# Georgia's State Implementation Plan
For 

# Regional Haze

January 25, 2010

Prepared by:



# Georgia Department of Natural Resources Environmental Protection Division Air Protection BranchThis page is left intentionally blank.Georgia Regional Haze State Implementation Plan



### Preface: This document contains summaries of the technical an alyses that will be used by Georgia Environmental Protection Division (GA EPD) to support the Regional Haze State Implementation Plan pursuant to §§169(A) of the Clean Air Act, as
amended.Georgia Regional Haze State Implementation Plan

i 

### EXECUTIVE SUMMARY

INTRODUCTION

Regional haze, pollution that impairs the visi bility over a large region, can adversely impact human health, especially respirator y and cardiovascular systems. Regional haze is caused by sources and activities emitting primarily fine particles and those precursors to particle pollution - sulfur diox ides (SO2), nitrogen ox ides (NOx), ammonia (NH3) and volatile organic compounds (VOC). These fine particles and precursors are often transported over large regions, impairi ng visibility in nati onal parks, forests, and wilderness areas including those areas termed “Class I” areas.

Fine particles, similar in size to the wavele ngth of light, affect visibility through the scattering and absorption of light. This is called light extinction, the result of which is a hazy condition. Light extinction is one method of measuring visibility. Another is visual range. Visual range is the greatest distance, in kilometers or miles, at which a dark object can be viewed against the sky. The m easure of visibility used by the Regional Haze Rule (RHR) is the deciview (dv) which is calculated directly from light extinction using a logarithmic scale. The deciview can also be used to express linear changes in visibility impairment that corresp ond to visual range. Theref ore, higher deciview levels are hazier, while lower deciview levels are cleaner.

Reducing fine particles in t he atmosphere is generally c onsidered to be an effective method of reducing regional haze, and thus, improving visibility.

REGULATORY HISTORY AND REGIONAL HAZE IN GEORGIA

Section 169A of the 1977 Amend ments to the Clean Air Act (CAA) set forth a program for protecting visibility in F ederal Class I areas. It called for the “prevention of any future, and the remedying of any existing, impairment of visibilit y in mandatory Class I Federal areas which impairment results from manmade air po llution.” On December 2, 1980, the United States Environmental Protection Agency (US EPA) promulgated regulations to address visibility impairm ent (45 FR 80084) t hat is “reasonably attributable” to a single source or sma ll group of sources. Then, in the 1990 Amendments to the CAA, Congress added Sect ion 169B and called on the US EPA to issue regional haze rules. The Regional Haze Rule that the US EPA promulgated on July 1, 1999 (64 FR 35713), revised the existi ng visibility regulat ions in order to integrate provisions ad dressing regional haze impairment and to establish a comprehensive visibility protection program fo r Class I Federal areas. On July 6, 2005, the US EPA published a revised final rule, including Appendix Y to 40 CFR Part 51, The Guidelines for BART Determinations Under the Regional Haze Rule.

The regional haze rule requires states to demonstrate reasonabl e progress toward meeting the national goal of a return to natural visibility conditions by 2064. The rule directs states to graphically show what w ould be a “uniform rate of progress,” also known as the “glide path,” toward natural conditions for each Class I area within theGeorgia Regional Haze State Implementation Plan

ii states and certain ones out side the states. The table below displays the natural visibility conditions for the most impaired and least impaired days for Georgia’s Class I areas.

Natural Visibility Conditi ons for Georgia Class I Areas Natural Background Visibility Conditions Class I Area Average for 20 percent Worst Days (deciviews) Average for 20 percent Best Days (deciviews)
Cohutta Wilderness Area 10.78 4.32
Okefenokee Wilderness 11.21 5.31
Wolf Island 11.21 5.31

Georgia has three Class I ar eas within its borders: Cohutta Wilderness Area, Okefenokee Wilderness Area and Wolf Island Wilderness Area, as designated in 40CFR Part 81 Subpart 408 where visibilit y has been determined to be an important value. The Georgia Environmental Protec tion Division (GA EPD) is responsible for establishing reasonable progress goals for visi bility improvement at each of these Class I areas, and a long-term strategy that will achieve those reasonable progress goals within the first regional haze planning period ending in 2018.

This SIP includes Georgia’s reasonable progr ess goals, expressed in deciviews, for visibility improvement at eac h affected Class I area for t he first 10-year period until 2064, and must include determinations of the bas eline visibility conditions (expressed in deciviews) for the most impaired and least im paired days. The table below displays the baseline conditions for Georgia’s Class I areas.

Baseline Conditions for Georgia Class I Areas Baseline Visibility Conditions 2000-2004 Class I Area Average for 20 percent Worst Days (deciviews) Average for 20 percent Best Days (deciviews)
Cohutta Wilderness Area 30.25 13.77
Okefenokee Wilderness 27.13 15.23
Wolf Island 1 27.13 15.23

The 20 percent worst visibilit y days at the Cohutta Wilderness generally occur in the period between April and September. The peak hazy days occur in the summer under stagnant weather conditions with high relati ve humidity, high temperatures, and low wind speeds. The 20 percent best visibility days can occur at any time of year. At Wolf Island, Okefenokee Wilderness Area and other c oastal sites, the 20 percent worst and best visibility days are dist ributed throughout the year.

1 There is no visibility monitor located at Wolf Island. Visibility at Wolf Island is assumed to be the same as the nearest Class I area, Okefenokee Wilderness.Georgia Regional Haze State Implementation Plan

iii States must include a monitoring strategy fo r measuring, characterizing, and reporting of regional haze visibility impairment in thei r SIP. The long-term strategy includes enforceable emissions limitations, comp liance schedules, and other measures as necessary to achieve the reasonable progres s goals. States must also consider ongoing control programs, measures to mitigate cons truction activities, source retirement and replacement schedules, smok e management techniques for agriculture and forestry, and enforceability of specific m easures. In developin g this SIP, we have
also considered that emission sources outside of Georgia may affect visibility at these Georgia Class I areas, and emission sources withi n Georgia that may affect visibility at Class I areas in neighboring states.

In addition, a specific component of each stat e’s first long-term strategy is dictated by the Best Available Retrofit Technology (BAR T) requirements in 40 CFR 51.308(e) of the RHR. The RHR at §51.308(e) requires states to include a determination of BART for each BART-eligible source in the State that emits any air pollutant which may reasonably be anticipated to cause or contribute to any impairment of visibility in any mandatory Class I Federal area.

The SIPs for the first review period were due December 17, 2007. These plans cover long-term strategies for vi sibility improvement betw een baseline conditions in 2000- 2004 and 2018. States are required to eval uate progress toward reasonable progress goals every five years to assure that in stalled emission controls are on track with emission reduction forecasts in each state implementation plan.

CONTROLS APPLIED

There are significant control programs being implemented between the baseline period and 2018. These programs will all reduce the particulate precursor emissions that affect visibility in the Class I areas.

Federal control measures incl ude the Clean Air Interstate Rule, NOx reductions from Federal Ozone Measures (NOx SIP Call), motor vehicle emission and fuel standards (e.g., Tiers 0, 1, and 2 em ission standards and fuel sulf ur requirements), and non-road engines and vehicle emission standards.

State control measures include existing NO x RACT measures, the Atlanta 1-Hour Ozone SIP, and the new Georgia Rule 391-3-1-.02(2)(sss) Multi-Pollutant Control for Electric Utility Generating Units that establishes a schedule for the installation and operation of NOx and sulfur diox ide pollution control systems on many of the coal-fired power plants in Georgia. Since the metr o Atlanta region is also designated nonattainment for the Federal PM2.5 standar ds and the 8-hour ozone standard, control strategies for PM2.5 and ozone will be integrated into modeling for this SIP to the extent possible.Georgia Regional Haze State Implementation Plan

iv BART control measures required by the RHR include a BART determination for Interstate Paper in Riceboro, Georgia. This facility will be required to use only natural gas for the Power Boiler (F1) at the fac ility except during periods of natural gas
curtailment.

Reasonable progress goals prom pted GA EPD to consider what additional control
measures would be reasonable. It was dete rmined that SO2 emission reductions from electric generating units (EGUs) and non- EGU point sources in the VISTAS states would be the most effective sources to control to improve visibility at the Georgia Class I areas and non-Georgia Class I areas impacted by Georgia sources. Our review was conducted in a “top down” fashion starti ng with an analysis of the major source categories in each SO2 Area of Influence to determine which major categories had the highest residual contribution to the area in 2018. The regional haze rule requires that states consider the following four factors and dem onstrate how these factors were taken
into consideration in select ing the reasonable progress goal:

• Costs of compliance

• Time necessary for compliance

• Energy and non-air quality environment al impacts of compliance, and

• Remaining useful life of any potentially affected sources.

Georgia EPD requested four-factor analyses from SO2 point sources for emissions units identified as likely to contribute 0.5% or more to the tota l visibility impairment caused by sulfate at any Class I area in 2018. Analyses were received for a total of 15
emissions units. For some em issions units additional data was submitted at the request of EPD or at the initiative of the facility . The submittals have been retained with Georgia EPD’s Regional Haze files. They are availabl e to the public for inspection during normal business hours of 8:00 a.m. to 4:30 p.m. at the Georgia EPD, Ai r Protection Branch, 4244 International Parkway, Suit e 120, Atlanta, Georgia 30354.

Three facilities requested limits on their a ffected emissions units in lieu of performing four-factor analyses: Rayonier Performance Fibers, Packaging Cor poration of America, and Southern States Phosphate and Fertilizer . The requested limit s dropped the sulfate contributions of these units bel ow 0.5 percent of the total sulfate impact on any affected Class I areas. Of those performing the four-factor analysis, GA EPD is requiring lower SO2 limits for three of the faciliti es: Georgia Pacific’s Brunswick Cellulose facility, Georgia Pacific’s Cedar Springs Operation, and International Paper’s Savannah Mill.Georgia Regional Haze State Implementation Plan

v Control measures implemented by other states include measures such as the North Carolina Clean Smokestacks Act, consent agreements with Tam pa Electric, Virginia Electric and Power Company, Gulf Power and American Electric Power, one-hour ozone SIPs submitted by Birmingham and Northern Kentucky, and NOx RACT in 8-hour non-attainment area SIPs.

CONCLUSION

In accordance with the requirements of 40 CFR §51.308(d)(1), this Regional Haze Implementation Plan establishes reasonabl e progress goals for each Class I area in Georgia. To calculate the rate of progress represented by each reasonable progress goal, GA EPD compared baseline visibility conditi ons to natural visibility conditions in each Class I area and determined the uniform rate of visibility improvement (in deciviews) that would need to be maintained during each implementation period in order to attain natural visibility conditions by 2064. Georgia EPD summarized expected visibility improvements under existing Federal and State regulations, BART determinations in Georgia and neighboring states, and any addi tional control measures found to be reasonable to implement in this review period. These controls were modeled in CMAQ as par t of the long-term strategy. Th e modeling results were used to set reasonable progress goals. The tables below display Georgia’s 2018 reasonable progress goals for the 20 percent worst days and the 20 percent best days. Since the Okefenokee Wilderness and Wolf Island reasonabl e progress goals show a slower rate of improvement in visibility than the ra te that would be needed to attain natural conditions by 2064 (uniform rate of progress g lide slope), it has been estimated that an additional 6-7 years are needed to attain natural conditions.

Georgia Reasonable Progress Goals – 20 Percent Worst Days

Class I

Area 2004 Baseline Visibility (dv) 2018 Reasonable Progress Goal (dv)

[2004 – 2018

decrease] 2018 Uniform Rate of Progress Glide Slope (dv)

[2004 – 2018 decrease to meet uniform progress] Natural Visibility (dv)

[2018-2064

decrease needed from

2018 goal]

Cohutta
Wilderness 30.25 22.78 [7.47] 25.71 [4.54] 10.78 [12.00]

Okefenokee
Wilderness 27.13 23.77 [3.36] 23.42 [3.71] 11.21 [12.56]

Wolf Island 27.13 23.77 [3.36] 23.42 [3.71] 11.21 [12.56]Georgia Regional Haze State Implementation Plan

vi Class I

Area 2004 Baseline Visibility (dv) 2018 Reasonable Progress Goal (dv)

[2004 – 2018

decrease] 2018 Uniform Rate of Progress Glide Slope (dv)

[2004 – 2018 decrease to meet uniform progress] Natural Visibility (dv)

[2018-2064

decrease needed from

2018 goal]

Georgia Reasonable Progress Goals – 20 Percent Best Days

Class I

Area 2004 and 2018 Baseline Visibility (dv) 2018 Reasonable Progress Goal (dv)

[2004 – 2018 improvement goal]

Cohutta
Wilderness 13.77 11.75 [2.02]
Okefenokee
Wilderness 15.23 13.92 [1.31]
Wolf Island 15.23 13.92 [1.31]Georgia Regional Haze State Implementation Plan

vii 

### TABLE OF CONTENTS

EXECUTIVE SUMMARY

............................................................................................................. i

INTRODUCTION

........................................................................................................................... i

REGULATORY HISTORY AND REGIONAL HAZE IN GEORGIA

....................................... i

CONTROLS APPLIED

...................................................................................................... iii

LIST OF APPENDICES

............................................................................................................... x

LIST OF FIGURES

.................................................................................................................... xiii

LIST OF TABLES

...................................................................................................................... xvi

1.0 INTRODUCTION

................................................................................................................... 1 1.1 Description of Regional Haze

.......................................................................................... 1 1.2 Clean Air Act Requirements for Addressing Regional Haze

...................................... 1

1.3 General Overview of R egional Haze SIP Requirements

............................................ 2 1.4 Class I Areas in Georgia

.................................................................................................. 4

1.5 State and Federal Land Manager Coordination

........................................................... 6 1.6 Supporting Documentation for the SIP

......................................................................... 9

2.0 ASSESSMENT OF BASELINE AND CU RRENT CONDITIONS AND ESTIMATE OF NATURAL BACKGROUND CONDIT IONS IN CLASS I AREAS

............................... 10 2.1 Estimating Natural Condit ions for Georgia Class I Areas

......................................... 11 2.2 Estimating Baseline Conditi ons for Georgia Class I Areas

....................................... 12 2.3 Summary of Natural Background and Base line Conditions for Georgia Class I
Areas

............................................................................................................................... . 12

2.4 Pollutant Contributions to Visibi lity Impairment (2000-2004 Baseline Data)

......... 13

3.0 GLIDEPATHS FOR CLASS I AREAS IN GEORGIA

..................................................... 18

4.0 NATURE OF THE PROBLEM: CHIEF CAUSES OF VISIBILI TY IMPAIRMENT IN GEORGIA CLASS I AREAS

............................................................................................ 20 4.1 Baseline Emissions Inventory

........................................................................................ 20 4.1.1 Stationary Point Sources

....................................................................................... 21 4.1.2 Stationary Area Sources

........................................................................................ 22

4.1.3 Off-Road Mobile Sources

...................................................................................... 23 4.1.4 Highway Mobile Sources

....................................................................................... 23 4.1.5 Biogenic Emission Sources

.................................................................................. 23 4.1.6 Model Performance Improvem ents through Emissions Inventory Improvements

................................................................................................................ 24Georgia Regional Haze State Implementation Plan

viii 4.1.7 Summary 2002 Base G2 Baseline Emissions Inventory for Georgia

............. 24

4.2 Assessment of Relative Contributions from Specific Pollutants and Sources Categories

....................................................................................................................... 25

5.0 REGIONAL HAZE MODELING METHODS AND INPUTS

........................................... 26 5.1 Analysis Method

.............................................................................................................. 26

5.2 Model Selection

............................................................................................................... 27

5.2.1 Selection of P hotochemical Grid Model

.............................................................. 27

5.2.2 Selection of Meteorological Model

....................................................................... 28 5.2.3 Selection of Emissions Processing System

....................................................... 29

5.3 Selection of the Modeling Year

..................................................................................... 31 5.4 Modeling Domains

........................................................................................................... 32 5.4.1 Horizontal Modeling Domain

................................................................................. 32 5.4.2 Vertical Modeling Domain

..................................................................................... 34

6.0 MODEL PERFORMANCE EVALUATION

....................................................................... 35 6.1 Modeling Performanc e Goals, and Criteria

................................................................. 36

6.2 VISTAS Domain - Wide Performance

.......................................................................... 37 6.3 Georgia Class I Areas Performance

............................................................................. 41

7.0 LONG-TERM STRATEGY FO R GEORGIA CLASS I AREAS

..................................... 45 7.1 Overview of the Long-Term Strategy Development Process

................................... 45 7.2 Expected Visibility Results in 2018 for Georgia Class I Areas under existing and planned emissions controls (Base G4 Inventory)

..................................................... 46 7.2.1 Federal and State Control Requirements

........................................................... 46

7.2.2 Additional State Pr ograms to Reduce Emissions

.............................................. 47 7.2.3 Projected 2009 and 2018 Base G4 Emissions Inventories

.............................. 47

7.2.4 Model Results for the 2018 Base G4 Inventory Compared to the Uniform

Rate of Progress Glidepaths for Georgia Class I Areas

.......................................... 50

7.3 Relative Contribution from International Emissions to Visibility Impairment in 2018 at VISTAS Class I Areas

.............................................................................................. 57 7.4 Relative Contributions to Visibility Impairment: Pollutants, Source Categories, and Geographic Areas

.......................................................................................................... 61 7.5 Relative Contributions to Visibility Impairment: Geographic Ar eas of Influence for Georgia Class I Areas

................................................................................................... 65 7.5.1 Back Trajectory Analyses

...................................................................................... 65

7.5.2 Residence Time Plots

............................................................................................ 66

7.5.3 SO2 Areas of Influence

.......................................................................................... 67

7.5.4 Emissions Sources wit hin SO2 Areas of Influence

........................................... 68 7.5.5 Specific Source Types in the Ar eas of Influence for Georgia Class I Areas

. 72 7.6 Reasonable Progress Determi nations for Individual Sources

.................................. 76Georgia Regional Haze State Implementation Plan

ix 7.6.1 Process for Determining Reasonable Progress

................................................ 76 7.6.2 Sources Eligible for Four Factor Analysis in Georgia

....................................... 79 7.6.3 Regional Haze Reasonable Progress Four-Factor Analysis

........................... 81 7.6.4 Required Controls for Sources Subj ect to Four-Factor Analysis in Georgia

...... 91 7.7 Control Determinations Representing Best Available Retrofit Technology (BART) for Individual Sources

.................................................................................................. 100 7.7.1 BART-Eligible Sources in Georgia

..................................................................... 101

7.7.2 Determination of Sources Subject to BART in Georgia

.................................. 102

7.7.3 BART Determination for Subject-to-BART Sources

........................................ 107

7.8 What Additional Emissions Controls Were Considered as Part of the Long-Term Strategy for Visibility Improvement by 2018?

