of model performance, soccer pl ots and bugle plots for the all of the VISTAS

STN and FRM monitors are included here. Plot s have been developed for the average monthly concentrations and the performance statistics for all of the PM 2.5 component species (SO 4 , NO 3 , NH 4 , OC, and EC) and reconstructed PM 2.5 total mass from the STN monitoring sites (Figures 4- 2 and 4-3), as well as the total FRM PM 2.5 mass (Figures 4-4 and 4-5).

The soccer plots for monthly average component performance for all the VISTAS/ASIP STN sites shows generally good model pe rformance for most species of PM 2.5 and total PM 2.5 . The exception is the prediction of NO 3 values, which most values fall outside the criteria level (Figure 4-2). There are a few months that the model’s performance falls in the criteria level, which is better seen in the zoomed view presen ted in the image on the right in Figure 4-2. However, when the very low concentration of NO 3 is taken into consideration, as presented in the bugle plots (Figures 4-3), NO 3 performance largely falls within the criteria and goal levels. One can still note a general te ndency for under prediction in NO 3 , and other species (e.g. OC) in left hand image in Figure 4-3, which leads to a slight under prediction in total reconstructed

PM 2.5

.

Monthly total PM 2.5 performance at all the VISTAS/ASIP FRM monitors largely falls within goal level thresholds, with only three months falling just outside goal le vel (Figure 4-4). Figure 4-5 suggests a slight negative bias in PM 2.5 prediction for most of the year, with mean fractional error values remaining within goal levels across the base year.

STN VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional BiasMean Fractional Error Sulfate

Nitrate

Ammon.

Organics

EC

PM2.5

Criteria

Goal STN VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

-75.0 -25.0 25.0 75.0

Fractional BiasMean Fractional Error Sulfate

Nitrate

Ammon.

Organics

EC

PM2.5

Criteria

Goal

Figure 4-2. VISTAS STN Soccer Plots The image on the left is a soccer plot depicting bo th 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 ar ea inside the criteria/goal lines. Each point represents a monthly value as compared to the model performan ce criteria (red box) and modeling performance goals (green box).

87 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

STN VISTAS Sites CMAQ 12km - 2002 Monthly

-200.0 -150.0 -100.0 -50.0

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Bias Sulfate

Nitrate

Ammon.

Organics

EC

PM2.5

(+) Criteria

(+) Goal

(-) Goal

(-) Criteria STN VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Error Sulfate

Nitrate

Ammon.

Organics

EC

PM2.5

Criteria

Goal

Figure 4-3. VISTAS STN Bugle Plots The image on the left is a bugle plot of the mean fra ction 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 compone nt species for all VISTAS STN monitoring sites. Each point represents a monthly mean fraction bias va lue as compared to the model performance criteria (red lines) and modeling performance goals (green lines).

FRM VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0

Fractional BiasMean Fractional Error

PM2.5

Criteria

Goal FRM VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

-75.0 -25.0 25.0 75.0

Fractional BiasMean Fractional Error

PM2.5

Criteria

Goal

Figure 4-4. VISTAS FRM Soccer Plots Soccer plots depicting both the mean fractional error and fractional bias for PM 2.5 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. E ach point represents a monthly value as compared to the model performance criteria (red box) a nd modeling performance goals (green box).

88 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

FRM VISTAS Sites CMAQ 12km - 2002 Monthly

-200.0 -150.0 -100.0 -50.0

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Bias

PM2.5

(+) Criteria

(+) Goal

(-) Goal

(-) Criteria FRM VISTAS Sites CMAQ 12km - 2002 Monthly

0.0 50.0 100.0 150.0 200.0

0.0 4.0 8.0 12.0 16.0 20.0 Average Concentration ( μ g/m 3 )Mean Fractional Error

PM2.5

Criteria

Goal

Figure 4-5. VISTAS FRM Bugle Plots The image on the left is a bugle plot of the mean fraction bias for particulate matter for all the VISTAS FRM Monitoring sites. The image on the right is a bugle plot of mean fraction error for

particulate matter for all the VISTAS FRM Monito ring sites. Each point represents a monthly mean fraction bias value as compared to the m odel performance criteria (red lines) and modeling performance goals (green lines).

The overall tendency of the model was that the model had some difficulties in predicting NO 3

. For example, the monthly average values tend to fall outside the criteria levels in the soccer plots. Part of this under prediction lies in the fact that NO 3 are generally found in low concentrations across the southeast, and the model usually has difficu lties representing any compound with low ambient conc entrations. The bugle plots are more encouraging with NO 3 performance, as these plots take into account for absolute concentrations of PM 2.5 components when evaluating performance. The bugle plots show all components and total PM 2.5 falling within criteria levels, if not goal levels, of model performance. The under predictions of NO 3 and OC account for the slight negative bias in the modeled PM 2.5 mass compared to the

measurements.

4.2.3 Model Performance within Georgia and in the Floyd County nonattainment area

Statistical metrics and performance plots were de veloped for the entire state of Georgia as well as the Floyd County nonattainment area. For GA, the primary monitoring networks available to evaluate the CMAQ modeling were: (1) EPA Federal Reference Method (FRM) PM 2.5 and PM 10 Mass Networks, (2) EPA Speciation Trends Network (STN) of PM 2.5 species, (3) Interagency Monitoring of Protected Visual Environments (IMPROVE), (4) Clean Air Status and Trends Network (CASTNET), and (5) Southeastern Aero sol Research and Characterization (SEARCH).

It should be noted that the ST N monitor here refers to the co mbination of the official STN monitors and the CSN (Chemical Speciation Ne twork) monitors. Table 4-6 and Figure 4-6 summarize the species data collected and loca tions of the monitoring sites for the FRM, IMPROVE, STN, CASTNET, and SEARCH monitoring networks used in this evaluation. The Floyd County nonattainment area contains one FRM monitor (13-115-0005) and a co-located STN monitor (13-115-0005).

89 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

Table 4-6. Ambient monitori ng data available in 2002.

Monitoring

Network Chemical Species Measured SAMPLING FREQUENCY;

DURATION

FRM Only total fine particulate mass (PM 2.5 ) Varies; 24 hr

IMPROVE Speciated PM 2.5 and PM 10 1 in 3 days; 24 hr

STN Speciated PM 2.5 Varies; Varies

CASTNET Speciated PM 2.5 and ozone Hourly, Weekly; 1 hr,

Week

SEARCH 24-hr PM 25 (FRM Mass, OC, BC, SO 4 , NO 3 , NH 4 , EC); 24-hr PM coarse (SO 4 , NO 3 , NH 4 , elements); Hourly PM 2.5 (Mass, SO 4 , NO 3 , NH 4 , EC, TC); and Hourly gases (O 3 , NO, NO 2 , NO y , HNO 3 , SO 2 , CO) Daily, Hourly

90 of 148Model Performance EvaluationPM2.5 Attainment SIP – Floyd County, GAFigure 4-6. FRM, STN, IMPROVE, CASTNET, NADP, and SEARCH monitoring sites located in and near the GA PM2.5nonattainment areas (left) and the Floyd County PM2.5nonattainment area (right).91 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

4.2.3.1 Model performance statistics

Model performance statistics were calculated coll ectively for the FRM monitors within Georgia, as well as individually for th e one FRM monitor in the Fl oyd County nonattainment area to demonstrate the model’s ability to replicate total PM 2.5 mass at these sites. In addition, the same approach was taken to conduct model performa nce evaluation for the STN monitors within Georgia and for the Rome STN site on PM 2.5 component species and total PM 2.5 basis for the entire base year. The statistic al measures selected were base d on the recomme ndations outlined

in section 18.4.1 of the USEPA’s Guidance On The Use Of Models And Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM 2.5 , and Regional Haze (“

Attainment Guidance ”).

4.2.3.1.1 Model Performance Statistics for the FRM Sites

To examine the overall model performance, th e annual model performa nce statistics were

estimated for all FRM sites in GA and the FRM s ite in the Floyd County nonattainment area. As shown in Table 4-7, the model’s performa nce at the FRM monitor in the Floyd County

nonattainment area is better than or comparable with that of the all FRM monitors in GA.

For more in-depth examinations, the model perfo rmance statistics are broken out by month at each of the FRM monitors in the Floyd County nonattainment area to see if there is any performance issue during the base y ear (Table 4-8). It was noted that the model had marginal (> 15 % or < -15 %) under-prediction in June and July. Thr oughout the year, errors were significantly larger in magnitude than the biases. It indicates most of biases are unsystematic. During the monthly performance evaluation, we found the model’s mean predictions were comparable to the mean observed concentrations . For example, the model predicted mean PM 2.5 concentration of 17.7 μ g/m 3 at 13-115-0005 in July and 20.9 μ g/m 3 was observed at the same monitor for the same period. In add ition, the model could replicate high PM 2.5 concentrations that were observed except March. More deta iled performance evaluation was conducted with graphical measures and the results are presented in Appendix K.3. Given the number of samples, however, these discrepancies may not be significant. In fact, other comparable statistics with less numbers of samples indicates the overall performance of model in the Floyd County nonattainment area can be equal or better than the model’s overall performance across GA.

92 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

Table 4-7. Annual model performance statistics for PM 2.5 at all FRM monitors in the State of Georgia and in the Floyd County nonattainment area.

Statistics GA 13-115-0005 MFB (%) -5.7 -0.7 MFE (%) 30.2 26.9

A p -0.1 -0.1 NMB (%) -2.7 -1.2 NME (%) 27.4 25.8 MNB (%) 4.5 6.0 MNGE (%) 32.9 29.2

MB -0.4 -0.2

MAGE 4.0 3.8

Geometric Mean Bias -0.1 0.0

Geometric Mean Error 0.3 0.3

RMSE 5.3 5.0

Max OBS 52.0 36.5

Max PRE 48.0 31.8

Mean Observations 14.5 14.8

Mean Predictions 14.1 14.6

Standard Deviation of

Observations 6.6 7.1

Standard Deviation of

Predictions 6.9 6.7

R 2 0.5 0.5

BF 1.0 1.1 Number of Samples 3166 108

93 of 148Model Performance EvaluationPM2.5 Attainment SIP – Floyd County, GATable 4-8. Monthly model performance statistics for PM2.5at 13-115-0005.StatisticsJanuaryFebruaryMarchAprilMayJuneJulyAugustSeptemberOctoberNovemberDecemberMFB (%)-0.73.39.1-3.8-10.6-17.4-20.3-7.411.712.712.65.1MFE (%)15.218.936.314.625.431.130.618.741.626.231.626.2Ap-0.20.20.9-0.1-0.1-0.1-0.1-0.20.00.30.00.1NMB (%)-3.18.615.7-3.9-11.3-14.1-16.2-10.68.718.915.27.4NME (%)16.517.843.915.325.927.226.917.329.932.228.527.3MNB (%)0.76.118.5-2.3-6.1-11.2-14.9-5.134.819.820.211.7MNGE (%)15.318.740.814.824.229.626.518.257.131.636.030.1MB-0.40.91.6-0.5-1.8-2.7-3.4-2.21.52.91.60.7MAGE2.31.84.41.84.15.15.63.65.25.03.02.7Geometric Mean Bias0.00.00.10.0-0.1-0.2-0.2-0.10.10.10.10.1Geometric Mean Error0.20.20.40.10.30.30.30.20.40.30.30.3RMSE2.72.35.72.35.26.06.84.55.96.93.53.3MaxOBS21.222.014.017.923.529.033.336.531.623.421.117.2MaxPRE17.227.227.116.620.725.428.627.931.830.620.818.5Mean Observations14.010.110.011.615.718.920.920.917.315.410.59.9Mean Predictions13.610.911.611.113.916.217.518.618.818.412.110.7Standard Deviation ofObservations5.45.23.63.95.96.85.78.110.25.44.84.3Standard Deviation ofPredictions3.87.06.83.74.76.36.55.08.68.55.15.3R20.70.90.30.70.30.40.20.80.60.40.60.6BF1.01.11.21.00.90.90.90.91.31.21.21.1Number of Samples5989101010910109994 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

4.2.3.1.2 Model Performance Statistics for STN Sites

The model performance was evaluated for partic ulate matter components measured at the all STN sites in GA and separately at the STN site in the Floyd County nonattainment area. Since detailed graphical performance evalua tion was conducted for all available PM 2.5 species, we briefly present annual summary statis tics for these speci es and total PM 2.5 here.

Sulfate and total PM 2.5 had negative bias and error at the GA STN monitors (Table 4-9). Nitrate was underestimated in GA as previously seen throughout the model performance evaluation for the entire VISTAS 12-km modeling domain. Howe ver, this is not a significant issue for the overall model performance because the contribution of NO 3 to the total PM 2.5 is relatively small in GA. Also, we saw under-predictions of OC c oncentrations in GA. This issue was closely examined in Appendix K.3. From Table 4-10, sim ilar tendencies can be seen at the STN monitor in the Floyd County nonattainment area. More detailed performa nce analyses with graphical measures can be found in the following sections.

95 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

Table 4-9. Annual model pe rformance statistics for PM 2.5 species and total PM 2.5 at all STN monitors in the State of Georgia.

