Georgia's State Implementation Plan 

for the 

Floyd County PM2.5 Nonattainment Area 

October 20, 2009 

Prepared by: 

Georgia Department of Natural Resources 

Environmental Protection Division 

Air Protection Branch 
This page was intentionally left blank 
 PM2.5 Attainment SIP – Floyd County, GA 

Preface 

This document is Georgia’s State Implementation Plan (SIP) for attainment of the Federal 

National Ambient Air Quality Standard (NAAQS) for PM2.5 in the Floyd County 

nonattainment area. The Floyd County nonattainment area includes all of Floyd County, 

Georgia. Specifically, this SIP demonstrates attainment of the annual PM2.5 NAAQS, 

promulgated in 1997, in the Floyd County 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 FINE PARTICLES ...................................................................................................... 18 

1.2 1997 NATIONAL AMBIENT AIR QUALITY STANDARDS FOR PM2.5 ........................... 19 

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

2.1 NONATTAINMENT AREA DESIGNATION................................................................... 22 

2.2 PM2.5 MONITORING STATION .................................................................................. 23 

2.3 CONCEPTUAL DESCRIPTION OF THE PM2.5 PROBLEM............................................. 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 SOURCES AND PRECURSORS ........................................................................ 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 ANALYSIS METHOD ................................................................................................. 59 

3.2 MODEL SELECTION .................................................................................................. 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 SELECTION OF THE BASE MODELING YEAR ............................................................. 65 

3.4 MODELING DOMAINS............................................................................................... 66 

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

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Table of Contents PM2.5 Attainment SIP - Floyd County, GA 

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

3.5 BASELINE EMISSIONS INVENTORY ........................................................................... 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 METEOROLOGICAL MODEL PERFORMANCE ............................................................. 80 

4.2 AIR QUALITY MODEL PERFORMANCE...................................................................... 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 FEDERAL CONTROL MEASURES FOR PM2.5 ATTAINMENT..................................... 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 STATE CONTROL MEASURES FOR PM2.5 ATTAINMENT ......................................... 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. SUMMARY OF SO2 EMISSIONS CHANGES ............................................................. 109 

5.4. CONTINGENCY MEASURES ................................................................................... 110 

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

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

5.5 UNMODELED CONTROL MEASURES....................................................................... 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 MODELED ATTAINMENT TEST ............................................................................... 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

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

6.2 SUPPLEMENTAL ANALYSIS..................................................................................... 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 UNMONITORED AREA ANALYSIS ........................................................................... 138 

6.4 DATA ACCESS ........................................................................................................ 139 

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

7.1 RACT/RACM REQUIREMENTS............................................................................. 141 

7.2 REASONABLE FURTHER PROGRESS ....................................................................... 141 

7.3 ACTUAL EMISSIONS INVENTORY........................................................................... 141 

7.4 PERIODIC EMISSIONS INVENTORY ......................................................................... 141 

7.5 PERMITT PROGRAM REQUIREMENTS ....................................................................... 141 

7.6 OTHER MEASURES ................................................................................................ 142 

7.7 COMPLIANCE WITH SECTION 110(A)(2) (INFRASTRUCTURE ELEMENTS) ............... 142 

7.8 EQUIVALENT TECHNIQUES .................................................................................... 142 

7.9 CONTINGENCY MEASURES .................................................................................... 142 

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

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

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

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List of Appendices PM2.5 Attainment 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 Visibility in the VISTAS Region 

E Insignificance of NH3, VOCs, and NOx to PM2.5 Attainment in 

Georgia Nonattainment Areas 

F Modeling Protocol For Association for Southeastern Integrated 

Planning (ASIP) Emissions and Air 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) Emissions 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) Requirements (SIP Infrastructure 

Elements): Communications dated 7-23-08 and 9-22-08 

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List of Figures PM2.5 Attainment 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 PM2.5 concentrations and composition in Atlanta (Site

ID 13-089-0002) for 2003-04 (MMO – Major Metal Oxides; Other – PM2.5 other than

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

Figure 2-15: Seasonal patterns in PM2.5 concentrations and composition in Chattanooga 

(Site ID 47-065-4002) for 2003-04 (MMO – Major Metal Oxides; Other – PM2.5 other

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

Figure 2-16: Seasonal patterns in PM2.5 concentrations and composition in Floyd County 

(Site ID 13-115-0005) for 2003-04 (MMO – Major Metal Oxides; Other – PM2.5 other

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

Figure 2-17. Seasonal patterns in PM2.5 concentrations and composition in Macon (Site

ID 13-021-0012) for 2003-04 (MMO – Major Metal Oxides; Other – PM2.5 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 

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List of Figures PM2.5 Attainment 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 PM2.5 nonattainment areas (left) and the Floyd County PM2.5

nonattainment area (right)................................................................................................. 91 

Figure 4-7. Stacked bar plots of daily PM2.5 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 

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List of Figures 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. ................................................................ 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 trends1 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 

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List of Tables PM2.5 Attainment 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. PM2.5 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 PM2.5 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 PM2.5 composition during 2003-2004 for the four STN sites in the

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

Table 2-6. Estimated primary and secondary percentage of PM2.5.................................. 39 

Table 2-7 Average factor contributions to PM2.5 (μg/m3) 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 

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List of Tables PM2.5 Attainment 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 PM2.5 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 PM2.5 at 13-115-0005................... 94 

Table 4-9. Annual model performance statistics for PM2.5 species and total PM2.5 at all

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

Table 4-10. Annual model performance statistics for PM2.5 at 13-115-0005. .................. 97 

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

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

Table 5-3. Georgia Multipollutant Rule SO2 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 SO2 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 

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List of Tables PM2.5 Attainment SIP - Floyd County, GA 

Table 6-4. Quarterly PM2.5 Component-Specific DVB (μg/m3) 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 (μg/m3) 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. PM2.5 2009 Future (Modeled) Design Values .............................................. 147 

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

Acronyms 

ASIP Association of Southeastern Integrated Planning 

CAA Clean Air Act 

CAIR Clean Air Interstate Rule 

CMAQ Community Multiscale 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 available 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 Kernel Emissions modeling system 

SOA Secondary Organic Aerosols 

STN Speciated Trends Network 

VISTAS Visibility Improvement State and Tribal Association of the Southeast 

VOC Volatile organic compound 

VMT Vehicle miles traveled 

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

Executive Summary 

This document is Georgia’s state implementation 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 microns or less, also called fine 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 (μg/m3

) or less. The nonattainment area designation 

was based upon a 2001 - 2003 design value at the Rome-Coosa High School monitor of 

15.7 μg/m3. This document does not address the 24-hour PM2.5 standard promulgated in 

December 2006, as nonattainment areas and requirements 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 utilization in this area 

includes both urban (City of Rome) and suburban land uses. 

PM2.5 is made up of a number of component 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 emission. 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 measured in this nonattainment area are sulfates and 

organic carbon. Other components are present in small fractions. 

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

Sulfate has made up approximately 30 percent 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. Atmospheric 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 attainment 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, the year in which modeling demonstrates 

attainment. 

Control measures for attainment focus on control of SO2 (and therefore sulfates) from 

EGUs. Biogenic formation of organic carbon is not addressed by control measures in this 

SIP. Significant State measures include Georgia 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 benefit toward demonstration of 

attainment in calendar year 2009. Federal 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 and Recreational Engines Standard 

• NOx SIP call in surrounding states 

The Clean Air Interstate Rule (CAIR) provides for reductions of both SO2 and NOx. The 

other federal measures provide for reductions of NOx and direct PM emissions.

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

PM fine concentrations. These measures include: 

15 of 148 
Executive 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 Scherer to lower sulfur coal; and 

• Planned early start-up of SO2 scrubbers at two EGUs (Bowen Unit 2 and Wansley 

Unit 2). 

These measures are discussed in more detail 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 SHOWING 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 are presented in Table E-1. 

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

EGUs in 2008 and 2009. 

Facility Unit Control Date1 2007 SO2 

Emissions2

(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.

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

Since it is performed on the basis of individual PM species (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 concentrations to observed concentrations in the baseline year (2002). 

Then a historical baseline emissions inventory (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 baseline average annual concentration, known as 

the relative response factor (RRF), is calculated 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 individual 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 provided in Table E-2. Since the modeled 

design value is less than 15.0 μg/m3, modeled attainment is demonstrated. Supplemental 

analyses (in addition to SMAT) are presented that also support the demonstration of 

attainment. 

Table E-2. PM2.5 2002 Baseline Design Values and 2009 Future (Modeled) Design 

Values 

Federal 

Reference 

Monitor 

Site ID 2002 Annual Design 

Value (DVB) 

 (μg/m3) 

2009 Annual 

Design Value 

(DVF) 

 (μg/m3) 

Rome-Coosa 

High School 

13-115-

0005 

15.7 14.0 

 As required by the EPA Clean Air Fine Particle Implementation Rule, sources of PM2.5 

and its precursors within the Floyd County Nonattainment Area were evaluated to verify 

that they were meeting at least 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 states 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 attainment five years 

after designation, so no RFP plan is required. 

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Executive 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 Demonstration 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 material to support the SIP narrative. 

Section 1. Introduction 

1.1 Fine Particles

Fine particles in the atmosphere, which may be solid or liquid, are comprised of a 

complex mixture of components. Common constituents include: sulfate (SO4); nitrate 

(NO3); ammonium (NH4); elemental carbon; a great variety of organic compounds; and 

inorganic material (including metals, dust, sea salt, and other trace elements) generally 

referred to as “crustal” material, although it may contain material 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 PM2.5). 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 liquid particles (e.g., elemental carbon from diesel 

engines or fire activities, or condensable organic particles from gasoline engines). 

“Secondary” particles (e.g., sulfate and nitrate) form in the atmosphere from emissions of 

gaseous precursors (e.g., SO2 and NOx) that subsequently undergo chemical reactions to 

form particulate matter. Secondary organic 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 PM2.5 based 

on evidence from numerous health studies demonstrating that serious health effects are 

associated with exposures to elevated levels of PM2.5. Epidemiological studies have 

shown statistically significant correlations between elevated PM2.5 levels and premature 

mortality. Other important effects associated with PM2.5 exposure include aggravation 

of respiratory and cardiovascular disease, changes in lung function and increased 

respiratory symptoms, as well as new evidence for more subtle indicators of 

cardiovascular health. Individuals particularly sensitive to PM2.5 exposure include older 

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Introduction PM2.5 Attainment SIP - Floyd County, GA 

adults, people with heart and lung disease, and children. [Source: Preamble to Clean Air 

Fine Particle Implementation Rule – Final Rule, April 25, 2007.] 

1.2 1997 National Ambient Air Quality Standards for PM2.5 

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

Description Standard (μg/m3

) 

Annual arithmetic mean concentration1 ≤ 15.0 

24-hour average concentration, 98th percentile1 ≤ 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 spatially averaged sites) is in attainment of 

the annual PM2.5 standard when the annual standard design value is less than or equal to 

15.0 micrograms per cubic meter (μg/m3). The annual standard design value is the 3-

year average of the annual mean, which is in turn the average of one year’s four calendarquarter averages. A monitoring site (or group of spatially-averaged sites) is in attainment 

of the 24-hour PM2.5 standard when the 24-hour standard design value is less than or 

equal to 65 μg/m3. The 24-hour standard design value is the three-year average of annual 

98th percentile 24-hour averages. The annual 98th percentile 24-hour average is the 24-

hour average PM2.5 concentration which is higher than 98 percent of the year’s valid 24-

hour averages. Therefore, to achieve attainment of the 1997 PM2.5 standards by a given 

date, the annual and 24-hour standard design values 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 achieve 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 PM2.5 NAAQS can be found in Appendix N of 40 

CFR Part 50. 

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Section 2. Floyd County Nonattainment Area 

There are currently four PM2.5 nonattainment areas in Georgia: Chattanooga (which 

also includes parts of Alabama and Tennessee), Floyd County, Atlanta, and Macon. 

Figure 2.1 shows their locations. The Floyd County 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 

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

The geographic boundaries of the Floyd County PM2.5 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 County was 90,565 in 2000 and is estimated at 

95,322 in 2006. The nonattainment area designation, the PM2.5 monitoring station, 

major PM2.5 sources, PM2.5 precursors, the 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 

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

2.1 Nonattainment Area Designation

EPA, based on data submissions from states 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 sources that contribute to the nonattainment 

status of a county with a nonattaining design value. Nonattainment counties are grouped 

together into nonattainment areas based on location within common metropolitan 

statistical areas (MSAs). EPA made initial designations of the nonattainment areas, 

including the Floyd County nonattainment area, for the PM2.5 NAAQS on January 5, 

2005 (70FR944), and amended the designations on April 5, 2005 (70FR19844). 

The designation of the Floyd County nonattainment 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 potentially included versus excluded areas; 

• Factor 3: Population density and degree of urbanization including 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 criteria 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. Details 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 PM2.5 Design Value 

 (μg/m3) 

Rome-Coosa High School 13-115-0005 15.7 

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2.2 PM2.5 Monitoring Station

There is currently one ambient PM2.5 monitoring site in the Floyd County nonattainment 

area. The location of the Rome-Coosa High 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 kilometers from the monitor. The site is 

considered to be part of the State and Local Air Monitoring Stations (SLAMS) 

monitoring network, with the monitoring objective of sampling for population exposure. 