.......................................................... 110

8.0 REASONABLE PROGRESS GOALS

............................................................................ 111

9.0 MONITORING STRATEGY

............................................................................................. 114

10.0 INTERSTATE CONSULTATION

.................................................................................. 118

11.0 COMPREHENSIVE PERIODIC IM PLEMENTATION PLAN REVISIONS

............. 121

12.0 DETERMINATION OF ADEQUACY OF THE EXISTING PLAN

............................. 123

13.0 COORDINATION WITH FEDERAL LAND MANAGERS

.......................................... 123Georgia Regional Haze State Implementation Plan

x 

### LIST OF APPENDICES

Appendix A: VISTAS Bylaws a nd Memorandum of Understanding

Appendix B: VISTAS Conceptual Description Support Document

Subappendices to Appendix B

• A. Nephelometer Comparisons

• B. Original and Revised Algorithm Comparisons by Site

• C. File Key for Substituted Data

• D. Data Substitution Resu lts for Individual Sites

• E. Extinction Trend Charts (Mm-1, DV and SVR)

• F. WinHaze Images (Baseline, 2018 and Natural Conditions)

• G. 2000-2004 Timelines

• H. DV Glidepaths

• I. Speciated Glidepaths

• J. Back Trajectory Maps

• K. Residence Time Maps

• L. International Attribution Plots

Appendix B.1:Twenty Percent Best and Worst Visibility Days, 2000 – 2004: Okefenokee and Cohutta

Appendix C: Emissions Preparation and Results

Appendix D: Modeling Anal ysis Protocol and Qualit y Assurance Project Plan

Appendix E: VISTAS Technical Support Document (with Subappendices A – H)

Appendix F: Model Pe rformance Evaluation

Appendix G: EPA Modeling GuidanceGeorgia Regional Haze State Implementation Plan

xi Appendix H: Reasonable Progre ss Evaluation/Long Term Strategy

Subappendices to Appendix H

• H.1 - Industrial Boiler/Process Heater/RICE MACT

• H.2 - VISTAS Class I Statistics

• H.3 - VISTAS Control Options Spreadsheet

• H.4 - Letters to Facilities

• H.5 - Emissions and Q/d for Geor gia's BART Eligible sources

• H.6 - BART VOC, NH3, and Primar y PM Sensitivity Modeling

• H.7 - BART Modeling Protocols

• H.8 - BART Determination Submittals

• H.9 - Correspondence Regarding Us e of New IMPROVE Equation

• H.10 - Supporting Data for Four-factor Analyses

• H.11 - Comparison between Original and Revised Improve Equation

Appendix I: GEOS-CHEM Report

Appendix J: Interstate Consultation Process

Appendix K: Recommended Improvements

Appendix L: Characterization of Me teorology in the VISTAS Region

Appendix M: Permit Conditions for Source s Subject to Additional BART or Reasonable Progre ss Requirements

Appendix N: CMAQ Modeling for Reasonable Pr ogress and BART Controls

Appendix O: Federal Land Manager Consultation

• O.1 – FWS and NPS Comments on Draft Prehearing SIP

• O.2 – USFS Comments on Draft Prehearing SIPGeorgia Regional Haze State Implementation Plan

xii • O.3 - EPD Responses to FLM Comments on Draft Prehearing SIP

Appendix P: BART Model Plant Criteria with PMGeorgia Regional Haze State Implementation Plan

xiii 

### LIST OF FIGURES

Figure 1.2-1. Geographical Areas of Regional Planning Organizations

.................................................. 2

Figure 1.4-1. Georgia Class I areas

.................................................................................................... 5

Figure 1.5-1. Class I Areas in the VISTAS Region

............................................................................... 7

Figure 1.5-2. Mandatory Class I Federal Areas in the VISTAS Region Where Visibility is an Important

Value

............................................................................................................................... ................. 8

Figure 2.4-1. Average light extinction for the 20 percent Haziest Days in 2000-2004 at VISTAS and neighboring Class I areas using New IMPROVE equation

.................................................................. 14

Figure 2.4-2. Average light extinction for the 20 percent Clearest Days in 2000-2004 at VISTAS and neighboring Class I areas using New IMPROVE equation

.................................................................. 14

Figure 3.1-1. Uniform Rate of Progress Glidepath fo r 20 percent worst days at Cohutta Wilderness Area

............................................................................................................................... ........................ 18

Figure 3.1-2. Uniform Rate of Progress Glidepath for 20 percent worst days at Okefenokee Wilderness

Area

............................................................................................................................... ................ 19

Figure 4.2-1. SO2 emissions in 2002 in the VISTAS States.

............................................................... 25

Figure 5.4.1-1. The MM5 horizontal domain is the ou ter most, blue grid, with the CMAQ 36-km domain

nested in the MM5 domain.

.............................................................................................................. 33

Figure 5.4.1-2. A more detailed view of the 12-km grid over the VISTAS region.

.................................. 34

Figure 6.0-1: Monitoring Networks used for VIST AS 2002 model performance evaluation, and their

location within the VISTAS 12km domain.

......................................................................................... 35

Figure 6.2-1.: Soccer plot depictin g both the mean fractional error and fractional bias for component concentration for all VISTAS sites based on Base G2 results. Each point represents a monthly value as compared to the model performance criteria (red box) and modeling performance goals (green box).

... 38

Figure 6.2-2.: A zoomed view of the soccer plot depi cting both the mean fractional error and fractional bias for component concentration for all VISTAS sites based on Base G2 results. Each point represents a monthly value as compared to the model perform ance criteria (red box) and modeling performance goals (green box).

............................................................................................................................ 38

Figure 6.2-3.: Seasonal soccer plots based on Ba se G1 results for all VISTAS IMPROVE monitors.

..... 39

Figure 6.2-4.: Bugle plot of the mean fraction error for particulate matter and its component concentrations for all VISTAS sites based on Base G2 results. Each point represents a monthly mean fraction error value as compared to the model perf ormance criteria (red lines) and modeling performance goals (green lines).

.......................................................................................................................... 40

Figure 6.2-5.: Bugle plot of mean fraction bias fo r particulate matter and its component species for all VISTAS sites based on Base G2 results. Each point represents a monthly mean fraction bias value as compared to the model performance criteria (r ed lines) and modeling performance goals (green lines). 40

Figure 6.3-1.: Stacked bar chart for COHU on t he 20% best days (top) and 20% worst days (bottom). Observed composition is presented in the left hand ba r, with modeled composition represented by the right hand bar.

............................................................................................................................... .. 43Georgia Regional Haze State Implementation Plan

xiv Figure 6.3-2.: Stacked bar chart for OKEF on t he 20% best days (top) and 20% worst days (bottom). Observed composition is presented in the left hand ba r, with modeled composition represented by the right hand bar.

............................................................................................................................... .. 44

Figure 7.2.3-1. Base G Annual SO2 emissions for 2002, 2009, and 2018 in the VISTAS states.

........... 49

Figure 7.2.3-2. Base G Annual NOx emission s in 2002, 2009, and 2018 in the VISTAS States.

............ 49

Figure 7.2.4-1. CMAQ 2018 Base G4 results comp ared to Uniform Rate of Progress at Cohutta

Wilderness Area

.............................................................................................................................. 51

Figure 7.2.4-2. CMAQ 2018 Base G4 results compar ed to Uniform Rate of Progress at Okefenokee

Wilderness Area

.............................................................................................................................. 51

Figure 7.2.4-3. CMAQ 2018 Base G4 results compar ed to Uniform Rate of Progress at wolf Island

....... 52

Figure 7.2.4-4. CMAQ 2018 Base G4 results at Cohutta Wilderness Area.

.......................................... 52

Figure 7.2.4-5. CMAQ 2018 Base G4 re sults at Okefenokee Wilderness Area.

.................................... 53

Figure 7.2.4-6. CMAQ 2018 Base G4 results at Wolf Island.

............................................................... 53

Figure 7.2.4-7. Projected visibility improvement on 20 percent worst visibility days at VISTAS and neighboring Class I areas for the 2018 Base G4 CMAQ run

............................................................... 55

Figure 7.2.4-8. Projected visib ility improvement on 20 percent be st visibility days at VISTAS and neighboring Class I areas for the 2018 Base G4 CMAQ run

............................................................... 55

Figure 7.2.4-9. Visibility improvem ent on 20 percent haziest days at Cohutta Wilderness Area between 2000-2004 baseline conditions (left) and 2018 Base G4 projected visibility (right). Image generated using

WinHaze.

............................................................................................................................... ......... 56

Figure 7.2.4-10. Projected visibility on 20 percent hazi est days for natural background visibility conditions at Cohutta Wilderness Area. Image generated using WinHaze.

......................................................... 56

Figure 7.3-1. Estimated international emissions cont ributions to sulfate at VISTAS and neighboring Class

I areas.

............................................................................................................................... ............ 58

Figure 7.3-2. PM component concent rations from US domestic sources on 20 percent worst visibility days in 2002 (left bars) and CMAQ-simulated international contributions (right bars) at Cohutta Wilderness Area, GA.

............................................................................................................................... ......... 59

Figure 7.3-3. Accounting for internat ional emissions contributions on modeled rate of progress by 2018 at Cohutta, GA. Open triangle = estimate with all em issions; Open diamond = estimate with international

emissions removed.

......................................................................................................................... 60

Figure 7.3-4. PM component concent rations from US domestic sources on 20 percent worst visibility days in 2002 (left bars) and CMAQ-simulated international contributions (right bars) at Okefenokee Wilderness Area, GA.

............................................................................................................................... ......... 60

Figure 7.3-5. Accounting for internat ional emissions contributions on modeled rate of progress by 2018 at Okefenokee, GA. Open triangle = estimate with all emissions; Open diamond = estimate with

international emissions removed.

...................................................................................................... 61

Figure 7.4-1. CMAQ projections of visibility res ponses on 20 percent worst days at Cohutta Wilderness Area, GA to 30 percent reductions from the 2009 Ba se D inventory for visib ility-reducing pollutants in different source categories and geographic areas.

............................................................................. 63

Figure 7.4-2. CMAQ projection s of visibility responses on 20 pe rcent worst days at Okefenokee Wilderness Area, GA to 30 percent reductions fr om the 2009 Base D inventory for visibility-reducing pollutants in different source categories and geographic areas.

.......................................................... 63Georgia Regional Haze State Implementation Plan

xv Figure 7.5.1-1. Example back traj ectories for 20 percent worst visibility days in 2002 for Cohutta

Wilderness Area.

............................................................................................................................. 66

Figure 7.5.2-1. Example residence time plot for 20 percent worst visibility days in 2000-2004 for Cohutta Wilderness Area. Based on trajectories with 100m start height.

.......................................................... 67

Figure 7.5.3-1. Example SO2 Area of Influence plot for sulfate extinc tion weighted residence time for 20 percent worst visibility days in 2000-2004 for Cohutta W ilderness Area, Georgia. Based on trajectories with 100m start height.

..................................................................................................................... 68

Figure 7.5.4-1. Cohutta Wilderness Area 2002 and 2018 SO2 distance weighted emissions x SO4 extinction-weighted residence time plots.

.......................................................................................... 69

Figure 7.5.4-2. 2018 SO2 distance weighted emissions x SO4 extinction-weighted residence time plot for Okefenokee, Georgia

. ...................................................................................................................... 70

Figure 7.6.4-1. Locations Of Fac ilities With Emission Units Eligible

.................................................... 99

Figure 7.7.3-1. Locations of facilitie s with BART-eligible emission units.

........................................... 109

Figure 8.0-1. CMAQ 2018 Base G4 results compared to Uniform Rate of Progress at Cohutta Wilderness Area with GA Reasonable Progress Goals

...................................................................................... 113

Figure 8.0-2. CMAQ 2018 Base G4 results compar ed to Uniform Rate of Progress at Okefenokee Wilderness Area with GA Reasonable Progress Goals

..................................................................... 113

Figure 9.0-1. PM2.5 Monito ring Network in Georgia

......................................................................... 116Georgia Regional Haze State Implementation Plan

xvi 

### LIST OF TABLES

Natural Visibility Conditions for Georgia Class I Areas

.......................................................... ii
Baseline Conditions for Georgia Class I Areas

....................................................................... ii
Georgia Reasonable Progress Go als – 20 Percent Worst Days

.......................................... v Georgia Reasonable Progress Go als – 20 Percent Best Days

........................................... vi
Table 2.3-1. Natural Background and Baseli ne Conditions for G eorgia Class I Areas

.. 13
Table 4.1. 2002 Emissions Inventory Summary for GA in tons per year.

........................ 25
Table 6.1-1.: Established model perform ance goals and criteria for the component species of fine particle mass.

................................................................................................... 36

Table 7.2.3-1. 2009 Emissions In ventory Summary for Georgia.

...................................... 50

Table 7.2.3-2. 2018 Emissions In ventory Summary for Georgia.

...................................... 50

Table 7.5.4-1. 2018 SO2 Point Source C ontribution (Using RTMax*Q/d) to Georgia Class I Areas by State

............................................................................................................... 71

Table 7.5.5-1. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for Cohutta Wilderness Area.

............................................................................. 73

Table 7.5.5-2. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for Okefenokee Wilderness Area.

...................................................................... 73

Table 7.5.5-3. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for Wolf Island.

...................................................................................................... 74

Table 7.5.5-4. 2018 SO2 Emissions Contributi ons from Major Source Categories in the Area of Influence for GA Class I areas.

.................................................................................. 75
Table 7.6.1-1. Projected 2018 SO2 em ission reductions associated with planned reduction measures at Georgia Power EGUs.

...................................................................... 78

Table 7.6.2-1. List of all fa cilities along with their units eligible for 4-factor analysis

...... 80

Table 7.6.2-2. Units Removed from 4-Fact or List Based on Facilities’ Updated 2018
Emission Estimates

.................................................................................................................... 81

Table 7.6.2-3. Facilities T hat Requested Emission Limits

................................................... 81
Table 7.6.4-1. Summary of Required Emissi ons Limits for Sources Subject to FourFactor Analyses

.......................................................................................................................... 93
Table 7.6.4-2. Permit Limits for Implem entation of Reasonable Progress Emissions
Reductions

............................................................................................................................... ... 98

Table 7.7.1-1. Facilities with BAR T-eligible sources in Georgia

....................................... 101
Table 7.7.2-1 Exempti on modeling results for BART-eligible sources.

........................... 103Georgia Regional Haze State Implementation Plan

xvii Table 7.7.2-2. Facilities exempt ed from BART via other methods

................................... 106

Table 7.7.3-1 BART determination resu lts for subject-to BART sources

........................ 108
Table 8.0-1. Georgia R easonable Progress Goals – 20 percent Worst Days

................ 112
Table 8.0-2. Georgia R easonable Progress Goals – 20 percent Best Days

.................. 112
Table 9.0-1. Class I areas in Georgia and IM PROVE monitors that represent conditions at each of them.

........................................................................................................................ 115
Table 10-1: Georgia point source contri bution to Joyce Kilmer-Slickrock (NC).

............ 119
Table 10-2: Georgia point source contribution to Shining Rock (NC).

............................ 119
Table 10-3: Georgia point source contri bution to Great Smo ky Mountains (NC/TN).

... 119
Table 10-4: Georgia point source contribution to Swanquarter (NC).

............................. 119
Table 10-5: Georgia point source cont ribution to Sipsey Wildernesses (AL).

................ 120
Table 10-6: Georgia point source contribution to Cape Romain (SC).

............................ 120
Table 10-7: Georgia point source contribution to St. Marks (FL).

.................................... 120Georgia Regional Haze State Implementation Plan

1 of 124 

### 1.0 INTRODUCTION

1.1 Description of Regional Haze

Regional haze is pollution from disparate sour ces that impairs visibility over a large region, including national parks, forests, and wilderness areas [Federal “Class I” areas defined by 40CFR Part 51.301(o) and Part 81, Subpart D]. Regional haze is caused by sources and activities emitting fine particles and the precursors. Those emissions are often transported over large regions.

Particles affect visibility through the scatteri ng and absorption of light, and fine particles – particles similar in size to the wavelength of light – are most effi cient, per unit of mass, at reducing visibility. Fine particles may either be emitt ed directly or formed from emissions of precursors, the most important of which are sulfur dioxides (SO2) and nitrogen oxides (NOx). R educing fine particles in the atmosphere is generally considered to be an effective method of r educing regional haze, and thus improving visibility. Fine particles also adversely impact human health, especially respiratory and cardiovascular systems. The United States Environmental Protection Agency (USEPA) has set national ambient air quality standards for daily and annual levels of fine particles
with diameter smaller than 2.5 μ m (PM2.5). The most impor tant sources of PM2.5 and its precursors are coal-fir ed power plants, industrial boilers and other combustion sources. Other significant contributors to PM2.5 and visibility impairment include mobile source emissions, area sources, fires, and wind blown dust.