Statistics SO 4 NO 3 NH 4 OC EC PM 2.5 MFB (%) -17.1 -68.2 12.0 -26.5 -2.4 -18.4 MFE (%) 34.3 110.6 42.1 42.7 46.6 34.2

A p -0.6 0.6 -0.5 0.1 0.0 -0.2 NMB (%) -13.7 9.4 8.9 -13.4 3.6 -14.9 NME (%) 31.5 95.5 41.5 35.0 42.4 29.4 MNB (%) -7.6 0.1 37.9 -11.3 28.2 -10.5 MNGE (%) 32.7 101.2 61.6 40.4 65.6 30.5

MB -0.7 0.1 0.1 -0.7 0.0 -2.3

MAGE 1.6 0.7 0.6 1.9 0.3 4.6

Geometric Mean Bias -0.2 -1.3 0.1 -0.3 0.0 -0.2

Geometric Mean Error 0.4 1.8 0.4 0.5 0.5 0.4

RMSE 2.6 1.1 0.8 2.4 0.4 5.9

Max OBS 39.9 5.0 10.7 13.6 3.5 40.9

Max PRE 15.9 7.8 5.2 14.7 3.4 32.5

Mean Observations 5.0 0.7 1.4 5.4 0.6 15.7

Mean Predictions 4.3 0.8 1.5 4.7 0.7 13.4

Standard Deviation of

Observations 3.3 0.6 0.9 2.1 0.5 7.0

Standard Deviation of

Predictions 2.8 1.3 0.8 3.1 0.6 6.6

R 2 0.5 0.3 0.4 0.4 0.6 0.5

BF 0.9 1.0 1.4 0.9 1.3 0.9 Number of Samples 400 400 400 316 316 395

96 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

Table 4-10. Annual model performance statistics for PM 2.5 at 13-115-0005.

Statistics SO 4 NO 3 NH 4 OC EC PM 2.5 MFB (%) -3.0 -68.1 12.3 -25.9 -19.4 -23.7 MFE (%) 36.3 117.2 43.4 50.0 55.3 35.6

A p 0.1 0.5 0.4 0.2 0.1 -0.1 NMB (%) -0.2 3.3 8.2 -14.0 -21.5 -20.4 NME (%) 34.5 103.6 41.0 39.4 48.2 30.3 MNB (%) 20.2 33.4 36.4 10.9 4.3 -16.3 MNGE (%) 51.8 139.7 61.7 66.8 60.6 30.6

MB 0.0 0.0 0.1 -0.8 -0.1 -3.7

MAGE 2.0 0.9 0.7 2.1 0.2 5.5

Geometric Mean Bias 0.0 -1.1 0.1 -0.3 -0.2 -0.2

Geometric Mean Error 0.4 1.7 0.4 0.5 0.6 0.4

RMSE 2.8 1.2 0.9 2.6 0.2 7.0

Max OBS 14.6 3.5 3.8 10.1 0.8 33.5

Max PRE 15.9 5.4 5.2 12.4 0.9 31.8

Mean Observations 5.8 0.8 1.6 5.4 0.4 18.3

Mean Predictions 5.8 0.9 1.8 4.7 0.3 14.6

Standard Deviation of

Observations 3.3 0.7 0.9 2.4 0.2 7.7

Standard Deviation of

Predictions 3.8 1.3 0.9 3.1 0.2 6.9

R 2 0.5 0.1 0.3 0.3 0.1 0.5

BF 1.2 1.3 1.3 1.1 1.0 0.8 Number of Samples 44 44 44 35 35 43

97 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

4.2.4 Summary of the performance e valuation of the CMAQ modeling

In general, the CMAQ modeling met the perf ormance “criteria level” for all major PM 2.5 constituents and the total PM 2.5 across the State of Georgia throughout the base year. As the first step of model performance evalua tion, GA EPD estimated several statistical

measures for all FRM monitors and all STN monitors within GA and in the Floyd County nonattainment area annually and monthly. Important findings from this statistical performance evaluation at the FRM monitors was the performance at the FRM monitor in the Floyd County nonattainment area was compar able to or better than the model’s performance at FRM monitors within GA. After examining the statistical performance measures, GA EPD found that the model’s performance is ge nerally adequate across GA and acceptable for the Floyd County nonattainment area.

Similar analyses were conducted for the STN monitors on total PM 2.5 and all of measured

PM 2.5 species. The most significant findings we re that (1) the model’s sulfate and PM 2.5 performance were quite good and (2) NO 3 and OMC were somewhat under predicted. In addition, the model’s performance at the STN monitor in the Floyd County

nonattainment area was similar to that of the STN monitors within GA.

During the graphical performance analyses, GA EPD examined a set of various graphical measures as a “package”. Each PM 2.5 species and total PM 2.5 concentrations were examined with these packages. Whenever da ta were available, each package included scatter plots for monitors within GA and in the Floyd County nonatta inment area, time series plot for the monitor in the Floyd Count y nonattainment area, ba r plots of fractional bias and fractional error for monitors within GA, bar plots of fractional bias and

fractional error for monitors in the Fl oyd County nonattainment area, bugle plots for monitors within GA, and soccer plots for mo nitors within GA. In addition, more graphical measures were examined if necessa ry. These graphical packages helped GA EPD conduct the analysis in a systematic and consistent manner. The following is a brief summary of what was found by this graphi cal analysis. The evaluation included speciated data available from IMPROVE, CASTNET, SEARCH, and STN as well as

total PM 2.5 from FRM monitors.

Overall, the model showed r easonable performance for PM 2.5 , SO 4 , NH 4 , and OC throughout the base year across all monitors in GA. During summer, the model showed a

seasonal variation of NO 3 performance with under-prediction bias greater than –100% and moderate winter over predic tion at CASTNET sites. The amount of error and bias in monthly time series was most likely co ntributed by low c oncentration (< 1.0 μ g/m 3 ) cases. As shown in Figure 4-7, SO 4 and OC were the major contributors to the Floyd County nonattainment areas. Therefore, GA EPD concluded that performance issues

found in minor constituents of PM 2.5 are not likely degrading the overall model performance.

98 of 148Model Performance Evaluation PM2.5 Attainment SIP – Floyd County, GA

Figure 4-7. Stacked bar plots of daily PM 2.5 species concentration at 13-115-0005.

Detailed graphical analyses led GA EPD to investigate a few exceptional performance

issues for SO 4 , OMC, and NH 4 . These analyses helped GA EPD to narrow down the possible causes of the performance issues. After reviewing these exceptional cases more closely, GA EPD concluded that these issues do not preclude the use of the model for the purpose of supporting this SIP for the Floyd County nonattainment area.

When the performance is looked at as a functio n of concentration, as in the bugle plots, the performance metrics indicate acceptable model performance for all species. Overall, GA EPD believes that the model predictions can be used to form the scientific foundation for proposed control options because its pe rformance is well within the limits of acceptable performance criteria establishe d in the Attainment Modeling Guidance.

99 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Section 5. Control and Contingency Measures

Control measures are used to reduce emissi ons of direct PM2.5 and PM2.5 precursors and are therefore of primary importance to de monstration of attainme nt. Those measures that had already been implemented through th e end of 2002 (the ye ar of the baseline emissions inventory) are not di scussed in this SIP. This section identifies those control measures which are included as inputs in the generation of the 2009 emissions inventory and are therefore relied upon to demonstrate attainment. These measures have been or will be implemented after 2002 but before 2009 (the modeled attainment year).

Contingency measures, required by Section 172(c)(9) of the CAA, are additional control measures to be implemented in the event that an area fails to attain the standard by its

attainment date. These measures must be ready to be implemented quickly without significant further action by the State or by EPA.

This section also describes other measures which were not relied upon for attainment demonstration but which should provi de small reductions to ambient PM 2.5 levels. Finally, this section also discusses the implementation of RACT and RACM in the

nonattainment area.

5.1 Federal Control Measures for PM2.5 Attainment

The following federal control measures were included in the generation of the 2009 emissions inventory:

• Clean Air Interstate Rule

• Tier 2 Vehicle Standards

• Heavy-duty Gasoline and Diesel Highway Vehicles Standards

• Ultra-low Sulfur Diesel Rule

• Large Nonroad Diesel Engines Rule

• Non-road Spark Ignition Engines a nd Recreational Engines Standard

• NOx SIP call in surrounding states

These measures are described in Ta ble 5-1 and in the following text.

5.1.1 Clean Air Interstate Rule

On May 12, 2005, the USEPA promulgated the “Rule To Reduce Interstate Transport of Fine Particulate Matter and Ozone (Clean Air Interstate Rule); Revisions to Acid Rain Program; Revisions to the NOX SIP Call”, referred to as CAIR. This rule established the requirement for States to adopt rules limitin g the emissions of NOx and sulfur dioxide (SO2) and a model rule for the states to use in developing their rule s. The purpose of the CAIR is to reduce interstate transport of precursors to fine particulate and ozone.

100 of 148Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GATable 5-1. Federal PM2.5 Control MeasuresControl Measure for AttainmentDemonstration1Control Measure – ContinuingBenefits2MeasureSourcesAffectedMeasure andScheduleSpeciesAffected/ReducedMeasure andScheduleSpeciesReducedClean Air Interstate Rule(CAIR)40 CFR 96, Subparts AAA -HHHCoal-firedElectric Gen.Units, 28eastern statesand D.C.Regional cap on NOxand SO2 emissionsfrom EGU’s: NOXPhase 1 starts2009NOXRegional cap onNOX and SO2emissions fromEGU’s: SO2 Phase1 starts 2010SO2,NOxTier 2 vehicle standards40 CFR 80, 85 , and 86NEWPASSENGERVEHICLESFleet average for NOxemissions per mile,effective 2004 through2007NOxContinuingvehicleturnoverNOxHeavyDuty EngineStandard (Gasoline andDiesel), second phase40 CFR 86, Subpart ANew gas anddiesel highwayvehicles 14001lbs or greaterEffective 2004 andlater – NOx and VOCcontrols;Effective 2007 andlater – PM controlsNOx, VOC,and PM (soot);PM limit of0.01 g/bhp/hrContinuing vehicleturnoverNOx, VOC, andPM (soot)Ultra Low Sulfur Diesel40 CFR 80, Subpart INew dieselhighwayvehicles 14001lbs or greaterLimits 80 % of pool ofhighway diesel tosulfur content of 15ppm or less, 2007 –2009: facilitatesproper operation ofheavy duty diesel PMcontrols (see above)PM (soot)Limits 100 % ofpool of highwaydiesel to 15 ppmsulfur or less; 2010on - facilitatesproper operation ofheavy duty dieselPM controls (seeabove)PM (soot)101 of 148Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GATable 5-1. Federal PM2.5 Control Measures (continued)Control Measure for AttainmentDemonstration1Control Measure – ContinuingBenefits2MeasureSourcesAffectedMeasure andScheduleSpeciesAffected/ReducedMeasure andScheduleSpeciesReducedNonroad Diesel Rule40 CFR 89NEWMOBILESOURCES:OFF-ROAD,SHIPS,LOCOMOTIVES2008 through 2014;Should reduce NOx andPM emissions by over90 %NOx, PM (soot)Continuing vehicleturnoverNOx, PM (soot)Large Spark Ignition andRecreational VehicleRule40 CFR 90Forklifts, airlineground serviceequipment, allterrain vehicles,off-highwaymotorcycles,marine dieselenginesLARGE SPARKIGNITIONEQUIPMENT(FORKLIFTS,AIRLINE GROUNDSERVICEEQUIPMENT) –2004; OFF-ROADVEHICLES – 2006;MARINE ENGINES -2006VOC, NOx, COContinuingequipment turnoverVOC, NOx, CONOx SIP Call inSurrounding Statesutility andindustrialboilers; internalcombustionenginesControls on utility andindustrial boilers and oninternal combustionengines in 22 easternstates by 2004NOx(1) Control measure for attainment demonstration – after 2002, before 2009 – permanent and enforceable, SIP counts toward attainment demonstration(2) Control measure – continuing benefits –effective 2009 or later – SIP does not counttoward attainment butwill provide emissions reductions102 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

The CAIR applies to (1) any stationary, fossil- fuel-fired boiler or stationary, fossil-fuelfired combustion turbine serving, at any tim e since the start-up of a unit's combustion chamber, a generator with a nameplate capacity of more than 25 MWe producing electricity for sale and (2) for a unit that qualifies as a cogenera tion unit during the 12- month period starting on the date that the un it first produces electrici ty and continues to qualify as a cogeneration unit, a cogeneration unit serving at any time a generator with nameplate capacity of more than 25 MWe a nd supplying in any calendar year more than one-third of the unit's potential electric out put capacity or 219,000 MWh, whichever is greater, to any utility power distribution system for sale.

This rule provides annual state caps for NOx and SO2 in two phases, with the Phase I caps starting in 2009 and 2010, respectively. Be cause the Phase I SO2 cap starts in 2010, it cannot be counted as a contingency measure for demonstration of attainment. Phase II caps for NOx and SO2 become effective in 2015, which is too late to count as a contingency measure. The USEPA is allowi ng the caps to be met through a cap and trade program if a state chooses to participate in the program. When fully implemented, the

CAIR will reduce SO2 emissions in the eastern United States by over 70 percent and NOx emissions by over 60 percent from 2003 levels.

As part of the final rule, EPA determined that Georgia contri butes significantly to

downwind PM2.5 nonattainment areas and/or in terferes with maintenance of the PM2.5 NAAQS (70 FR 25246-25250). Accordingly, a St ate CAIR rule (Geo rgia rule 391-3-1- .02(13)) has been promulgated that, for the most part, mirrors the provisions of the federal rule. Georgia will have statewide SO2 caps of 213,057 tons/yr and 149,140 tons/year, effective in 2010 and 2015, respecti vely. Adjacent CAIR states that have been identified as contributing significantly to nonattainment of the PM2.5 standard in the Floyd County PM2.5 nonattainment area are Alab ama, Florida, North Carolina, South Carolina, and Tennessee. These states will also have caps on SO 2 that will reduce the

ambient concentration of sulfates in the Floyd County nonattainment area.

5.1.2 Tier 2 Vehicle Standards

Federal Tier 2 vehicle standards will reduce NO

x emissions from passenger vehicles. The standards require all passenger vehicles in a manufacturer’s fleet, including light-duty trucks and sport utility vehicles (SUVs), to meet an average standard of 0.07 grams of NOx per mile. Implementation began in 2004, and was completely phased in by 2007. The Tier 2 standards will also cover pa ssenger vehicles over 8,500 pounds gross vehicle weight rating (the larger pi ckup trucks and SUVs), which are not covered by the current Tier 1 regulations. Fo r these vehicles, the standards will be phased in beginning in 2008, with full compliance in 2009. The new standa rds require vehicles to be 77% to 95% cleaner than those on the road prior to implementation of Tier 2. The Tier 2 rule also reduced the sulfur content of gasoline to 30 parts per million (ppm) starting in January of 2006. Sulfur occurs naturally in gasoline, bu t interferes with the operation of catalytic

103 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

converters on vehicles resulting in higher em issions. Lower-sulfur gasoline is necessary

to achieve the Tier 2 vehicle emission standards.