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

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

One PM2.5 Federal Reference Method (FRM) monitor and one PM2.5 speciation monitor 

are located at the Rome-Coosa High School site (13-115-0005). The PM2.5 FRM monitor 

was installed in accordance with 40 CFR 58, and has been collecting data since January 

18, 1999 (Table 2-2). Its sampling schedule was every three days until March 1, 2007, 

when it started sampling daily. The PM2.5 speciation monitor has been collecting data 

since March 3, 2002. The sampling schedule of the PM2.5 speciation monitor has been 

and remains every six days. 

Table 2-2. Rome PM2.5 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 nonattainment area. The evaluations include long-term trends of 

PM2.5 levels obtained from the FRM monitor and the speciation monitor. Both trends in 

annual averages and quarterly averages are evaluated. For the speciation monitor, trends 

in the different PM2.5 species measured are analyzed and are compared to speciation data 

from other PM2.5 nonattainment areas in Georgia. Receptor modeling results are 

presented to provide an insight into the relative amount of ambient PM2.5 attributable to 

different emission source categories. CART analysis was performed to examine the 

relationship between meteorology and air quality. Lastly, sensitivity modeling was 

conducted to examine the response in predicted 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 with 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 concentrations (arithmetic average of 

quarterly averages) from 1999 to 2008. Overall, PM2.5 concentrations have decreased 

for this time period. 

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

The overall trend can be divided into three 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 compared with 2002. The last period (2005-

2008) shows a small decrease of PM2.5 concentrations through 2007 and a marked 

decrease in 2008. The actual values used to create Figure 2-4 are listed in Table 2-3. In 

2008, the PM2.5 annual mean concentration dropped to 12.7 μg/m3

 , which is well below 

the 15.0 μg/m3 standard. 

 

0

5

10

15

20

25

1999 2000 2001 2002 2003 2004 2005 2006 2007 2008

Year

Concentration [ug/m3

]

13-115-0005

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. 

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Attainment 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

(μg/m3) 

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 with the exception of an increase from 2004 to 2005. The 

actual values used to make Figure 2-5 are listed in Table 2-4. 

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Attainment 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

Year

Concentration [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

(μg/m3) 

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 quarter from 1999 to 2007 at 13-115-0005. In 

general, PM2.5 concentrations were higher in the 2nd and 3rd quarters. This is to be 

expected due to higher temperatures and more photochemistry during these quarters. 

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Attainment 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 concentrations (arithmetic 

average of daily averages) from 1999 to 2007 at the Coosa High School PM2.5 

Speciation site (13-115-0005). The PM2.5 Speciation site started measuring PM2.5 

species in 2002. With respect to contributions of each species to total PM2.5 

concentrations, OC (4.8-6.2 μg/m3

) and SO4 (4.5-5.8 μg/m3) 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 concentrations and SO4 concentrations from 2006 to 

2007. From 2002 to 2007, NH4 concentrations were around 1.5 μg/m3

. For the same 

period, NO3 and EC concentrations were approximately 0.79 μg/m3 and 0.53 μg/m3

, 

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

with the trends of the summed individual species because the total PM2.5 annual 

averages are based on measurements taken daily whereas the speciated components were 

measured every sixth day. Therefore, unusually high or low values on a specific day 

would be weighted more by the individual species 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. 

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

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). 

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

Figure 2-8 shows quarterly averages of PM2.5 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. Overall, PM2.5 concentrations were higher 

in the second and third quarters than in the first and fourth quarters at this site. 

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

in the Floyd County NAA (13-115-0005) 

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

Figure 2-9 shows quarterly averages 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 the third quarter showed an overall decrease from 2002 to 

2007. The largest decrease of SO4 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 during the second and third quarters than the 

first and fourth quarter. 

Figure 2-9. Quarterly averages of SO4 concentrations at the PM2.5 Speciation site 

in the Floyd County NAA (13-115-0005) 

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

Figure 2-10 shows quarterly averages of NO3 concentrations at the PM2.5 Speciation site 

in the Floyd County NAA (13-115-0005). Contrary to PM2.5 and SO4 trends, NO3 

concentrations were low in the second and third quarters and high in the first and fourth 

quarters. From 2006 to 2007, NO3 concentrations increased for the first quarter. In 

terms of absolute values, however, NO3 concentrations did not change significantly. 

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

in the Floyd County NAA (13-115-0005) 

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

Figure 2-11 shows quarterly averages of NH4 concentrations 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 concentrations at the PM2.5 Speciation site 

in the Floyd County NAA (13-115-0005) 

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

Figure 2-12 shows quarterly averages 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 quarters. In 2007, the third quarter ended 

up showing the highest OC concentrations. 

Figure 2-12. Quarterly averages of OC concentrations at the PM2.5 Speciation site 

in the Floyd County NAA (13-115-0005) 

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

Figure 2-13 shows quarterly averages of EC concentrations at the PM2.5 Speciation site 

in the Floyd County NAA (13-115-0005). Overall, EC concentrations of the fourth 

quarter from 2004 to 2006 were higher than those of other quarters. From 2005 to 2007, 

EC concentrations largely increased in the third quarter. However, EC concentrations did 

not change dramatically in terms of absolute values. 

Figure 2-13. Quarterly averages of EC concentrations at the PM2.5 Speciation site 

in the Floyd County NAA (13-115-0005) 

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Attainment 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 PM2.5 concentration and composition, GA EPD used 2003-

04 data from the Speciation Trends Network (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 similar seasonal trends, with 

PM2.5 peaking in summertime. This peak is mainly due to elevated sulfate (SO4) 

concentrations, as well as elevated organic matter (OM), some of which is classified here 

under the “Other” category (OC is a measure of organic carbon, while other constituents 

of organic matter cannot be measured directly, and hence classified as “Other”). Sulfate 

and OC are by far the two dominant PM2.5 species, followed by ammonium (NH4), 

elemental carbon (EC), nitrate (NO3), 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 cooler temperatures favor nitrate particle 

formation. Ammonium levels follow those of sulfate and nitrate, as it binds with these 

anions. The similarities in seasonal patterns and composition of PM2.5 in these four 

nonattainment areas are indications of the regional nature of PM2.5. 

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Attainment 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-Dec

ug/m3

Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-14: Seasonal patterns in PM2.5 concentrations and composition in Atlanta 

(Site ID 13-089-0002) for 2003-04 (MMO – Major Metal Oxides; Other – PM2.5

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-Dec

ug/m3

Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-15: Seasonal patterns in PM2.5 concentrations and composition in 

Chattanooga (Site ID 47-065-4002) for 2003-04 (MMO – Major Metal Oxides; Other 

– PM2.5 other than sulfate, nitrate, ammonium, MMO, elemental carbon and 

organic carbon). 

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Attainment 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-Dec

ug/m3

Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-16: Seasonal patterns in PM2.5 concentrations and composition in Floyd 

County (Site ID 13-115-0005) for 2003-04 (MMO – Major Metal Oxides; Other – 

PM2.5 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-Dec

ug/m3

Other

OC

EC

MMO

NH4

NO3

SO4

Figure 2-17. Seasonal patterns in PM2.5 concentrations and composition in Macon 

(Site ID 13-021-0012) for 2003-04 (MMO – Major Metal Oxides; Other – PM2.5

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

carbon). 

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

Assessing the relative contribution of primary and secondary species is not trivial, since 

OC is part primary and part secondary. Also, 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 possible to estimate that about 40% of PM2.5 in the 

region is primary, with the remaining fraction being secondary (Table 2-6). 

Table 2-5. Average PM2.5 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 secondary percentage of PM2.5 

Site % primary % secondary 

Atlanta 40 60 

Chattanooga 32 68 

Floyd County 43 57 

Macon 44 56 

Despite the regional nature of PM2.5 and the high fraction of secondary components, there 

is clear evidence of impacts of local sources of primary PM2.5 at some of the sites. Both 

the Macon and Floyd County monitors show higher levels of crustal elements (MMO, 

Table 2-5), compared to Chattanooga and Atlanta (1.47, 1.05, 0.62 and 0.55 μg/m3, 

respectively). The Floyd County monitor also exhibits higher levels of unspecified 

(“Other”) PM2.5, compared to the other three sites. Elemental carbon levels are highest in 

Atlanta (1.0 μg/m3

 compared to 0.5-0.7 μg/m3 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, concentrations of OC (partially secondary) and 

secondary ionic PM2.5 (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 identifying the sources contributing to measured 

levels of pollutants. One of the most recently used source-apportionment models in 

recent years is the Positive Matrix Factorization (PMF) model. PMF is a factor analytic 

method that distinguishes correlation patterns among speciated PM2.5 measurements in a 

given location. 

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Presented here are source-apportionment results 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 major impacting factors at all sites are secondary 

sulfates, secondary nitrates, SOA, mobile sources and biomass burning. The Atlanta 

area, as expected, has higher levels of mobile-source PM2.5, compared to Floyd County 

and Macon. On the other hand, these latter two sites exhibit higher levels 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 preliminary assessment of control strategies. Given the 

large contributions to PM2.5 from the secondary-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 understood, and limited available knowledge suggests 

biogenic sources as the primary SOA precursors. Reducing primary PM2.5 may be best 

achieved by emission reduction measures for 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 general, 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 apportionment 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 Macon

ug/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 Atlanta, Floyd County, 

and Macon STN sites using PMF 

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

Table 2-7 Average factor contributions to PM2.5 (μg/m3) 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 characterization study designed to examine 

the relationships between meteorology, fine particulates, and regional haze at air quality 

monitoring sites throughout the Southeastern U.S. (Characterization 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 Tree (CART) statistical analysis was used to examine 

relationships between meteorology, fine particulates, and visibility that are important to 

atmospheric modeling. Separate CART analyses were conducted for visibility (as 

defined by the extinction coefficient) and fine particulates [particulate 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 bins) with similar air 

quality (visibility or PM2.5) and meteorological characteristics. Classification accuracy 

ranged from approximately 72 to 85 percent for 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 dependent 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 meteorological 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 148 
Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA 

particle species to light extinction—may account for the overall better classification 

accuracy for PM2.5 compared to extinction coefficient. 

A CART analysis was not performed for the Rome monitor. However, a CART analysis 

was performed for the Yorkville SEARCH monitor which is located relatively close to 

the Floyd monitor and can be considered representative of the Floyd County 

nonattainment area. The categorical comparisons for PM2.5 in Yorkville consisted of 

four categories: <15.0 (Category 1), 15.0-22.5 (Category 2), 22.5-30.0 (Category 3), and 

> 30 (Category 4) μg/m3

, respectively. A summary of the 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 surface parameters leading to higher PM2.5 

concentrations include higher PM2.5 the day before in Atlanta, Birmingham, and 

Yorkville; higher surface temperature; lower 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 winds, and more stability in Atlanta. 

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

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

Category in Yorkville. 

For Yorkville, there are six key bins (group of days with similar meteorological 

conditions) falling into the Category 3 and Category 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 μg/m3

) and by high prior-day PM2.5 concentrations in Yorkville 

(> 28 μg/m3

). 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. 

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

Table 2-9 Summary of average input parameters 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 sulfate followed by organic matter. 

In summary, high PM2.5 for Yorkville is associated with moderate temperatures, high 

PM2.5 on previous day (Atlanta, Birmingham, and Yorkville), very low wind speeds near 

the surface and low wind speeds aloft, and stable conditions. The high PM2.5 

classification categories are associated with higher sulfate concentrations. 

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

 

Figure 2-19: Average composition for 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 episode (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 specific subset of counties submitted by each 

state. Below is a list of the specific 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 148 
Attainment 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, respectively. 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 wintertime, the most important anthropogenic 

source category is VISTAS NH3 followed by Georgia ground-level PC, Georgia EGU 

SO2, and domainwide VOCs. 

46 of 148 
Attainment 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

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

ΔPM2.5 (

μg/m

3

)

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

SO2_EGU

SO2_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

ΔPM2.5 (

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% reduction of pollutant levels 

from 2009 levels. 

47 of 148 
Attainment 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 weighted response of the summer and winter 

episodes in Floyd County. Both of these figures 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 temperatures). Thus, reduction of either NH3 or 

SO2 emissions should result in a lowering of the other. Furthermore, there are currently 

no known cost-effective ways to reduce NH3 emissions 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_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

ΔPM2.5 (

μg/m

3

)

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 summer and winter episodes in Floyd County. 

48 of 148 
Attainment 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_nonEGU

NOx_Ground

NOx_Point

NH3

VOCs

PC_Ground

PC_Point

PC_Fires

ΔPM2.5 (

μg/m

3

)

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 discussion of sources of PM2.5 emissions and of 

significant PM2.5 precursors in the Floyd County Nonattainment Area. The technical 

justification is also presented for reversal of the presumption, under the PM 

Implementation Rule, that NOx is a significant PM2.5 precursor in Georgia. 

2.4.1 Sources of PM2.5

Sources of PM2.5 and PM2.5 precursors in the 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. 

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

Table 2-10 shows typical base year inventories 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 and 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 Power’s Plant Hammond, located in the nonattainment area. Plant Hammond has four coal-burning EGUs which contribute the 

majority of the SO2 and NOx emissions in the non-attainment area. Coal-burning power 

plants located outside of the non-attainment area but within the State boundaries are also 

important sources of SO2 emissions that affect ambient sulfate levels inside of the nonattainment area. Table 2-11 lists point sources that are Title V major sources of one or 

more of the following pollutants: NOx, VOC, PM, and SO2. 