1.2 Clean Air Act Requirement s for Addressing Regional Haze

In Section 169A of the 1977 Amendments to the Clean Air Act (CAA), Congress set forth a program for protecting visibility in Federal Class I areas which calls for the “prevention of any future, and the remedying of any existing, impairment of visibility in mandatory Class I Federal areas which impairment results fr om manmade air pollution.” Congress adopted the visibility provisions to protect visibility in 156 national parks and wilderness areas. On Decem ber 2, 1980, US EPA promulgated regulations to address visibility impairment (45 FR 80084). The 19 80 regulations were developed to address visibility impairment that is “reasonably attri butable” to a single sour ce or small group of sources. These regulations represented the first phase in addressing visibility impairment and deferred action on regional haze that emanat es from a variety of sources until monitoring, modeling and scien tific knowledge about the relationships between pollutants and visibi lity impairment improved.

In the 1990 Amendments to t he CAA, Congress added Section 169B and called on US EPA to issue regional haze rules. The Regional Haze Rule (RHR) that US EPA promulgated on July 1, 1999 (64 FR 35713), revis ed the existing visibility regulations in order to integrate provisions addressi ng regional haze impairm ent and establish a comprehensive visibility protection program for Class I Federal areas. States are required to submit state implementation plans (SIPs) to USEPA that set out each state’sGeorgia Regional Haze State Implementation Plan

2 of 124 plan for complying with the regional haze ru le, including consultation and coordination with other states and with Federal land managers. The timing of SIP submittal is tied to US EPA’s promulgation of des ignations for the National Am bient Air Quality Standard (NAAQS) for PM2.5. Regional Haze SIPs are due at the same time as PM2.5 SIPs are due under section 172 of Clean Air Act. Therefor e, states must submit a regional haze implementation plan to USEPA within three y ears after the date of PM2.5 designations. Because USEPA promulgated de signation dates on December 17, 2004, regional haze SIPs must be submitted by December 17, 2007.

The regional haze rule addressed the combi ned visibility effects of various pollution sources over a wide geographic region. This wide-reaching pollution net meant that many states – even those without Class I Ar eas – would be required to participate in haze reduction efforts. US EPA designated fi ve regional planning organizations (RPOs)
to assist with the coordinat ion and cooperation needed to address the visibility issue. Those states that make up the southeastern portion of the contiguous United States are known as VISTAS (Visibility Improvement – State and Tribal A ssociation of the Southeast), and include the following states: Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia.

Figure 1.2-1. Geographical Areas of Regional Planning Organizations

1.3 General Overview of Re gional Haze SIP Requirements

The regional haze rule (RHR) at 51.308(d) requires states to demonstrate reasonable progress toward meeting the nati onal goal of a return to natu ral visibility conditions by 2064. As a guide for reasonable progress, t he RHR directs states to graphically show what would be a “uniform rate of progre ss” toward natural conditions for each mandatory Class I Federal ar ea within the State and/or for each mandatory Class I Federal area located outside the State, wh ich may be affected by emissions from sources within the State. St ates are to establish baselin e visibility conditions for 2000-Georgia Regional Haze State Implementation Plan

3 of 124 2004, natural background visibility conditions in 2064, and the rate of uniform progress between baseline and background conditions. The uniform ra te of progress is also known as the “glidepath.”

The RHR then requires States to estab lish reasonable progress goals (RPGs), expressed in deciviews, for visibility improvem ent at each affected Class I area covering each (approximately) 10-year period until 2064. The goals must provide for reasonable progress towards achieving natural visibility conditions, provide for improvement in visibility for the most impaired days over the period of the impl ementation plan, and ensure no degradation in visibility for the leas t impaired days over the same period [see §51.308(d)(1)].

In order to ensure that visi bility goals are properly met a nd set, state implementation plans must include determinations, for eac h Class I area, of t he baseline visibility conditions for the most impaired and least im paired days. SIPs must also contain supporting documentation for a ll required analyses used to calculate the degree of visibility impairment under natural visibility conditions for the most impaired and least impaired days [see §51.308(d)(2)]. In additi on, states must include a monitoring strategy for measuring, characterizing, and reporting of regi onal haze visibility impairment that is representat ive of all mandatory Class I F ederal areas within the state [see §51.308(d)(4)].

This first set of reasonable progress goals must be met through measures contained in the state’s long-term strategy covering the per iod from the present until 2018. The longterm strategy includes enforceable emissi ons limitations, compliance schedules, and other measures as necessary to achieve the reasonable progress goals, including all controls required or expect ed under all Federal and State regulations by 2009 and by 2018. During development of the long-term strategy, stat es are also required to consider specific factors such as the above-mentioned ongoing control programs, measures to mitigate construction activi ties, source retirement and replacement schedules, smoke management programs for agric ulture and forestry, and enforceability of specific measures [see §51.308(d)(3)].

In addition, a specific component of each stat e’s first long-term strategy is dictated by the specific Best Available Retrofit Technology (BART) requirements in 40 CFR 51.308(e) of the RHR. T he RHR at §51.308(e) require s states to include a determination of BART for each BART-eligible source in t he State that emits any air pollutant, which may reasonably be anticipated to cause or contribute to any impairment of visibility in any mandatory Class I Feder al area. Clean Air Act Section 169A(b) defines BART-eligible sources as sources in 26 specific source categories in operation within a 15-year period prior to enactm ent of the 1977 Clean Ai r Act Amendments. States must determine BART according to five factors set out in Section 169A(g)(7) of the Clean Air Act. Emission limitations representing BART and schedules forcompliance with BART for each source subject to BART must be included in the longterm strategy.Georgia Regional Haze State Implementation Plan

4 of 124 State Implementation Plans for the first re view period are due December 17, 2007. These plans will cover long-term strategies fo r visibility improvement between baseline conditions in 2000-2004 and 2018. States are required to evaluate progress toward reasonable progress goals every five years to assure that installed emissions controls are on track with emissions reduction forecasts in each SIP. The first interim review would be due to US EPA in December of 2012. If emissions controls are not on track to meet SIP forecasts, then states would need to take action to assure emissions controls by 2018 will be consistent with the SIP or to revise the SI P to be consistent with the revised emissions forecast.

1.4 Class I Areas in Georgia

Georgia has three Class I ar eas within its borders: Cohutta Wilderness Area, Okefenokee Wilderness Area and Wolf Island as designated in 40CFR Part 81 Subpart 408 where visibility has been determined to be an important value. The Georgia Environmental Protection Division (GA EPD) in the Georgia Department of Natural Resources is responsible for developing the R egional Haze SIP. This SIP establishes reasonable progress goals for visibility impr ovement at each of these Class I areas, and a long-term strategy that will achieve thos e reasonable progress goals within the first regional haze planning period.

In developing this SIP, we have also cons idered that emission sources outside of Georgia may affect visibility at these Georgia Class I areas, and emission sources within Georgia that may affect visibility at the followi ng Class I areas in neighboring states. Through VISTAS, the southeastern states have worked together to assess state-by-state contributions to visibility impai rment in specific class I areas, including those in GA and those affected by emissions from Georgia. This technical work is discussed further in chapters 5, 6, and 7 bel ow. Consultations to date between Georgia and other states are summarized in Chapter 10.

Visibility at the following class I areas in the neighborin g states may be affected by emission sources with Georgia:

• Cape Romain Wilderness Area, South Carolina

• Linville Gorge Wilderne ss Area, North Carolina

• Shining Rock Wilderness Area, North Carolina

• Joyce Kilmer - Slick Rock Wilderness Area, North Carolina and Tennessee

• Great Smoky Mountains, T ennessee, North Carolina

• Sipsey Wilderness area, Alabama

• St. Marks, Florida

• Chassahowitzka, FloridaGeorgia Regional Haze State Implementation Plan

5 of 124 Figure 1.4-1. Georgia Class I areas

Prior to VISTAS, the southern states cooperated in a volunt ary regional partnership “to identify and recommend reasonable measures to remedy existing and prevent future adverse effects from human-i nduced air pollution on the air quality-related values of the Southern Appalachian Mountains.” States cooperated with Federal land managers, the Environmental Protection Agency, industry, environmental organiza tions and academia to complete a technical assessment of the impacts of acid deposition, ozone, and fine particles on sensitive resources in the Southern Appalachians. The Southern Appalachian Mountain Initiative (SAMI) Fi nal Report was delivered in August of 2002. The SAMI Assessment concluded that ammonium sulfate is the major contributor to GEORGIA CLASS I AREASGeorgia Regional Haze State Implementation Plan

6 of 124 visibility impairment in the Southern Appalachi an Mountains and to improve visibility, it is most important to reduce sulfur diox ide emissions. SAMI also concluded that reducing ammonia emissions would be he lpful to reduce ammonium nitrate contributions to visibility impairment. Emis sions controls for organic carbon, elemental carbon, and soil were expected to be less im portant for improvi ng visibility. SAMI modeling found that on the hazie st days, much of the bene fit of emissions reductions
would occur in the state where emissions reductions were made. Emissions in surrounding SAMI states and states outside the SAMI region also contribute to air quality in the SAMI Class I areas. The SAMI states supported stro ng national multipollutant legislation to accomplish its mission. Emissions reductions to meet national health standards for ozone and fine particles we re expected to also improve air quality in the Southern Appalachian Mountains. SAMI states committed to consider air quality benefits in the Southern Appalachians as t hey developed State Im plementation Plans for the health standards.

In 2004, US EPA promulgated the Clean Air Inters tate Rule (CAIR) to require emissions reductions for sulfur dioxide and nitrogen dioxi de from electric gener ating utilities in 26 eastern states. The CAIR rule allows for in terstate trading of emi ssions to find cost effective reductions. These reductions will impr ove visibility in Class I areas in Georgia.

1.5 State and Federal Land Manager Coordination

As required by 40 CFR §51.308(i), the regi onal haze SIP must include procedures for continuing consultation between the Stat e of Georgia and F ederal Land Managers (FLMs) on the implementation of the visibility protection program, including development and review of implementation plan revisions and 5-year progress reports, and on the implementation of other progr ams having the potential to c ontribute to impairment of visibility in any mandatory Class I Federal area within the State. Coordination with FLMs is described in more detail in Section 13.

1.6 Interstate Consultation

Successful implementation of a regional haze pr ogram will involve long-term regional coordination among states. VISTAS was form ed in 2001 to address regional haze and visibility problems in the southeastern Unit ed States. Jurisdictions represented by VISTAS members include the Eastern Band of Cherokee Indians; the States of Alabama, Florida, Georgia, Kentucky, Mississippi, North Carolina, South Carolina, Tennessee, Virginia, and West Virginia; and the local air pollution control programs located in these states. A copy of the VISTAS Bylaws and Memorandum of Understanding is enclosed as Appendix A. Inte rstate consultation is described in more detail in Section 10.Georgia Regional Haze State Implementation Plan

7 of 124 The objectives of the VISTAS project are to establish na tural background visibility conditions across the mandatory Class I Feder al areas, identify current visibility impairment levels, analyze emission control le vels that will achieve interim visibility goals, and provide adequate documentation to member agencies so that they can develop their regional haze State/Tribal Impl ementation Plans (SIP/TIP). Figure 1.5-1 shows the 18 mandatory Class I Federal areas in the VISTAS Region where visibility is an important value. Figure 1. 5-2 lists these Class I areas.

Figure 1.5-1. Class I Areas in the VISTAS RegionGeorgia Regional Haze State Implementation Plan

8 of 124 Mandatory Class I Federal Areas in the VISTAS Region Where Visibility is an Important Value

State Area Name Acreage Federal
Land Manager 40 CFR §81.401 Alabama Sipsey Wilderness 12,646 USDA-FS 40 CFR §81.407 Florida Chassahowitzka Wilderness 23,360 USDI-FWS Everglades National Park 1,397,429 USDI-NPS St. Marks Wilderness 17,745 USDI-FWS 40 CFR §81.408 Georgia Cohutta Wilderness 33,776 USDA-FS Okefenokee Wilderness 343,850 USDI-FWS Wolf Island Wilderness 5,126 USDI-FWS 40 CFR §81.411 Kentucky Mammoth Cave National Park 51,303 USDI-NPS 40 CFR §81.422 North
Carolina Great Smoky Mountains National
Park 273,551 USDI-NPS

Joyce Kilmer-Slickrock Wilderness 10,201 USDA-FS Linville Gorge Wilderness 7,575 USDA-FS Shining Rock Wilderness 13,350 USDA-FS Swanquarter Wilderness 9,000 USDI-FWS 40 CFR §81.426 South
Carolina Cape Romain Wilderness 28,000 USDI-FWS

40 CFR §81.428 Tennessee Great Smoky Mountains National
Park 241,207 USDI-NPS

Joyce Kilmer-Slickrock Wilderness 3,832 USDA-FS 40 CFR §81.433 Virginia James River Face Wilderness 8,703 USDA-FS Shenandoah National Park 190,535 USDI-NPS 40 CFR §81.435 West Virginia Dolly Sods Wilderness 10,215 USDA-FS

Otter Creek Wilderness 20,000 USDA-FS

Figure 1.5-2. Mandatory Class I Federal Areas in the VISTAS Region Where Visibility is an Important Value

A technical support document for the regi onal haze state implem entation plans is contained in Appendix E. The report includ es a review of the science and situation, calculation of initial base line visibility, review of monitoring data/data gaps, and recommendations for additional monitoring, initial emission inventory characterization and projections, and compliance with existing cont rol programs. Source contributions to VISTAS mandatory Class I Federal areas are also assessed.Georgia Regional Haze State Implementation Plan

9 of 124 1.6 Supporting Documentation for the SIP

Supporting files and databases t hat would be impracticabl e to print are available electronically, both on the submitted CD-R and via perm anent EPD web links. In addition, files are permanently archived on EPD computer networks. To request access to any of these files please contact the Georgia EPD Air Protection Branch at (404) 363- 7000.Georgia Regional Haze State Implementation Plan

10 of 124 

### 2.0 ASSESSMENT OF BASELINE AND CURRENT CONDITIONS AND

ESTIMATE OF NATURAL BACKGRO UND CONDITIONS IN CLASS I

AREAS

The goal of the Regional Haze Rule is to re store natural visibility conditions to the 156 Class I areas identified in the 1977 Clean Ai r Act Amendments. Section 51.301(q) defines natural conditions: “Natural condi tions include naturally occurring phenomena that reduce visibility as measur ed in terms of light extinction , visual range, contrast, or coloration.” The Regional Haze SIPs must contain measures that make “reasonable progress” toward this goal by reducing ant hropogenic emissions that cause haze.

An easily understood measure of visibility to most people is visual range. Visual range is the greatest distance, in kilometers or miles, at which a dar k object can be viewed against the sky. For evaluating the relative contributions of pollutants to visibility impairment, however, the most us eful measure of visibility im pairment is light extinction, which is usually expressed in units of inverse megameters (Mm -1 ). Light extinction affects the clarity and colo r of objects being viewed.

The measure used by the regi onal haze rule is the deciview (dv). Deciviews are calculated directly from light extinction us ing a logarithmic scale . The deciview is a useful measure for tracking progress in im proving visibility because each deciview change is an equal incremental change in visibi lity perceived by the human eye. Most people can detect a change in vi sibility at one deciview.

For each Class I area, there are three metr ics of visibility that are part of the determination of reasonable progress:

1) Natural conditions, 2) Baseline conditions, and 3) Current conditions.

Each of the three metrics includes the concent ration data of the visibility pollutants as different terms in the light extinction algor ithm, with respective extinction coefficients and relative humidity factors. Total light extinction when converted to deciviews (dv) is calculated for the average of the 20 percent best and 20 percent worst visibility days.

“Natural” visibility is determined by estimati ng the natural concentrations of visibility pollutants and then calculating tota l light extinction. “Baseline” visibility is the starting point for the improvement of visibility condi tions. It is the average of the Interagency Monitoring of Protected Visual Envir onments (IMPROVE) monitoring data for 2000 through 2004 and is equivalent to “current” visibi lity conditions for this initial review period. The comparison of in itial baseline conditions to nat ural visibility conditions indicates the amount of improvement necessary to attain natural visibility by 2064. Each state must calculate baseline and natural visibility levels for Class I areas within itsGeorgia Regional Haze State Implementation Plan

11 of 124 borders [51.308(d)(2)]. “Current conditions” are assessed every five years as part of the SIP review where actual progress in reducin g visibility impairment is compared to the reductions committed to in the SIP.

2.1 Estimating Natural Conditions for Georgia Class I Areas

Natural background visibility, as defined in 2003 US EPA guidance, is based on annual average concentrations of fi ne particle components. The same annual average natural background visibility is assumed for all Class I areas in the eastern United States (separate values are estimated for the we stern United States). Natural background visibility for the 20 percent worst days is estimated by assumi ng that fine particle concentrations for natural background are normally distributed and the 90 th percentile of the annual distribution repres ents natural background visibi lity on the 20 percent worst days.

In the 2003 guidance, US EPA also provided that states may use a “refined approach”
to estimate the values that characterize the natural visibility conditions of the Class I areas. The purpose of such a refinement woul d be to provide more accurate estimates with changes to the extinction algorithm that may include the concentration values, factors to calculate extincti on from a measured particular species and particle size, the extinction coefficients for certain compounds , geographical variation (by altitude) of a fixed value, and the addition of visibility pollutants.