5.1.3 Heavy-Duty Gasoline and Diesel Highway Vehicles Standards

New USEPA standards designed to reduce NOx and VOC emissions from heavy-duty gasoline and diesel highway vehicles began to take effect in 2004. A second phase of standards and testing procedures, which be gan in 2007, will reduce particulate matter from heavy-duty highway engines, and will also reduce highway diesel fuel sulfur content to 15 ppm to prevent damage to th e emission control devices. The total program is expected to achieve a 90% reduction in particulate matter (PM) emissions and a 95% reduction in NOx emissions for these new engi nes using low sulfur diesel, compared to older engines using diesel with higher sulfur content.

5.1.4 Large Nonroad Diesel Engines Rule

In May 2004, the USEPA promulgated new rules for large nonroad diesel engines, such as those used in construction, agricultural, and industrial equipment, to be phased in

between 2008 and 2014. The non road diesel rules also reduce the allowable sulfur in nonroad diesel fuel by over 99%. Nonroad diesel fuel curre ntly averages about 3,400 ppm sulfur. The rule limits nonroad diesel sulfur content to 500 ppm in 2006 and 15 ppm in 2010. The combined engine and fuel rules would reduce NOx and PM emissions from large nonroad diesel engines by over 90%, compared to older engines using diesel with higher sulfur content.

5.1.5 Nonroad Spark-Ignition Engines and Recreational Engines Standard

The new standard, effective in July 2003, regulates NOx, hydrocarbons (HC) and carbon monoxide (CO) for groups of previously unregulated nonroad engines. The new standard will apply to all new engines sold in the United States and imported after these standards began and apply to large spark-ignition en gines (forklifts and airport ground service equipment), recreational vehicles (off-highway motorcycles and all-te rrain-vehicles), and recreational marine diesel engines. The re gulation varies based upon the type of engine

or vehicle.

104 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

The large spark-ignition engines contribute to ozone formation and ambient CO and PM

levels in urban areas. Tier 1 of this sta ndard was implemented in 2004 and Tier 2 started in 2007. Like the large spark- ignition engines, recr eational vehicles co ntribute to ozone

formation and ambient CO and PM levels. For the off-highway motorcycles and allterrain-vehicles, model year 2006, the new e xhaust emissions standard was phased-in by 50% and for model years 2007 and later at 100% . Recreational marine diesel engines

over 37 kilowatts are used in yachts, cruisers, and other types of pleasure craft. Recreational marine engines contribute to oz one formation and PM levels, especially in marinas. Depending on the size of the e ngine, the standard began phasing in 2006.

When all of the nonroad spark-ignition engi nes and recreational engines standards are fully implemented, an overall 72% reduction in HC, 80% reduction in NOx, and 56%

reduction in CO emissions ar e expected by 2020. These controls will help reduce ambient concentrations of ozone, CO, and fine PM.

5.1.6 NOx SIP Call in Surrounding States

In October 1998, the USEPA made a findi ng of significant contribution of NOx emissions from certain states and published a rule that set ozone season NOx budgets for the purpose of reducing regional tr ansport of ozone (63 FR 57356). This rule, referred to as the NOx SIP Call, called for ozone season c ontrols to be put on ut ility and industrial boilers, as well as internal combustion engines in 22 states in the Eastern United States. A NOx emissions budget was set for each stat e and the states were required to develop

rules that would allow the state to meet their budget. A NOx trading program was established, allowing sources to buy credits to meet their NOx budget as opposed to actually installing controls. The emission bud gets were to be met by the beginning of

2004.

5.2 State Control Measures for PM2.5 Attainment

The following State control measures are included in the ge neration of the 2009 emissions inventory:

• Multipollutant Rule for coal-fired electric generating units (EGUs)

• Heavy-duty Diesel Engines Rule

These measures are described in Ta ble 5-2 and in the following text.

105 of 148Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GATable 5-2. State PM2.5 Control Measures and Contingency MeasuresControl Measure – AttainmentDemonstration1Control Measure – ContinuingBenefits2MeasureSourcesAffectedMeasure andScheduleSpeciesAffected/ReducedMeasure andScheduleSpeciesand QtyReduced (tons)Multipollutant ruleAir Quality Control 391-3-1-.02 (2) (sss)Electric Gen.Units, CoalFired, GAFlue Gas Desulf. for7 EGUS3STARTINGIN 2008 -APPROXIMATELY194,000 TONS/YRREDUCEDSO2sourcesoutside thenonattainmentareaFlue Gas Desulf.for Bowen Unit 2,June 1, 2009,Wansley Unit 2,December 31,2009, and BowenUnit 1, June 1,2010SO2sourceoutside thenonattainmentarea – approx.127,263 tons/yrreducedHeavy Duty Diesel EnginesruleAir Quality Control 391-3-1-.02 (2) (ooo)DieselVehicles14001 lbs orgreaterDiesel Vehicles 14001lbs or greater meetCARB standards;2005 and subsequentmodelsPM (soot)sources insidethenonattainmentareaContinuingequipment turnoverPM (soot) sourcesinside thenonattainmentarea(1) Control measures for attainment demonstration – after 2002, before 2009 – permanent and enforceable, SIP counts toward attainment demonstration(2) Control measures – continuing benefits – effective 2009 or later – SIP does not count toward attainment but will provide emissions reductions(3) Bowen Units 3 and 4, Hammond Units 1 – 4, and Wansley Unit 1106 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

5.2.1 Multipollutant Control for Electric Utili ty Steam Generating Units, GA Rule 391-3-1-.02(2)(sss)

This state rule requires flue gas desulfurization (FGD) and selective catalytic reduction (SCR) controls on coal-fired EGUs in Georgi a. It was enacted in 2007 for the purposes of lowering ozone and PM2.5 concentrations and reducing mercury deposition. The

controls will reduce SO 2 emissions from the affected emissions units by at least 95 percent and will reduce NO

x emissions by approximately 85 percent.

The control implementation date of the ru le varies by EGU, starting on December 31, 2008. Controls are required on seven of the units prior to the atta inment demonstration year (see Table 5-3). Four of these units are located at Plant Hammond, which is located inside the nonattainment area. Two of the units are located at Plant Bowen, which is located in the county immediately to the east. The la st unit is located at Plant Wansley, which is located approximately 50 miles south of the nonattainment area. The Title V permit of each affected facility has been amended to permit operation of the FGD

controls. Controls on three more units lo cated outside the nonattainment area will be implemented in 2009 and 2010.

A separate Georgia rule, rule (uuu), places sp ecific SO2 emissions limits on each of the EGUs addressed by rule (sss). Reductions will occur beginning in 2008 as a result of implementation of rule (sss). The emi ssion limits required by rule (uuu) become effective January 1, 2010, through June 1, 2015, depending upon the unit.

Table 5-3. Georgia Multipollutant Rule SO 2 Control Requirements and Construction

Permit Conditions

Plant/Unit County Required FGD operation date, per rule (sss) 1 ConTrol 4 Conting. Construction

Permit

Number Permit Effective

Date

Bowen Unit 3 Bartow 12/31/2008 X 4911-015-

0011-V-02-1 2/27/06

Bowen Unit 4 Bartow 12/31/2008 X 4911-015-

0011-V-02-1 2/27/06

Hammond

Unit 1 Floyd 12/31/2008 X 4911-115-

0003-V-02-2 12/20/06

Hammond

Unit 2 Floyd 12/31/2008 X 4911-115-

0003-V-02-2 12/20/06

Hammond

Unit 3 Floyd 12/31/2008 X 4911-115-

0003-V-02-2 12/20/06

Hammond

Unit 4 Floyd 12/31/2008 X 4911-115-

0003-V-02-2 12/20/06

Wansley

Unit 1 Heard 12/31/2008 X 4911-149-

0001-V-02-0 (incorporated draft permit 1/1/2007

107 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Plant/Unit County Required FGD operation date, per rule (sss) 1 ConTrol 4 Conting. Construction

Permit

Number Permit Effective

Date

V01-9 (permit to construct))

Bowen Unit 2 Bartow 06/01/2009 NA 2 4911-015-

0011-V-02-3 12/20/06

Wansley

Unit 2 Heard 12/31/2009 NA 2 4911-149-

0001-V-02-0 (incorporated draft permit V01-9 (permit to construct)) 1/1/2007

Bowen Unit 1 Bartow 6/1/2010 NA 2 4911-015-

0011-V-02-3 12/20/06

Scherer Unit 3 Monroe 12/31/2011 X FGD control to

be incorporated into permit

renewal 3

(1) rule (sss) is not federally enforceable (2) control not needed to meet one year of emissions (3) current permit expires December 2010 and construction permit will be incorporated into permit

renewal (4) controls on these units are modeled in the attainment demonstration

The total estimated reduction of SO2 emissions from the seven EGUs by 2009 is 216,412 tons/yr. The estimated state-wide level of SO2 emissions (from all sources) in 2009 is 527,580 tons/yr after the EGU reductions. Therefore, the EGU reductions are equivalent to 29.1 percent of uncontrolled statewide SO2 emissions (216,412 tons/yr plus 527,580 tons/yr).

5.2.2 Heavy Duty Diesel Engines Rule (ooo)

This rule requires heavy duty diesel engine s (vehicle weight of 14001 lbs or more) to meet the California Air Resources Board (C ARB) emissions standards by 2005. These standards are essentially the same as the fe deral heavy duty engine standards (40 CFR 86, Subpart A) described in the federal control measures section. The CARB heavy duty diesel engine standards were adopted to en sure that the emission reductions would be

achieved in the event that U.S. EPA relaxed the federal requirements and did not require 2005 and 2006 model year engines to meet the Not-To-Exceed (NTE) test requirements. The CARB standards and Georgia’s rule (ooo) were promulgated prior to the federal standards. The rule was expected to redu ce NOx by 13 tons per day statewide and 8 tons per day in the 45 county Atlanta ozone contro l area in 2005. These emissions benefits would potentially double in 2006 if the manufacturers contin ued to not meet the NTE test requirements. Manufacturers were required fe derally to begin testing the engines to the

108 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

NTE requirements with the 2007 model year. Georgia has kept th e CARB standards in place to prevent a delay in the state receiving cleaner engines in the event that EPA were to relax or delay the federal 2007 or 2010 engi ne standards. Also, the CARB engine requirements differ from EPA’s in that CA RB requires a 5 minute idle shutdown or the use of a clean-idle engine beginning with the 2008 model year. The benefit of this 5- minute idle limit has not been quantified for Geor gia. However, it is expected to reduce

NOx and PM emissions.

5.3. Summary of SO2 Emissions Changes

Control of SO2 sources is the primary mechan ism for attainment of the PM2.5 standard. Expected changes in SO2 emissions between the typical baseline and 2009, including the effects of SO2 controls, are quantified by so urce category in the tables below. The changes for the nonattainment area and the st ate are presented in Tables 5-4 and 5-5, respectively. Reductions in emissions are s hown as negative numbers. Note that fire emissions are not affected by controls included in attainment modeling.

Table 5-4. Changes in SO2 Emissions, 2002 to 2009, Nonattainment Area (tons)

EGU point NonEGU point Nonroad Area Mobile Fire Total

2002* 30376 4869 81 968 128 12 36434

2009 1858 5006 14 970 16 12 7876 Change -28518 137 -67 2 -112 0 -28558 * typical emissions

Table 5-5. Changes in SO2 Emission s, 2002 to 2009, Statewide (tons)

EGU point NonEGU point Nonroad Area Mobile Fire Total

2002* 515958 55453 9006 57555 12183 2815 652970

2009 406918 55749 2725 57692 1585 2912 527580 Change -109040 296 -6281 137 -10598 97 -125390 * typical emissions

The total SO2 change in the nonattainment area is a decrease of 28,558 tons. Reductions

of SO2 occurred at Plant Hammond when controls were inst alled in May 2008.

109 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

The total statewide SO2 emissions change is a decrease of 125,390 tons. The statewide change is more pertinent to de monstrating attainment in 2009.

5.4. Contingency Measures

Section 172(c)(9) of the Clean Ai r Act requires states to id entify and include contingency

measures in their attainment demonstration plans. Contingency measures must take effect without significant further action by the State or USEPA upon determination by

EPA that an area has either failed to dem onstrate Reasonable Further Progress (RFP)

toward attainment or failed to demonstrate attainment of the applicable NAAQS.

The preamble of the Clean Air Fine Particle Implementation Rule (72 FR 20586) states the following (page 20642): “Under subpart 1 of the CAA, all PM2.5 nonattainment areas must include in their SIPs contingency measures consistent with section 172(c)(9). Contingency measures are additional control measures to be implemented in the event

that an area fails to meet RFP or fails to atta in the standards by its attainment date. These contingency measures must be fully adopted ru les or control measures that are ready to be implemented quickly upon failure to meet RFP or failure of the area to meet the standard by its attainment date . The preamble to the proposal stated that the SIP should contain trigger mechanisms for the con tingency measures, specify a schedule for implementation, and indicate that the measur es will be implemented without significant further action by the State or by EPA. The c ontingency measures should consist of other

control measures for the area that are not incl uded in the control strategy for the SIP.”