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

Table 2-11. Point Sources in the Floyd County Non-Attainment Area 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 whose individual emissions are relatively small, 

but, due to the large number of these sources, the collective emissions from the source 

category could be significant (i.e., dry cleaners, service stations, agricultural sources, fire 

emissions, etc.). These types of emissions are estimated on a countywide level. 

Emissions from large fires that occur in South Georgia, outside of the non-attainment 

area, can also have significant effects on ambient PM levels in the non-attainment area. 

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, 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 countywide level. 

2.4.2 Precursors

The PM2.5 SIP must address both direct PM and secondary PM. As discussed previously, 

secondary PM is formed from emissions of PM precursors. Therefore, it is critical to 

identify the precursors that are relevant to a specific non-attainment area. 

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

40 CFR 51.1000 defines a “PM2.5 precursor” as any air pollutant other than direct PM2.5

that contributes to the formation of PM2.5. Emissions inventories required for attainment 

demonstration must include emissions of all PM2.5 precursors identified for the nonattainment area. 

40 CFR 51.1000 defines a “PM2.5 attainment plan precursor” as SO2 and any other 

precursor which the State must evaluate for emissions 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 the 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 [reference 40 CFR 51.1002 (3) and (4)]. 40 CFR 51.1002 

(c) implies that all sources of precursors within the State boundaries must be evaluated 

for emissions reduction measures. However, the 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 emissions 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 demonstration to show that VOC 

or ammonia significantly contributes to PM to overcome EPA’s presumption that they are 

not to be regulated as precursors. Georgia EPD has determined that NOx is not a 

significant precursor for PM2.5 formation in the Floyd County non-attainment area. The 

technical justification for NOx insignificance is presented in the following subsection. 

2.4.3 Technical Justification for Reversal of NOx Precursor Presumption

The U.S. EPA, in 72 FR 20586, requires states to “evaluate and consider control 

strategies for sources of SO2, direct PM2.5, and NOx emissions in all nonattainment 

areas.” However, the rule does allow states to make technical demonstrations to reverse 

the inclusion of NOx as precursor of PM2.5, or deem the precursor insignificant, based 

on geographical regions, emissions, etc. This then eliminates the need to examine NOx 

control measures for purposes of reducing PM2.5 concentrations. Georgia EPD’s 

analysis, summarized below, demonstrates that NOx is an insignificant PM2.5 precursor 

52 of 148 
Attainment 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 nonattainment areas were evaluated using FRM 

measurements and speciated data. The “Sulfate, Adjusted Nitrate, Derived Water, 

Inferred Carbonaceous mass Hybrid” (“SANDWICH”) material balance approach was 

used to speciate the FRM total PM2.5 mass into its components - SO4, NO3, NH4, PBW, 

OC, EC, and crustals. Figure 2-24 contains the annual average PM2.5 concentrations 

averaged across all FRM monitors in each nonattainment area. The measurements show 

annual average nitrate concentrations (plus ammonium and PBW associated with nitrate) 

collected on the FRM filters range from 0.27 to 0.33 μg/m3 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

20

Atlanta

Macon 

Rome 

Chatta. 

Atlanta

Macon 

Rome 

Chatta. 

Atlanta

Macon 

Rome 

Chatta. 

Atlanta

Macon 

Rome 

Chatta. 

Atlanta

Macon 

Rome 

Chatta. 

 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 Concentrations 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 (SMAT) 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 reductions, the annual average NO3 concentrations 

are only reduced by 0.00 to 0.03 μg/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 148 
Attainment 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 NOx 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 148 
Attainment 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

0.45

Clayton-0091

Cobb-0003Cobb-0004

DeKalb-0002DeKalb-2001

Fulton-0032Fulton-0039

Gwinnett-0002

Hall-0003

Paulding-0003

Bibb-0007Bibb-0012

Floyd-0005

Hamilton-1011

Hamilton-31-1

Hamilton-4002

Walker-0002

Monitor Location

ug/m3

EC

OC

NO3

Figure 2-25. Reductions in EC, OC, and 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 maximum predicted PM2.5 reductions are 

approximately 1.2 μg/m3 for 100% statewide NOx removal, 0.4 μg/m3 for 70% removal, 

0.22 μg/m3

 for 50% removal (Figure 2-26), and 0.11 μg/m3 for 30% removal (Figure 2-

27). 

55 of 148 
Attainment 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

0.00

DeKalb-2001

Fulton-0032Fulton-0039

Clayton-0091

Hall-0003

Gwinnett-0002

Cobb-0003

DeKalb-0002

Paulding-0003

Bibb-0007Bibb-0012

Floyd-0005

Hamilton-4002

Walker-0002

Δ PM2.5 (

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

0.04

DeKalb-2001

Fulton-0032Fulton-0039

Clayton-0091

Hall-0003

Gwinnett-0002

Cobb-0003

DeKalb-0002

Paulding-0003

Bibb-0007Bibb-0012

Floyd-0005

Hamilton-4002

Walker-0002

Δ PM2.5 (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 148 
Attainment Demo Methods and Inputs PM2.5 Attainment SIP - Floyd County, GA 

GA EPD feels it is inappropriate to apply 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 conditions. 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 evaluate more realistic, yet aggressive, NOx 

reductions from sources across the state. GA EPD conducted a technical analysis looking 

at potential statewide reductions 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 all 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 nonattainment areas is 2015. Assuming all the 

controls listed for 2030 are achievable by 2014 and replacing the 2030 on-road mobile 

fleet turnover with 2014 on-road mobile emissions, results in a 31% statewide reduction 

in NOx emissions. As a result, GA EPD feels that a statewide 30% or, at worst, a 

statewide 50% NOx reduction run would be the most appropriate scenario to use in the 

NOx insignificance demonstration. Modeling results show a maximum impact of 0.11 

μg/m3

 across all nonattainment monitors in the state for a 30% statewide NOx reduction 

run (monitors in downtown Atlanta showed a slight increase in PM2.5 formation) and a 

maximum impact of 0.22 μg/m3 across all nonattainment monitors in the state for a 50% 

statewide NOx reduction run. 

2.4.3.4 CMAQ Model Performance for Organic Carbon 

OC modeling is still developing 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 isoprene, 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 was developed based on SOA formation rates under 

ambient atmospheric conditions and that SOA formation rates have not been tested under 

the artificially low oxidant levels that result from zeroing out all NOx emissions in a 

large state. This introduces additional uncertainty 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 compared to OC observations (black line). 

The model predicts unrealistically high OC predictions in the early morning hours when 

the mixing height is low. It is during these 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 aerosols, 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 

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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

40

6/1/02 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 0:00

6/10/02 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

Date

Abs 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 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. 

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 insignificant precursor to PM2.5 in Georgia’s 

nonattainment areas. GA EPD feels it is inappropriate 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 the predicted changes in OC resulting from 

NOx reductions since the CMAQ modeling system does not properly simulate hourly OC 

temporal variations and was not designed to predict concentrations under extreme 

reductions in precursor emissions and oxidant levels. 

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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 PM2.5. Modeling results 

show a maximum impact of 0.11 μg/m3 across all nonattainment monitors in the state for 

a 30% statewide NOx reduction scenario and a maximum impact of 0.22 μg/m3

 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/m3

 to evaluate interstate 

impacts (e.g., Georgia emissions impacts on non-Georgia PM2.5 monitors). Therefore, it 

would seem reasonable to assume that the significance threshold level for a state on itself, 

for the purpose of reversal of the NOx precursor presumption, should be higher than a 

state on a neighboring state. The proposed Prevention of Significant Deterioration (PSD) 

significant impact levels (SILs) 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 threshold level should set at 

0.3 μg/m3

. 

Since both the 30% statewide NOx reduction and 50% statewide NOx reduction 

modeling scenarios result in a reduction of PM2.5 impact of less 0.3 μg/m3, EPD has 

clearly demonstrated that NOx is insignificant as a precursor to PM2.5 in the Georgia 

nonattainment areas. 

Section 3. Attainment Demonstration Methods and Inputs 

The attainment modeling for the Floyd County PM2.5 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 PM2.5 and ozone (O3) modeling being done by the 

Association of Southeastern Integrated Planning (ASIP). VISTAS and ASIP are run by 

the ten Southeast states (Alabama, Florida, Georgia, Kentucky, Mississippi, North 

Carolina, South Carolina, Tennessee, Virginia and West Virginia). Since the regional 

haze and PM2.5 modeling use annual simulations and include an intermediate year that is 

the attainment year required for the Floyd County PM2.5 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) Mesoscale Meteorological Model (MM5) is 

a nonhydrostatic, prognostic meteorological model routinely used for urban- and 

regional-scale photochemical, fine particulate matter, and regional haze regulatory 

modeling studies. 

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• Emissions Model: The Sparse Matrix Operator Kernel Emissions (SMOKE) 

modeling system is an emissions modeling system that generates hourly gridded 

speciated emission inputs of mobile, nonroad mobile, area, point, fire, and 

biogenic emission sources for photochemical grid models. 

• Air Quality Model: The USEPA’s Models-3/ Community Multiscale Air Quality 

(CMAQ) modeling system is a “One-Atmosphere” photochemical grid model 

capable of addressing O3, particulate matter, visibility, and acid deposition at 

regional scale for periods up to one year. 

Additionally, an historical year is selected to model that represents typical meteorological 

conditions in the Southeast when high ozone, high PM2.5 and poor visibility are observed 

throughout the region. Once the historical year is selected, meteorological inputs are 

developed using the meteorological model. 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, PM2.5 and visibility, with the results compared to 

the historic data. The model performance is evaluated by comparing the modeled 

predicted data to the historic air quality data. 

 

Once model performance is deemed adequate, typical baseline and future year emissions 

are processed through the emissions model. For this demonstration, the baseline year 

was 2002, which corresponds with the same year as the historic meteorology used in the 

modeling. The attainment future year GA EPD is using for this demonstration is 2009, 

since the mandatory attainment date for the Floyd County PM2.5 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 air quality model with the meteorological 

inputs. The air quality modeling results are used to determine a relative reduction in 

future PM2.5, which is used in the attainment demonstration. 

The complete modeling protocol used for this 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 methods. Freely accessible means that model 

formulations and coding are freely available for review and that the models are available 

to stakeholders, and their consultants, for execution and verification at no or low cost. 

The following sections outline the criteria for selecting a modeling system that is both 

defensible and capable of meeting the study's goals. These criteria were used in selecting 

the modeling system used for this modeling attainment demonstration. 

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3.2.1 Selection of Air Quality Model

3.2.1.1 Criteria 

 

For an air quality model to qualify as a candidate for use in an attainment demonstration, 

a state needs to show that it meets several general criteria: 

• The model has received a scientific peer review. 

• The model can be demonstrated applicable to the problem on a theoretical basis. 

• Databases needed to perform the analysis are available and adequate. 

• Available past appropriate performance evaluations have shown the model is not 

biased toward underestimates or overestimates. 

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

• 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 modeling 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-Atmosphere” air quality modeling system capable 

of addressing ozone, fine particulate matter, visibility and acid deposition within a 

common platform. The original justification for the Models-3 development emerged 

from the challenges posed by the CAAA and the USEPA’s desire to develop an advanced 

modeling framework for “holistic” environmental modeling utilizing state-of-science 

representations of atmospheric processes in a high performance computing environment. 

The USEPA completed the initial stage of development with Models-3 and released the 

CMAQ model in mid-1999 as the initial operating science model under the Models-3 

framework. 

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

ozone and PM2.5 attainment demonstration state implementation 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 PM2.5 modeling. 

The configuration used for this modeling demonstration, as well as a more detailed 

description of the CMAQ model, can be found in Appendix G. 

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3.2.2 Selection of Meteorological Model

3.2.2.1 Criteria 

Meteorological models, either through objective, diagnostic, or prognostic analysis, 

extend available information about the state of the atmosphere to the grid upon which 

photochemical grid modeling is to be carried out. The criteria for selecting a 

meteorological model are based on both the model's ability to accurately replicate 

important meteorological phenomena in the region of study, and the model's ability to 

interface with the rest of the modeling systems, particularly the air quality model. With 

these issues in mind, the following criteria were established for the meteorological model 

to be used in this study: 

• Non-Hydrostatic Formulation 

• Reasonably current, peer reviewed formulation 

• Simulates Cloud Physics 

• Publicly available at no or low cost 

• Output available in I/O API format 

• Supports Four Dimensional Data Assimilation 

• Enhanced treatment of Planetary Boundary Layer heights for AQ modeling 

3.2.2.2 Overview of MM5 

The non-hydrostatic MM5 model is a three-dimensional, limited-area, primitive equation, 

prognostic model that has been used widely in regional air quality model applications. 

The basic model has been under continuous development, improvement, testing, and 

open peer-review for more than 20 years and has been used worldwide by hundreds of 

scientists for a variety of mesoscale studies. 

 

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

coordinate similar to that used in many operational and research models. In the nonhydrostatic MM5, the sigma levels are defined according to the initial hydrostatically 

balanced reference state so that the sigma levels are also time-invariant. The gridded 

meteorological fields produced by MM5 are directly compatible with the input 

requirements of “one atmosphere” air-quality models using this coordinate. MM5 fields 

can be easily used in other regional air quality models with different coordinate systems 

by performing a vertical interpolation, followed by a mass-conservation readjustment. 