In 2005, the IMPROVE Steering Committ ee made recommendations for a refined equation that modifies the terms of the original equation to account for the most recent data. The choice between use of the ol d or the new equation for calculating the visibility metrics for each Class I area is made by the state in which the Class I area is
located.

b ext ≈ 2.2 x f S (RH) x [Small Sulfate] + 4.8 f L (RH) x [Large Sulfate] + 2.4 x f S (RH) x [Small Nitrate] + 5.1 f L (RH) x [Large Nitrate] + 2.8 x [Small Organic Mass] + 6.1 x [Large Organic Mass] + 10 x [Elemental Carbon] + 1 x [Fine Soil] + 1.7 x f SS (RH) x [Sea Salt] + 0.6 x [Course Mass] + Rayleigh Scattering (Site Specific) + 0.33 x [NO 2 (ppb)]

The new IMPROVE equation accounts for the effe ct of particle size distribution on light extinction efficiency of sulfat e, nitrate, and organic carbon henc e the total sulfate, nitrate and organic carbon compound concentrations are each split into two fractions, representing small and large size distributions of those components. The mass multiplier for organic carbon (par ticulate organic matter) is in creased from 1.4 to 1.8. New terms are added to the equation to account for light extinction by sea salt and light absorption by gaseous nitrogen dioxide. Si te-specific values are used for RayleighGeorgia Regional Haze State Implementation Plan

12 of 124 scattering to account for the site-specific effe cts of elevation and te mperature. Separate relative humidity enhancement factors are used for small- and large-sized distributions of ammonium sulfate and amm onium nitrate and for sea sal t. The elemental carbon (light-absorbing carbon), fine soil, and c oarse mass terms do not change between the original and new IMPROVE equation.

The VISTAS states chose to use the new IMPROVE equation as the basis for the conceptual description because it takes into account the most recent review of the science and because it is recommended by the IMPROVE Steering Committee. For more detailed discussion of the two IMPROVE equations, see Appendix B.

Georgia EPD requested in writ ing (from Carol Couch to J. I. Palmer, dated August 19, 2008) to use the new IMPROVE equation to calc ulate light extincti on effects from two BART-eligible facilities: Georgia Paci fic Cedar Springs and Georgia Power Plant Bowen. EPA Region IV approved this reques t in a letter dated September 11, 2008.

2.2 Estimating Baseline Conditi ons for Georgia Class I Areas

Baseline visibility conditions at each Geor gia Class I area are estimated using sampling data collected at IMPROVE monitoring site s. A -5year average (2000 to 2004) was calculated for each of the 20 percent wors t and 20 percent best visibility days in accordance with 40 CFR 51.308(d)(2) and the US EPA Guidance for Tracking Progress Under the Regional Haze Rule. IMPROVE data records for Okefenokee for the period 2000 to 2004 meet US EPA requirements for data completeness (75 percent for the year and 50 percent for each quarter). Cohutta did not meet completeness criteria in 2000, 2001, and 2003. Data records for 2001 and 2003 were filled using data substitution procedures outlined in Appendix B, but there was too little data in 2000 to perform data filling. IMPROVE does not operat e a monitor at Wolf Island and considers the IMPROVE monitor at Okef enokee Wilderness Area to be re presentative of visibility at Wolf Island. The light extinction and dec iview visibility values for the 20 percent worst and 20 percent best visibility days at the Class I areas are based on data and calculations included in Append ix B of this SIP. The 20 percent worst and 20 percent best visibility days with their respective extinc tion values are present ed in Appendix B.1.

2.3 Summary of Natural Background and Baseline Conditions for Georgia Class I

Areas

Table 2.3-1 presents estimated natural ba ckground and baseline visibility metrics for Georgia Class I areas. Note t hat Georgia is not considering international emissions to be a component of natural background. Baselin e visibility on the 20 percent worst days at Cohutta Wilderness Area, Okefenokee Wil derness Area, and Wolf Island is generally between 27 and 30 dv. Natural background visibi lity at all three sites is predicted to be between 11 and 12 dv. The class I area with t he worst visibility impairment is Cohutta Wilderness Area at great er than 30 dv on the 20 percent worst days.Georgia Regional Haze State Implementation Plan

13 of 124 Table 2.3-1. Natural Background and Ba seline Conditions for Georgia Class I
Areas

Natural Background Conditions Class 1 Area Average for 20 percent Worst Days (deciviews) Average for 20 percent Best Days (deciviews) Average for 20 percent Worst Days Bext (Mm-1) Average for 20 percent Best Days Bext (Mm-1)
Cohutta Wilderness Area 10.78 4.32 29.38 15.40
Okefenokee Wilderness 11.21 5.31 30.67 16.99
Wolf Island 11.21 5.31 30.67 16.99

Baseline Visibility Conditions 2000-2004 Class 1 Area Average for 20 percent Worst Days (deciviews) Average for 20 percent Best Days (deciviews) Bext (Mm-1) Average for 20 percent Worst Days Bext (Mm-1) Average for 20 percent Best Days
Cohutta Wilderness Area 30.25 13.77 206.21 39.62
Okefenokee Wilderness 27.13 15.23 151.50 45.85
Wolf Island 27.13 15.23 151.40 45.85

2.4 Pollutant Contributions to Visib ility Impairment (2000-2004 Baseline Data)

The 20 percent worst visibility days at the Southern Appalachi an sites (in Georgia: only the Cohutta Wilderness Area is part of the Southern Appala chian sites) generally occur in the period April to S eptember. The peak hazy days occur in the summer under stagnant weather conditions with high relati ve humidity, high temperatures, and low wind speeds. The 20 percent best visibility days at the Cohutta Wilderness Area can occur at any time of year. At Wolf Island, Okefenokee Wilderness Area and other coastal sites, the 20 percent worst and best visibility days are distributed throughout the

year.

Ammonium sulfate , (NH 4 ) 2 SO 4 , is the most important contri butor to visibility impairment and fine particle mass on the 20 percent worst and 20 percent best visibility days at all the Georgia Class I areas. Sulfate levels on the 20 percent worst days account for 60- 70 percent of the visibility impairment. Acro ss the VISTAS region, sulfate levels are higher at the Southern Appalachi an sites than at the coastal si tes (Figure 2.4-1). On the 20 percent clearest days, sulfate levels are more uniform across the region (Figure 2.4- 2). [Note that in these two figures, leve ls at Okefenokee Wilderness Area should be considered to be representative of levels at Wolf Island.]Georgia Regional Haze State Implementation Plan

14 of 124 Figure 2.4-1. Average light extinction for the 20 percent Haziest Days in 2000-2004 at VISTAS and neighboring Class I areas using New IMPROVE equation

Figure 2.4-2. Average light extinction for the 20 percent Clearest Days in 2000-2004 at VISTAS and neighboring Class I areas using New IMPROVE equation VISTAS coastal VISTAS inland Neighboring non-VISTAS 0 50 100 150 200 250 300Swanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, ARExtinction (Mm-1)

Sea Salt
Coarse
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTAS 0 50 100 150 200 250 300Swanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, ARExtinction (Mm-1)

Sea Salt
Coarse
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

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

Sea Salt
CM
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

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

Sea Salt
CM
Soil
EC

POM

NH4NO3 (NH4)2SO4 Rayleigh

VISTAS coastal VISTAS inland Neighboring non-VISTASSwanquarter, NCCae Romain, SCOkefenokee, GAEverglades, FLChassahowitzka, FLSt. Marks, FLDolly Sods, WVShenandoah, VAJames River Face, VALinville Gorge, NCShining Rock, NCGreat Smoky Mtns., TNCohutta, GASipsey, ALMammoth Cave, KYBrigantine, NJBreton, LAMingo, MOHercules Glade, MOUpper Buffalo, ARCaney Creek, ARGeorgia Regional Haze State Implementation Plan

15 of 124 Particulate Organic Matter (POM) is the second most important contributor to fine particle mass and light extinction on the 20 perc ent haziest and the 20 percent clearest days at the Georgia Class I areas. Elevated le vels of POM and elemental carbon (EC) indicate impact from wildfires or prescribed fires. Signific ant fire impacts are infrequent at Class I areas in Georgia. Wood burning is more important in the fall, winter, and early spring months. Biogeni c emissions, chiefly emissions of volatile organics (VOC) from vegetation, peak in spring and summe r. Biogenic carbon emissions at Cape Romain, South Carolina, a coastal site simila r to Wolf Island, Georgia were lower than emissions at the forested mount ain sites. Carbon from gasol ine and diesel engines is a relatively small contribution at the rural si tes. Modeling results suggest that controlling anthropogenic sources of carbon will have little benefit in impr oving visibility in Class I areas. Controlling anthropogenic sources of carbon will likely be more effective to reduce levels of PM2.5 in urban areas.

Ammonium nitrate , NH 4 NO 3 , is formed in the atmosphere by reaction of ammonia and nitrogen oxides. In the VISTAS region, nitrate formation is limited by availability of ammonia and by temperature. Ammonia preferentially reac ts with sulfur dioxide and sulfate before reacting with nitrogen oxides. Particle nitrate is formed at lower temperatures; at elevated temperatures nitric acid remains in gaseous form. For this reason, particle nitrate levels are very lo w in the summer and a minor contributor to visibility impairment. Particle nitrate c oncentrations are higher on winter days and are more important for the coastal sites wher e 20 percent worst days can occur on winter days. Nitrogen oxides are emitted by fossil fu el combustion by point, area, on-road, and non-road sources. Modeling data (see Section 7) indicate that in the VISTAS region ammonium nitrate formation is limited by ammonia concentrations and suggest that for winter days, controls of ammonia source s would be more effective in reducing
ammonium nitrate levels than controls of nitrogen oxides.

Elemental Carbon( EC) is a comparatively minor cont ributor to visibility impairment. Sources include agriculture, prescribed, wildland, and wild fires and incomplete combustion of fossil fuels. EC levels are higher at urba n monitors than at the Class I areas and suggest controls of fossil fuel com bustion sources would be more effective to reduce PM2.5 in urban areas than to impr ove visibility in Class I areas.

Soil fine particles are minor contributors to vi sibility impairment at most sites on most days. Occasional episodes of elevated fi ne soil can be attributed to Saharan dust episodes, particularly at Everglades, Florida but rarely are seen at the Georgia Class I areas. No control strategies are indicated for fine soil.

Sea salt (NaCl) is observed at the coastal site s. Sea salt contributes to visibility impairment are most important on the 20 percent clearest days when sulfate and POM levels are low. Sea salt levels do not contribute significantly to visibility on the 20 percent worst visibility days. The new IMPROVE equation uses Chloride ion (Cl - ) from routine IMPROVE measur ements to calculate sea salt levels. Cl - may react with nitrates and volatize off the filter, so that Cl - may underestimate sea salt levels. VISTAS funded sodium ion (Na + ) analyses of the IMPRO VE filters from October 2003 to DecemberGeorgia Regional Haze State Implementation Plan

16 of 124 2004 for nine sites. Sodium ion measures may overestimate sea salt levels because sodium nitrate is an additional source of so dium ion that cannot be distinguished from sodium chloride. Our best understandi ng to date suggests that using Cl - may underestimate sea salt levels by as much as a factor of two. This uncertainty has greatest implications for calculating sea salt levels under natural visibility conditions.

Coarse particle mass (particles with diameters between 2.5 and 10 microns) has a relatively small contribution to visibility impairment because the light extinction efficiency of coarse mass is very low co mpared to the extinction efficien cy for sulfate, nitrate, and
carbon.

An unidentified component is reported by IMPROVE as the difference between the total PM2.5 mass measured on the filter and the sum of the measured components. This unidentified mass may be positiv e or negative and is attributable to water and/or the factors used to calculate molecula r weights of the other components.

The new IMPROVE equation , compared to the former ve rsion, generally results in higher calculated light extinction on days wit h higher mass and lower light extinction on days with lower mass. This tends to increas e calculated light ex tinction for current conditions and to decrease calculated light extinc tion for natural visi bility conditions. Adding sea salt to the new IM PROVE equation increases light extinction for both current and natural visibility conditions. Increasing the mass multiplier for particulate organic matter in the new IMPROVE equation increases light extinction for current conditions more than for natural conditions. The new algorithm does not change the conclusion that, in the VISTAS region and in Georgia, the most effectiv e means to improve visibility is to reduce sulfate concentrations.

PM2.5 trends in urban and Class I areas: IMPROVE data was compared to monitoring data from the Speciated Trends Network (STN ) in nearby urban areas to understand the similarities and differences in compositi on of fine particle mass. Several PM2.5 nonattainment areas are in clos e proximity to the Class I areas in the southeastern United States, including Atlanta, G eorgia; Birmingham, Alabama; Charleston, West Virginia; Chattanooga, Tennessee; Louisville, Kentucky; and Knoxville, Tennessee. Ammonium sulfate concentrations are comparable bet ween urban and nearby Class I areas, while organic carbon, elemental carbon, and nitrat e concentration are generally higher in urban areas than in the Class I areas. Thes e results suggest that sulfate is widely distributed regionally while ur ban areas see additional incr emental pollutant loadings from local emissions sources.

Role of meteorology in determi ning visibility conditions: Classification and Regression Tree Analyses were used to characterize the relationship between meteorological conditions and visibility condi tions at the Class I areas. Days were assigned to one of five visibility classes ranging from poor to good visibility. Days were then assigned to bins based on meteorological conditions. Weights were assigned to days based on frequency of occurrence of days with similar me teorological conditions. For the Georgia Class I areas, poor visibility days were mo st likely to occur on days with highGeorgia Regional Haze State Implementation Plan

17 of 124 temperatures, high relative humidity, low wind speeds, and elevated PM2.5 mass at upwind urban areas. Precipitat ion was not a good predictor of visibility condition.

The above analyses are further discussed in Appendix L.Georgia Regional Haze State Implementation Plan

18 of 124 

### 3.0 GLIDEPATHS FOR CLAS S I AREAS IN GEORGIA

The following are glidepaths for the 20 perc ent most impaired days Cohutta Wilderness Area, assuming uniform rate of progress toward regional haze goals. Natural background visibility at all four sites is predicted to be between 11 and 12 dv. The Class I area with the steepest slope from baselin e to natural background conditions is Cohutta Wilderness Area. Note that the rate of progress for Okef enokee is considered representative of Wolf Island.

Figure 3.1-1. Uniform Rate of Progress Glidepath for 20 percent worst days at Cohutta Wilderness
Area Uniform Rate of Progress Glide Path Cohutta - Worst 20% Data Days

30.25
28.63

25.71

22.46

19.22

15.97

12.73

10.78

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Uniform rate of p ro g ress = 4.5 dv b y 2018Georgia Regional Haze State Implementation Plan

19 of 124 Figure 3.1-2. Uniform Rate of Progress Glidepath for 20 percent worst days at Okefenokee Wilderness Area Uniform rate of p ro g ress = 3.7 dv b y 2018 Uniform Rate of Progress Glide Path 

### Ok e f eno k ee

27.13 25.81

23.42

20.76

18.11

15.45

12.80
11.21

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064
YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) ObservationGeorgia Regional Haze State Implementation Plan

20 of 124 

### 4.0 NATURE OF THE PR OBLEM: CHIEF CAUSES OF VISIBILITY

IMPAIRMENT IN GEORGIA CLASS I AREAS

4.1 Baseline Emissions Inventory

The Regional Haze Rule at 51.308(d)(4)(v) requires a state wide emissions inventory of pollutants that are reasonably anticipated to c ause or contribute to visibility impairment in any mandatory Class I area. An invent ory was developed for the baseline year 2002 and projected to 2009 and 2018. The pollutants inventoried include volatile organic compounds (VOCs), nitrogen oxides (NOx), fine particulate (P M2.5), coarse particulate (PM10), ammonia (NH3) and sulfur dioxide (S O2). The baseline emissions inventory for 2002 was developed for Georgia following the methods describ ed in Appendix C.

There are five different emission inventory source classifications: stationary point and area sources, off-road and on-r oad mobile sources, and biogeni c sources. Stationary point sources are those sources that emit greater than a spec ified tonnage per year, with data provided at the facility level. El ectric generating utilitie s and industrial sources are the major categories for stationary point sources. Stationary area sources are those sources whose individual emissions are relati vely 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, agricultura l sources, fire emi ssions, etc.). These types of emissions are estimated on a county wide 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, ai rcraft, etc. The em issions from these sources, like stationary area sources, are estimated on a countywide level. On-road mobile sources are automobiles, trucks, buses, and motorcycles that use the roadway system. The emissions from these sources ar e estimated by vehicle type and road type and are summed to the countywide level. Bi ogenic sources are the natural sources like trees, crops, grasses and natural decay of pl ants. The emissions from these sources are estimated on a countywide level.

In addition to the various source classifications, there are al so various types of emission inventories. The first is the actual base-year inventory. This inv entory is the base-year emissions that correspond to the meteorolog ical 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 typica l emission value is us ed. In this modeling effort, typical emissions were developed for the electric gener ating units (EGUs) and the wildland fire emissions. The air quality modeling runs using the typical base-year inventory provide results, wh ich are then used to calculate relative reduction factors for future years. These relative reduction factors for future years are then used to demonstrate reasonable progress toward visibility goals.Georgia Regional Haze State Implementation Plan

21 of 124 Below is an overview of the inventories used for each source classification. More detailed discussion of the emissions invent ory development is contained in Appendix C.

4.1.1 Stationary Point Sources Point source emissions are emissions from individual sources having a fixed location. Generally, these sources must have permi ts to operate, and t heir emissions are inventoried on a regular schedule. Point sour ces emitting at least 100 tons per year (tpy) of VOC, PM 10 , PM 2.5 , NH 3 , SO2, or NO x are inventoried. The point source emissions data can be grouped as EGU sources and other industrial point sources, also called non-EGUs.