40 CFR 51.1009(b) states the following: “If the State submits to EPA an attainment demonstration and State implementation plan for an area which demonstrates that it will attain the PM NAAQS within five years of the date of designati on, the State is not required to submit a separate RFP plan. Compliance with the emission reduction

measures in the attainment demonstration and State implementation plan will meet the requirements for achieving reasonable further progress for the area.” The preamble (page 20643) to the April 2007 final ru le requires states to adopt “contingency measures equal to approximately one year’s worth of reducti ons necessary to achieve RFP for the area.” Because an RFP plan will not be required for Floyd County, a quantity of emissions reductions equivalent to one year of the reduc tions needed to meet attainment will satisfy the requirement for contingency measures.

The purpose of these contingency measures “i s to provide a cushion while the plan is being revised to meet the missed milest one” (page 20643). Calendar year 2009 is the final year for which emissions control measures are to be included in an attainment demonstration for the attainment date of Apr il 5, 2010. It is EPD’s understanding, based on evaluation of the language of the CAA and from discussions with EPA Region 4, that these contingency measures are to be implem ented approximately within 2 calendar years following the final emissions control year in the attainment demonstration. This time period takes into consideration the time requi red for EPA to make a finding of failure to attain the NAAQS and the requirement to s ubmit a revision to the SIP. Contingency

110 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

measures will be those reductions that occur after the 2009 control year and prior to the submittal of a revised SIP if this area fails to attain. Therefore contingency measures for the purpose of this plan are those measures that will be implemented any time during the calendar years 2010 and 2011.

Demonstration of attainment in the Floyd County NAA is based largely on statewide

reductions of SO 2 emissions from Georgia’s coal-fir ed EGUs, as required by Georgia rules 391-3-1-.02(2)(sss) and (uuu). There is one coal-fired pl ant located in Floyd County, Georgia Power’s Plant Hammond. Th e plant has 4 EGU’s controlled by FGD for SO2 during the attainment period. Fl oyd County also demonstrates SO2 reductions

from the mobile and nonroad sectors due to federal fuel requirements. Table 5-6 below

illustrates the SO 2 emissions changes in the Floyd Count y NAA for the attainment period.

Reductions in emissions are s hown as negative numbers.

Table 5-6. Predicted changes in SO 2 emissions inside the Floyd County Nonattainment Area, 2002 to 2009C

Sources 2002 SO2

Emissions (tpy) 1 2009 SO2

Emissions (tpy) 1 Change (tpy) 1

Point 35,245.1 6864.4 -28,380.7

Area 979.5 981.8 2.3

Mobile 128.1 15.5 -112.6

Nonroad 81.2 13.5 -67.7

Total 36,433.9 7875.2 -28,558.7

Table 5-7 below illustrates the emission trends during the contingency period. This trend demonstrates a slight increase in emissions (683 tons of SO2), mo stly due to typical growth factors applied to point and area sources.

Table 5-7 Predicted changes in SO2 emissions inside the Floyd County Nonattainment Area, 2009 to 2012

Sources 2009 SO2

Emissions (tpy) 1 2012 SO2

Emissions (tpy) 1 Change (tpy)

Point 6864.4 7547 682.6

Area 981.8 993.1 11.3

Mobile 15.5 15.2 -0.3

Nonroad 13.5 3.0 -10.5

Total 7875.2 8558.3 683.1

(1) Source: VISTAS 2002, 2009, and 2012 inventories.

111 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Since there are no additional coal-fired E GUs, or other point s ource reductions of SO2 occurring within the Floyd County NAA, and ther e are no federal meas ures that result in additional emission reductions, contingency measures for Floyd County will be based on

control of SO2 emissions from sources lo cated outside of the nonattainment area and located in Georgia.

5.4.1 Region for Contingency Measures

The application of RFP procedures to calcu late the emission reductions necessary for contingency measures will also apply to determining the geographical area from which

the emission reductions will occur. Because of the regional nature of PM2.5, sources of SO2 outside of the non-attainment area may be impacting the PM2.5 concentrations in

the non-attainment area. “EPA be lieves that states could be ab le to justify considering not only all emissions in the NAA, but also emissi ons within a distance that may be up to 200

kilometers from the nonattainment area” (72 FR 20636). Given that all EGU SO2 emissions reductions in Floyd County occur prior to 2009, and that there are no additional significant reductions of SO2 that occur in Floyd County prior to 2012, GA EPD will be required to go beyond the non-atta inment area for its contingency measure emission reductions and rely on ad ditional reductions from EGUs.

EPA has concluded “Since the demonstrations of impact are best done by states, in conjunction with their attainment planning, EPA intends to allow States to justify the area to be included, within the distance limits discussed above” (72 FR 20638). For the Floyd County NAA’s contingency measures, GA EPD has defined an area that includes counties within, and bisected, by an arc from the monitoring location in Rome GA to the nearest significant source of SO2 emissions relied upon for reduction to demonstrate attainment, Georgia Power’s Plant Bowen.

Figure 5-1 shows the area for which contingency measures are being considered with respect to the Floyd County non-attainment area. The circle represents a 35.6 km radius

from the Rome FRM monitor to Plant Bowe n. GA EPD notes that this method of determining the area from the monitor is mo re stringent that the typical method of determining the area from the border of the NAA. All net emissions from the Georgia counties within the circle were considered in the analysis. For simplicity, these counties

will be referred to as the “area of influence” for the Floyd County non-attainment area.

112 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Figure 5-1 Floyd County Area of Influence

5.4.2 Area of Influence Emission Re ductions for Contingency Measures

The guidance from the preamble for the PM2.5 Implementation rule requiring a quantity of emission reductions equivalent to one year of the reductions needed to meet attainment cannot be applied within the NAA for this dem onstration since there is actually a slight increase in SO2 emissions within the 7-year period. Therefore, EPD will evaluate all

sources of emissions within the area of in fluence to demonstrate contingency emission

reductions.

113 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Table 5-8 displays the 2002 baseline SO2 emissions, by source sector, for the counties

located within the area of influence fo r the Floyd County non-attainment area and includes Floyd County. The to tal 2002 baseline SO2 emissions , for the area of influence, are 196,952.6 tons per year.

Table 5-8. 2002 Baseline SO2 Emissions For Floyd County Area of Influence

County EGU Point

Sources

(tons/year) Non-EGU

Point

Sources

(tons/year) Non-road

Mobile

Sources

(tons/year) Area

Sources

(tons/year) Highway

Mobile

Sources

(tons/year) Total SO2

Emissions

(tons/year)

Bartow 153,848.8 1752.1 105.9 1006.8 180.8 156,894.4 Chattooga 0.0 1507.7 11.0 492.6 39.3 2050.6 Floyd 30,376.2 4868.9 81.2 979.5 128.1 36,433.9

Gordon 0.0 0.0 75.4 992.5 105.1 1173.0

Polk 0.0 0.0 35.2 306.7 58.8 400.7

Total 184,225 8128.7 308.7 3778.1 512.1 196,952.6

Table 5-9 displays the 2009 attainment contro l year SO2 emissions, by source sector, for

the counties located within the area of influence for the Floyd County non-attainment area and includes Floyd County. The total 2009 SO2 emissions, for the area of influence, are 97,435.2 tons. This demonstrates a reduction of 99,517.4 tons of SO2 in the area of influence during the attainment period.

Table 5-9. 2009 SO2 Emissions For Floyd County Area of Influence

County EGU Point

Sources

(tons/year) Non-EGU

Point

Sources

(tons/year) Non-road

Mobile

Sources

(tons/year) Area

Sources

(tons/year) Highway

Mobile

Sources

(tons/year) Total SO2

Emissions

(tons/year)

Bartow 83,349.3 1866.9 17.8 1009.0 25.5 86,268.5 Chattooga 0.0 1451.1 1.8 493.6 4.7 1951.2 Floyd 1857.9 5006.5 13.5 981.8 15.5 7875.2

Gordon 0.0 0.0 12.6 994.6 12.7 1019.9

Polk 0.0 0.0 5.9 307.6 7.0 320.5

Total 85,207.1 8324.6 51.6 3786.6 65.4 97,435.2

114 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Table 5-10 displays the 2012 year SO2 emi ssions, by source sector, for the counties

located within the area of influen ce for the Floyd County NAA and includes Floyd County. The total 2012 SO2 emissions, for the ar ea of influence, are 24,403.1 tons. This

demonstrates an additional reduction of 73,032.1 tons of SO2 in the area of influence during the period of time for contingency measures to be evaluated.

Table 5-10. 2012 SO2 Emissions For Floyd County Area of Influence

County EGU Point

Sources

(tons/year) Non-EGU

Point

Sources

(tons/year) Non-road

Mobile

Sources

(tons/year) Area

Sources

(tons/year) Highway

Mobile

Sources

(tons/year) Total SO2

Emissions

(tons/year)

Bartow 9540.0 1883.0 3.6 1020.5 24.8 12,471.9 Chattooga 0.0 1528.5 0.3 499.1 4.5 2032.4 Floyd 2190.0 5357.0 3.0 993.1 15.2 8558.3

Gordon 0.0 0.0 2.9 1005.8 12.3 1021.0

Polk 0.0 0.0 1.5 311.2 6.7 319.4

Total 11,730.0 8768.4 11.4 3829.8 63.5 24,403.1

Table 5-11 summarizes the area of influence emissions for the attainment period and the contingency period. The emission reduction du ring the attainment period within the area of influence, which includes Floyd County, is 99,517.4. One sevent h of this value is 14,216.7 tons of SO2. The emission reducti on for the area during th e contingency period is 73,032.1 tons of SO2, which is far in ex cess of one year’s worth of emission for RFP of 14,216.7.

Table 5-11. Total SO2 Emissions Fo r Floyd County Area of Influence

Area 2002 (tpy) 2009 (tpy) 2012 (tpy) Attainment

Reductions

2002 -2009 (tpy) Contingency

Reductions

2009-2012 (tpy) Floyd County 36,433.9 7875.2 8558.3 28,558.7 -683.1

Outside Nonattainment

Area 160,518.7 89,560.0 15,844.8 70,958.7 73,715.2

Total Area Combined 196,952.6 97,435.2 24403.1 99,517.4 73,032.1

115 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

5.4.3 Adopted Controls for Contingency Measures

The emissions values in Tables 5-9, 5-10, a nd 5-11 demonstrate that the majority of the SO2 emission reductions occur from EGU point sources. The emi ssion reductions prior

to attainment were contributions from both EGU reduction and federal fuel programs. The emission reductions during the conti ngency period were overwhelmingly EGU SO2

reductions.

The EGU point source located within th e area of influence but outside of the nonattainment area is Georgia Power’s Plant Bowen. Units 1 & 2 of Plant Bowen will start operating SO2 controls no later than June of 2010, whic h is within th e contingency measure time period. The Title V permit of this facility has been amended to permit construction and operation of the FGD controls and the facility is required to submit a CAM plans as soon as the units come online. The facility will be subject to an emission reduction requirement that will reflect the new controls an d that will be required by Georgia Rule (uuu). The controls and limit w ill effect emissions reductions of 73,809.3 tons, as shown in Table 5-12, dur ing the contingency period.

Table 5-12. SO2 emissions reductions expected from control and contingency measures at coal-fired electric genera ting units outside the Floyd County

Nonattainment Area.

Plant/

Unit County 2002

baseline

(tpy) 2009

emissions 2012

emissions Attainment

Reductions

2002--2009 Contingency

Reductions

2009-2012

Georgia

Power Plant

Bowen Bartow 153,848.8 83,349.3 9,540.0 70,499.5 73,809.3

The Georgia Power Plant Bowen SO2 control m easure is required by Georgia rule 391-3- 1-.02(2)(uuu) and will take affect regardless of the attain ment status of the Floyd County NAA. Therefore, no trigger mechanism is n eeded and no further action is needed from EPD or EPA for this rule to be implemented. The Plant Bowen control measure therefore satisfies the contingency measure requirement.

5.5 Unmodeled Control Measures

The following unmodeled measures, some of wh ich are voluntary act ions, should provide

additional reductions to ambi ent PM2.5 concentrations:

• Open burning rule

• Switching of two EGUs to lower sulfur coal

• Planned early start-up of SO 2 scrubbers at two EGUs

116 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

Because the measures are voluntary and/or th e benefits are relatively small, credits for

these measures have not been taken in the projected emissions inve ntory for attainment demonstration modeling. These measures are described in Table 5-13 and in the following text.

Table 5-13. Unmodeled Control Measures

Unmodeled Control Measure 1 Measure Sources

Affected

Measure and

Schedule Species

Affected/

Reduced Open burning rule Air Quality Control 391- 3-1-.02 (2)(5) Vegetation, tires, municipal waste,

construction debris, agriculture, etc. Restricts types of outdoor burning,

2005. Direct PM, organic carbon.

Switch 2 coal-fired EGUs to lower sulfur coal Plant Scherer

Units 1 and 2 Switched to PRB coal

in 2003 and 2004 SO2

Multipollutant rule, early implementation of

controls Air Quality Control 391- 3-1-.02 (2) (sss) Control start-up nominally 6

months before regulatory date Planned early start-up

of SO2 scrubbers at

Bowen Unit 2 and Wansley Unit 2 would

achieve emissions

reductions not

credited in the 2009 inventory SO2

(1) Unmodeled measure that becomes effective after 2002 but before 2009.

5.5.1 GA Rule 391-3-1-.02 (2)(5) Open Burning

Georgia’s Open Burning Rule places additiona l restrictions on open burning in Catoosa and Walker Counties. The rule prohibits ope n burning with the excep tion of 12 types of burning activities. During May through Sept ember the number of allowed exceptions is

reduced to six. The rule reduces emissions of elemental carbon a nd organic carbon year

round. The ban further reduces emissions of elemental carbon and organic carbon during the spring and summer months, when PM2.5 is typically higher.