Two planetary boundary layer parameterizations are available for air-quality applications, 

both of which represent sub-grid-scale turbulent fluxes of heat, moisture and momentum. 

One scheme uses a first-order eddy diffusivity formulation for stable and neutral 

environments and a modified first-order scheme for unstable regimes. The other scheme 

uses a prognostic equation for the second-order turbulent kinetic energy, while 

diagnosing the other key boundary layer terms. 

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Initial and lateral boundary conditions 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 using a relaxation technique applied in the outermost five 

rows and columns of the coarsest grid domain. 

Results of detailed performance evaluations of the MM5 modeling system in regulatory 

air quality application studies have been widely reported in the literature (e.g., Emery et 

al., 1999; Tesche et al., 2000, 2003) and many have involved comparisons with other 

prognostic models such as the Regional Atmospheric Modeling System (RAMS) and the 

Systems Application International Mesoscale Model. The MM5 enjoys a far richer 

application history in regulatory modeling studies compared with RAMS or other models. 

Furthermore, in evaluations of these models in over 60 recent regional scale air quality 

application studies since 1995, it has generally been found that the MM5 model tends to 

produce somewhat better photochemical model inputs than alternative models. 

The configuration used for this modeling demonstration, as well as a more detailed 

description of the MM5 model, can be found in Appendix G. 

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3.2.3 Selection of Emissions Processing System

3.2.3.1 Criteria 

The principal criterion for an emissions processing system is that it accurately prepares 

emissions files in a format suitable for the photochemical grid model being used. The 

following list includes clarification of this criterion and additional desirable criteria for 

effective use of the system. 

• File System Compatibility with the I/O API 

• File Portability 

• Ability to grid emissions on a Lambert Conformal projection 

• Report Capability 

• Graphical Analysis Capability 

• MOBILE6 Mobile Source Emissions 

• Biogenic Emissions Inventory System 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 Micro-computing Center of North Carolina. As with most 

emissions models, SMOKE is principally an emission processing system and not a true 

emissions modeling system in which emissions estimates are simulated from “first 

principles.” This means that, with the exception of mobile and biogenic sources, its 

purpose is to provide an efficient, modern tool for converting emissions inventory data 

into the formatted emission files required by an air quality simulation model. For mobile 

sources, SMOKE actually simulates emissions rates based on input mobile-source 

activity data, emission factors and estimates of vehicle miles traveled. 

SMOKE was originally designed to allow emissions data processing methods to utilize 

emergent high-performance-computing as applied to sparse-matrix algorithms. Indeed, 

SMOKE is the fastest emissions processing tool currently available to the air quality 

modeling community. The sparse matrix approach utilized throughout SMOKE permits 

both rapid and flexible processing of emissions data. The processing is rapid because 

SMOKE utilizes a series of matrix calculations instead of less efficient algorithms used in 

previous systems. The processing is flexible because the processing steps of temporal 

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projection, controls, chemical speciation, temporal allocation, and spatial allocation have 

been separated into independent operations wherever possible. The results from these 

steps are merged together at a final stage of processing. 

SMOKE contains a number of major features that make it an attractive component of the 

modeling system. The model supports a variety of input formats from other emissions 

processing systems and models. It supports both gridded and county total land use 

scheme for biogenic emissions modeling. SMOKE can accommodate emissions files 

from up to 10 countries and any pollutant can be processed by the system. 

For additional information about the SMOKE 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 changes 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 modeling attainment with air quality standards. 

The USEPA recommends that episode selection derive from four principal criteria: 

• Simulate a variety of meteorological conditions 

• Model time periods in which observed concentrations are close to the appropriate 

baseline design value or visibility impairment 

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

• Model a sufficient number of days so that the modeled attainment test applied at 

each monitor violating the NAAQS is based on multiple days 

VISTAS adopted a logical, stepwise approach in implementing the Attainment Modeling 

Guidance in order to identify the most preferable, 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 relevant to the evaluation of candidate annual 

modeling episodes. 

• Initial Episode Typing: At the time of selection in 2003, meteorological and air 

quality data were available for 2002 for model inputs and model performance 

evaluation. VISTAS used Classification and Regression Tree (CART) analyses to 

evaluate the candidate modeling years. The year 2002 was found to be 

representative of conditions in the other years. Subsequently, these analyses were 

repeated with the meteorological and air quality monitoring data for 2000 to 2004 

to evaluate how well the 2002 modeling year represented the full 2000-2004 

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baseline period. This analysis confirmed that visibility and PM2.5 concentrations 

in 2002 were representative of the five-year baseline period. This analysis is 

discussed in more detail in the 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 PM2.5, meteorological, and 

emissions data and representativeness of alternative baseline modeling periods 

from a regulatory standpoint. Additionally, 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 advantage of the 2002 inventory. 

• Years to be used by other RPOs: VISTAS also considered what years other RPOs 

would be modeling, and several had already chosen calendar year 2002 as the 

modeling year. 

After a lengthy process of integrated studies, the episode selection process culminated in 

the selection of calendar year 2002 (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 grid mode. This allowed the larger outer 

domains to feed concentration data to the inner nested domain. The horizontal coarse 

grid modeling domain boundaries were determined through a national effort to develop a 

common grid projection and boundary. A smaller 12-km grid modeling domain was 

selected in an attempt to balance location of areas of interest, such as ozone and fine 

particulate matter nonattainment areas. Processing time was also a factor in choosing a 

smaller 12-km grid modeling domain. 

The coarse 36-km horizontal grid domain covers the continental United States. This

domain was used as the outer grid domain for MM5 modeling with the CMAQ domain 

nested within the MM5 domain. Figure 3-1 shows the MM5 horizontal domain as the 

outermost, blue grid with the CMAQ 36-km domain nested in the MM5 domain. 

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

To achieve finer spatial resolution in the VISTAS states, a one-way nested high 

resolution (12-km grid resolution) was used. 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 

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3.4.2 Vertical Modeling Domain

The vertical grid used in the MM5 modeling primarily defines the CMAQ vertical 

structure. The MM5 model employed a terrain-following coordinate system defined by 

pressure, using 34 layers that extend from the surface to the 100 mb. 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 averaging 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-layer and a 19-layer CMAQ models were 

compared to ambient monitoring data. 

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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 

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3.5 Baseline Emissions Inventory

The CAA Amendments revised many of the provisions 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 that were designated nonattainment 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 inventoried include volatile organic 

compounds (VOC), NOx, PM2.5, coarse particulate (PM10), ammonia (NH3) and SO2. 

Tables 3-2 and 3-3 show the typical annual emissions from the various source sectors for 

the Floyd County PM2.5 nonattainment area for 2002 and 2009. The baseline emissions 

inventory for 2002 was developed for Georgia following the methods described in 

Appendix H. The 2002 BaseG2 and the 2009 BaseG4 emission inventories are the latest 

emission inventories developed by VISTAS for 2002 and 2009, respectively. 

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

Area Source 

Type 

Emissions (tons) 

VOC NOx SO2 PM-10 PM-2.5 

point 1835.3 13,053.3 35,245.1 1080.9 651.0 

non-road 808.2 1100.6 81.2 64.8 60.9 

area 4565.0 622.1 979.5 7823.3 1378.5 5

mobile 3730.9 3058.7 128.1 70.0 49.4 1

biogenic 16,562.4 113.2 NA NA NA 

Floyd Co. 

total 27,501.8 17,947.9 36,433.9 9,039.0 2,139.8 6

point 34,964.4 197,376.8 571,410.9 33,077.3 22,531.6 3

non-road 85,965.4 97,961.4 9005.4 8617.9 8226.4 

area 333,044.8 49,987.4 60,370.2 757,656.1 159,437.8 83

mobile 283,420.6 307,731.7 12,183.5 7245.9 5167.8 10

biogenic 1,972,795.4 24,159.2 NA NA NA 

State 

total 2,710,191.0 677,216.5 652,970.0 806,597.2 195,363.6 97

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

Area Source 

Type 

Emissions (tons) 

VOC NOx SO2 PM-10 PM-2.5 

point 1880.3 10859.4 6864.3 1858.0 1104.5 non-road 732.1 927.5 13.5 55.6 52.1 

Floyd Co. 

area 4235.5 647.9 981.8 8763.4 1463.1 mobile 2592.9 2175.7 15.5 59.2 37.1 biogenic 16,562.4 113.2 NA NA NA 

total 26,003.2 14,723.7 7875.1 10,736.2 2,656.8 

point 36,430.1 148,849.7 462,666.5 40,993.6 29,889.7 non-road 67,686.1 85,732.9 2724.7 7521.1 7174.6 area 306,337.3 51,925.0 60,604.0 840,244.9 169,011.4 mobile 195,125.2 209,349.2 1585.0 6072.0 3840.1 biogenic 1,972,795.4 24,159.2 NA NA NA 

State 

total 2,578,374.0 520,016.0 527,580.2 894,831.6 209,915.8 1

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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 that emit greater than a specified tonnage per 

year, with data provided at the facility level. Electric generating utilities and industrial 

sources are the major categories for stationary point sources. Stationary area sources are 

those sources whose individual emissions are relatively small, but due to the large 

number of these sources, the collective emissions from the source category could be 

significant (i.e., dry cleaners, service stations, agricultural sources, fire emissions, etc.). 

These types of emissions are estimated on a countywide level. 

Non-road (or off-road) mobile sources are equipment that can move but do not use the 

roadways, i.e., lawn mowers, construction equipment, railroad locomotives, aircraft, etc. 

The emissions from these sources, like stationary 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, and are summed to the countywide level. 

Biogenic sources are the natural sources like trees, crops, grasses and natural decay of 

plants. The emissions from these sources are estimated on a countywide level. 

In addition to the various source classifications, there are also various types of emission 

inventories. The first is the actual base year inventory. This inventory is the base year 

emissions that correspond to the meteorological data used, which for this modeling effort 

is data from 2002. These emissions are used for evaluating the air quality model 

performance. The second type of inventory is the typical base year inventory. This 

inventory is similar to the actual base year inventory, except that for sources whose 

emissions change significantly from year to year, a more typical emission value is used. 

In this modeling effort, typical emissions were developed for the electric generating units 

(EGUs) and the fire emissions. The air quality modeling runs using the typical base year 

inventory are used to calculate relative response factors used in the attainment 

demonstration test. 

 

The future year base inventory is an inventory developed for some future year for which 

attainment of the air quality standard is needed. For this modeling project, the future year 

inventory will be 2009, the last complete year for which the standard must be attained. It 

is for the future base year inventory that sensitivities will be evaluated to determine what 

additional controls beyond those control measures already included in the future year 

base inventory will need to be implemented to attain and maintain the annual PM2.5

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 other counties in Georgia, are in Appendix 

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

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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 sources emitting at least 100 tons per year (tpy) 

of a criteria pollutant are inventoried annually. Smaller sources have been inventoried 

less frequently. The point source emissions data can be grouped as EGU sources and 

other industrial point sources, also called non-electric generating units (non-EGUs). 

Appendix H documents the point source modeling 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 USEPA’s Acid Rain program or 2002 hourly 

emissions data provided by stakeholders. These data provide hourly emissions profiles 

for SO2 and NOx that can be used in air quality modeling. Emissions profiles are used to 

estimate emissions of other pollutants (VOC, carbon monoxide, NH4, PM2.5, soil) based 

on measured emissions of SO2 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 variability in meteorology, 

economic and outage factors in 2002. This approach is consistent with the Attainment 

Modeling Guidance. To develop a typical year 2002 emissions inventory for EGU 

sources, each unit’s average CEM heat input for 2000 through 2004 was divided by the 

2002 actual heat input to generate a unit-specific normalizing factor. This normalizing 

factor was then multiplied by the 2002 actual emissions. The heat inputs for 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 years the unit was operational was used. If 

a unit was shut down in 2002, but not permanently shut down, the emissions and heat 

inputs 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 generate future year emission inventories for 

the electric generating sector of the contiguous United States using the Integrated 

Planning Model (IPM). IPM is a dynamic linear optimization model that can be used to 

examine air pollution control policies for various pollutants throughout the contiguous 

United States for the entire electric power system. The dynamic nature of IPM enables 

projection of the behavior of the power system over a specified future period. 

Optimization logic in IPM determines the least-cost means of meeting electric generation 

and capacity requirements while complying with specified constraints including air 

pollution regulations, transmission bottlenecks, and plant-specific operational constraints. 

The versatility of IPM allows users to specify which constraints to exercise, and to 

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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 

Georgia Power SGM1 2442 13802 165 73 2127 11134 323 192 

– 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 

Georgia Power SG01 10960 38741 445 193 2430 1890 1566 933 

– 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 category uses annual emissions as reported 

under the CERR for the year 2002. These emissions are temporally allocated to month, 

day, and hour using source category code (SCC)-based allocation factors. 

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The general approach for assembling future year 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 individual emissions are relatively small, but 

due to the large number of these sources, the 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 households, or population. Stationary area source 

emissions are estimated at the countywide level. 

A portion of the area source 2002 base year inventory for Georgia was developed by the 

GA EPD and provided to the VISTAS/ASIP contractor. The VISTAS/ASIP contractor 

calculated the remaining portion of the area source inventory. The sources estimated by 

the contractor include emissions from animal husbandry, wildland fires, and particulate 

matter from paved and unpaved roads. For the other states within the modeling domain, 

either state-supplied data or data reported under CERR for 2002 was used. 