Electric Generating Units

The actual base year inventory for the EGU sources used 2002 continuous emissions monitoring (CEM) data reported to the US EPA’s Acid Rain program or 2002 hourly emissions data provided by st akeholders. The data provides hourly emissions profiles for SO2 and NOx that can be used in air qua lity modeling. Emissi ons profiles are used to estimate emissions of other pollu tants (volatile organic compounds, carbon monoxide, ammonia, fine particles, soil) based on measured emissions of SO2 and NOx.

Emissions from EGUs vary da ily and seasonally as a function of variability in energy demand and utilization and outage schedules. To avoid anomalies in future-year emissions created by relyi ng on 2002 operations to represent future operations, a typical base-year emissions inventory wa s developed for EGUs. This approach is consistent with the US EPA’s modeling guid ance (Appendix G). To develop a typical year 2002 emissions inventory for EGU sour ces, 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 normalizi ng factor was then multiplied by the 2002 actual emissions. The heat inputs for t he period 2000 through 2004 were used because the modeling current desi gn 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 shutdown, the emissions and heat inputs from 2001 (or 2000) were used in the normalizing calculations.

As part of the VISTAS air quality modelin g, VISTAS, in cooper ation 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 conti guous United States using the Integrated Planning Model (IPM). IPM is a dynamic linear optimization model that can be used to examine air pollution control po licies for various pollutants throughout the contiguous United States for t he entire electric power system . The dynamic nature of IPM enables projection of the behavior of th e 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, tr ansmission bottlenecks, and plant-specificGeorgia Regional Haze State Implementation Plan

22 of 124 operational constraints. The versatility of IP M allows users to specify which constraints to exercise and to populate IP M with their own datasets.

The IPM modeling runs took into cons ideration both CAIR implementation and Georgia’s Multipollutant rule r equirements for Georgia Power.

Other Industrial Point Sources

For the non-EGU sources, the same inventor y is used for both the actual and typical base-year emissions inventories. The non-EGU category uses annual emissions as reported under the Consolidated Emissions Reporting Rule (CER R) for the year 2002. These emissions are temporally allocat ed to month, day, and hour using source category code (SCC)-based allocation factors.

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

4.1.2 Stationary Area Sources Stationary area sources are sources whose indi vidual emissions are relatively small, but due to the large number of thes e sources, the collective emissions could be significant (i.e., combustion of fuels for heat ing, structure fires, service stations, etc.). Emissions are estimated by multiplying an emission fact or by some known indicator of collective activity, such as fuel usage, number of households, or population. Stationary area
source emissions are estimat ed at the countywide level.

The VISTAS contractor used data report ed by Georgia under CERR for 2002 area source inventory. GA EPD on ly provided additional data from other years in order to generate typical fire emissions.

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 t he 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 us ed 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.

Future Year Emissions The VISTAS contractor generated future-year emissions inventories for 2009 and 2018 for the regional haze modeling. Growth factors, supplied either by states or taken from the CAIR emission projections, were applied to project the controll ed emissions to 2018. If no growth factor was available from either a state or the CAIR growth factor files, thenGeorgia Regional Haze State Implementation Plan

23 of 124 the US EPA’s Economic Growth and Analysis System Version 5 growth factors were
used.

4.1.3 Off-Road Mobile Sources Off-road (or non-road) mobile so urces 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 US EPA ’s NONROAD2005 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 baseyear emissions inventories.

For the source categories estimated usi ng the US EPA’s NONROAD model, the model growth assumptions were used to create the 2009 and 2018 future-year inventories. The NONROAD model takes into considerati on regulations affecting emissions from these source categories. For the comme rcial marine, railroad locomotives and the airport emissions, the VISTAS contractor calculated the future growth in emissions using detailed inventory data (both bef ore and after controls) for 1996 and 2010, obtained from the CAIR Technical Support Docu ment. When availabl e, state-specific growth factors were used.

4.1.4 Highway Mobile Sources For on-road vehicles, the newest version of the MOBILE model, MOBI LE6.2, 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 vehicl es on the roads, any programs in place in an area to reduce emissions for motor vehi cles (e.g., emissions inspection programs), and temperature.

The MOBILE model takes into consideration r egulations that affect emissions from this source sector. The same MOBILE run is us ed to represent the actual and typical year emissions for on-road vehicles using input dat a reflective of 2002. The MOBILE model then is run for 2018 inventory us ing input data reflective of that year. Area-specific vehicle age distributions were modeled. Emissions were modeled using vehicle miles traveled estimates obtained from the G eorgia Department of Transportation.

4.1.5 Biogenic Emission Sources Biogenic emissions were prepared with the SMOKE-BEIS3 (Biogenic Emission Inventory System 3 version 0. 9) preprocessor. SMOKE-BEIS3 is a m odified version of the Urban Airshed Model (UAM)-BEIS3 model. Modifications include use of MM5 data, gridded land use data, and impr oved emissions characterizati on. The emission factors that are used in SMOKE-BEIS3 are the same as the emission factors as in UAM-BEIS3. 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 US EPA. A separate land classification sch eme, based upon satellite (AVHRR, 1 kmGeorgia Regional Haze State Implementation Plan

24 of 124 spatial resolution) and census information, ai ded in defining the forest, agriculture and urban portions of each county.

4.1.6 Model Performance Improvements through Emissions Inventory Improvements Since the initial model performance evaluation, VISTAS has made several improvements to the emissions inventory, which, in turn, improve model performance. These inventory improvements are detailed in the VISTAS emissions inventory report and Appendix C, and are summarized here:

• For electric generating utilities, the Int egrated Planning Model (IPM) was used to provide estimates of future-year utilit y production and emissions. Continuous Emissions Monitoring data was used to def ine seasonal variability in production and emissions. For Base G4 emissions, states updated IPM model projections from 2005 with control data provided by utility companies in 2006 through winter 2007.

• For on-road vehicle emissions, states and local agencies provided updated MOBILE model input and vehi cle-miles-traveled data.

• For ammonia emissions from agricul tural sources, the Carnegie Mellon University ammonia model was used to improve annual and monthly estimates.

• For fires, the VISTAS states provided fi re activity data for 2002 for wildfires, prescribed fire, land clearing and agricul tural burning and MACTEC developed a 2002 fire inventory. Wher e data allowed, Alpine Geop hysics modeled fire events as point sources. In 2006, the United States Forest Service and the Fish and Wildlife Service provided projections of increased prescribed burning in 2009 and 2018. The data was incorporated in the Ba se G inventory for all states except
Florida.

• For non-road engines, the updated US EPA NONROAD2005 emissions model was used in Base G.

For commercial marine emissions in shipping l anes in the Gulf of Mexico and Atlantic Oceans, ENVIRON created gridded emission s for the VISTAS modeling domain using inventory data newly developed for US EPA by Corbett at University of Delaware. These emissions were incorporat ed in the Base G modeling. Updated inventories from the neighboring RPOs, Mexico, and Canada were incorporated as available.

4.1.7 Summary 2002 Base G2 Baseline Emissions Inventory for Georgia Table 4.1 is a summary of the 2002 baseli ne emission inventory for Georgia. The complete inventory and discussion of the met hodology is contained in Appendix C. The emissions summaries for other VISTAS stat es can also be found in Appendix C.Georgia Regional Haze State Implementation Plan

25 of 124 Table 4.1. 2002 Emissions Inventory Summary for GA in tons per year.
VOC NOx PM2.5 PM10 NH3 SO2
Point 34,964.3 197,376.9 22,531.7 33,077.3 3,699.2 571,410.9
Area 333,044.8 49,987.4 159,437.8 757,656.1 83,066.0 60,370.2
On-Road
Mobile 283,420.6 307,731.7 5,167.8 7,245.9 10,546.2 12,183.5

NonRoad Mobile 85,965.4 97,961.4 8,226.4 8,617.9 60.4 9,005.4

Biogenics 1,972,795.40 20,942.38 0 0 0 0
TOTAL 2,710,190.50 673,999.78 195,363.50 806,597.20 97,371.80 652,970

4.2 Assessment of Relative Contributions from Specifi c Pollutants and Sources Categories

Ammonium sulfate is the larges t contributor to visibility im pairment at the Georgia Class I areas, and reduction of SO2 emissions woul d be the most effective means of reducing ammonium sulfate. As illust rated in Figure 4.2-1, 96 perce nt of SO2 emissions in the VISTAS states are attributable to electr ic generating facilities and industrial point sources. As shown in Table 4.1, approximat ely 90 percent of SO2 emissions in Georgia are attributable to electric generating fa cilities and industrial point sources.

Figure 4.2-1. SO2 emissions in 2002 in the VISTAS States. Vistas States SO2 Emissions (Tons) - 2002

EGU

Other Fuel Combustion

Industrial

Onroad

Nonroad

Miscellaneous utilities: 75% 4.8 million TonsGeorgia Regional Haze State Implementation Plan

26 of 124 

### 5.0 REGIONAL HAZE MODELING METHODS AND INPUTS

Modeling for regional haze was performed by VISTAS for the ten southeastern states, including Georgia. The sections below outline the methods and inputs used by VISTAS for the regional modeling. A dditional details are provided in Appendices C, D, and E.

5.1 Analysis Method

The modeling analysis is a complex technical evaluation that begins by selection of the modeling system. VISTAS decided to use the following modeling system:

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

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

• Air Quality Model: US EPA’s Models-3/ Community Multiscale Air Quality (CMAQ) modeling system is a ‘One-At mosphere’ photochemical grid model capable of addressing ozone, particulate matter (PM), visibility and acid deposition at regional scale for periods up to one year.

The US EPA Modeling Guidance (Appendix G) recommends modeling an entire year or at a minimum several days in each quarter of a year to adequately represent the range of meteorological conditions t hat contribute to elevated levels of fine particulate matter. The year 2002 was selected by VISTAS as the modeling year for this demonstration. Meteorological inputs were developed for 2002 using the meteorological model. Emission inventories were also deve loped for 2002 and processed through the emissions model. These inputs were used in t he air quality model to predict fine particle mass and visibility. The model result s for 2002 were compared with observed meteorological and air quality data to ev aluate model performance. Several configurations of the meteor ological and air quality model were evaluated to select a configuration that gave t he best overall performance for the VISTAS region.

Once model performance was deemed adeq uate, the current- and future-year emissions were processed through the em issions model. The air quality modeling results are used to determine a relative reducti on in future visibility impairment, which is used to determine reasonable progress.

The complete modeling protocol used for this analysis can be found in Appendix D.Georgia Regional Haze State Implementation Plan

27 of 124 5.2 Model Selection

To ensure that a modeling study is defensible, care must be taken in the selection of the
models to be used. The models selected mu st be scientifically appropriate for the intended application and be freel y accessible to all stakeholders. Scientifically appropriate means that t he models address important physical and chemical phenomena in sufficient detail, using peer-revi ewed methods. Freely accessible means that model formulations and coding are freely available for review and that the models are available to stakeholders, and their consul tants, for execution a nd verification at no
or low cost.

The following sections outline t he criteria for selecting a m odeling system that is both defensible and capable of meet ing the study's goals. These criteria were used in selecting the modeling system used for this modeling demonstration.

5.2.1 Selection of Photochemical Grid Model

Criteria

For a photochemical grid model to qualify as a candidate for use in a regional haze SIP,
a state needs to show that it meets the same several general criteria as a model for an attainment demonstration for a national ambient air quality standard (NAAQS):

• 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 analysi s are availabl e and adequate.

• Available past appropriate performance eval uations 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 co st, and the model cannot otherwise be proprietary.

Overview of CMAQ

The photochemical model selected for this study was CMAQ Version 4.5. For more than a decade, the US EPA has been developi ng the Models-3 CMAQ modeling system with the overarching aim of producing a ”O ne-Atmosphere” air qua lity modeling system capable of addressing ozone, fi ne particulate matter, visibility and acid deposition within a common platform. The orig inal justification for the Models-3 development emerged from the challenges pos ed by the 1990 Clean Air Ac t Amendments and the USEPA’s desire to develop an advanced modeling fram ework for “holistic” environmental modeling utilizing state- of-science representations of at mospheric processes in a high performance computing environment. The US EPA completed the initial stage of development with Models-3 and released the CMAQ model in mid-1999 as the initialGeorgia Regional Haze State Implementation Plan

28 of 124 operating science model under the Models-3 fram ework. The most recent rendition is CMAQ Version 4.5, which was re leased in September of 2005.

An advantage of choosing CMAQ as the atmo spheric model is the ability to do oneatmospheric modeling. The same model configuration is being applied for the ozone
and PM 2.5 attainment demonstration SIPs, as we ll as the regional haz e SIP. A number of features in CMAQ’s t heoretical formulation and technical implementation make the model well-suited for annual PM modeling.

The configuration used for this modeling de monstration, as well as a more detailed description of the CMAQ model, can be found in the Modeling Prot ocol (Appendix D).

5.2.2 Selection of Me teorological Model

Criteria

Meteorological models, either through obj ective, diagnostic, or prognostic analysis, extend available information abo ut the state of t he atmosphere to the grid upon which photochemical grid modeling is to be carri ed out. The criteria for selecting a meteorological model are bas ed on both the model’s ability to accurately replicate important meteorologic al phenomena in the region of st udy and the model's ability to interface with the rest of the modeling systems -- particu larly the photochemical grid 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

• Simulation of Cloud Physics

• Public availability at no or low cost

• Output available in I/O API format

• Support of Four Dimensional Data Assimilation (FDDA)

• Enhanced treatment of Planetary Bound ary Layer heights for AQ modeling

Overview of MM5

The non-hydrostatic MM5 model is a three-di mensional, 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-dimensio nalized pressure, or "sigma," vertical coordinate similar to that used in many oper ational and research models. In the nonhydrostatic MM5, the sigma levels are defined according to the initial hydrostatically-Georgia Regional Haze State Implementation Plan

29 of 124 balanced reference state so that the sigma levels are also time-invariant. The gridded meteorological fields produced by MM5 ar e directly compatible with the input requirements of ”one atmosphere” air-quality m odels using this coordinate. MM5 fields can be easily used in other regional air qual ity models with different coordinate systems by performing a vertical interpolation followe d by a mass-conservation re-adjustment.

Distinct planetary boundary layer (PBL) paramet erizations are available for air-quality applications, both of which represent sub-grid -scale turbulent flux es of heat, moisture and momentum. One scheme uses a first-order eddy diffusivity formulation for stable and neutral environments and a modified first-or der scheme for unstable regimes. The other scheme uses a prognostic equation for t he second-order turbulent kinetic energy, while diagnosing the other key boundary layer terms.

Initial and lateral boundary conditions are spec ified for real-data cases from mesoscale 3-dimensional analyses perfo rmed at 12-hour intervals on the outermost grid mesh selected by the user. Surface fields are analyzed at 3-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 is introduced using a relaxation te chnique applied in the outermost five rows and columns of the coarsest grid domain.

MM5 modeling systems, in regulatory air qua lity application studies, have been widely reported in the literature (e.g ., Emery et al., 1999; Tesc he et al., 2000, 2003) and many have involved comparisons with other pr ognostic models such as the Regional Atmospheric Modeling System (RAMS) and the Systems Application International Mesoscale Model. The MM5 enjoys a far ri cher application history in regulatory modeling studies compared with RA MS or other models. Furt hermore, in evaluations of these models in over 60 recent, regional-sca le air quality application studies since 1995, it has generally been found that the MM5 model tends to produce somewhat better photochemical model inputs t han alternative models.

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

5.2.3 Selection of Emi ssions Processing System

Criteria

The principal criterion for an emissions proce ssing system is that it accurately prepares emissions files in a format suitable for t he photochemical grid model being used. The following list includes clarification of this criterion and additional des irable 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 projectionGeorgia Regional Haze State Implementation Plan

30 of 124 • Report Capability

• Graphical Analysis Capability

• MOBILE6 Mobile Source Emissions

• Biogenic Emissions Inventory System Version 3 (BEIS-3)

• Ability to process emissions for the pr oposed domain in a reasonable amount of

time

• Ability to process control strategies

• No or low cost for acquisition and maintenance

• Expandability to support other species and mechanisms

Overview of SMOKE

The SMOKE Emissions Processi ng System Prototype was orig inally developed at the Micro-computing Center of North Carolina. As with mo st ”emissions models,” SMOKE is principally an emission processing system and not a true emissions modeling system in which emission estimates are simulated from ”first principles.” This means that, with the exception of mobile and bi ogenic sources, its purpose is to provide an efficient, modern tool for converting emissions inventor y data into the formatted emission files required by an air quality simulation model. For mobile sources, SMOKE actually simulates emissions rates based on input mobi le-source activity data, emission factors and outputs from transportation travel-demand models.

SMOKE was originally designed to allow emi ssions data processing methods to utilize emergent high-performance-comput ing as applied to sparse-matr ix 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 processi ng of emissions data. The processing is rapid because SMOKE utilizes a series of matrix calculatio ns instead of less efficient algorithms used in previous systems. The processing is flexible because the processing steps of temporal projection, controls, chemical s peciation, temporal allocation, and spatial allocation have been separated into independent operations wherever possible. The results from these steps are merged t ogether at a final stage of processing.

SMOKE contains a number of ma jor features that make it an attractive component of the modeling system. The model supports a variety of input formats from other emissions processing systems and models. It supports bot h gridded and county total land use schemes for biogenic emissions modeling. SMOKE can accommodate emissions files from up to 10 countries and any pollutant can be processed by the system. For additional information about the SM OKE model, please refer to Modeling Protocol (Appendix D).Georgia Regional Haze State Implementation Plan

31 of 124 5.3 Selection of the Modeling Year

A crucial step to SIP modeling is the selection of the period of time to model to represent current air quality conditions and to project changes in air quality in response to changes in emissions. The year 2002 was selected as the base year for several

reasons.