5.5.2 Switch to Lower Sulfur Coal, Georgia Power Plant Scherer

Two of Plant Scherer’s coal-fired units were voluntarily switched to Powder River Basin (PRB) coal, which is lower in both sulfur a nd BTU value than Appalachian coal. Plant Scherer is located south of Atlanta, inside the Macon PM2.5 nonattainment area. Units 1

and 2 were switched to the PRB coal in Ju ly 2003 and January 2004, respectively. The sulfur levels in the PRB coal, as measured in 2007, were 0.285%, whereas the Georgia Power system-wide average was 1.12% over the same time period. Based on 2007

117 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

monitoring data, the estimated unmodeled emissions savings is approximately 54,000 tons of SO2 at each unit. These savings were not modeled because the switch to PRB coal was not a Federal or State requirement.

5.5.3 Multipollutant Rule, Early Implementation of Controls

Table 5-3 shows the compliance dates required by Georgia rule (sss) for installation and operation of SO 2 controls on coal-fired EGUs. Becau se the start-ups of scrubbers on Bowen Unit 2 and Wansley Unit 2 are not requ ired until June and December of 2009,

SO2 emissions reductions associated with thes e controls are not credited in the projected 2009 inventory used for modeled attainment demonstration. However, to ensure compliance with the rule, Georgia Power has planned for nominal start-up dates that are six months prior to the required dates. If the start-ups occu r early as planned, then the

scrubbers at Bowen Unit 2 and Wans ley Unit 2 would achieve 2009 SO 2 emissions reductions beyond those credited in the modeled attainment demonstration. The quantity

of unmodeled 2009 emissions reductions woul d be approximately 16,900 tons and 21,600 tons, respectively.

5.6 RACT and RACM

Section 172(c)(1) of the CAA requires SIPS to provide for the implementation of all reasonably available control measures (RACM) that cont ribute to attainment as “expeditiously as practicabl e” in the specific nonattainment area. The EPA has consistently interpreted RACM as a collec tion of measures that would advance the attainment date by at least one year. This requirement also applies to emissions reductions from existing stationary sources th rough the adoption of reasonably available control technology (RACT). “Reasonably availabl e” allows the state to consider both the cost and benefits of applying the measure and whether the measure can be readily and effectively implemented without undue administrative burden.

The Implementation Rule (72 FR 20612, 20617) defines a process by which a limited RACT and RACM analysis can be conducted for areas that are projected to attain within five years of designation as a result of existing national measures and are projected to have a design value of 14.5 ug/m 3 or lower. The 2009 annual modeled Future Design Value (DVF) for the Floyd County Annual PM 2.5 nonattainment area is 14.0. Therefore the Floyd County nonattainment area is s ubject to a limited RACT/RACM analysis.

EPA has stated (72 FR 20617) that “If the St ate could not achieve significant emissions reductions by the beginning of 2008 due to the time needed to implement reasonable measures or other factors, then it could be concluded that reasonably available local

measures would not advance the attainment date.” The EPA promulgated the Clean Air Fine Particle Implementation Rule (72 FR 20586) on April 25, 2007. This rule defined the requirements for RACT and RACM and also reaffirmed the due date for submission of the SIP revision for fine particles as April 5, 2008. EPA also acknowledges in the Implementation Rule that, due to the short tim e from the promulgation of the rule to the

118 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

SIP due date, it would be diffi cult for states to devise, adopt, and implement RACM in

time to advance the attainment date. EP D concurs that either a case-by-case RACT analysis and permitting or new RACT/RACM ru le development, including the analysis, stakeholder process, rule development, pub lic comment, and admini strative rule adoption procedures take far in excess of a year. Therefore, given the time constraints, EPD concludes that RACM, however limited, is not “reasonable” and is “impractical” to implement as “expeditiously as practicable.”

However, EPD had previously (prior to th e promulgation of the implementation rule) extensively evaluated the nature and sources of fine particulate matter emissions in the state and in the Floyd County nonattainment area . This led to a de termination that the primary component of ambient monitored PM2.5 is the precursor SO 2 , with the primary

source of SO 2 emissions within the State of Georgia (and, to a lesser extent, the Southeast) being coal-fired EGUs located at power plants. Table 5- 14 identifies the EGU

and non-EGU sources of SO2 emissions in the Floyd County Nonattainment Area and

serves to demonstrate the re lative difference in the magnit ude of emissions of EGU and

non-EGU sources of SO2 emissions. The s upplemental analysis in the attainment

demonstration section of this document discusses EPD’s determination that SO 2 is the significant contributor of PM2.5 emissions and that the control of SO 2 emissions from EGUs is the most effective strategy for significant PM2.5 air quality improvements. Using the results of this modeling anal ysis, evaluating Georgia’s other PM2.5 nonattainment areas (Atlanta, Chattanooga, a nd Macon), and incorporating Georgia’s responses to the Clean Air Interstate Rule (CAIR), the Clean Air Mercury Rule (CAMR) (currently vacated), and the Clean Air Visi bility Rule (CAVR), the State of Georgia adopted State Rule 391-3-1-.02(2)(sss) “Multip ollutant Control for Electric Utility Steam Generating Units” (Multipollutant Rule) e ffective March 14, 2007 (see Appendix L). This rule includes a schedule that identifies the dates by which specific EGUs are to install flue gas desulfurization (FGD).

Table 5-14 Floyd Co. Nonatta inment Area Major Source SO 2 Emissions

Facility 2002 tpy (actual) 2009 tpy

Georgia Power Plant Hammond 27594 1858

Temple-Inland Rome Linerboard 4869 5006

Metal Container Corporation 0.1 0.1

Planning for the Floyd County area was includ ed in this rule by requiring all EGUs located at Georgia Power Plant Hammond, which is located within the Floyd County nonattainment area, to in stall FGD. The rule requires al l four units at Plant Hammond to begin operation of FGD in 2008. While 72 FR 20623 includes a presumption that

119 of 148Control and Contingency Measures PM 2.5 Attainment SIP – Floyd County, GA

compliance with CAIR satisfies RACT for SO 2 emissions, it also specifies that “after consulting with power companies, the State may conclude that establishing additional ‘beyond CAIR’ emission control requirements on specific sources in nonattainment areas is warranted to provide for attainment as e xpeditiously as practicable. The timing of the installation and operation of controls at Pl ant Hammond will not advance the attainment date for Floyd County. EPD not es that Georgia’s Multipolluta nt rule requires SO2, NOx, and Hg controls on all large EGUs in the stat e. The controls at Plant Hammond are being installed as “expeditiously as practicable” given the extent of the engineering and

construction schedules involved in retrofitting all large EGUs with in the State of Georgia.

120 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Section 6. Attainment Demonstration

This chapter details the procedures that were used to demonstrate attainment of the annual fine particulate matter (PM2.5) Nati onal Ambient Air Quality Standard (NAAQS) for the Floyd County nonattainment area. As described in the US Environmental Protection Agency’s (USEPA’s) Guidance on th e Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze (“

Attainment Guidance ”), an attainment demonstration consists of (a) analyses which

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 Guidance recommends applying both a modeled attainment test and a subsequent unmonitored area an alysis (UAA) to the air quality modeling

results to determine if the annual PM2.5 NAA QS will be met. A dditional 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. The modeled attainment test, additional corroborative analyses and weight of evidence, and unmonitored area analysis are described in further detail in this section.

6.1 Modeled Attainment Test

The purpose of a modeled attainment test is to determine if control strategies currently being implemented or currently adopted with a future compliance date (“on the books”)

will lead to attainme nt of the NAAQS for PM2.5 by the attainment year of 2009. The modeling is applied in a rela tive 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 of different species. In th e test, ambient PM2.5 is divided into major components, with a separate relative respon se factor (RRF) and future design value (DVF) calculated for each of the PM2.5 com ponents. 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) . The following subsections outline the process that was used to determine 2009 mode l projections of PM2.5 and compare them to the NAAQS. Complete calculations a nd results are contained in Appendix M.

6.1.1 Determination of Baseline Design Values

The first step in any attainment test proce ss is to determine the baseline design value (DVB). In the Attainment Guidance, the US EPA recommends using a DVB that is the average of the three design value periods that straddle the baseline inventory year (e.g., the average of the 2000-2002, 2001-2003, and 2002-2004 design value periods for a 2002 baseline inventory year). This works out to a 5-year weighted average, with the baseline

121 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

year having the heaviest weight (e .g. {[2000] + 2*[2001] + 3*[2002] + 2*[2003] + [2004]}/9).

For the SMAT process, a mean PM2.5 DVB is determined, as well as component specific DVB for each quarter. The following section will detail the calculation of baseline design values needed for the PM2.5 attainment test.

6.1.1.1 Mean PM2.5 Baseline Design Values

To begin the SMAT process, a mean PM2.5 DVB is calculated on a quarterly basis for each Federal Reference Method (FRM) moni tor in the PM2.5 nonattainment area.

Concentrations are calculated based on calenda r quarters (Q1: January - March; Q2: April - June; etc.) as the NAAQS is calculated for a calendar year, and the quarters need to fit evenly within a year. Also, calculating the attainment test on a quarterly basis allows

states to examine the differences in PM2. 5 composition that occu r during the different

seasons.

Table 6-1 contains the quarterly average PM2. 5 concentration for the FRM monitor in the Floyd County nonattainment area. This quarter ly data was then averaged, using the weighted scheme suggested by the US EPA, to produce a 5- year weighted DVB. Table 6-2 presents the final mean PM2.5 DVBs for the nonattainment areas.

Table 6-1. Quarterly Average PM2.5 Mass for the FRM Monitor in the Floyd County

Nonattainment Area

AIRS ID County Site Name Year Q1 Q2 Q3 Q4

13-115-0005 Floyd Rome 2000 15.85 17.14 17.81 20.67

2001 12.54 17.78 20.16 13.15

2002 10.94 15.52 19.62 12.10

2003 13.77 18.88 20.26 12.00

2004 12.36 17.95 19.15 13.00

Table 6-2. Observed Quarterly and An nual Mean PM2.5 DVB for Monitor in the Floyd County Nonattainment Area

AIRS ID County Site Name 2000-2004
Q1 2000-2004
Q2 2000-2004
Q3 2000-2004
Q4 2000-2004

DVB

13-115-0005 Floyd Rome 12.628 17.219 19.630 13.365 15.7

122 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

6.1.1.2 Speciated Baseline Conditions

The attainment test for PM2.5 utilizes both PM2.5 and individual PM2.5 component species. A separate RRF is calculated for each PM2.5 species. In order to perform the recommended modeled attainment test, States should divide observed mass

concentrations of PM2.5 into 7 components (plus passive mass):

1. Mass associated with sulfates (SO4) 2. Mass associated with nitrates (NO3) 3. Mass associated with ammonium (NH4) 4. Mass associated with organic carbon (OC) 5. Mass associated with elemental carbon (EC)

6. Mass associated with particle bound water (PBW) 7. Mass associated with “other” primar y inorganic particulate matter (Crustal) 8. And passively collected mass or the mass of the blank filter (Blank = 0.5 μ g/m 3 )

The second part of the process is to use th e quarterly mean PM2.5 DVBs (as calculated in Section 6.1.1.1) with speciated data to calculate the quarterly mean concentrations of these 7 components at the FRM sites. This need to speciate the FR M data presents two

issues:

1. FRM measurements and speciated PM2. 5 measurements do not always measure

the same mass 2. Not all FRM monitoring sites have co-located speciation monitors.

The Floyd County Rome site (13-115-0005) ha s a co-located SPECIATION monitor. The following sections will explain how this data was used to produce the speciated

values needed for this at tainment demonstration.

6.1.1.2.1 SANDWICH

As the Attainment Guidance notes, recent da ta analyses (Frank, 2006) have shown that

the FRM monitors do not measure the same components and do not retain all of the PM2.5 that is measured by routine speciation samplers and therefore cannot be directly compared to speciation measurements from speciation. By design, the FRM mass

measurement does not retain all ammonium nitrate and other semi-volatile materials (negative sampling artifacts) and includes part icle bound water associated with sulfates, nitrates and other hygroscopic species (positive sampling arti facts). This results in concentrations (and percent c ontributions to PM2.5 mass), wh ich may be different than

the ambient levels of some PM2.5 chemical constituents.

To resolve the differences between FRM a nd speciation total mass, the US EPA has recommended using the S ulfate, A djusted N itrate, D erived W ater, I nferred C arbon

H ybrid (SANDWICH) material balance appr oach. With the SANDWHICH approach, nitrate mass is adjusted to account for volatilization based on hourly meteorology parameters. Subsequently, quarterly averag e nitrate, sulfate, elemental carbon, and

123 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

crustal mass can be calculated, as well as the Degree of Neut ralization (DON) of sulfates. Quarterly average NH4 can then be calculated from the adjusted nitrate mass, sulfate mass, and DON of sulfate. Next the mass of particle bound water can be calculated from the previously obtained DON, sulfate, nitrat e, and ammonium values. Finally, organic carbon is calculated by taking the difference between the total PM2.5 mass as measured at the FRM monitor, and the calculated co mponent mass (i.e. OC from mass balance ([OCMmb]) = PM2.5 FRM - {[EC] + [SO4] + [NO3] + [NH4] + [PBW] + [Crustal] + [Blank]}).

6.1.1.2.2 Speciated Profiles

While the SANDWICH method reconciles the differences between FRM and speciation, a lingering issue is not all FRM monitoring site s have co-located sp eciation monitors to provide speciated data. The US EPA Attainme nt Guidance suggests four measures that can be taken to resolve the lack of speciated data:

1. Use of concurrent data from a nearby speciated monitor 2. Use of representative data (from a different time period) 3. Use of interpolation techniques to creat e a spatial field using ambient speciation

data 4. Use of interpolation techniques to cr eate spatial fields, and gridded modeling outputs to adjust the species concentrations

Of the four methodologies, the US EPA recommends using one of the spatial interpolation techniques to estimate species c oncentrations at FRM sites that do not have speciation data (numbers 3 and 4 above). To assist in th is task, EPA is developing a

software tool called “Modeled Attainment Test So ftware” (or MATS) that will perform the spatial analysis of options number 3 an d 4 described above. However, the PM2.5 portion of the MATS tool had not been released at the time th is analysis was performed. In trying to pursue the US EPA recommended c ourse, we have used the speciated profiles from the Clean Air Interstate Rule (CAIR) SMAT tool, which is the predecessor for the MATS program, as an alternative.