The actual base year inventory will serve as the typical base year inventory for all area 

source categories except for wildland fires. For wildland fires, a typical year inventory 

was used to avoid anomalies in wildfire activity in 2002 compared to longer-term 

averages. Development of a typical year fire inventory provided the capability of using a 

comparable data set for both the base year and future years. 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 state 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 contractor 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 System Version 5 growth factors were used 

if no growth factor was available from either the 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 discussion of the area source inventory. 

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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 

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3.5.3 Off-Road Mobile Sources

Off-road (or non-road) mobile sources are equipment 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 using the USEPA’s NONROAD model, the model 

growth assumptions were used to create the 2009 future year inventory. The NONROAD 

model takes into consideration 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 available, state-specific growth factors were 

used. Appendix H provides a detailed discussion of the nonroad mobile source 

inventory. 

3.5.4 Highway Mobile Sources

For onroad vehicles, the newest version of the MOBILE model, MOBILE6.2, was used. 

Key inputs for MOBILE include information on the age of vehicles 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 vehicles (such as emissions inspection programs), 

and temperature. 

The MOBILE model takes into consideration regulations 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 data 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 obtained from the Georgia Department of 

Transportation (GDOT). The VMT for 2009 were projected by the VISTAS contractors 

based on linear growth as derived from the 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 the 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 

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the Urban Airshed Model (UAM)-BEIS3 model. Modifications include use of MM5 

data, gridded land use data, and improved emissions characterization. The emission 

factors that are used in SMOKE-BEIS3 are the same as the emission factors 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 Database version 3 (BELD3) provided by the 

USEPA. A separate land classification scheme, based upon satellite (AVHRR, 1 km 

spatial resolution) and census information aided in defining the forest, agriculture, and 

urban portions of each county. 

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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 USEPA for evaluating the performance of the 

air quality model. Before the 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 directly 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 modeling performance was quite good at both the 36-

km and 12-km grid resolutions. Synoptic features were routinely accurately predicted and the 

meteorological model showed considerable skill in replicating the state variables (e.g. 

temperature, mixing ratio, relative humidity, wind speed and direction, cloud cover, and 

precipitation). The meteorological modeling performance statistics fell within expected and 

acceptable ranges of error during the majority of the 2002 modeled year. 

The meteorological modeling performance for Georgia was very similar to the performance 

for the VISTAS/ASIP region for the 12-km modeling domain. Again, large-scale 

meteorological patterns were accurately predicted. The meteorological model demonstrated 

substantial skills throughout the entire year and was especially skillful during the 

summertime season from May through September. 

U.S. EPA guidance (EPA, 2007) recognizes the complexity and importance of evaluating 

meteorological modeling results for air quality applications. Since MM5 algorithms and 

modules have undergone significant peer review and testing, 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 quantities. In the case of a prognostic meteorological 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 Square Error (RMSE), Systematic Root Mean 

Square Error (RMSEs), Unsystematic Root Mean Square Error (RMSEu) 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 depend 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 general confidence in meteorological model output. 

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A graphical summary of the daily and hourly mean performance statistics 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 Table 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

1 2

⎥

⎦

⎤ ⎢

⎣

⎡ = ∑∑ − = =

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

S j OP

IJ

RMSE

Unsystematic Root Mean Square Error ( )

2/1

1 1

2 ˆ 1 ⎥

⎦

⎤ ⎢

⎣

⎡ = ∑∑ − = =

J

j

I

i

i

j

i

u j 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 for 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 

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Model Performance Evaluation PM2.5 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

January

Feburary

March

April

May

June

July

August

September

October

November

December

Bias (degree K)

Monthly Average Humidity Bias

-1.00

-0.80

-0.60

-0.40

-0.20

0.00

0.20

0.40

January

Feburary

March

April

May

June

July

August

September

October

November

December

Bias (g/kg)

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

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

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

The MM5 simulation is able to capture meteorological conditions observed during the study 

period with an adequate level of accuracy. Performance statistics for most days are within the 

benchmarks proposed by Emery (2001). Monthly average statistics reveal under prediction in 

humidity from May through November, and an over prediction in temperature during the 

summer months (May through September). The simulation tends to over predict daytime and 

nighttime temperature, and consistently over-predicts nighttime wind speed. However, the 

magnitude of these under/over predictions remains small. 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 atmospheric dynamics during a particular 

time period. In an unlikely event of unusually poor air quality model performance, it is 

reasonable to further investigate the performance 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 PM2.5 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 were 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 sites should be evaluated. STN data was also 

utilized as this data is used to speciate the 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 described in Section 6.1 and Appendix G. 

Only a brief summary of the model performance 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 domain, please refer to Appendix K.3. 

4.2.1 Modeling Performance Goals and Criteria

In 2004, VISTAS/ASIP established model performance “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 Guidance (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 are included for FRM and STN monitors. 

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

Species 

Mean Fractional 

Bias 

Mean Fractional 

Error 

Comment 

<15 percent <35 percent Goal for PM2.5 model performance based on ozone 

model performance, considered “excellent 

performance” 

<30 percent <50 percent Goal for PM2.5 model performance, considered good 

performance; hereafter, it is called “(performance) 

goal level” 

<60 percent <75 percent Criteria for PM2.5 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 triggers 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 visualize 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 named because the dotted lines resemble a soccer goal. 

The soccer plot is useful as both bias and error are shown on a single plot. As bias and error 

approach zero, the points are plotted 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 criteria lines are adjusted based on the average 

concentration of the observed species concentrations 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 demonstrated that greater emphasis should be placed on performance 

of those components with the greatest contribution to PM2.5 mass (e.g. SO4 and OC) and that 

greater bias and error could be accepted for components with smaller contributions to total PM2.5

mass (e.g. EC, NO3, and SOIL). The soccer plots and bugle plots have been included as 

suggested in the Attainment Modeling Guidance. 

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Table 4-5 Statistical Metric Calculations 

Statistical Measure Shorthand 

Notation 

Mathematical Expression Notes 

Accuracy of Paired 

Peak 

 Ap

peak

peak

O

− OP

Coefficient of 

Determination 

 R2

( )( )

∑ ∑

∑

= =

=

− −

⎥

⎦

⎤ ⎢

⎣

⎡ −−

N

i

N

i

i i

N

i

i i

OOPP

OOPP

1 1

2 2

2

1

)()(

Pi= prediction at time and 

 location i; 

Oi = observation at time and 

 location i; 

P = arithmetic average of Pi, 

 i = 1, 2, . . ., N; 

O = arithmetic average of Oi, 

 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

1 2

⎥

⎦

⎤ ⎢

⎣

⎡ ∑ − =

N

i

OP ii 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

OP ii N 1

1

Mean Normalized 

Gross Error 

MNGE 

∑=

N −

i i

ii

O

OP

N 1

1 Reported as % 

Mean Biased MB ∑( ) =

−

N

i

OP ii 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) 

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

4.2.2 Domain-Wide Model Performance

 

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

STN and FRM monitors are included here. Plots have been developed for the average monthly 

concentrations and the performance statistics for all of the PM2.5 component species (SO4, NO3, 

NH4, OC, and EC) and reconstructed PM2.5 total mass from the STN monitoring sites (Figures 4-

2 and 4-3), as well as the total FRM PM2.5 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 performance for most species of PM2.5 and total PM2.5. The 

exception is the prediction of NO3 values, which most values fall outside the criteria 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 presented in the image on the right in Figure 4-2. 

However, when the very low concentration of NO3 is taken into consideration, as presented in 

the bugle plots (Figures 4-3), NO3 performance largely falls within the criteria and goal levels. 

One can still note a general tendency for under prediction in NO3, and other species (e.g. OC) in 

left hand image in Figure 4-3, which leads to a slight under prediction in total reconstructed 

PM2.5. 

Monthly total PM2.5 performance at all the VISTAS/ASIP FRM monitors largely falls within 

goal level thresholds, with only three months falling just outside goal level (Figure 4-4). Figure 

4-5 suggests a slight negative bias in PM2.5 prediction for most of the year, with mean fractional 

error values remaining within goal levels across the 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 Bias

Mean 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 Bias

Mean 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 both the mean fractional error and fractional bias for 

component concentration for all VISTAS STN monitoring sites. The image on the right is a zoomed view 

of the soccer plot on the left to better depict the area inside the criteria/goal lines. Each point represents a 

monthly value as compared to the model performance criteria (red box) and modeling performance goals 

(green box). 

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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 (μg/m3)

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 (μg/m3)

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 fraction bias for particulate matter and its component 

concentrations for all VISTAS STN monitoring sites. The image on the right is a bugle plot of mean 

fraction error for particulate matter and its component species for all VISTAS STN monitoring sites. 

Each point represents a monthly mean fraction bias value as compared to the model performance criteria 

(red lines) and modeling performance goals (green lines). 

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 Bias

Mean 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 Bias

Mean 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 PM2.5 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. Each point represents a monthly value as compared to 

the model performance criteria (red box) and modeling performance goals (green box). 

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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 (μg/m3)

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 (μg/m3)

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 Monitoring sites. Each point represents a monthly 

mean fraction bias value as compared to the model performance criteria (red lines) and modeling 

performance goals (green lines). 

The overall tendency of the model was that the model had some difficulties in predicting NO3. 

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 NO3 are generally found in low 

concentrations across the southeast, and the model usually has difficulties representing any 

compound with low ambient concentrations. The bugle plots are more encouraging with NO3

performance, as these plots take into account for absolute concentrations of PM2.5 components 

when evaluating performance. The bugle plots show all components and total PM2.5 falling 

within criteria levels, if not goal levels, of model performance. The under predictions of NO3

and OC account for the slight negative bias in the modeled PM2.5 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 developed 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) PM2.5 and PM10

Mass Networks, (2) EPA Speciation Trends Network (STN) of PM2.5 species, (3) Interagency 

Monitoring of Protected Visual Environments (IMPROVE), (4) Clean Air Status and Trends 

Network (CASTNET), and (5) Southeastern Aerosol Research and Characterization (SEARCH). 

It should be noted that the STN monitor here refers to the combination of the official STN 

monitors and the CSN (Chemical Speciation Network) monitors. Table 4-6 and Figure 4-6 

summarize the species data collected and locations 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).

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

Monitoring 

Network Chemical Species Measured 

SAMPLING 

FREQUENCY; 

DURATION 

FRM Only total fine particulate mass (PM2.5) Varies; 24 hr 

IMPROVE Speciated PM2.5 and PM10 1 in 3 days; 24 hr 

STN Speciated PM2.5 Varies; Varies 

CASTNET Speciated PM2.5 and ozone Hourly, Weekly; 1 hr, 

Week 

SEARCH 

24-hr PM25 (FRM Mass, OC, BC, SO4, 

NO3, NH4, EC); 24-hr PM coarse (SO4, 

NO3, NH4, elements); Hourly PM2.5

(Mass, SO4, NO3, NH4, EC, TC); and 

Hourly gases (O3, NO, NO2, NOy, HNO3, 

SO2, CO) 

Daily, Hourly 

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

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

nonattainment areas (left) and the Floyd County PM2.5 nonattainment area (right). 

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4.2.3.1 Model performance statistics

Model performance statistics were calculated collectively for the FRM monitors within Georgia, 

as well as individually for the one FRM monitor in the Floyd County nonattainment area to 

demonstrate the model’s ability to replicate total PM2.5 mass at these sites. In addition, the same 

approach was taken to conduct model performance evaluation for the STN monitors within 

Georgia and for the Rome STN site on PM2.5 component species and total PM2.5 basis for the 

entire base year. The statistical measures selected were based on the recommendations 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, PM2.5, and Regional Haze

(“Attainment Guidance”). 

4.2.3.1.1 Model Performance Statistics for the FRM Sites

To examine the overall model performance, the annual model performance statistics were 

estimated for all FRM sites in GA and the FRM site in the Floyd County nonattainment area. As 

shown in Table 4-7, the model’s performance 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 performance 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 year (Table 4-8). It was noted that the model had marginal (> 

15 % or < -15 %) under-prediction in June and July. Throughout 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 PM2.5

concentration of 17.7 μg/m3

 at 13-115-0005 in July and 20.9 μg/m3 was observed at the same 

monitor for the same period. In addition, the model could replicate high PM2.5 concentrations 

that were observed except March. More detailed 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. 

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Table 4-7. Annual model performance statistics for PM2.5 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 

Ap -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 

MaxOBS 52.0 36.5 

MaxPRE 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 

R2 0.5 0.5 

BF 1.0 1.1 

Number of Samples 3166 108 

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Table 4-8. Monthly model performance statistics for PM2.5 at 13-115-0005. 