The US EPA’s April 2007 Guidance on the Use of Models and Other Analyses for Demonstrating Attainment of Air Quality Goals for Ozone, PM2. 5, and Regional Haze identifies specific goals to consider when selecting one or more episodes for use in demonstrating reasonable progress in attaining the regional haze air quality goals. The US EPA recommends that episode selection derive from three pr incipal criteria:

• Simulate a variety of me teorological 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 qua lity/meteorological data bases exist; and

• Model a sufficient number of days so that the modeled attainm ent test applied at each monitor violating the NAAQ S is based on multiple days.

For regional haze modeling, the guidance goes further by s uggesting that the preferred approach is to model a full, representative year. Moreover, the required RRF values should be based on model results averaged over the 20% worst and 20% best visibility days determined for each Class I area based on monitoring data from the 2000 – 2004 baseline period.

The US EPA also lists several other cons iderations to bear in mind when choosing potential regional haze episodes including: (a) choosing periods which have already been modeled, (b) choosing periods which are drawn from the years upon which the current design values are based, (c) incl uding weekend days among those chosen, and (d) choosing modeling periods that meet as many episode selection criteria as possible in the maximum number of non-attainment or Class I areas as possible. Finally, the US EPA explicitly recommended in its 2007 guidanc e to use 2002 as the baseline inventory

year.

VISTAS adopted a logical, stepwise approach in implementing the US EPA guidance in order to identify the most pr eferable, representative year for regional haze modeling. These steps include the following:

• Representativeness of Meteorological Conditions: The VISTAS meteorological contractor (BAMS) identi fied important meteorologica l characteristics and data sets in the VISTAS region directly relev ant to the evaluation of candidate annual modeling episodes.Georgia Regional Haze State Implementation Plan

32 of 124 • 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 Classificat ion and Regression Tree Analyses to evaluate visibility conditions for 2000, 2001, and 2002, the candidate modeling years. The year 2002 was found to be repr esentative of conditions in the other two years. Subsequently, these analyses were repeat ed with the meteorological and air quality monitoring data for 2000 to 2004 to evaluate how well the 2002- modeling year represented the full 2000-2004 baseline period. This analysis confirmed that visibility and PM2.5 mass in 2002 were representative of the 5- year baseline period for the VISTAS Class I areas. This analysis is discussed in more detail in the project report in Appendix L.

• Data Availability: In parallel with the CART a nalysis, episode characterization analyses, collaborative investigations by VISTAS states (e.g., NCDAQ, GAEPD, FL DEP) intensively studied the availa bility of PM2.5, meteorological, and emissions data and represent ativeness of alternative baseline modeling periods from a regulatory standpoint. Additionally , 2002 was the year that US EPA was requiring states to provide emissions inventory data for the Comprehensive Emissions Reporting Rule; ther efore, 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 consi dered what years other RPO 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 pragm atic choice for VISTAS regional haze modeling. All of the US EPA criteria for regional haze episo de selection were directly considered in this process together with many other considerations (e.g., timing of new emissions or aerometric data deliveries by the US EPA or the states to the modeling teams).

5.4 Modeling Domains

5.4.1 Horizontal Modeling Domain The US EPA’s modeling guidance (Appendix G) recommends a 12-km modeling grid resolution for PM2.5 modeling while a 36-km grid is considered acceptable for regional haze. For the VISTAS modeling, a coarse 36-km grid resolution was used for modeling the entire United States and a finer 12-km grid was used to model the eastern United States.

The CMAQ model was run in one-way nested grid mode. This allowed the larger outer domains to feed concentration data to the i nner nested domain. T he horizontal coarse grid modeling domain boundaries were determi ned 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 fineGeorgia Regional Haze State Implementation Plan

33 of 124 particulate matter non-attainment areas, as well as Class 1 and wilderness areas for regional haze. Processing time was also a factor in choosing a smaller 12-km grid, modeling domain

.

The coarse 36-km horizontal grid domain cove rs the continental Un ited States. This domain was used as the outer grid domain for MM5 modeling with the CMAQ domain nested within the MM5 domain. Figure 5.4. 1-1 shows the MM5 horizontal domain as the outer most, blue grid with the CMAQ 36- km domain nested in the MM5 domain.

Figure 5.4.1-1. The MM5 horizontal domain is th e outer most, blue grid, with the CMAQ 36-km domain nested in the MM5 domain.

To achieve finer spatial resolution in the VISTAS states, a 1-way nested high resolution (12-km grid resolution) was used. Figur e 5.4.1-2 shows the 12-km grid, modeling domain for the VISTAS region. This is t he modeling domain for which the reasonable progress goals will be assessed.Georgia Regional Haze State Implementation Plan

34 of 124 Figure 5.4.1-2. A more detailed view of the 12-km grid over the VISTAS region.

5.4.2 Vertical Modeling Domain The CMAQ vertical structure is primarily defined by the vert ical grid used in the MM5 modeling. The MM5 model employed a terrain-following coordinate system defined by pressure, using 34 layers that extend from t he surface to the 100 mb. A layer-averaging scheme was used to generate 19 vertical laye rs for CMAQ to reduce the computational cost of the CMAQ simulations. The effe cts of layer averaging were evaluated in conjunction with the VISTAS modeling effort and was found to have a relatively minor effect on the model perfo rmance metrics when both the 34-layer and a 19-layer CMAQ models were compared to ambient monitoring data.Georgia Regional Haze State Implementation Plan

35 of 124 

### 6.0 MODEL PERFORMANCE EVALUATION

The initial modeling effort focused on evalua ting previous regional air quality modeling applications and testing candidate model conf igurations for the SMOKE emissions and CMAQ model for the VISTAS 36 -km and 12-km modeling domains. This effort resulted in a report recommending the model config uration for the annual emissions and air quality modeling, which is included as par t of the VISTAS Emissions and Air Quality Modeling Protocol. The eval uation of the meteor ological modeling configuration can be found in Appendix F, with a summ ary of the final meteorolog ical and air quality modeling configuration in Appendix F and Appendix E, respectively.

Air quality model performance for the 2002 m odeling year was initially tested in 2004 using an early version of the VISTAS emissi ons inventory. In keeping with the oneatmosphere objective of the CMAQ m odeling platform, model performance was evaluated based on measured ozone, fine parti cles, and acid deposition in the Air Quality System (AQS), IMPROVE, Specia ted Trends Network (STN), Southeastern Aerosol Research and Characterization (S EARCH), National Acid Deposition Program (NADP) and Clean Air Status and Trends Network (CASTNet) monitoring networks (Figure 6.0-1).

Figure 6.0-1: Monitoring Networks used for VIST AS 2002 model performance evaluation, and their location within the VISTAS 12km domain.Georgia Regional Haze State Implementation Plan

36 of 124 6.1 Modeling Performance Goals, and Criteria

In 2004, VISTAS established model perform ance goals and criteria for components of fine particle mass (Table 6.1-1) based on pr evious model performance for ozone and fine particles. The US EPA modeling guidance (Appendix G) 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’ ev aluation considered several statistical performance measures and displays. Fracti onal bias and mean fractional error were selected as the most appropriate metri cs to summarize model performance; other
metrics were also calculated and are include d for IMPROVE monitors in the full model performance evaluation (Appendix E).

Table 6.1-1.: Established model performan ce goals and criteria for the component species of fine particle mass.

Fractional Bias Mean Fractional Error Comment

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

< 30 percent < 50 percent Goal for PM model performance, considered good performance

< 60 percent < 75 percent Criteria for PM model performance, considered average performance. Exceeding this level of performance indicates fundamental concerns with the modeling system and triggers diagnostic evaluation.

Several graphic displays of model performance were prepared including:

1. Scatter plots of predicted and obser ved concentrations and deposition by species, monitoring network, and month; 2. Time series plots of predicted and observed concentrations and deposition by species, monitoring site, and month; 3. Spatially average time series plots; 4. Time series plots of monthly fractional bias and error for a species, region, and network; 5. Performance goal plots (“soccer plots ”) that summarize model performance by species, region, season; and

6. Concentration performance plots (“bugle plot s”) that display fractional bias or error as a function of concentration by species, region, m onitoring network, and month.

The “soccer plots” and “bugle plots” are relatively new tools in model performance evaluations, and have recently been included as model performance evaluation displaysGeorgia Regional Haze State Implementation Plan

37 of 124 in US EPA’s modeling guidanc e for Ozone, PM2.5, and Regi onal Haze (Appendix G). Both “soccer plots” and “bugle plots” a llow for convenient ways to examine model performance with respect to set goals and cr iteria. The bugle plots have the added benefit of adjusting the goals and cr iteria to consider the concentration of the species. Analysis of “bugle plots” generally suggests that greater emphasis should be placed on performance of those com ponents with the greatest cont ribution to PM mass and visibility impairment (e.g. su lfate and organic carbon) and t hat greater bias and error could be accepted for components with smaller contributions to total PM mass (e.g. elemental carbon, nitrates, and soil).

6.2 VISTAS Domain - Wide Performance

Further discussion of model performance in th is document will focus on the comparison of observational data from t he IMPROVE monitors and model output data from the 2002 VISTAS BaseG4-Actual annual ai r quality modeling. Focus is limited to the IMPROVE monitoring network as these sites are the lo cations used in projecting attainment visibility improvement goals in the Class I areas.

The evaluation will primarily focus on the ai r quality model’s performance with respect to individual components of fine particulate matter (PM 2.5 ), as good model performance of the component species will dictate good model perfo rmance of total or reconstituted fine particulate matter. Model performance of the total fine particulate matter and the resulting total light extinction will also be provided as a means to discuss the overall model performance for this Implementation Plan.

In our analyses, mean fractional bias (error) is used in lieu of mean bias (error), to prevent low observations and model predictions from skewing the metr ics. A full list of model performance statistics is found in Appendi x E. The soccer and bugle plots for all of the VISTAS IMPROVE monitors are incl uded here for summary purposes. Plots have been developed for the av erage monthly concentrations and the performance statistics for all of the mo st significant light-scattering component species (sulfate, nitrate, and organic carbon) for the 20% best days and 20% worst days. Plots for individual IMPROVE monitors associated wit h Georgia Class I areas are included in Appendix E

.

The soccer plots of monthly concentrations (F igures. 6.2-1 and 6.2-2) show that values for nitrate generally fall outside of criteria performance thres holds. Sulfates and organic carbon generally fall within goal thresholds with a couple of mont hs falling just outside the goal thresholds but well within the crit eria thresholds. Figure 6.2-3 contains separate soccer plots for each season. T he seasonal plots emphas ize poorer nitrate performance in the summer (does not ev en appear on the plots provided because performance is off scale with other constit uents) when observed nitrate is quite low and predicted nitrate is even lower. When c oncentration is factored into performance criteria, nitrate performance improves with respect to MFB and MFE (Figures 6.2-4 and 6.2-5).Georgia Regional Haze State Implementation Plan

38 of 124 Additionally, performance assessed at the “one atmosphere” level was also deemed acceptable for ozone and particu late matter at va rious monitoring sites (STN, FRM, CASTNet, etc.). Overall, VISTAS found the Base G2 modeling results to be representative and acceptable for use in m odeling projection for ozone, particulate matter, and regional haze.

Figure 6.2-1.: Soccer plot depicting both the mean fractional error and fractional bias for component concentration for all VISTAS sites based on Base G2 results. Each point represents a monthly value as compared to the model performance criteria (red box) and modeling performance goals (green box).

Figure 6.2-2.: A zoomed view of the soccer plot depicting both the mean fractional error and fractional bias for component concentration for all VISTAS sites based on Base G2 results. Each

point represents a monthly value as compared to the model performance criteria (red box) and modeling performance goals (green box). All Sites CMAQ 12km - 2002 Monthly

0.0 20.0 40.0 60.0 80.0 100.0 120.0 140.0 160.0 180.0 200.0

-180.0 -120.0 -60.0 0.0 60.0 120.0 180.0
Fractional BiasMean Fractional Error Sulfate

Nitrate

Organics

Criteria

Goal

All Sites CMAQ 12km - 2002 Monthly

0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0 90.0 100.0

-75.0 -25.0 25.0 75.0
Fractional BiasMean Fractional Error Sulfate

Nitrate

Organics

Criteria

GoalGeorgia Regional Haze State Implementation Plan

39 of 124 Figure 6.2-3.: Seasonal soccer plots based on Base G1 results for all VISTAS IMPROVE monitors.Georgia Regional Haze State Implementation Plan

40 of 124 Figure 6.2-4.: Bugle plot of the mean fraction error for particulate matter and its component concentrations for all VISTAS sites based on Base G2 results. Each point represents a monthly mean fraction error value as compared to the model performance criteria (red lines) and modeling performance goals (green lines).

All Sites CMAQ 12km - 2002 Monthly

-200.0 -150.0 -100.0

-50.0

0.0 50.0 100.0 150.0 200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 Average Concentration ( μ g/m 3 )Mean Fractional Bias Sulfate

Nitrate

Organics

(+) Criteria

(+) Goal

(-) Goal

(-) Criteria

Figure 6.2-5.: Bugle plot of mean fraction bias for particulate matter and its component species for

all VISTAS sites based on Base G2 results. E ach point represents a monthly mean fraction bias value as compared to the model performance criteria (red lines) and modeling performance goals (green lines). All Sites CMAQ 12km - 2002 Monthly

0.0 50.0 100.0 150.0 200.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 Average Concentration ( μ g/m 3 )Mean Fractional Error Sulfate

Nitrate

Organics

Criteria

GoalGeorgia Regional Haze State Implementation Plan

41 of 124 6.3 Georgia Class I Areas Performance

The following section provides bar charts comparing observed fine particulate matter composition and modeled fine particulate matte r composition. The charts have been split into two charts, with t he first displaying the 20% best days followed by the chart for the 20% worst days. Stacked bar char ts have been developed for each of the IMPROVE monitoring sites relevant to Georgia: Cohutta Wilderness Area and Okefenokee Wilderness Area (See Figure 1.4- 1). The Okefenokee Wilderness Area’s IMPROVE monitor is used to represent Wolf Island.

The stacked bar chart allows a side-by-side comparison of the each day observed and modeled compositional and total light extinction. Within each bar the color codes are:

• Yellow = light extinction due to sulfates (bextSO4)

• Red = light extinction due to nitrates (bextNO3)

• Green = light extinction due to organic carbon (bextOC)

• Black = light extinction due to elemental (bextEC)

• Brown = light extinction due to soil (bextSoil)

• Grey = light extinction due to coarse mass (bextCM)

The components are presented in the same order for both the observed (left hand bar) and modeled bar (right hand bar), so it is easy to identify days when the prediction light extinction for the component differs from t he observed. The tota l height of the bar provides the total reconstructed part iculate matter light extinction value.

A cursory view of the stacked bar charts reiterates that sulfates are a large contributor to light extinction in the Georgia Class I areas on both 20% best days and 20% worst days. The bar charts also suggest that organic carbon and ni trates are important on the 20% best days at the two IMPROVE sites of interest for Georgi a. The bar charts for the 20% best reiterate the general over prediction. The over predi ction of sulfate on most of the 20% best days appears to be the crux of the over prediction, with the over prediction of nitrate factoring in heavily on some days.

Comparing the 20% best day charts to the 20% worst days charts, the various components of particle pollution play a more prominent role in the 20% best days than with the 20% worst days. Also, the species makeup on the 20% best days varies more widely compared to the 20% worst days. This suggests accurately modeling each species is especially import ant on the 20% best days.

With the bar chart for the 20% worst days, you can see the general under prediction. The under prediction of sulfate on some of the 20% worst days appears to be the cause of the overall under prediction with the under prediction of organic carbon factoring in heavily on few days.Georgia Regional Haze State Implementation Plan

42 of 124 Overall, the GA EPD found model performance to fall within acceptable limits for model performance. The GA EPD further assert s the “one atmosphere” modeling performed by the VISTAS contractors is representative of conditions in the southeastern states and is applicable for use in attainment demonstrations.Georgia Regional Haze State Implementation Plan

43 of 124 6.3.1 Cohutta Wilderness Area

Best 20% Obs (left) vs 2002gt2a (right) at COHU1

0 10 20 30 40 50 60 70 80

23 26 32 38 44 62 77 89 113 116 119 173 194 257 269 308 320 341 347 356 _ _ _ _ _ Avg
Julian Day in Best 20% groupbEXT (1/Mm) bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at COHU1

0 100 200 300 400 500 600

56 122 152 155 185 188 191 197 206 215 218 221 224 227 233 248 251 260 263 266 281 _ _ _ _ Avg
Julian Day in Worst 20% groupbEXT (1/Mm) bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-1.: Stacked bar chart for COHU on the 20% best days (top) and 20% worst days (bottom). Observed composition is presented in the left hand bar, with modeled composition represented by the right hand bar.Georgia Regional Haze State Implementation Plan

44 of 124 6.3.2 Okefenokee Wilderness Area

Best 20% Obs (left) vs 2002gt2a (right) at OKEF1

0 10 20 30 40 50 60

11 20 38 59 62 104 170 173 176 179 191 239 242 257 266 275 284 335 344 347 356 359 _ _ _ Avg
Julian Day in Best 20% groupbEXT (1/Mm) bCM

bSOIL

bEC

bOC

bNO3

bSO4

Worst 20% Obs (left) vs 2002gt2a (right) at OKEF1

0 50 100 150 200 250 300 350

17 23 44 56 89 95 122 128 155 188 197 200 218 236 254 260 263 281 296 308 338 341 350 _ _ Avg
Julian Day in Worst 20% groupbEXT (1/Mm) bCM

bSOIL

bEC

bOC

bNO3

bSO4

Figure 6.3-2.: Stacked bar chart for OKEF on the 20% best days (top) and 20% worst days (bottom). Observed composition is presented in the left hand bar, with modeled composition represented by the right hand bar.Georgia Regional Haze State Implementation Plan

45 of 124 

### 7.0 LONG-TERM STRATEGY FO R GEORGIA CLAS S I AREAS

As stated in Section 1.3 above, the regional haze rule requires States to establish reasonable progress goals, expressed in deciv iews, for visibility improvement at each affected Class I area covering each (approximatel y) 10-year period until 2064. This first set of reasonable progress goals must be met through measures contained in the state’s long-term strategy co vering the period from the bas eline until 2018. This section discusses development of G eorgia’s long-term strategy.