The CAIR SMAT tool uses data from bot h the Interagency Monitoring of Protected Visual Environments (IMPROVE) and the US EPA’s Speciation Network (ESPN) to

derive mean concentrations for six PM2.5 co mponents. Quarterly average concentrations

between Jan 2002 to December 2002 were retain ed for sites that had at least 11 monitored values per quarter for each of the major PM2.5 species. Major species for ESPN include EC, OC, NH4, SO4, NO3, and cr ustal material (which includes the five trace elements aluminum, calcium, iron, sili con, and titanium). The major species for IMPROVE are the same except for NH4, whic h is not routinely measured in the IMPROVE protocol.

The quarterly averaged species concentra tions at the IMPROVE and ESPN monitors were used to interpolate concentrations at the PM2.5 FRM monitoring sites using a technique called Voronoi Neighbor Averaging (VNA).

124 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

As a result of the CAIR SMAT process, quarterly species fr actions were ge nerated for the Rome FRM site, which are presented in Tabl e 6-3 below. These fractions were then applied to Observed Quarterly Mean PM2.5 values calculated in Section 6.1.1.1 to determine quarterly component specific concentrations. Table 6-4 shows the quarterly DVBs for crustal, EC, OC, SO4, NO3, NH4 and PBW assuming a cons tant passive blank

mass of 0.5 μ g/m 3 . DON refers to degree of neutraliz ation of sulfate and ranges from 0.0 (sulfuric acid) to 0.375 (completely neutraliz ed in the form of ammonium sulfate).

Table 6-3. DVB Quarterly Species Frac tions (%) from the CAIR SMAT Tool

AIRS ID Site Name Blank

Mass qtr DON Frac.
Crustal Frac.
EC Frac.
OC Frac.
SO4 Frac.

NO3 Frac.

NH4 Frac.

H2O

13-115-0005 Rome 0.5 1 0.29235 0.03352 0.05747 0.45073 0.27296 0.02203 0.08619 0.07710

2 0.29398 0.05925 0.04461 0.41481 0.30358 0.00067 0.08944 0.08764

3 0.25274 0.03887 0.02097 0.29644 0.44088 0.00051 0.11158 0.09075

4 0.26964 0.05257 0.04309 0.38463 0.30939 0.03792 0.09442 0.07798

Table 6-4. Quarterly PM2. 5 Component-Specific DVB ( μ g/m 3 ) for Monitor in the Floyd County Nonattainment Area

AIRS ID Site Name Blank

Mass qtr FRM

Mass Non-Blank

Mass Crustal EC OC SO4 NO3 NH4 PBW

13-115-0005 Rome 0.5 1 12.63 12.13 0.41 0.70 5.47 3.31 0.27 1.05 0.94

2 17.22 16.72 0.99 0.75 6.94 5.08 0.01 1.50 1.47

3 19.63 19.13 0.74 0.40 5.67 8.43 0.01 2.13 1.74

4 13.36 12.86 0.68 0.55 4.95 3.98 0.49 1.21 1.00

6.1.2 Relative Response Factor Calculation

The next step in the SMAT process is to use base year and future year modeling results to estimate a relative response factor (RRF) fo r each component of PM2.5 for each quarter. Simply put, the RRF is the quarterly average future year concentration near a monitor divided by the quarterly average base year co ncentration near the same monitor, or:

X""Monitor Near""ion Concentrat Year Base Modeled Mean Quarterly X""Monitor Near""ion Concentrat Year Future Modeled Mean Quarterly

= RRF

Instead of focusing on the indi vidual cell containing the monitor, an array of cells that are “near” a monitor are considered in the attainment test. By sampling an array of cells from the modeling, the attainment test allows for variations in the model performance, as the peak concentrations may not occur in th e grid cell that contains the monitor, but

125 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

rather nearby the monitor. Table 6-5 provides the USEPA's recommendations for defining “nearby” cells for grid systems having cells of various sizes. Since the modeling for the Georgia attainment demonstration was preformed at a 12km grid resolution, a 3x3 grid array was used.

Table 6-5. USEPA’s Recommendation for Defining “Near” Cells

Size of Cell (km) Size of the Array of “Nearby” Cells

< 5 7 x 7

>5-8 5 x 5

>8-15 3 x 3

>15 1 x 1

For the PM2.5 SMAT, the RRF is calculated for each component, for each quarter. To accomplish this step, the 24-hour average concentration for each component of PM2.5 is extracted from the base year and future ye ar modeling output n ear the FRM monitoring sites for each day. The daily component c oncentrations from each cell of the 3x3 array are then averaged to develop a single m ean 24-hour average concentration for each component on each day in both the base and fu ture years. These mean daily component concentrations are then averaged for each quarter to develop ba se and future year quarterly mean component concentration. The future year quarterly mean component concentrations are then divided by their resp ective base year quarterly mean component concentrations to develop quarterly RRFs fo r each component of PM2.5. The quarterly RRFs for the FRM monitors in the Floyd C ounty PM2.5 nonattainment area are presented

below in Table 6-6. In lie u of using RRFs, the estimated future mass of NH4 and PBW will be determined by the estimated future mass of SO4 and NO3, as was done in the CAIR SMAT tool, per the following equations:

NH4 = DON * SO4 + 0.29*NO3

PBW =(-0.002618) + (0.980314*NH4) + (-0 .260011* NO3) + (-0.000784* SO4) + (- 0.159452* (NH4^2)) + (-0.356957* NO3* NH4) + (0.153894* (NO3^2)) + (0.212891* SO4* NH4) + 0.0444366* SO4* NO3) + (-0.048352* (SO4^2))

126 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Table 6-6. Quarterly Component RRF s for Monitor in the Floyd County

Nonattainment Area

AIRS ID Site Name qtr Crustal

RRF EC

RRF OC

RRF SO4

RRF NO3

RRF

13-115-0005 Rome 1 1.080 0.904 0.981 0.920 1.026

2 1.127 0.841 0.966 0.822 0.764

3 1.141 0.824 0.957 0.708 0.745

4 1.096 0.829 0.984 0.892 0.954

6.1.3. Future Year Quarterly Concentration Calculation

The next step in the SMAT process is to cal culate future quarterly mean concentration estimates (DVFs) for each component of PM2.5. To accomplish this, the quarterly component-specific DVBs from Table 6-4 are multiplied by the component-specific RRFs contained in Table 6-6. The quarter ly component DVFs for the monitor in the Floyd County PM2.5 nonattainment area are provided below in Table 6-7.

Table 6-7. Quarterly Comp onent Future Design Values for Monitor in the Floyd County Nonattainment Area

AIRS ID Site Name qtr Crustal

DVF EC

DVF OC

DVF SO4

DVF NO3

DVF NH4

DVF PBW

DVF

13-115-0005 Rome 1 0.439 0.630 5.363 3.047 0.274 0.970 0.859

2 1.117 0.627 6.700 4.171 0.009 1.229 1.203

3 0.849 0.331 5.428 5.972 0.007 1.511 1.303

4 0.741 0.459 4.868 3.549 0.466 1.092 0.895

6.1.4. Future Year Annual Average Estimate

The next step in the SMAT process is to sum the quarterly mean components from Table 6-7 to get annual mean PM2.5 values for each quarter. The quarterly mean PM2.5 values are then averaged to produce a “non-blank” future year annual average PM2.5 estimate for each FRM site in the nonattainment area (Table 6-8).

Table 6-8. Quarterly Mean PM2.5 Mass estimates for 2009

AIRS ID Site Name Non-Blank
Mass Q1 Non-Blank
Mass Q2 Non-Blank
Mass Q3 Non-Blank
Mass Q4 Non-Blank Mass Avg.

13-115-0005 Rome 11.581 15.057 15.402 12.071 13.527

Finally, the “non-blank” future year annual average PM2.5 estimate is corrected for the

0.5 μ g/m 3 blank mass. The 2009 annual PM2.5 con centration (DVF) is then compared to the NAAQS (15.0 μ g/m 3 ). Since the value is less than 15.0 μ g/m 3 , the test is passed.

127 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Table 6-9. Estimated Annual Mean 2009 PM2.5 Mass Compared to the DVB

AIRS ID Site Name 2002

Annual

DVB 2009

Non-Blank

Mass Blank

Mass 2009

Annual

DVF

13-115-0005 Rome 15.7 13.5 0.5 14.0

6.2 Supplemental Analysis

The Attainment Guidance asserts that all attainment demonstrations should be accompanied by supplemental analysis that further supports the modeling conclusions. This supplemental analysis can include additio nal analyses of air quality, emissions and meteorological data, and consider modeli ng outputs other than the results of the

attainment test. If the attainment test resu lts fall short of the standard, the results of corroboratory analyses may be used in a we ight of evid ence determination (WOE) to show that attainment is likely despite modeled results, which may be inconclusive.

The Attainment Guidance defines the guideline s for supplemental analysis/WOE for the

annual PM2.5 standard as follows:

- Site with a DVF less than 14.5 μ g/m 3 should submit basic supplemental analysis

to confirm the outcome of the model attainment test.

- Sites with a DVF between 14.5 and 15.5 μ g/m 3 should submit a weight of

evidence demonstration to aggregate supplemental analysis to support the model

attainment demonstration. - Sites with a DVF greater than or equal to 15.5 μ g/m 3 should consider additional control measure to ensure attainment, as more qualitative analysis is unlikely to

demonstrate attainment.

Because the Floyd County PM2.5 nonattainme nt monitor has a DVF lower than 14.5

μ g/m 3 , the following supplemental analysis to corroborate modeling results should be adequate to complete the attainment demonstr ation, rather than a WOE analysis to show attainment. In the following sections we explore refinements to the attainment test, additional modeling studies, an d air quality and emissions trends as part of a supplemental analysis for the Floyd County PM2.5 nonattainment area.

6.2.1 Additional Air Quality Modeling

The Attainment Guidance suggests several additional modeling exercises that can be performed as part of supplemental/WOE an alysis. Suggestions include completing additional analysis on the air quality modeling preformed, or modeling alternative set ups and emissions as part of sensitivity. Each of theses items will be discussed in the following sections.

128 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

6.2.1.1 Analysis of Modeled Cell-Day Concentrations

In Section 7.0 of the Attainment Guidance, various aspects of air quality models, modeled performance, and uncertainties associated with the length of modeled episodes and

limited observational datasets are described. Section 7.1 suggests that some types of “absolute” modeling results may be used to assess general progress towards attainment from the baseline inventory to the projected future inventory. The Attainment Guidance goes on to describe several metrics that can be considered as part of this type of additional analysis, which include:

1. Percent change in total amount of PM2.5 > 15 μ g/m 3 within the nonattainment

area 2. Percent change in number of grid cells > 15 μ g/m 3 within the nonattainment area 3. Percent change in gr id cell-hours (days) > 15 μ g/m 3 within the nonattainment area 4. Percent change in maximum modeled 24-hour PM2.5 concentrations within the

nonattainment area

As the US EPA notes in the Attainment Gu idance, care should be taken in interpreting

absolute metrics if the model evaluation s hows a large under predic tion or over prediction of PM2.5 concentrations, because under (over) prediction of observed concentrations will make it artificially easy (hard) to show progress towards absolute attainment levels.

Because of the complexity of the model extraction for PM2.5, only the third metric is presented for supplemental analysis. In this analysis, all 364 days were used. The celldays counts of absolute modeled PM2.5 conc entrations were tallied from both the 2002 baseline and the 2009 attainment year modeling run for each day. Data was extracted for only the grid cells that contained a porti on of the Floyd County nonattainment area. Figure 6-1 highlights the 17 cells that enco mpass the Floyd County nonattainment area.

129 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Figure 6-1. Grid cells for which the air quality metrics were applied in the Floyd County PM2.5 nonattainment area.

The cell-days counts were binned based on concentration ranges of 5 μ g/m 3 intervals. Figure 6-2 presents the cell-da ys count results graphically and shows an increase in the number of cell-days below 15 μ g/m 3 . By 2009 67.4% of cell-days fall in the 0 –15 range,

a substantial increase from the 60.6% in 2002. Raw cell-days counts show a total of 421 cell-days (17.3% decrease) shifted from the greater than 15 μ g/m 3 range to the less than

15 μ g/m 3 range between 2002 and 2009 (Table 6-10).

Figure 6-2 also shows a decrease in the number of cell-days in the 15 – 20 μ g/m 3 bin (23 cell-days decrease), the 20 – 25 μ g/m 3 bin (197 cell-days decrease), the 25 – 30 μ g/m 3

bin (169 cell-days decrease), the 30 – 35 μ g/m 3 bin (21 cell-days decrease), and the 35 –

40 μ g/m 3 bin (10 cell-days decrease). In additi on, the number of cell-days in the greater

than 40 μ g/m 3 bin decreased to 0 cell-days (100. 0% decrease) from 2002 to 2009. Overall, the results from the air quality mode ling metric are encouraging as shown by the

substantial increase in the number of cell-days below 15 μ g/m 3

.

130 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Figure 6-2. Percentage of Cell-Days in the Floyd County Nonattainment Area within Concentration Categories for 2002 and 2009.

Table 6-10. Number of Cell-Days within Concentration Bins. Increases (decreases)

in the number of cell-days (and percent ch ange) within the bins are noted by red (blue) coloration.