Statistics January February March April May June July August September October No

MFB (%) -0.7 3.3 9.1 -3.8 -10.6 -17.4 -20.3 -7.4 11.7 12.7 

MFE (%) 15.2 18.9 36.3 14.6 25.4 31.1 30.6 18.7 41.6 26.2 

Ap -0.2 0.2 0.9 -0.1 -0.1 -0.1 -0.1 -0.2 0.0 0.3 

NMB (%) -3.1 8.6 15.7 -3.9 -11.3 -14.1 -16.2 -10.6 8.7 18.9 

NME (%) 16.5 17.8 43.9 15.3 25.9 27.2 26.9 17.3 29.9 32.2 

MNB (%) 0.7 6.1 18.5 -2.3 -6.1 -11.2 -14.9 -5.1 34.8 19.8 

MNGE (%) 15.3 18.7 40.8 14.8 24.2 29.6 26.5 18.2 57.1 31.6 

MB -0.4 0.9 1.6 -0.5 -1.8 -2.7 -3.4 -2.2 1.5 2.9 

MAGE 2.3 1.8 4.4 1.8 4.1 5.1 5.6 3.6 5.2 5.0 

Geometric Mean Bias 0.0 0.0 0.1 0.0 -0.1 -0.2 -0.2 -0.1 0.1 0.1 

Geometric Mean Error 0.2 0.2 0.4 0.1 0.3 0.3 0.3 0.2 0.4 0.3 

RMSE 2.7 2.3 5.7 2.3 5.2 6.0 6.8 4.5 5.9 6.9 

MaxOBS 21.2 22.0 14.0 17.9 23.5 29.0 33.3 36.5 31.6 23.4 

MaxPRE 17.2 27.2 27.1 16.6 20.7 25.4 28.6 27.9 31.8 30.6 

Mean Observations 14.0 10.1 10.0 11.6 15.7 18.9 20.9 20.9 17.3 15.4 

Mean Predictions 13.6 10.9 11.6 11.1 13.9 16.2 17.5 18.6 18.8 18.4 

Standard Deviation of 

Observations 5.4 5.2 3.6 3.9 5.9 6.8 5.7 8.1 10.2 5.4 

Standard Deviation of 

Predictions 3.8 7.0 6.8 3.7 4.7 6.3 6.5 5.0 8.6 8.5 

R2 0.7 0.9 0.3 0.7 0.3 0.4 0.2 0.8 0.6 0.4 

BF 1.0 1.1 1.2 1.0 0.9 0.9 0.9 0.9 1.3 1.2 

Number of Samples 5 9 8 9 10 10 10 9 10 10 

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4.2.3.1.2 Model Performance Statistics for STN Sites

The model performance was evaluated for particulate 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 evaluation was conducted for all available PM2.5 species, we 

briefly present annual summary statistics for these species and total PM2.5 here. 

Sulfate and total PM2.5 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. However, this is not a significant issue for the 

overall model performance because the contribution of NO3 to the total PM2.5 is relatively small 

in GA. Also, we saw under-predictions of OC concentrations in GA. This issue was closely 

examined in Appendix K.3. From Table 4-10, similar tendencies can be seen at the STN monitor 

in the Floyd County nonattainment area. More detailed performance analyses with graphical 

measures can be found in the following sections. 

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Table 4-9. Annual model performance statistics for PM2.5 species and total PM2.5 at all STN 

monitors in the State of Georgia. 

Statistics SO4 NO3 NH4 OC EC PM2.5

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 

Ap -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 

MaxOBS 39.9 5.0 10.7 13.6 3.5 40.9 

MaxPRE 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 

R2 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 

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Table 4-10. Annual model performance statistics for PM2.5 at 13-115-0005.

Statistics SO4 NO3 NH4 OC EC PM2.5

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 

Ap 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 

MaxOBS 14.6 3.5 3.8 10.1 0.8 33.5 

MaxPRE 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 

R2 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 

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

4.2.4 Summary of the performance evaluation of the CMAQ modeling

In general, the CMAQ modeling met the performance “criteria level” for all major PM2.5

constituents and the total PM2.5 across the State of Georgia throughout the base year. As 

the first step of model performance evaluation, 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 comparable 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 generally adequate across GA 

and acceptable for the Floyd County nonattainment area. 

Similar analyses were conducted for the STN monitors on total PM2.5 and all of measured 

PM2.5 species. The most significant findings were that (1) the model’s sulfate and PM2.5

performance were quite good and (2) NO3 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 PM2.5 species and total PM2.5 concentrations were 

examined with these packages. Whenever data were available, each package included 

scatter plots for monitors within GA and in the Floyd County nonattainment area, time 

series plot for the monitor in the Floyd County nonattainment area, bar plots of fractional 

bias and fractional error for monitors within GA, bar plots of fractional bias and 

fractional error for monitors in the Floyd County nonattainment area, bugle plots for 

monitors within GA, and soccer plots for monitors within GA. In addition, more 

graphical measures were examined if necessary. 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 graphical analysis. The evaluation included 

speciated data available from IMPROVE, CASTNET, SEARCH, and STN as well as 

total PM2.5 from FRM monitors. 

Overall, the model showed reasonable performance for PM2.5, SO4, NH4, and OC 

throughout the base year across all monitors in GA. During summer, the model showed a 

seasonal variation of NO3 performance with under-prediction bias greater than –100% 

and moderate winter over prediction at CASTNET sites. The amount of error and bias in 

monthly time series was most likely contributed by low concentration (< 1.0 μg/m3

) 

cases. As shown in Figure 4-7, SO4 and OC were the major contributors to the Floyd 

County nonattainment areas. Therefore, GA EPD concluded that performance issues 

found in minor constituents of PM2.5 are not likely degrading the overall model 

performance. 

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Figure 4-7. Stacked bar plots of daily PM2.5 species concentration at 13-115-0005. 

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

issues for SO4, OMC, and NH4. 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 function 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 performance is well within the limits of 

acceptable performance criteria established in the Attainment Modeling Guidance. 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Section 5. Control and Contingency Measures 

Control measures are used to reduce emissions of direct PM2.5 and PM2.5 precursors 

and are therefore of primary importance to demonstration of attainment. Those measures 

that had already been implemented through the end of 2002 (the year of the baseline 

emissions inventory) are not discussed 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 provide small reductions to ambient PM2.5 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 and Recreational Engines Standard 

• NOx SIP call in surrounding states 

These measures are described in Table 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 limiting the emissions of NOx and sulfur dioxide 

(SO2) and a model rule for the states to use in developing their rules. The purpose of the 

CAIR is to reduce interstate transport of precursors to fine particulate and ozone. 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Table 5-1. Federal PM2.5 Control Measures 

Control Measure for Attainment Demonstration1

Control Measure – Benefits2

Measure Sources 

Affected 

Measure and Schedule 

Species Affected/ Reduced 

Measure and Schedule 

Clean Air Interstate Rule (CAIR) 40 CFR 96, Subparts AAA - HHH 

Coal-fired Electric Gen. Units, 28 eastern states and D.C. 

Regional cap on NOx and SO2 emissions from EGU’s: NOX Phase 1 starts 2009 

NOX Regional cap on NOX and SO2 

emissions from EGU’s: SO2 Phase 1 starts 2010 

Tier 2 vehicle standards 40 CFR 80, 85 , and 86

NEW PASSENGER VEHICLES 

Fleet average for NOx emissions per mile, effective 2004 through 2007 

NOx Continuing vehicle 

turnover 

Heavy Duty Engine Standard (Gasoline and Diesel), second phase 40 CFR 86, Subpart A

New gas and diesel highway vehicles 14001 lbs or greater 

Effective 2004 and later – NOx and VOC controls; Effective 2007 and later – PM controls

NOx, VOC, and PM (soot); PM limit of 0.01 g/bhp/hr 

Continuing vehicle turnover 

Ultra Low Sulfur Diesel 40 CFR 80, Subpart I

New diesel highway vehicles 14001 lbs or greater 

Limits 80 % of pool of highway diesel to sulfur content of 15 ppm or less, 2007 – 2009: facilitates proper operation of heavy duty diesel PM controls (see above) 

PM (soot) Limits 100 % of 

pool of highway diesel to 15 ppm sulfur or less; 2010 on - facilitates proper operation of heavy duty diesel PM controls (see above) 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Table 5-1. Federal PM2.5 Control Measures (continued) 

Control Measure for Attainment Demonstration1

Control Measure – Benefits2

Measure Sources 

Affected 

Measure and Schedule 

Species Affected/ Reduced 

Measure and Schedule 

Nonroad Diesel Rule 40 CFR 89

NEW MOBILE SOURCES: OFF-ROAD, SHIPS, LOCOMOTIVES 

2008 through 2014; Should reduce NOx and PM emissions by over 90 % 

NOx, PM (soot) Continuing vehicle 

turnover 

Large Spark Ignition and Recreational Vehicle Rule 40 CFR 90 

Forklifts, airline ground service equipment, allterrain vehicles, off-highway motorcycles, marine diesel engines 

LARGE SPARK IGNITION EQUIPMENT (FORKLIFTS, AIRLINE GROUND SERVICE EQUIPMENT) – 2004; OFF-ROAD VEHICLES – 2006; MARINE ENGINES - 2006 

VOC, NOx, CO Continuing 

equipment turnover 

NOx SIP Call in Surrounding States 

utility and industrial boilers; internal combustion engines 

Controls on utility and industrial boilers and on internal combustion engines in 22 eastern states by 2004 

NOx 

(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 count toward attainment but will provide emissions reductions 

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Control and Contingency Measures PM2.5 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 time 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 cogeneration unit during the 12-

month period starting on the date that the unit first produces electricity 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 and supplying in any calendar year more than 

one-third of the unit's potential electric output 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. Because 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 allowing 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 contributes significantly to 

downwind PM2.5 nonattainment areas and/or interferes with maintenance of the PM2.5 

NAAQS (70 FR 25246-25250). Accordingly, a State CAIR rule (Georgia 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, respectively. 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 Alabama, Florida, North Carolina, South 

Carolina, and Tennessee. These states will also have caps on SO2 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 NOx 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 passenger vehicles over 8,500 pounds gross vehicle 

weight rating (the larger pickup trucks and SUVs), which are not covered by the current 

Tier 1 regulations. For these vehicles, the standards will be phased in beginning in 2008, 

with full compliance in 2009. The new standards 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, but interferes with the operation of catalytic 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

converters on vehicles resulting in higher emissions. 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 began 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 the 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 engines 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 nonroad diesel rules also reduce the allowable sulfur in 

nonroad diesel fuel by over 99%. Nonroad diesel fuel currently 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 engines (forklifts and airport ground service 

equipment), recreational vehicles (off-highway motorcycles and all-terrain-vehicles), and 

recreational marine diesel engines. The regulation varies based upon the type of engine 

or vehicle. 

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

levels in urban areas. Tier 1 of this standard was implemented in 2004 and Tier 2 started 

in 2007. Like the large spark-ignition engines, recreational vehicles contribute to ozone 

formation and ambient CO and PM levels. For the off-highway motorcycles and allterrain-vehicles, model year 2006, the new exhaust 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 ozone formation and PM levels, especially in 

marinas. Depending on the size of the engine, the standard began phasing in 2006. 

When all of the nonroad spark-ignition engines and recreational engines standards are 

fully implemented, an overall 72% reduction in HC, 80% reduction in NOx, and 56% 

reduction in CO emissions are 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 finding 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 transport of ozone (63 FR 57356). This rule, referred to 

as the NOx SIP Call, called for ozone season controls to be put on utility 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 state 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 budgets 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 generation of the 2009 

emissions inventory: 

• Multipollutant Rule for coal-fired electric generating units (EGUs) 

• Heavy-duty Diesel Engines Rule 

These measures are described in Table 5-2 and in the following text. 

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Table 5-2. State PM2.5 Control Measures and Contingency Measures 

Control Measure – Attainment Demonstration1

Control Measure – Benefits2

Measure Sources 

Affected 

Measure and Schedule 

Species Affected/ Reduced 

Measure and Schedule 

Multipollutant rule Air Quality Control 391-3-1-.02 (2) (sss) 

Electric Gen. Units, CoalFired, GA 

Flue Gas Desulf. for 7 EGUS3 STARTING 

IN 2008 - APPROXIMATELY 194,000 TONS/YR REDUCED 

SO2 sources 

outside the nonattainment area 

Flue Gas Desulf. for Bowen Unit 2, June 1, 2009, Wansley Unit 2, December 31, 2009, and Bowen Unit 1, June 1, 2010 

Heavy Duty Diesel Engines rule Air Quality Control 391-3-1-.02 (2) (ooo) 

Diesel Vehicles 14001 lbs or greater 

Diesel Vehicles 14001 lbs or greater meet CARB standards; 2005 and subsequent models 

PM (soot) sources inside the nonattainment area 

Continuing equipment turnover 

(1) Control measures for attainment demonstration – after 2002, before 2009 – permanent and enforceable, SIP counts toward attainment demonstratio(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 1 

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5.2.1 Multipollutant Control for Electric Utility 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 Georgia. It was enacted in 2007 for the purposes 

of lowering ozone and PM2.5 concentrations and reducing mercury deposition. The 

controls will reduce SO2 emissions from the affected emissions units by at least 95 

percent and will reduce NOx emissions by approximately 85 percent. 

The control implementation date of the rule varies by EGU, starting on December 31, 

2008. Controls are required on seven of the units prior to the attainment 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 last 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 located outside the nonattainment area will be 

implemented in 2009 and 2010. 

 

A separate Georgia rule, rule (uuu), places specific 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 emission limits required by rule (uuu) become 

effective January 1, 2010, through June 1, 2015, depending upon the unit.