7.1 Overview of the Long-Term Strategy Development Process

The monitored data and modeling analyses cit ed in Sections 2 and 5 above establish that for the VISTAS region, the key contributors to regional haze in the 2000-2004 baseline timeframe were large stationary sour ces of sulfur dioxide emissions. Keeping that key conclusion in mind, this se ction addresses the following questions:

Assuming implementation of existi ng federal and stat e air regulatory requirements in Georgia and the VI STAS region, how much visibility improvement, compared to the glidepath, would we expect to see at Class I areas in Georgia between now and 2018?

If additional emission reductions are to be considered, from what pollutants and source categories would the greatest vi sibility benefits be rea lized between the baseline and 2018?

Narrowing down further, in what geographic locations do we find the emissions which have the greatest impact on vi sibility in specific Class I areas?

What types of emissions sources do we find in those geographic locations?

Which specific individual sources in those geographic locations have the greatest visibility impacts at a given Class I area?

What additional emission controls repr esent reasonable progress for those specific sources?

What additional emission controls represent BART in Georgia?

Given the additional emission reductions expected from reasonable progress and BART, how much additional visibility im provement, compared to the glidepath, will we expect to see at Class I areas in Georgia between the baseline and 2018?Georgia Regional Haze State Implementation Plan

46 of 124 7.2 Expected Visibility Results in 2018 for Georgia Class I Areas under existing and planned emissions controls (Base G4 Inventory)

There are significant control programs being implemented between the baseline period and 2018. These programs are descr ibed in more detail below.

7.2.1 Federal and State Control Requirements

• Clean Air Interstate Rule (CAIR). Utility projections are based on Integrated Planning Model. US EPA issued CAIR, which will permanently cap emi ssions of sulfur dioxide (SO2) and nitrogen oxides (NOx) in the eastern United Stat es. CAIR achieves large reductions of SO2 and/or NOx emissions across 28 eastern states and the District of Columbia. When fully implemented, CAIR will reduce SO2 emissions in these states by over 70 percent and NOx emissions by over 60 percent from 2003 levels . These reductions were taken into account in the 2018 base G4 inventory

• Heavy Duty Diesel (2007) Engine Standard. A PM emissions standard for new heavy-duty engines of 0.01 grams per brake-horsepower-hour (g/bhp-hr), to take full effect for diesels in the 2007 model year. Also includes standards for NOx and non-methane hydrocarbons (NMHC) of 0.20 g/bhp-hr and 0.14 g/ bhp-hr, respectively. These NOx and NMHC standards will be phased in together between 2007 and 2010 for diesel engines. Sulfur in diesel fuel must be lowered to enable modern pollution-control technology to be effective on these trucks and buses. EPA will require a 97 percent reduction in the sulfur content of highway diesel fuel from its current level of 500 parts per million (low sulfur diesel, or LSD) to 15 parts per million (ultra-low sulfur diesel, or ULSD).

• Tier 2 Tailpipe. US EPA’s Tier 2 is a fleet averaging program, modeled after the California LEV II standards. Manufacturers can produce vehicles with emissions ranging from relatively dirty to zero, but the mix of vehicles a manufacturer sells each year must have average NO
x emissions below a specified value.

• Large Spark Ignition and Recreational Vehicle Rule. In this rule, US EPA sets emission standards for these categories of non-road engines and vehicles.

• Non-Road Diesel Rule. In this rule, US EPA im plements a low-sulfur fuel requirement that affects both future (Commercial Marine Vessels) CMV and locomotive emissions.

• Combustion Turbine MACT. US EPA issued this rule; however, the projection inventories do not include the NOx co-benefit effects resulting from this rule. EPA estimates them to be small compared to the overall inventory.

• Industrial Boiler/Process Heater/RICE MACT. The Environmental Protection Agency (EPA) issued final rules to substantially reduce emissi ons of toxic air pollutants from industrial, commercial and institutional boilers, process heaters and from stationary reciprocating internal combustion engines (RICE). These rule s reduce emissions of a number of toxic air pollutants, including hydrogen chloride, manganese, lead, arsenic and mercury by 2009. This rule also reduces emissions of sulfur dioxide and particulate matter in conjunction with the toxic air pollutant reductions. The applied Maximum Achievable Control Technology (MACT) control efficiencies were 4 percent for SO2 and 40 percent for PM10 and PM2.5. However, EPA’s industrial boiler MACT rules were vacated on June 8, 2007. The emissionsGeorgia Regional Haze State Implementation Plan

47 of 124 reductions that were modeled to account for the industrial boiler MACT were 1,343.5 tons/year of SO2, 879.4 tons/year of PM 2.5, and 1,304.2 tons/year of PM10. These reductions are insignificantly small (0.69% for SO2, 0.39% for PM2.5, and 0.13% for PM10) compared to the statewide totals (193,665. 5 tons/year SO2; 225,104.5 tons/year PM2.5; and 1,002,873.2 tons/year PM10) and should not impact the conclusions made in the SIP. If another VISTAS “best and final” modeling run is performed, it will remove control assumptions solely due to this MACT rule.

• VOC 2-, 4-, 7-, and 10-year MACT Standards. The point source MACTs and associated emission reductions were designed from Federal Register (FR) notices and discussions with EPA’s Emission Standards Division (ESD) staff. We did not apply reductions for MACT standards with an initial compliance date of 2001 or earlier, assuming that the effects of these controls are already accounted for in the 2002 inventories supplied by the States.

• Georgia Rule 391-3-1-.02(2)(yy), (i.e. Emissions of Nitrogen Oxides from Major sources based on Section 182 of the Federal CAA Amendments of 1990, requires that every major source (i.e. source with potential to emit > 50 tons/yr) of NOx located in 13 county Atlanta non-attainment area should apply reasonably available control technology (RACT) in controlling NOx emissions. Georgia EPD has r equired full compliance with NOx RACT limits since July 31, 1995; however, Georgia EPD has not taken these emission reductions into account in any inventory or modeling scenario.

• 1-hr Ozone SIPs (Atlanta/Birmingham/Northern Kentucky). These SIPs have been implemented for attainment and maintenance of the 1-hour ozone National Ambient Air Quality Standard (NAAQS). Reductions from these SIPs have been taken into account in the 2018 modeling runs.

• Georgia Rule 391-3-1-.02(2)(sss), Multipollutant Control for Electric Utility Steam Generating Units, was adopted in 2007. The effective date of the rule varies for various EGU units but will start being effective from December 31, 2008, and required controls for all affected units will be in place before June 1, 2015. When fully implemented, Rule (sss) will reduce SO2 emissions by about 90 percent, NOx emissions by approximately 85 percent and mercury emissions by approximately 79 percent.

7.2.2 Additional State Progr ams to Reduce Emissions In addition to accounting for specific emi ssion reductions due to ongoing air pollution programs as required under the RHR Section 308 (d)(3)(v)(A), states are also required to consider the air quality benefits of measures to mitigate the impacts of construction activities [Section 308(d)(3)(v)(B)] and agricultural and forestry smoke management [Section 308(d)(3)(v) (E)].

7.2.3 Projected 2009 and 2018 B ase G4 Emissions Inventories The Base G inventories for 2009 and 2018 a ccount for post-2002 emission reductions from promulgated and pr oposed federal, state, local, and site-specific control programs as of July 1, 2004. In general, emissions inventories were developed for 2009 and 2018 using current control information in Georgi a and for growing the 2002 inventory using EGAS6, MOBILE6, and IPM for electr ic generating units (EGUs).Georgia Regional Haze State Implementation Plan

48 of 124 For EGUs, IPM results were adjusted based on State and local (S/L) agency knowledge of planned emission controls at specific EGUs, including cont rols required by Georgia’s Rule (sss). These updates for Base G4 are documented in the MACTEC emissions inventory report “Documentat ion of the 2002 Base Year and 2009 and 2018 Projection Year Emission Inventories fo r VISTAS” dated February 2007.

For non-EGUs, we used recently updated growth and control data consistent with the data used in US EPA’s CAIR analyses supplemented by Stat e and local agency data and updated forecasts from the D epartment of Energy (DOE).

Area source controls were estimated usi ng known state-level, Stage I controls on gasoline dispensing facilities and open burning es timates, as well as controls used to project emissions for US EPA’s Heavy Du ty Diesel rulemaking and for the CAIR rulemaking.

Mobile source controls included local c ontrols underlying the 2002 baseline inventory (vehicle emission inspection, Stage II vapor re covery, anti-tampering, etc.) with changes based on specific State input. Non-road c ontrol data and projections for 1996, 2010, 2015, and 2020 were obtained from the US EPA's Clean Air Interstate Rule (CAIR) Technical Support Document, and straight line projections were used to estimate 2009 and 2018 levels.

The following bar charts show expected dec reases in emissions of SO2 and NOx across the VISTAS states from 2002 through 2018. (Similar c harts for other visibilityimpairing pollutants are contai ned in Appendix H). Note that for SO2 emissions in particular, which are the largest contributors to haze, emissions from electric generating facilities are expected to decrease dramat ically (70 percent) between 2002 and 2018. However, even with this significant reduc tion in SO2 emissions , EGU emissions are projected to remain the largest contributor to haze, comprising more than half of remaining SO2 emissions in most of the VISTAS states.Georgia Regional Haze State Implementation Plan

49 of 124 Figure 7.2.3-1. Base G Annual SO2 emissions fo r 2002, 2009, and 2018 in the VISTAS states.

Figure 7.2.3-2. Base G Annual NOx emissions in 2002, 2009, and 2018 in the VISTAS States. 0 100 200 300 400 500 600 700

A labam a

F lorida Geor gi a

K ent

uc ky Mississippi
Nort h C aroli

n a

S out

h Car

ol ina Tennessee Virginia West VirginiaAnnual SO2 (Thousand Tons)
Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU 2002 Typical

2009 OTW

2018 OTW

0 200 400 600 800 1,000 1,200

Alabama Florida

G e or gi a

K entuck y

M i s sis

s i ppi

Nor t h Carolina South C a rolin

a

T e nnes

see
V i r gi

n i a

W es t V i r gini

aAnnual NOx (Thousand Tons) Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU 2002 Typical

2009 OTW

2018 OTWGeorgia Regional Haze State Implementation Plan

50 of 124 Summary of Final Base G4 Emi ssions Inventories for 2009 and 2018

Table 7.2.3-1 is a summary of the 2009 Base G4 emission inventory. The complete inventory and discussion of the methodolog y is contained in Appendix C.

Table 7.2.3-1. 2009 Emissions In ventory Summary for Georgia.

VOC NOx PM2.5 PM10 NH3 SO2 Point 36,430.1 148,849.7 29,889.7 40,993.6 4648.8 462,666.4 Area 306,337.3 51,925.0 169,011.4 840,244.9 91,439.1 60,604.0
On-Road
Mobile 195,125.2 209,349.2 3,840. 1 6,072.0 12,686.9 1,585.0

Non-Road Mobile 67,686 85,732.9 7,174.6 7,521.1 67.5 2,724.7

Biogenics 1,972,795.4 20,942.38 0 0 0 0 TOTAL 2,578,374 516,799.18 209,915. 8 894,831.60 108,842.3 527,580.1

Table 7.2.3-2 is a summary of the 2018 Base G4 emission inventory. The complete inventory and discussion of the methodolog y is contained in Appendix C.

Table 7.2.3-2. 2018 Emissions In ventory Summary for Georgia.

VOC NOx PM2.5 PM10 NH3 SO2 Point 43,097.8 125,680.0 36,297. 4 48,005.1 6,474.4 127,863.6 Area 353,224.5 55,518.5 180,697. 2 944,009.4 102,112.4 62,636.2
On-Road
Mobile 109,763.3 102,179.2 2,380. 2 4,843.6 14,873.2 1,457.0

Non-Road Mobile 56,760.7 64,578.8 5,729.7 6,015.1 78.6 1,708.8

Biogenics 1,972,795.4 20,942.38 0 0 0 0 TOTAL 2,535,641.7 368,898.88 225,104. 5 1,002,873.2 123,538.6 193,665.6

7.2.4 Model Results for the 2018 Base G4 Inventory Compared to the Uniform Rate of Progress Glidepaths for Georgia Class I Areas Using 2000 - 2004 IMPROVE monitoring data, t he deciview values for the 20 percent best days in each year are averaged toget her, producing a single average deciview value for the best days. Similarly, the deciv iew values for the 20 percent worst days in each year are averaged together, producing a single average deciview value for the worst days.

Figures 7.2.4-1 through 7.2. 4-6 illustrate the predicted vi sibility improvement by 2018 resulting from the Base G4 inventory that represents implementati on of existing Federal and State regulations, compared to the Uniform Rate of Progress glidepath for Cohutta Wilderness Area (COHU), Okefenokee W ilderness Area (OKEF), and Wolf Island Wilderness Area (WOLF). The pink lines show the target natural condition in 2064 for the 20 percent worst days or 20 percent best days, and the incremental deciview changes resulting from a uniform rate of progress between current and natural conditions in 2064 for average 20 percent wo rst visibility days or 20 percent bestGeorgia Regional Haze State Implementation Plan

51 of 124 visibility days in the 2000-2004 baseline period. The purple lines show the improvement expected from existing and plann ed emission controls during the period of the first longterm strategy.

Figure 7.2.4-1. CMAQ 2018 Base G4 results compared to Uniform Rate of Progress at Cohutta Wilderness Area

Figure 7.2.4-2. CMAQ 2018 Base G4 results compared to Uniform Rate of Progress at Okefenokee Wilderness Area Uniform Rate of Progress Glide Path Cohutta - Worst 20% Data Days New IMPROVE Equation

30.25 28.63

25.71

22.46

19.22

15.97

12.73
10.78 27.05

22.80

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model Prediction

Uniform Rate of Progress Glide Path Okefenokee - Worst 20% Data Days New IMPROVE Equation

27.13 25.81

23.42

20.76

18.11

15.45

12.80 11.21 25.38 23.82

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model PredictionGeorgia Regional Haze State Implementation Plan

52 of 124 Reasonable Progress Assessment Base G4 inventory, new IMPROVE Algorithm Cohutta - Best 20% Days

13.77 13.77 13.77

13.01 11.75

4.32

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064
YearHaziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure 7.2.4-3. CMAQ 2018 Base G4 results compared to Uniform Rate of Progress at wolf Island Okefenokee Wilderness Area represents visibility improvement at Wolf Island

Figure 7.2.4-4. CMAQ 2018 Base G4 results at Cohutta Wilderness Area. Uniform Rate of Progress Glide Path

Wolf Island - Worst 20% Data Days New IMPROVE Equation

27.13 25.81

23.42

20.76

18.11

15.45

12.80 11.21 25.38 23.82

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model PredictionGeorgia Regional Haze State Implementation Plan

53 of 124 Figure 7.2.4-5. CMAQ 2018 Base G4 results at Okefenokee Wilderness Area.

Figure 7.2.4-6. CMAQ 2018 Base G4 results at Wolf Island. Okefenokee Wilderness Area represents visibility Improvement at Wolf Island. Reasonable Progress Assessment Base G4 inventory, new IMPROVE Algorithm Okefenokee - Best 20% Days

15.23 15.23 15.23

14.25 13.92

5.31

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064
YearHaziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction

Reasonable Progress Assessment Base G4 inventory, new IMPROVE Algorithm Okefenokee - Best 20% Days

15.23 15.23 15.23

14.25 13.92

5.31

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064
YearHaziness Index (Deciviews)

Baseline Natural Condition (20% Best Days) Observation Method 1 PredictionGeorgia Regional Haze State Implementation Plan

54 of 124 Note that at Cohutta wilderness area in G eorgia, visibility improvement on the 20 percent worst days is expected to be better than the uniform rate of progress glidepath by 2018 based solely on reductions from ex isting and planned emissions controls. A 4.4 dv improvement in visibility would meet uniform rate of progr ess in 2018; expected emissions reductions by 2018 are project ed to achieve a 7.41 dv improvement.

Okefenokee Wilderness Area and Wolf Island expected emissions reductions by 2018 are projected to achieve a 3.28 dv of impr ovement in visibility, while a 3.6 dv of improvement in visibility would meet uniform rate of progress in 2018.

In Figure 7.2.4-7 the percentage of the target reduction achi eved for the Georgia Class I areas using the new IMPROVE equation is 90-170 percent. This means that the rate of improvement is between –10 to +70 percent of the required uniform rate of progress by 2018.