Concentration

[ μ g/m 3 ] 2002 2009 Difference % Difference

0-5 357 413 56 15.7

5-10 1642 1861 219 13.3

10-15 1752 1898 146 8.3

15-20 1316 1293 -23 -1.7

20-25 734 537 -197 -26.8

25-30 325 156 -169 -52.0

30-35 49 28 -21 -42.9

35-40 12 2 -10 -83.3

> 40 1 0 -1 -100.0

131 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

6.2.1.2 EPA CAIR Modeling

One way to acquire modeling sensitivity runs is to examine the modeling results from other Regional Planning Organizations or from EPA modeling studi es. Other modeling studies may use different physical and chemical modeling options for their meteorological and air quality modeling runs, which would provide a sensitivity of these different options.

An air quality modeling exercise that c ontained results for the Floyd County PM2.5

nonattainment area is the USEPA’ s modeling for the Clean Air Interstate Rule (CAIR). The Technical Support Document for the final CAIR, March 2005, provided modeling results with and without the implementati on for the CAIR. Diff erences between the USEPA’s modeling and the attainment demons tration are: 1) th e 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 6.1 are the same. These modeling results are listed in Table 6-11 below.

Table 6-11. US EPA CAIR Modeling Result s for Floyd County (highest monitor)

Future Year PM2.5 ( μ g/m 3 )

2010 15.87

2015 15.79

The USEPA’s results were for the highest monitor in counties with more than one monitor. The USEPA’s modeling results pr edicts that the Fl oyd County nonattainment area would be slightly above the annual PM2.5 standard in 2010 and 2015

. Although these projections are above the PM2.5 stan dard, it should be noted that the CAIR modeling did not account for all the EGU controls that will be installed by 2009. If the CAIR modeling had properly accounted for thes e controls, it is highly likely that the Floyd County nonattainment area would have m odeled attainment of the annual PM2.5 standard by 2010 and 2015.

6.2.2 Air Quality and Emission Trends Analysis

Figure 6-3 shows changes of annual PM2.5 concentrations (ar ithmetic average of quarterly averages) from 1999 to 2008. Overa ll, PM2.5 concentrations have decreased for this time period.

132 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

The overall trend can be divided into thr ee periods. The first period (1999 to 2002) shows relatively large decreases with each year. The second period (2003 to 2004)

shows increased PM2.5 concentrations co mpared with 2002. The last period (2005- 2008) shows a small decrease of PM2.5 c oncentrations through 2007 and a marked

decrease in 2008. The actual values used to cr eate Figure 6-3 are listed in Table 6-12. In 2008, the PM2.5 annual mean concentration dropped to 12.7 μ g/m 3 , which is well below

the 15.0 μ g/m 3 standard.

133 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Table 6-12. Annual Average PM2.5 values ( μ g/m 3 ) in Floyd County, 1999 - 2008.

Year Rome (13-115-0005)

1999 21.3

2000 17.9

2001 16.2

2002 14.6

2003 16.2

2004 15.6

2005 16.6

2006 15.9

2007 15.6

2008 12.7

0 5 10 15 20 25

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

YearConcentration [ug/m3] 13-115-0005

Figure 6-3. Annual PM2.5 Average Values for the Rome Monitor (13-115-0005) in the Floyd County Nonattainment Area.

When one takes into account the period of record, PM2.5 design values improved since 2001. It is also important to note the Rome monito r (13-021-0012) has maintained

134 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

design values that were close to the NAAQS for design value periods starting with 2000 – 2002, with the 2006 – 2008 design value droppi ng below the standard (See Table 6-13).

135 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Table 6-13. Three-year Desi gn Values for the Monitor ( 13-115-0005) in the Floyd County PM2.5 Nonattainment Area.

Site Name 99-01

DV 00-02

DV 01-03

DV 02-04

DV 03-05

DV 04-06

DV 05-07

DV 06-08

DV

Rome 18.5 16.2 15.7 15.5 16.2 16.1 16.0 14.7

When evaluating the trends in air quality values it is important to not e that there are still significant sulfur dioxide (SO2) emission re ductions that are expected prior to the attainment year in the utility sector. As a result of CAIR and the Georgia Multipollutant Rule, multiple scrubbers will be installed by Georgia Power on some of their large coalfired power plants between 2007 and 2009, in cluding all four of the EGUs in Floyd County. Table 6-14 lists the units in the stat e of Georgia and shows the date the controls did come or are expected to come on lin e and the estimated am ount of yearly SO2 emissions reductions. In total, over 244,000 tons of SO2 will be reduced annually in Georgia. This reduction represents a 43% reduction in state-wide SO2 emissions from point sources compared to 2002 levels (571,410.9 tons/year). As sulfates are one of the larger contributors to total PM2.5 in Georgi a, this substantial reduction in SO2 should result in significant reductions of the obs erved PM2.5 concentrations and push the annual average PM2.5 concentration at the Rome -Coosa High School site (13-115-0005) below the NAAQS.

Table 6-14. Projected SO2 emission reducti ons from new controls on Georgia Power

EGUs in 2008 and 2009.

Facility Unit Control Date 1 2007 SO2

Emissions 2
(tons) Estimated

2008 (tons) Estimated

2009 (tons) 2008
Reductions (tons) 2009
Reductions (tons)

Bowen 1 5/30/2010 42,967.2 42,967.2 42,967.2 0.0 0.0

2 5/30/09 39,888.2 39,888. 2 17,783.5 0.0 22,104.7

3 5/01/08 64,745.5 23,740. 0 3,237.3 41,005.5 61,508.2

4 12/31/08 49,240.0 49,240. 0 2,462.0 0.0 46,778.0

Hammond 1 5/30/08 6,028.2 2, 687.6 301.4 3,340.6 5,726.8

2 5/30/08 6,047.4 2,696. 1 302.4 3,351.3 5,745.0

3 5/30/08 6,147.9 2,740. 9 307.4 3,407.0 5,840.5

4 5/30/08 29,585.3 13,190. 1 1,479.3 16,395.2 28,106.0

Wansley 1 12/31/08 42,739.9 42,739.9 2,137.0 0.0 40,602.9

2 5/30/09 51,105.7 51,105. 7 22,784.6 0.0 28321.1

TOTAL (tons) 338,495.3 270,995.8 93,762.0 67,499.5 244,733.3

(1) Dates prior to 2009 are actual field installation da tes. Dates 2009 or later are company-provided

forecast installation dates. (2) Calculated from continuous emissions monitor data.

136 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Statewide EGU emission trends for SO2 (bas ed on CEMS data) are plotted for Georgia and the neighboring states in Figure 6-4. The 2008 and 2009 SO2 emissions for Georgia

are estimated based on the emission reductions discussed in Table 6-14. The annual average PM2.5 concentrations in Floyd Count y (13-115-0005) are plotted in the same figure to allow a comparison between emission changes and changes in PM2.5

concentrations. The 2009 PM2. 5 concentration is from the model projections and the 2008 value is calculated by in terpolating between the 2007 observations and the 2009 projections. SO2 emissions in Georgia are higher in 2003-2007 compared to 2002, as are PM2.5 concentrations. However, PM2.5 conc entrations start to trend downward in 2006 due to emission reductions in neighboring st ates. The large emission reduction in Georgia between 2007 and 2009 are projected to be more than enough to bring Floyd County into attainment. It should be noted that the year-to-year variability in PM2.5

concentrations are due to a combinati on of emission changes and meteorological

fluctuations.



## Monitoring Trends in Floyd County

0 100,000 200,000 300,000 400,000 500,000 600,000 700,000 800,000 900,000 1,000,00019992000200120022003200420052006200720082009SO2 Emissions (Tons/Year)

0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0PM2.5 (μg/m3)

Figure 6-4. PM2.5 monitoring trends 1 in Floyd County (13-115-0005) compared to

statewide EGU SO2 emissions from Georgia and neighboring states.

(1) 2009 value is modeled projection and 2008 value is interpolated from 2007 and 2009. SO2-GA SO2-AL SO2-FL SO2-NC

SOX-SC SO2-TN 13-115-0005

137 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

6.2.3 Supplemental Analysis Conclusions

After examining the totality of the modeli ng evidence, GA EPD is confident the Floyd County nonattainment area should reach attainme nt status by the 2009 deadline. PM2.5 annual average concentrations should conti nue to decrease due to substantial sulfate reductions anticipated in the state over th e next two years. GA EPD feels these reductions will more than likely allow the PM2.5 nonattainment areas to achieve the NAAQS by 2009.

6.3 Unmonitored Area Analysis

The modeled attainment test does not address fu ture air quality at locations where there is not a PM2.5 monitor nearby. To guard against the possibility that ai r quality levels could

exceed the standard in areas with limited monitoring, Section 3.4 of the Attainment

Guidance suggests that additional review is “n ecessary, particularly in nonattainment

areas where the ozone or PM 2.5 monitoring network just meets or minimally exceeds the size of the network required to report data to Air Quality System (AQS).” This review is intended to ensure that a control strategy lead s to reductions in PM2.5 and its constituent pollutants at other locations that could have baseline (and future) design values exceeding the NAAQS were a monitor deployed there. The test is called an “unmonitored area analysis”. 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.

GA EPD currently operates one FRM monitor in the nonattainment county and believes that the density of this monitoring networ k relieves the necessity of applying this additional analysis. However, GA EPD decide d to apply some additional analysis and

looked at 2009 PM2.5 concentrat ions directly from the mode l (did not apply SMAT or SANDWICH to results). A map of the PM2.5 monitor and its position relative to the 12- km modeling grid is provided in Figure 6-4. As can be seen by the figure, the spatial coverage of the monitor, and the resulting “n earby” 3x3 array, covers the majority of the urban area where PM2.5 tends to be higher. In addition, the absolute annual modeled PM2.5 concentrations for each grid cell in the vicinity of the Floyd County nonattainment area have been added to Figure 6-4. From th is figure, it can be seen that there are no significant concentration gradients across the area of interest. Therefore, it can be

concluded that there are no unmon itored hotspots that need to be addressed. It should be

noted that the 2009 absolute modeled PM2. 5 annual concentrations (no SMAT or SANDWICH) are lower than that calculate d at the FRM monitor using SMAT and SANDWICH. However, this discrepancy betw een the absolute and relative (RRF) 2009 concentration will have no impact on our conclusion that there are no unmonitored hotspots in the Floyd County area.

138 of 148Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA

Figure 6-5. Modeled 2009 Annual Mean PM2.5 Concentration near the Floyd County Nonattainment Area on the VISTAS 12km Grid

6.4 Data Access

The modeling input and output files are very large and it would not be reasonable to

submit all of these files with the SIP attainment demonstration. These include all files used to process the emissions, meteorology an d air quality models and any other files used to develop the modeling. To request ac cess to these files please contact the Georgia

EPD Air Protection Branch’s Data & Modeling Unit at 404-362-4851.

139 of 148Other Clean Air Act Requirements PM2. 5 Attainment SIP - Floyd County, GA

Section 7. Other Clean Air Act Requirements

Section 172(c) of the CAA, as amende d, contains the plan requirements for nonattainment areas in general. The Floyd County PM2.5 nona ttainment area must meet these requirements, which are listed in Table 7-1 and summarized below.

Table 7-1. General Plan Requi rements for Nonattainment Areas

Federal

CAA Description Found Where in Plan?

172(c)(1) Provide for the implementation of RACM as expeditiously as practicable and shall provide for attainment of the primary NAAQS Section 5.5

172(c)(2) Provide for Reasonable Further Progress Section 7.2 172(c)(3) Provisions shall include a comprehensive current inventory of actual emissions from all sources of the relevant pollutant or pollutants in such area, including periodic revisions as determined necessary. Section 7.3, Appendix I.

172(c)(4) Plan shall expressly identify and quantify the emissions of any such pollutant(s)

which will be allowed in accordance from section 173(a)(1)(B) from the construction and operation of major new or modified stationary sources in each such area. Emissions quantified for this purpose will

be consistent with the achievement of RFP

and will not interfere with attainment of the applicable NAAQS. Section 7.5

172(c)(5) Plan shall require permits for the construction of new or modified major stationary sources as applicable. Section 7.5

172(c)(6) Plan shall incl ude enforceable emission

limitations and such other control measures, means or techniques as well as schedules and timetables for compliance as deemed necessary to provide for attainment of the applicable NAAQS. Section 5

172(c)(7) Shall meet the applicable provisions of section 110(a)(2). Section 7.7

172(c)(8) Administrator may allow the use of equivalent modeling, emission inventory, and planning procedures. Section 7.9.

172(c)(9) Plan shall provide for the implementation of specific measures to be undertaken if

the area fails to make RFP or to attain the applicable NAAQS. Such measures shall be included in the plan revision as contingency measures to take effect in any such case without further action by the

State/Administrator. Section 5.3

140 of 148Other Clean Air Act Requirements PM2. 5 Attainment SIP - Floyd County, GA

7.1 RACT/RACM Requirements

Section 172(c)(1) of the CAA requires SIPs to provide for the implementation of all reasonably available control measures (R ACM) to demonstrate attainment as expeditiously as practicable. A subset of RACM is RACT, which relates specifically to stationary point sources. RACM and RACT are discussed in Section 5.5.

7.2 Reasonable Further Progress

Reasonable further progress (RFP) is a set of control measures with milestones that demonstrates that an attainment plan is being implemented on schedule. However, 40 CFR 51.1009(b) states the following: “If the State submits to EPA an attainment demonstration and State implementation plan for an area which demonstrates that it will attain the PM NAAQS within five years of the date of designati on, the State is not required to submit a separate RFP plan. Compliance with the emission reduction

measures in the attainment demonstration and State implementation plan will meet the requirements for achieving reasonable further progress for the area.” This SIP demonstrates attainment of the NAAQS within five years of designation, so no RFP plan is required.

7.3 Actual Emissions Inventory

Section 172(c)(3) requires the development of statewide inventorie s of emissions of direct PM2.5 and PM2.5 precursors. Such inventories were due to EPA 3 years after designation of the PM2.5 nonattainment areas, or by April 5, 2008. The Georgia EPD met this requirement through the submittal of the 2002 emission inventories under the Consolidated Emission Reporting Rule (CERR). The final emission inventories used in the attainment demonstration will go thr ough the public hearing process with the full attainment demonstration, which will include any updates or revisions that are necessary

since the CERR submittal.