Table 5-3. Georgia Multipollutant Rule SO2 Control Requirements and Construction 

Permit Conditions 

Plant/Unit County Required FGD 

operation date, 

per rule (sss) 1

ConTrol4Conting. 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 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Plant/Unit County Required FGD 

operation date, 

per rule (sss) 1

ConTrol4Conting. Construction 

Permit 

Number 

Permit Effective 

Date 

V01-9 (permit 

to construct)) 

 Bowen Unit 2 Bartow 06/01/2009 NA2 4911-015-

0011-V-02-3 

12/20/06 

 Wansley 

Unit 2 

Heard 12/31/2009 NA2 4911-149-

0001-V-02-0 

(incorporated 

draft permit 

V01-9 (permit 

to construct)) 

1/1/2007 

 Bowen Unit 1 Bartow 6/1/2010 NA2 4911-015-

0011-V-02-3 

12/20/06 

Scherer Unit 3 Monroe 12/31/2011 X FGD control to 

be 

incorporated 

into permit 

renewal3

(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 engines (vehicle weight of 14001 lbs or more) to 

meet the California Air Resources Board (CARB) emissions standards by 2005. These 

standards are essentially the same as the federal 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 ensure 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 reduce NOx by 13 tons per day statewide and 8 tons 

per day in the 45 county Atlanta ozone control area in 2005. These emissions benefits 

would potentially double in 2006 if the manufacturers continued to not meet the NTE test 

requirements. Manufacturers were required federally to begin testing the engines to the 

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NTE requirements with the 2007 model year. Georgia has kept the 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 engine standards. Also, the CARB engine 

requirements differ from EPA’s in that CARB 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 Georgia. However, it is expected to reduce 

NOx and PM emissions. 

5.3. Summary of SO2 Emissions Changes

Control of SO2 sources is the primary mechanism 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 source category in the tables below. The 

changes for the nonattainment area and the state are presented in Tables 5-4 and 5-5, 

respectively. Reductions in emissions are shown 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 Emissions, 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 installed in May 2008. 

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The total statewide SO2 emissions change is a decrease of 125,390 tons. The statewide 

change is more pertinent to demonstrating attainment in 2009. 

5.4. Contingency Measures

Section 172(c)(9) of the Clean Air Act requires states to identify 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 demonstrate 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 attain the standards by its attainment date. These 

contingency measures must be fully adopted rules 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 contingency measures, specify a schedule for 

implementation, and indicate that the measures will be implemented without significant 

further action by the State or by EPA. The contingency measures should consist of other 

control measures for the area that are not included 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 designation, 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 rule requires states to adopt “contingency measures equal 

to approximately one year’s worth of reductions 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 reductions needed to meet attainment will satisfy 

the requirement for contingency measures. 

The purpose of these contingency measures “is to provide a cushion while the plan is 

being revised to meet the missed milestone” (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 April 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 implemented approximately within 2 calendar years 

following the final emissions control year in the attainment demonstration. This time 

period takes into consideration the time required for EPA to make a finding of failure to 

attain the NAAQS and the requirement to submit a revision to the SIP. Contingency 

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Control and Contingency Measures PM2.5 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 SO2 emissions from Georgia’s coal-fired EGUs, as required by Georgia 

rules 391-3-1-.02(2)(sss) and (uuu). There is one coal-fired plant located in Floyd 

County, Georgia Power’s Plant Hammond. The plant has 4 EGU’s controlled by FGD 

for SO2 during the attainment period. Floyd County also demonstrates SO2 reductions 

from the mobile and nonroad sectors due to federal fuel requirements. Table 5-6 below 

illustrates the SO2 emissions changes in the Floyd County NAA for the attainment period. 

Reductions in emissions are shown as negative numbers. 

Table 5-6. Predicted changes in SO2 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), mostly 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. 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Since there are no additional coal-fired EGUs, or other point source reductions of SO2 

occurring within the Floyd County NAA, and there are no federal measures that result in 

additional emission reductions, contingency measures for Floyd County will be based on 

control of SO2 emissions from sources located outside of the nonattainment area and 

located in Georgia. 

5.4.1 Region for Contingency Measures

The application of RFP procedures to calculate 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 believes that states could be able to justify considering not 

only all emissions in the NAA, but also emissions 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-attainment area for its contingency measure 

emission reductions and rely on additional 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 Bowen. GA EPD notes that this method of 

determining the area from the monitor is more 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. 

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Figure 5-1 Floyd County Area of Influence 

5.4.2 Area of Influence Emission Reductions 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 demonstration 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 influence to demonstrate contingency emission 

reductions. 

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Table 5-8 displays the 2002 baseline 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 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 control 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

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

Table 5-10 displays the 2012 year SO2 emissions, by source sector, for the counties 

located within the area of influence for the Floyd County NAA and includes Floyd 

County. The total 2012 SO2 emissions, for the area 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 during the attainment period within the area 

of influence, which includes Floyd County, is 99,517.4. One seventh of this value is 

14,216.7 tons of SO2. The emission reduction for the area during the contingency period 

is 73,032.1 tons of SO2, which is far in excess of one year’s worth of emission for RFP 

of 14,216.7. 

Table 5-11. Total SO2 Emissions For 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

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Control and Contingency Measures PM2.5 Attainment SIP – Floyd County, GA 

5.4.3 Adopted Controls for Contingency Measures 

 

The emissions values in Tables 5-9, 5-10, and 5-11 demonstrate that the majority of the 

SO2 emission reductions occur from EGU point sources. The emission reductions prior 

to attainment were contributions from both EGU reduction and federal fuel programs. 

The emission reductions during the contingency period were overwhelmingly EGU SO2 

reductions. 

The EGU point source located within the 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, which is within the 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 and that will be required by 

Georgia Rule (uuu). The controls and limit will effect emissions reductions of 73,809.3 

tons, as shown in Table 5-12, during the contingency period. 

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

measures at coal-fired electric generating 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 measure is required by Georgia rule 391-3-

1-.02(2)(uuu) and will take affect regardless of the attainment status of the Floyd County 

NAA. Therefore, no trigger mechanism is needed 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 which are voluntary actions, should provide 

additional reductions to ambient PM2.5 concentrations: 

• Open burning rule 

• Switching of two EGUs to lower sulfur coal 

• Planned early start-up of SO2 scrubbers at two EGUs 

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Because the measures are voluntary and/or the benefits are relatively small, credits for 

these measures have not been taken in the projected emissions inventory 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 Measure 1 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 additional restrictions on open burning in Catoosa 

and Walker Counties. The rule prohibits open burning with the exception of 12 types of 

burning activities. During May through September the number of allowed exceptions is 

reduced to six. The rule reduces emissions of elemental carbon and 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 and 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 July 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 

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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 SO2 controls on coal-fired EGUs. Because the start-ups of scrubbers on 

Bowen Unit 2 and Wansley Unit 2 are not required until June and December of 2009, 

SO2 emissions reductions associated with these 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 occur early as planned, then the 

scrubbers at Bowen Unit 2 and Wansley Unit 2 would achieve 2009 SO2 emissions 

reductions beyond those credited in the modeled attainment demonstration. The quantity 

of unmodeled 2009 emissions reductions would 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 contribute to attainment as 

“expeditiously as practicable” in the specific nonattainment area. The EPA has 

consistently interpreted RACM as a collection of measures that would advance the 

attainment date by at least one year. This requirement also applies to emissions 

reductions from existing stationary sources through the adoption of reasonably available 

control technology (RACT). “Reasonably available” 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/m3

 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 subject to a limited RACT/RACM analysis. 

EPA has stated (72 FR 20617) that “If the State 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 time from the promulgation of the rule to the 

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SIP due date, it would be difficult for states to devise, adopt, and implement RACM in 

time to advance the attainment date. EPD concurs that either a case-by-case RACT 

analysis and permitting or new RACT/RACM rule development, including the analysis, 

stakeholder process, rule development, public comment, and administrative 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 the 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 determination that the 

primary component of ambient monitored PM2.5 is the precursor SO2, with the primary 

source of SO2 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 relative difference in the magnitude of emissions of EGU and 

non-EGU sources of SO2 emissions. The supplemental analysis in the attainment 

demonstration section of this document discusses EPD’s determination that SO2 is the 

significant contributor of PM2.5 emissions and that the control of SO2 emissions from 

EGUs is the most effective strategy for significant PM2.5 air quality improvements. 

Using the results of this modeling analysis, evaluating Georgia’s other PM2.5 

nonattainment areas (Atlanta, Chattanooga, and 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 Visibility Rule (CAVR), the State of Georgia 

adopted State Rule 391-3-1-.02(2)(sss) “Multipollutant Control for Electric Utility Steam 

Generating Units” (Multipollutant Rule) effective 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. Nonattainment Area Major Source SO2 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 included in this rule by requiring all EGUs 

located at Georgia Power Plant Hammond, which is located within the Floyd County 

nonattainment area, to install FGD. The rule requires all four units at Plant Hammond to 

begin operation of FGD in 2008. While 72 FR 20623 includes a presumption that 

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compliance with CAIR satisfies RACT for SO2 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 expeditiously as practicable. The timing of the 

installation and operation of controls at Plant Hammond will not advance the attainment 

date for Floyd County. EPD notes that Georgia’s Multipollutant rule requires SO2, NOx, 

and Hg controls on all large EGUs in the state. 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 within the State of Georgia. 

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Section 6. Attainment Demonstration 

This chapter details the procedures that were used to demonstrate attainment of the 

annual fine particulate matter (PM2.5) National Ambient Air Quality Standard (NAAQS) 

for the Floyd County nonattainment area. As described in the US Environmental 

Protection Agency’s (USEPA’s) Guidance on the Use of Models and Other Analyses for 

Demonstrating Attainment of Air Quality Goals for Ozone, PM2.5, and Regional Haze 

(“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 analysis (UAA) to the air quality modeling 

results to determine if the annual PM2.5 NAAQS will be met. Additional technical or 

corroboratory analyses may also be used as part of a “supplemental analysis” or a more 

stringent “weight of evidence” determination to supplement the modeled attainment test 

and to further support a demonstration of attainment of the NAAQS. 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 attainment of the NAAQS for PM2.5 by the attainment year of 2009. The 

modeling is applied in a relative sense, similar to the 8-hour ozone attainment test. 

However, the PM2.5 attainment test is more complicated and reflects the fact that PM2.5 

is a mixture of different species. In the test, ambient PM2.5 is divided into major 

components, with a separate relative response factor (RRF) and future design value 

(DVF) calculated for each of the PM2.5 components. Since the attainment test is 

calculated on a per species basis, the attainment test for PM2.5 is referred to as the 

Speciated Modeled Attainment Test (SMAT). The following subsections outline the 

process that was used to determine 2009 model projections of PM2.5 and compare them 

to the NAAQS. Complete calculations and results are contained in Appendix M. 

6.1.1 Determination of Baseline Design Values 

The first step in any attainment test process 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 

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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) monitor in the PM2.5 nonattainment area. 

Concentrations are calculated based on calendar 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 occur 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 quarterly 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 Annual 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 

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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” primary inorganic particulate matter (Crustal) 

8. And passively collected mass or the mass of the blank filter (Blank = 0.5 μg/m3

) 

The second part of the process is to use the 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 FRM 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) has a co-located SPECIATION monitor. 

The following sections will explain how this data was used to produce the speciated 

values needed for this attainment demonstration. 

6.1.1.2.1 SANDWICH 

As the Attainment Guidance notes, recent data 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 particle bound water associated with sulfates, 

nitrates and other hygroscopic species (positive sampling artifacts). This results in 

concentrations (and percent contributions to PM2.5 mass), which may be different than 

the ambient levels of some PM2.5 chemical constituents. 

To resolve the differences between FRM and speciation total mass, the US EPA has 

recommended using the Sulfate, Adjusted Nitrate, Derived Water, Inferred Carbon 

Hybrid (SANDWICH) material balance approach. With the SANDWHICH approach, 

nitrate mass is adjusted to account for volatilization based on hourly meteorology 

parameters. Subsequently, quarterly average nitrate, sulfate, elemental carbon, and 

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crustal mass can be calculated, as well as the Degree of Neutralization (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, nitrate, 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 component mass (i.e. OC from mass balance 

([OCMmb]) = PM2.5FRM - {[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 sites have co-located speciation monitors to 

provide speciated data. The US EPA Attainment 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 create a spatial field using ambient speciation 

data 

4. Use of interpolation techniques to create 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 concentrations at FRM sites that do not have 

speciation data (numbers 3 and 4 above). To assist in this task, EPA is developing a 

software tool called “Modeled Attainment Test Software” (or MATS) that will perform 

the spatial analysis of options number 3 and 4 described above. However, the PM2.5 

portion of the MATS tool had not been released at the time this analysis was performed. 

In trying to pursue the US EPA recommended course, 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 both the Interagency Monitoring of Protected 

Visual Environments (IMPROVE) and the US EPA’s Speciation Network (ESPN) to 

derive mean concentrations for six PM2.5 components. Quarterly average concentrations 

between Jan 2002 to December 2002 were retained 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 crustal material (which includes the five 

trace elements aluminum, calcium, iron, silicon, and titanium). The major species for 

IMPROVE are the same except for NH4, which is not routinely measured in the 

IMPROVE protocol. 

The quarterly averaged species concentrations 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). 

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As a result of the CAIR SMAT process, quarterly species fractions were generated for the 

Rome FRM site, which are presented in Table 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 constant passive blank 

mass of 0.5 μg/m3

. DON refers to degree of neutralization of sulfate and ranges from 0.0 

(sulfuric acid) to 0.375 (completely neutralized in the form of ammonium sulfate).

Table 6-3. DVB Quarterly Species Fractions (%) 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 (μg/m3) 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) for 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 concentration near the same monitor, or: 

Quarterly Mean Year Base Modeled Concentrat X""Monitor Near""ion 

Quarterly Mean Year Future Modeled Concentrat X""Monitor Near""ion RRF =

Instead of focusing on the individual 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 the grid cell that contains the monitor, but 

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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 year modeling output near the FRM monitoring 

sites for each day. The daily component concentrations from each cell of the 3x3 array 

are then averaged to develop a single mean 24-hour average concentration for each 

component on each day in both the base and future years. These mean daily component 

concentrations are then averaged for each quarter to develop base and future year 

quarterly mean component concentration. The future year quarterly mean component 

concentrations are then divided by their respective base year quarterly mean component 

concentrations to develop quarterly RRFs for each component of PM2.5. The quarterly 

RRFs for the FRM monitors in the Floyd County PM2.5 nonattainment area are presented 

below in Table 6-6. In lieu 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)) 

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Table 6-6. Quarterly Component RRFs 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 calculate 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 quarterly component DVFs for the monitor in the 

Floyd County PM2.5 nonattainment area are provided below in Table 6-7. 

Table 6-7. Quarterly Component 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 μg/m3

 blank mass. The 2009 annual PM2.5 concentration (DVF) is then compared to 

the NAAQS (15.0 μg/m3

). Since the value is less than 15.0 μg/m3, the test is passed. 

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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 additional analyses of air quality, emissions and 

meteorological data, and consider modeling outputs other than the results of the 

attainment test. If the attainment test results fall short of the standard, the results of 

corroboratory analyses may be used in a weight of evidence determination (WOE) to 

show that attainment is likely despite modeled results, which may be inconclusive. 

The Attainment Guidance defines the guidelines for supplemental analysis/WOE for the 

annual PM2.5 standard as follows: 

- Site with a DVF less than 14.5 μg/m3

 should submit basic supplemental analysis 

to confirm the outcome of the model attainment test. 

- Sites with a DVF between 14.5 and 15.5 μg/m3

 should submit a weight of 

evidence demonstration to aggregate supplemental analysis to support the model 

attainment demonstration. 

- Sites with a DVF greater than or equal to 15.5 μg/m3

 should consider additional 

control measure to ensure attainment, as more qualitative analysis is unlikely to 

demonstrate attainment. 

Because the Floyd County PM2.5 nonattainment monitor has a DVF lower than 14.5 

μg/m3, the following supplemental analysis to corroborate modeling results should be 

adequate to complete the attainment demonstration, rather than a WOE analysis to show 

attainment. In the following sections we explore refinements to the attainment test, 

additional modeling studies, and 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 analysis. 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. 

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Attainment 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 μg/m3

 within the nonattainment 

area 

2. Percent change in number of grid cells > 15 μg/m3

 within the nonattainment area 

3. Percent change in grid cell-hours (days) > 15 μg/m3

 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 Guidance, care should be taken in interpreting 

absolute metrics if the model evaluation shows a large under prediction 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 concentrations 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 portion of the Floyd County nonattainment area. 

Figure 6-1 highlights the 17 cells that encompass the Floyd County nonattainment area. 

129 of 148 
Attainment 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 μg/m3 intervals. 

Figure 6-2 presents the cell-days count results graphically and shows an increase in the 

number of cell-days below 15 μg/m3

. 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 μg/m3 range to the less than 

15 μg/m3 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 μg/m3 bin (23 

cell-days decrease), the 20 – 25 μg/m3

 bin (197 cell-days decrease), the 25 – 30 μg/m3

bin (169 cell-days decrease), the 30 – 35 μg/m3

 bin (21 cell-days decrease), and the 35 – 

40 μg/m3

 bin (10 cell-days decrease). In addition, the number of cell-days in the greater 

than 40 μg/m3

 bin decreased to 0 cell-days (100.0% decrease) from 2002 to 2009. 

Overall, the results from the air quality modeling metric are encouraging as shown by the 

substantial increase in the number of cell-days below 15 μg/m3

. 

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Attainment 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 change) within the bins are noted by red 

(blue) coloration. 

 

Concentration 

[μg/m3

] 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 

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Attainment 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 studies. 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 contained 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 implementation for the CAIR. Differences between the 

USEPA’s modeling and the attainment demonstration are: 1) the meteorology was for 

2001, 2) the DVB was the weighted design values for the 1999-2003 period and 3) the 

modeling results were for 2010. The DVF was calculated using the CAIR SMAT tool, so 

methodologies between the CAIR DVF and the values presented in Section 6.1 are the 

same. These modeling results are listed in Table 6-11 below. 

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

Future Year PM2.5 (μg/m3

) 

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 predicts that the Floyd County nonattainment 

area would be slightly above the annual PM2.5 standard in 2010 and 2015. Although 

these projections are above the PM2.5 standard, 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 these controls, it is highly likely that the 

Floyd County nonattainment area would have modeled 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 (arithmetic average of 

quarterly averages) from 1999 to 2008. Overall, PM2.5 concentrations have decreased 

for this time period. 

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Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA 

The overall trend can be divided into three 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 compared with 2002. The last period (2005-

2008) shows a small decrease of PM2.5 concentrations through 2007 and a marked 

decrease in 2008. The actual values used to create Figure 6-3 are listed in Table 6-12. In 

2008, the PM2.5 annual mean concentration dropped to 12.7 μg/m3

 , which is well below 

the 15.0 μg/m3

 standard. 

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Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA 

Table 6-12. Annual Average PM2.5 values (μg/m3) 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

Year

Concentration [ug/m 3]

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 monitor (13-021-0012) has maintained 

134 of 148 
Attainment 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 dropping below the standard (See Table 6-13). 

135 of 148 
Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA 

Table 6-13. Three-year Design 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 note that there are still 

significant sulfur dioxide (SO2) emission reductions 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, including all four of the EGUs in Floyd 

County. Table 6-14 lists the units in the state of Georgia and shows the date the controls 

did come or are expected to come on line and the estimated amount 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 Georgia, this substantial reduction in SO2 should 

result in significant reductions of the observed 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 reductions from new controls on Georgia Power 

EGUs in 2008 and 2009. 

Facility Unit Control Date1 2007 SO2 

Emissions2

(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 company-provided 

forecast installation dates. 

(2) Calculated from continuous emissions monitor data.

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Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA 

Statewide EGU emission trends for SO2 (based 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 County (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 interpolating 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 concentrations start to trend downward in 2006 

due to emission reductions in neighboring states. 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 combination 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

1,000,000

19992000200120022003200420052006200720082009

SO2 Emissions (Tons/Year)

0.0

2.0

4.0

6.0

8.0

10.0

12.0

14.0

16.0

18.0

20.0

PM2.5 (

μg/m3)

Figure 6-4. PM2.5 monitoring trends1 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 148 
Attainment Demonstration PM2.5 Attainment SIP – Floyd County, GA 

6.2.3 Supplemental Analysis Conclusions

After examining the totality of the modeling evidence, GA EPD is confident the Floyd 

County nonattainment area should reach attainment status by the 2009 deadline. PM2.5 

annual average concentrations should continue to decrease due to substantial sulfate 

reductions anticipated in the state over the 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 future air quality at locations where there is 

not a PM2.5 monitor nearby. To guard against the possibility that air quality levels could 

exceed the standard in areas with limited monitoring, Section 3.4 of the Attainment 

Guidance suggests that additional review is “necessary, particularly in nonattainment 

areas where the ozone or PM2.5 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 leads 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 network relieves the necessity of applying this 

additional analysis. However, GA EPD decided to apply some additional analysis and 

looked at 2009 PM2.5 concentrations directly from the model (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 “nearby” 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 this 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 unmonitored 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 calculated at the FRM monitor using SMAT and 

SANDWICH. However, this discrepancy between 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 148 
Attainment 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 and air quality models and any other files 

used to develop the modeling. To request access to these files please contact the Georgia 

EPD Air Protection Branch’s Data & Modeling Unit at 404-362-4851. 

139 of 148 
Other 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 amended, contains the plan requirements for 

nonattainment areas in general. The Floyd County PM2.5 nonattainment area must meet 

these requirements, which are listed in Table 7-1 and summarized below. 

Table 7-1. General Plan Requirements 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 include 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 148 
Other 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 (RACM) 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 designation, 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 inventories 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 through 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 inventory 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 identification 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 development should be targeted. Georgia has no 

such zones targeted for economic development identified by the Administrator. 

141 of 148 
Other Clean Air Act Requirements PM2.5 Attainment SIP - Floyd County, GA 

Section 172(c)(5) requires a permit program consistent with the requirements of Section 

173. Georgia EPD updated rules for nonattainment 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 including 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 SIPs to include enforceable limits and other 

control measures, along with schedules for compliance as needed to demonstrate 

attainment. Section 5 of this document discusses 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 nonattainment 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 EPA Region 4, certifying that its existing SIP 

contains provisions that address the requirements for the 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 section 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 elements 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 procedures for modeling, emissions inventory and 

planning follow the US EPA guidance and is not requesting approval for equivalent 

techniques, as envisioned under Section 172(c)(8). 

7.9 Contingency Measures

The Clean Air Act requires States containing nonattainment areas to adopt contingency 

measures that will take effect without further action by the State 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 applicable NAAQS, as described in Section 

172(c)(9). These measures are discussed in Section 5.3. 

142 of 148 
2009 Motor Vehicle Emissions Budget PM2.5 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 rule1

 as "...the implementation plan's 

estimate of future [motor vehicle] emissions." 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 Vehicle 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), the metropolitan planning organization for 

Rome/Floyd County, to develop the estimates of mobile2

 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 source emissions on which the 2009 MVEB is 

based is discussed below and, in greater detail, in Appendix J. 

The MOBILE6.2 motor vehicle emission factor model was used to calculate 2009 

emission factors with all proposed 2009 mobile 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 program, and Georgia's seasonal low-RVP 

gasoline marketing requirement. 

The emission factors resulting from the MOBILE6.2 runs for the Floyd County 

nonattainment area were used with GDOT's link-based emissions estimation procedure to 

calculate 2009 tons per year emissions in the following manner: 

• For each of four times of day (a.m. peak, midday, p.m. peak, and night), the HPMSadjusted3

 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 148 
2009 Motor Vehicle Emissions Budget PM2.5 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 converted 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 travel 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 calculated emissions inventory for the Floyd County PM2.5 

nonattainment area. 

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

Nonattainment Area 

PM2.5 

(tons/year) 

2009 Mobile Emissions for Floyd County 41.8290

2009 Motor Vehicle Emissions Budget 41.8290

This Floyd County PM2.5 Attainment Demonstration 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 consultation among the relevant agencies occurred 

during the development of this MVEB and prior 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 demonstration is based on new estimates of 

VMT and speeds from an updated, state-of-the-art travel demand model; on the latest 

version of EPA's motor vehicle emission factor model; and on registration distributions 

by age developed using registration data4

 obtained from R.L. Polk & Company. 

To show the MVEB "together with all other emissions sources5," point, area, and nonroad emissions from the 2009 "best-and-final" modeling inventories developed by the 

VISTAS/ASIP contractors were used. Total projected 2009 annual PM2.5 emissions for 

the Floyd County nonattainment area are 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 conformity 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 148 
2009 Motor Vehicle Emissions Budget PM2.5 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 148 
Summary and Conclusion PM2.5 Attainment 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 observed 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 Value for Floyd County Nonattainment Area 

Monitor 

Site name Monitor ID PM2.5 Design 

Value 

 (μg/m3) 

PM2.5

Standard 

 (μg/m3) 

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 organic carbon. 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. 

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 sulfates to the ambient PM2.5 problem in the 

nonattainment area, the most important measures 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 estimated reduction of SO2 emissions from seven 

EGUs between 2002 and 2009 is equivalent to 29.1 percent of projected 2009 statewide 

SO2 emissions (744,000 tons/yr) if no controls were assumed. Other modeled state and 

federal control measures, as well as unmodeled 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 regional haze modeling being done by VISTAS and the PM2.5 and 

ozone modeling being done by ASIP. The models used were as follows: 

• Meteorology model: MM5 

• Emissions model: SMOKE 

• Air Quality model: CMAQ

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Summary and Conclusion PM2.5 Attainment SIP – Floyd County, GA 

An emissions inventory for the modeling was developed for the baseline year 2002 and 

projected to 2009. The pollutants inventoried include VOC, NOx, PM2.5, coarse 

particulate (PM10), NH3, and SO2. The projection to 2009 accounted for control measures 

expected to be implemented.

The CMAQ modeling performance was measured 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 performance is well within the limits of acceptable 

performance criteria established 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 project total PM2.5. The 2009 modeled PM2.5 

design value is presented in Table 9-2. Since the modeled design value is less than 15.0 

μg/m3

, modeled attainment is demonstrated. 

Table 9-2. PM2.5 2009 Future (Modeled) Design Values 

Federal 

Reference 

Monitor 

2009 Annual Design 

Value (DVF) 

 (μg/m3) 

PM2.5 Standard 

 (μg/m3) 

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 that 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 attainment at the FRM monitor located in the Floyd County 

Nonattainment Area. 

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References 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 Commission (TNRCC), ENVIRON International 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 Guide To Interpret Data. University of 

California Davis. Prepared for National Park Service, 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 Implementation Plans (Draft Final Report). 

ENVIRON International Corporation, Novato, California. November 14. 

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