7.4 Periodic Emissions Inventory

Section 172(c)(3) requires periodic inventor y submittals. The Georgia EPD met this requirement by submitting the CERR inventory to EPA on June 1, 2007.

7.5 Permit Program Requirements

Section 172(c)(4) requires the id entification and quantification of emissions that will be allowed under the provisions of section 173(a)(1)(B), pertaining to zones identified by

the Administrator to which economic devel opment should be targeted. Georgia has no such zones targeted for economic devel opment identified by the Administrator.

141 of 148Other Clean Air Act Requirements PM2. 5 Attainment SIP - Floyd County, GA

Section 172(c)(5) requires a permit program cons istent with the requirements of Section 173. Georgia EPD updated rules for nonattain ment new source review (NNSR) effective July 25, 2007. These provisions can be found at 391-3-1-.03(8) of the Georgia Rules for Air Quality Control. The Georgia EPD has met the permit program requirements for a PM2.5 nonattainment area. Georgia EPD is currently complying with the recently promulgated May 16, 2008, rulemaking incl uding implementation of nonattainment NSR under 40 CFR 51, Appendix S, until Georgia has amended its nonattainment New Source Review requirements consistent with this rulemaking.

7.6 Other Measures

Section 172(c)(6) requires the nonattainment SI Ps to include enforceable limits and other control measures, along with schedules for compliance as needed to demonstrate

attainment. Section 5 of this document discu sses in detail the Federal and State measures that are necessary for attainment.

7.7 Compliance with Section 110(a )(2) (Infrastructure Elements)

Section 172(c)(7) requires nonatta inment SIPs to meet the applicable provisions of Section 110(a)(2). Georgia EPD has submitted a letter dated July 23, 2008, to Mr. James I. Palmer, Jr., Regional Administrator for EP A Region 4, certifying that its existing SIP contains provisions that a ddress the requirements for th e 1997 PM2.5 NAAQS for section 110(a)(2). Georgia EPD submitted supplemental information in a letter dated September 22, 2008, regarding the requirements for sectio n 110(a)(2)(G). A copy of these letters can be found in Appendix N.

EPA signed the final rule regarding the status of the el ements of Section 110(a)

Infrastructure Elements for 1997 8-hour PM2.5 NAAQS on October 3, 2008. Georgia was found to have a complete SIP revision on file at EPA that addresses these

infrastructure elements for PM2.5.

7.8 Equivalent Techniques

The Georgia EPD believes that the procedur es for modeling, emissions inventory and planning follow the US EPA guidance and is not requesting appr oval for equivalent techniques, as envisione d under Section 172(c)(8).

7.9 Contingency Measures

The Clean Air Act requires States containi ng nonattainment areas to adopt contingency

measures that will take effect without fu rther action by the Stat e or US EPA upon a determination by the US EPA that an area failed to demonstrate Reasonable Further Progress (RFP) or to timely attain the a pplicable NAAQS, as described in Section 172(c)(9). These measures ar e discussed in Section 5.3.

142 of 1482009 Motor Vehicle Emissions Budget PM 2.5 Attainment SIP – Floyd County, GA

Section 8. 2009 Motor Vehicle Emissions Budget

8.1 Background

Attainment demonstrations are control strategy SIP revisions. As such, they establish motor vehicle emissions budgets (MVEB). A motor vehicle emissions budget is described in EPA's transportation conformity rule 1 as "...the implementation plan's estimate of future [motor vehicle] emissi ons." Such budgets establish caps on motor vehicle emissions; projected emissions from transportation plans and programs must be equal to or less than these caps for a positive conformity determination to be made.

8.2 Establishment of 2009 Motor Vehicl e Emissions Budgets for the Floyd County PM2.5 Nonattainment Area

In preparation for this Floyd County PM2.5 Attainment Demonstration, EPD worked closely with the Georgia Department of Transportation (GDOT) and the Floyd-Rome Urban Transportation Study (FRUTS), th e metropolitan planning organization for Rome/Floyd County, to develop the estimates of mobile 2 source emissions for the Floyd County nonattainment area. Mobile source inventories for 2009 were developed using the latest available planning assumptions, the most recent travel demand model, and

EPA's latest motor vehicle emission factor model, MOBILE6.2.03. The methodology used to calculate the highway mobile s ource emissions on which the 2009 MVEB is based is discussed below and, in greater detail, in Appendix J.

The MOBILE6.2 motor vehicle emission f actor model was used to calculate 2009 emission factors with all proposed 2009 mob ile source control rules in place. The

emission factors reflect all federal controls , e.g., the Federal Motor Vehicle Control Program including Tier 1 and (beginning with 2006 models) Tier 2 tailpipe standards; and the National Low Emission Vehicle pr ogram, and Georgia's seasonal low-RVP gasoline marketing requirement.

The emission factors resulting from th e MOBILE6.2 runs for the Floyd County

nonattainment area were used with GDOT's li nk-based emissions estim ation procedure to calculate 2009 tons per year em issions in the following manner:

• For each of four times of day (a.m. peak, midday, p.m. peak, and night), the HPMSadjusted 3 2009 VMT from each link in the Rome/Floyd travel demand model were multiplied by the 2009 MOBILE6.2 emission factor at the average speed closest to the congested-flow speed on that link.

1 40 CFR Part 93.124(a)

2 The term "mobile" is used to describe emissions from on-road motor vehicles.

3 The VMT from the travel demand model were adjusted based on the VMT estimates that GDOT develops for the Highway Performance Monitoring System (HPMS).

143 of 1482009 Motor Vehicle Emissions Budget PM 2.5 Attainment SIP – Floyd County, GA

• Emissions from all the links and all four time periods were summed together to get grams per day inventories, which were convert ed from grams per day to tons per day, then multiplied by 365 to get tons per year.

These mobile source inventories reflect up-to-date mobile modeling assumptions, including 2009 VMT projected from a trav el demand model and 2009 emission factors

from EPA's latest mobile source emission factor model. Details of the mobile source emissions modeling methodology, along with the MOBILE6.2 input files, emission factors, and other documentation, are in Appendix J.

Table 8-1 shows the calcula ted emissions inventory fo r the Floyd County PM2.5

nonattainment area.

Table 8-1. 2009 PM2.5 Motor Vehicle Emissions Budget, Floyd County

Nonattainment Area

PM2.5 (tons/ y ear) 2009 Mobile Emissions for Floyd County 41.8290 2009 Motor Vehicle Emissions Budget 41.8290

This Floyd County PM2.5 Attainment Dem onstration hereby establishes a 2009 motor vehicle emissions budget of 41.8290 PM2.5 tons per year for the Floyd County PM2.5 nonattainment area. Interagency consultati on among the relevant agencies occurred during the development of this MVEB and pr ior to the submittal of this attainment demonstration. Full implementation plan documentation was provided to EPA, and

EPA's stated concerns have been addressed.

The MVEB established by this attainment de monstration is based on new estimates of VMT and speeds from an updated, state-of-t he-art travel demand model; on the latest

version of EPA's motor vehicle emission fact or model; and on regist ration distributions by age developed using registration data 4 obtained from R.L. Polk & Company.

To show the MVEB "together with all other emissions sources 5 ," point, area, and nonroad emissions from the 2009 "best-and-fina l" modeling inventor ies developed by the

VISTAS/ASIP contractors were used. Tota l projected 2009 annual PM2.5 emissions for the Floyd County nonattainment area ar e shown in Table 8-2 below.

4 Registration data was from R. L. Polk & Co.'s National Vehicle Population Profile ® current as of October 2002 and from R. L. Polk & Co.'s TIPNet ® current as of March 2003. See Appendix C, Exhibit 1, for more details on the registration distribution by age.

5 Section 93.118(e)(4)(iv) of the transportation conformi ty rule requires that the "motor vehicle emissions budget(s), when considered together with all other emissions sources, is consistent with applicable requirements for...attainment...."

144 of 1482009 Motor Vehicle Emissions Budget PM 2.5 Attainment SIP – Floyd County, GA

Table 8-2. Floyd County Nonattainment Area Total Projected 2009 PM2.5 Emissions, Tons/Year

Point Nonroad Area Mobile total

1,104.4915 52.1000 1,463.0616 41.8290 2,661.4821

145 of 148Summary and Conclusion PM2.5 A ttainment SIP – Floyd County, GA

Section 9. Summary and Conclusion

This section summarizes and concludes the results of the attainment demonstration

documented in this SIP revision. EPA designated the Floyd County area as nonattainment for the annual PM2.5 NAAQS on January 5, 2005, and confirmed the designation on April 5, 2005. The observe d 2001 - 2003 PM2.5 design value at the

nonattainment area monitor violated the annual standard, as shown in Table 9-1 below.

Table 9-1. 2001 – 2003 PM2.5 Design Va lue for Floyd County Nonattainment Area

Monitor

Site name Monitor ID PM 2.5 Design

Value
(μg/m 3 ) PM 2.5 Standard
(μg/m 3 )

Rome-Coosa High School 13-115-0005 15.7 15.0

Speciated monitoring data from the Rome – Coosa High School site have shown that the most significant components of ambient PM2.5 are sulfates and orga nic carbon. Sulfates are formed primarily from sulfur dioxide em issions from coal-fired electric generating units (EGUs), including EGUs located inside the nonattain ment area and other more

distant EGUs located both inside and outside of Georgia.

Control measures that may be credited in the SIP toward attainment are those that have been or will be implemented after 2002 but before 2009 (the modeled attainment year). Because of the large contribution of sulfat es to the ambient PM2.5 problem in the nonattainment area, the most important measur es for achieving attainment are those that

reduce SO2 emissions from coal-fired EGUs. Georgia’s Multipollutant Rule (391-3-1- .02 (2) (sss)), enacted in 2007, is expected to achieve the needed reductions by reducing

SO2 emissions from EGUs. The total estimat ed reduction of SO2 emissions from seven EGUs between 2002 and 2009 is equivalent to 29.1 percent of pr ojected 2009 statewide SO2 emissions (744,000 tons/yr) if no controls were assumed. Other modeled state and federal control measures, as well as unm odeled measures, will contribute to PM2.5

reduction to a smaller extent.

Models were used to demonstrate attainment of the PM2.5 standard and the modeling was performed per EPA’s Attainment Modeling Guidance. The modeling was performed in conjunction with the re gional haze modeling being done by VISTAS and the PM 2.5 and ozone modeling being done by ASIP. The models used were as follows:

• Meteorology model: MM5

• Emissions model: SMOKE

• Air Quality model: CMAQ

146 of 148Summary and Conclusion PM2.5 A ttainment SIP – Floyd County, GA

An emissions inventory for the modeling was developed for the baseline year 2002 and projected to 2009. The pollutant s inventoried include VOC, NOx, PM 2.5 , coarse particulate (PM 10 ), NH 3 , and SO 2 . The projection to 2009 accounted for control measures expected to be implemented.

The CMAQ modeling performance was meas ured by accepted methods. Overall, GA EPD believes that the model predictions can be used to form the scientific foundation for proposed control options because its performan ce is well within the limits of acceptable performance criteria es tablished in the Attainment Modeling Guidance.

To demonstrate attainment, the models were used to perform the SMAT test at the federal reference monitor site. The SMAT test projects future concentrations of individual PM species and then sums the results to pr oject total PM2.5. The 2009 modeled PM2.5 design value is presented in Table 9-2. Sin ce the modeled design value is less than 15.0 μg/m 3 , modeled attainment is demonstrated.

Table 9-2. PM 2.5 2009 Future (Model ed) Design Values

Federal

Reference

Monitor 2009 Annual Design Value (DVF)
(μg/m 3 ) PM 2.5 Standard
(μg/m 3 )

Rome-Coosa High School 14.0 15.0

In conclusion, this revision to Georgia’s State Implementation Plan, in accordance with regulatory requirements and guidance provided by EPA, provides a comprehensive technical analysis that demonstrates th at the Floyd County PM2.5 Nonattainment Area will attain the annual PM2.5 NAAQS on or before April 5, 2010. This demonstration is based upon implementation of the control measures described previously in this narrative

and will demonstrate attainme nt at the FRM monitor located in the Floyd County

Nonattainment Area.

147 of 148References PM2.5 Attainment SIP – Floyd County, GA

Section 10. References

Boylan, J.W. and Russell, A.G. (2006) PM and Light Extinction Model Performance Metrics, Goals, and Criteria for Three-Dimensional Air Quality Models; Atmos. Environ.

, Volume 40, pp. 4946-4959.

Emery, C., E. Tai, and G. Yarwood, 2001: Enhanced meteorological modeling and performance evaluation for two Texas episodes, A report prepared for the Texas Natural

Resources Conservation Comm ission (TNRCC), ENVIRON Inte rnational Corporation, Novato, CA.

EPA, 2007. Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5 and Regional Haze. U.S. Environmental Protection Agency, Research Triangle Park, NC. EPA-454/B-07-002. April.

IMPROVE, 1995. IMPROVE Data Guide - A Guid e To Interpret Data. University of California Davis. Prepared for National Park Se rvice, Air Quality Research Division, Fort Collins, CO. Data located at

< http://vista.cira.colostate.edu/improve/Data/IMPROVE/improve_data.htm >.

Mass, C. F., D. Ovens, K. Westrick, B. A. Colle, 2002, Does increasing horizontal resolution produce more skillful forecast. Bulletin of American Meteorological Society, 83, 407-430.

Morris, R.E., B. Koo, B. Wang, G. Stella, D. McNally, C. Loomis, C-J. Chien, and G. Tonnesen. 2007. Technical Support Document for VISTAS Emission and Air Quality Modeling to Support Regional Haze State Impl ementation Plans (Draft Final Report). ENVIRON International Corporation, Novato, California. November 14.

148 of 148