In addition to improving visibility on the 20 per cent worst visibility da ys, states are also required to protect visibility on the 20 per cent best days at the Class I areas. As illustrated in Figure 7.2.4-8, visibility on the 20 percent best days is projected to improve in 2018 at all VISTAS Class I areas as a re sult of the 2018 Base G4 emissions reductions. In Figure 7.2.4-8 the percentage of t he target achieved for the Georgia Class I areas is about -10 percent. Zero percent change would mean no change in visibility; -10 percent means that visibility is better than no change, or a 10 percent improvement (values lower than current conditions).

The expected change in visibility at any VISTAS and neighboring class I areas between 2000-2004 baseline conditions on the 20 percent worst days and 2018 projections for Base G4 is illustrated in Figure 7.2.4-7. In contrast, natural background visibility conditions for the 20 percent best days are illustrated in Figure 7.2.4-8.Georgia Regional Haze State Implementation Plan

55 of 124 CMAQ 2018g4a/2002gt2a Method 1 predictions for VISTAS+ sites

0% 20% 40% 60% 80% 100% 120% 140% 160% 180% 200% 220%COHU1DOSO1GRSM1JARI1LIGO1CADI1MACA1SHEN1SHRO1SIPS1CHAS1EVER1OKEF1ROMA1SAMA1SWAN1BRET1BRIG1CACR1HEGL1MING1UPBU1Percent of target reduction achieved CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

VISTAS non-VISTAS

CMAQ 2018g4a/2002gt2a Visibility Projection for VISTAS+ sites on Best 20% days

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%COHU1DOSO1GRSM1JARI1LIGO1CADI1MACA1SHEN1SHRO1SIPS1CHAS1EVER1OKEF1ROMA1SAMA1SWAN1BRET1BRIG1CACR1HEGL1MING1UPBU1Percent of target reduction achieved CMAQ New IMPROVE Algorithm

CMAQ Old IMPROVE Algorithm

VISTAS non-VISTAS Figure 7.2.4-7. Projected visibili ty improvement on 20 percent worst visibility days at VISTAS and neighboring Class I areas for the 2018 Base G4 CMAQ run (12 km grid)

Figure 7.2.4-8. Projected visibili ty improvement on 20 percent best visibility days at VISTAS and neighboring Class I areas for the 2018 Base G4 CMAQ runGeorgia Regional Haze State Implementation Plan

56 of 124 Figure 7.2.4-9. Visibility improvement on 20 perc ent haziest days at Cohutta Wilderness Area between 2000-2004 baseline conditions (left) and 2018 Ba se G4 projected visibility (right). Image generated using WinHaze.

Figure 7.2.4-10. Projected visibili ty on 20 percent haziest days for natural background visibility conditions at Cohutta Wilderness Area. Image generated using WinHaze.Georgia Regional Haze State Implementation Plan

57 of 124 Figure 7.2.4-9 and 7.2.4-10 show images that were generated using WINHAZE, a photographic imaging tool that a ccounts for the effect of c oncentrations of fine particle components and relative humidity on visibility. These images illustrate that notable improvements in visibility are expect ed by 2018 and that significantly greater improvements are needed to reach natural background conditions.

7.3 Relative Contribution from Internationa l Emissions to Visibility Impairment in

2018 at VISTAS Class I Areas

Emissions from Mexico, Canada, Central Americ a, Asia, and Africa contribute to PM2.5 loadings and visibility impairm ent at Class I areas in the co ntinental United States. To
evaluate the relative contributi on of international emissions to visibility at Class I areas in the southeastern United States, VISTAS us ed a combination of m odeling results from the global three-dimensional chemical transport model (GEOS-Chem) and CMAQ. VISTAS used the GEOS-Chem global model to generate initial and boundary conditions for the CMAQ modeling domain. GEOS-C hem was run for the 2002 modeling year using a 4x5 degree horizontal grid resolu tion and a 3-hour temporal resolution. Because emissions were based on monthly averages, the model does not capture the episodic variability in emi ssions. The GEOS-Chem outputs were used to calculate initial and boundary conditions for the national CMAQ mode ling domain. The national CMAQ domain included portions of Canada and Mexico, so emissions for these
countries were included within the national CMAQ modeling domain or as part of the boundary conditions outside the national modeling domain, as appropriate.

Two complementary methods were used to calculate the impact of international emissions at Class I areas. Because all in ternational fires are treated as natural emissions in these runs, both cases underestima te the contributions from international fires that are due to anthropogenic burning.

1) International emissions are represented by the differences between two GEOSChem runs. In the first run, Un ited States anthropogenic emissions were removed, and in the second run both United States and international anthropogenic emissions were removed. Th e difference represents international anthropogenic emissions in the absenc e of United States anthropogenicemissions (e.g. compared to 2064 levels). Harvard University provided GEOSChem results to VISTAS for 2002 internati onal contribution on 4x5 degree grid. Concurrently, Harvard modeling for the Elec tric Power Research Institute (EPRI) provided GEOS-Chem results for 2001 inte rnational contribution on a 1x1 degree grid scale.

2) International emission s are represented by the di fference between two CMAQ 36-km simulations, both using 2018 Base F emissions and boundary conditions from GEOS-Chem. In the first CMAQ r un, all global natural and anthropogenic emissions in 2018 are active. In the second CMAQ run, only global (United States and international) natural emissi ons are active. Here the impacts ofGeorgia Regional Haze State Implementation Plan

58 of 124 

### Transboundary Man-Made Impacts

0.0 0.2 0.4 0.6 0.8 1.0 1.2BRIGHEGLCACRMINGUPBUBRETEVERCHASSAMACOHUOKEFROMASIPSSHROGRSMLIGOMACASWANJARIDOSOSHEN(NH4)2SO4Conc. (μg/m3)

GEOS_4x5 GEOS_1x1 PSAT CMAQ international emissions are compared agai nst 2018 conditions rather than natural background conditions.

Separate from VISTAS, the CENRAP RP O used PM Source Apportionment Technology (PSAT) in the CAMx regional air quality model to calculate the impact of Canadian and Mexican emissions and boundar y conditions on visibility at Class I areas in 2002.

As illustrated in Figure 7.3-1 for annual av erage contributions to sulfate at VISTAS and neighboring Class I areas, the estimated in ternational contributions are higher at Class I areas near the Canadian and Mexica n borders and along the eastern coast. The estimated international contribution is higher using CMAQ and PSAT than in the GEOS-Chem runs because the grid scale is finer (more accurate dispersion of emissions) and because the background atmos phere includes loadings from current United States anthropogenic emi ssions (greater photochemical activity). Similar charts for nitrate and organic carbon mass, for impacts on 20 percent worst visibility days, and for impacts of international em issions on calculated light extinction are included in Appendix I.

Figure 7.3-1. Estimated international emissions contributions to sulfate at VISTAS and neighboring Class I areas.

In Figure 7.3-2 and 7.3-4 CMAQ projections of contributions from international emissions to PM mass on 20 percent worst visibility days in 2002 at Cohutta and Okefenokee are compared to United States domestic contributions to PM components at the site on those days. Figure 7.3-3 and 7.3-5 illustrates the effect of removing the
incremental contribution due to international emissions when consi dering the visibility improvement in 2018 compared to the unifo rm rate of progress at Cohutta and Okefenokee wilderness area. Since there is not an IMPROVE monitor located at WolfGeorgia Regional Haze State Implementation Plan

59 of 124 Island, the Okefenokee uniform rate of pr ogress glide slope and reasonable progress goals are being used as surrogates for Wolf Island.

Figure 7.3-2. PM component concentrations from US domestic sources on 20 percent worst visibility days in 2002 (left bars) and CMAQ-simulat ed international contributions (right bars) at Cohutta Wilderness Area, GA. COHU1 Domestic and International Aerosol Mass by Species 20% Worst Days (2002)

0 10 20 30 40 50 60DomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternationalDomesticInternational

2/25 5/2 6/1 6/4 7/4 7/7 7/10 7/16 7/25 8/3 8/6 8/9 8/12 8/15 8/21 9/5 9/8 9/17 9/20 9/23 10/8Mass (μg/m3)

Amm SO4 Amm NO3 POM LAC Soil CM Sea SaltGeorgia Regional Haze State Implementation Plan

60 of 124 Figure 7.3-3. Accounting for international emissions contributions on modeled rate of progress by 2018 at Cohutta, GA. Open triangle = estimate wi th all emissions; Open diamond = estimate with international emissions removed.

Figure 7.3-4. PM component concentrations from US domestic sources on 20 percent worst visibility days in 2002 (left bars) and CMAQ-simulat ed international contributions (right bars) at Okefenokee Wilderness Area, GA. OKEF1 Domestic and International Aerosol Mass by Species 20% Worst Days (2002)

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

1/17 1/23 2/13 2/25 3/30 4/5 5/2 5/8 6/4 7/7 7/16 7/19 8/6 8/24 9/11 9/17 9/20 10/8 10/23 11/4 12/4 12/7 12/16Mass (μg/m3)

Amm SO4 Amm NO3 POM LAC Soil CM Sea Salt Uniform Rate of Progress Glide Path Cohutta - Worst 20% Data Days New IMPROVE Equation

30.25 28.96

25.71

22.46

19.22

15.97

12.73

10.78 23.19 21.77

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model Prediction Model Prediction w/o Intl. Trans.Georgia Regional Haze State Implementation Plan

61 of 124 Figure 7.3-5. Accounting for international emissions contributions on modeled rate of progress by

2018 at Okefenokee, GA. Open triangle = estimate with all emissions; Open diamond = estimate with international emissions removed.

For the Okefenokee Class I areas, it can be s een that accounting for the international contribution along with reductions of Unit ed States anthropogenic em issions will result in visibility improvement gr eater than the uniform rate of progress by 2018. As the atmosphere becomes closer to natural ba ckground conditions in the future, the incremental contribution from international emissions will be come more important. The information is included in this SIP document ation to provide reference for future assessments of reasonable progress.

7.4 Relative Contributions to Visibility Impairment: Pollutants, Source Categories, and Geographic Areas

An important step toward ident ifying further reasonab le progress measures is to identify the key pollutants contributing to visibilit y impairment at each Class I area. To understand the relative benefit of further redu cing emissions from di fferent pollutants, source sectors, and geographic areas, VI STAS engaged the Georgi a Institute of Technology to perform emission sensitivit y model runs using CMAQ. Emissions sensitivities were initially performed for three episodes representing winter and summer conditions: January 2002, July 2001, and July 2002. These runs used the initial 2018 projections inventory and considered 30 percent reductions from specific pollutants, source categories, and geographic areas. Emi ssions sensitivities were repeated using the 2009 Base D projection inventory and tw o-month-long episodes from 2002: June 1- Uniform Rate of Progress Glide Path Okefenokee - Worst 20% Data Days New IMPROVE Equation

27.13 26.07

23.42

20.76

18.11

15.45

12.80 11.21 24.37 22.64

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model Prediction Model Prediction w/o Intl. Trans.Georgia Regional Haze State Implementation Plan

62 of 124 July 10 and November 19 through December 19. Emissions in 2009 were reduced by 30 percent for each pollutant sensitivity run. The pollutant contributions that were evaluated were:

• SO2 from EGU sources in each VISTAS state, other RPOs in the VISTAS 12 km grid, and Boundary Conditions from outside the 12 km domain;

• SO2 from non-EGU point sources in each VISTAS state, other RPOs, and Boundary Conditions;

• NOx from ground level (on-road plus non-road plus area) sources in each VISTAS state and other RPOs;

• NOx from point (EGU plus non-EGU) s ources in each VISTAS state and other RPOs;

• NH3 from all sources in VISTAS and other RPOs;

• Volatile Organic Compounds from anthr opogenic and biogenic sources in the 12 km modeling domain;

• Primary Carbon from all ground level s ources in each VISTAS state and other RPOs;

• Primary Carbon from all point source s in each VISTAS state and other RPOs;
and

• Primary Carbon from all fires in each VISTAS state and other RPOs.Georgia Regional Haze State Implementation Plan

63 of 124 Results are shown in Figures 7.4-1 thr ough 7.4-2 below for the average of the 20 percent worst visibility days for the two Georgia Class I areas.

Figure 7.4-1. CMAQ projections of visibility responses on 20 percent worst days at Cohutta Wilderness Area, GA to 30 percent reductions fr om the 2009 Base D inventory for visibilityreducing pollutants in different source categories and geographic areas.

Figure 7.4-2. CMAQ projections of visibility responses on 20 percent worst days at Okefenokee Wilderness Area, GA to 30 percent reductions fr om the 2009 Base D inventory for visibilityreducing pollutants in different source categories and geographic areas.Georgia Regional Haze State Implementation Plan

64 of 124 Responses for 20 percent worst days were ca lculated by averaging the responses of the 20 percent worst days that were modeled in the two episodes. For the Georgia sites, responses on five-to-six of the 20 per cent worst visibility days were included in these graphics.

As Figures 7.4-1 through 7.4- 2 illustrate, the greatest visi bility benefits on the 20 percent worst days for the Georgia Class I areas are projected to re sult from further reducing SO2 from EGUs. At the mountain Class I areas, benefits are projected from SO2 reductions from EGUs in several VISTAS stat es including Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, Vi rginia, and West Virginia. Contributions from other RPOs and from the boundary conditions are co mparatively small and the greatest benefits would likely be from further EGU reductions within the VISTAS states. MRPO states have some contribution, as do SO2 and SO4 coming into the modeling domain from outside the boundary.

Additional, smaller benefits ar e projected from additional SO2 emission reductions from non-utility, industrial point sources. The patte rn of relative SO2 contributions from nonEGUs among the various VISTAS states is similar to the pattern of relative SO2 contributions from EGUs.

Because ammonium nitrate is a small contributor to PM2.5 mass and visibility impairment on the 20 percent worst days at the mountain Class I areas, the benefits of reducing NOx and NH3 emissions at these sites are small. Some of the 20 percent worst days at coastal sites in the VISTAS states occur in the winter when ammonium nitrate has a somewhat larger contribution to visibility impairment. As shown in Figure 7.4-2, reducing ammonia emissions would be more beneficial for reducing ammonium nitrate contributions to visibility impairment at Okefenokee Wilderness area than further reducing nitrogen oxide emissions from eit her ground or point sources. Ammonium emissions are the result of agricultural acti vity, specifically fertilizing operations and animal farming. Since there are no economical ly feasible options for controlling these types of area sources of ammonia emission s, and EPD lacks authority over agricultural activities, no further consideration was given.

VOCs do contribute to visibility impairment, bu t as shown in the charts above, this contribution is from biogenic sources such as vegetative emissions. Controlling anthropogenic sources of VOC emissions has little, if any, visibility benefit at the Class I areas. Reducing primary carbon from point sources, ground level s ources or fires are projected to have small to no visibility benefi t. This is consistent with the monitoring data that shows that most of measured or ganic carbon is secondary in origin and primary carbon is only a small fraction of the total measured carbon (Appendix B). Reducing carbon from fires was not found to be effective because there was little fire activity at these sites on the days modeled in the sensitivity analyses.

Note that these results from the emission sensitivity runs are consistent with the conclusions drawn from the 2000-2004 base line monitoring data (see Section 2.4 above). The results indicate that sulfate is the dominant contributor to visibilityGeorgia Regional Haze State Implementation Plan

65 of 124 impairment on the 20 percent wors t days at all sites, and that ammonium nitrate may be important for sites where the 20 percent worst days occur in the winter. We conclude that reducing SO2 emissions from EGU and non-EGU point sources in the VISTAS states would have the greatest visibility benefits for the GA Class I areas. Contributions from the Midwest RPO and MANE-VU are great er at the Class I ar eas bordering these RPOs. Contributions from outside t he VISTAS 12-km modeling domain are more important for the coastal Class I areas. Th ese results are consistent with the CMAQ model results indicating that contributions from international emissions to visibility impairment at VISTAS Class I areas are gr eater closer to the boundaries of the modeling domain (see summary in Section 7. 3 and further discussion in Appendix I).

7.5 Relative Contributions to Visibility Impairment: Geographic Areas of Influence for Georgia Class I Areas

Once it was determined that SO2 emissi on reductions from EG U and non-EGU point sources in the VISTAS states would be the mo st effective sources to control to improve visibility at the Georgia Class I areas and non-Georgia Class I areas impacted by Georgia sources, the next step was to identify the specific geographic areas that most likely influence visibility in each Class I area, and then to identify the major SO2 point sources located in those geographic areas . An SO2 Area of Influence (AoI) was defined for each Class I area to represent the geographic area containing sources that would likely have the greatest impact on visib ility at that Class I ar ea. All SO2 point sources within these Areas of Influence were identified and ranked by their 2018 Base G4 emissions. The following sections contai n a broad overview of the steps in the Area of Influence analyses. See Appendix H for a more detailed discussion of these analyses and plots for additional Class I areas.

7.5.1 Back Trajectory Analyses The first step was to generate meteorological back trajectories for IMPROVE monitoring sites in Georgia and neighboring Class I areas for the 2000-2004 baseline period. Back trajectory analyses use interpolated measur ed or modeled meteorological fields to estimate the most likely central path of air ma sses that arrive at a receptor at a given time. The method essentially follows a par cel of air backward in hourly steps for a specified length of time. Figure 7.5.1-1 is an example of a back trajectory analysis for Cohutta Wilderness Area for the 20 percent worst days in 2002.Georgia Regional Haze State Implementation Plan

66 of 124 Figure 7.5.1-1. Example back traj ectories for 20 percent worst visibility days in 2002 for Cohutta Wilderness Area.

Trajectories were started at 100 meters and 500 meters above the surface and run backward from the site for 72-hours. These individual back trajecto ries for 20 percent worst days in 2002 were also useful in ev aluating model performance for individual days at the Class I areas.

7.5.2 Residence Time Plots The next step was to plot residence time fo r each Class I area using five years of back trajectories for the 20 percent worst visibility days in 2000-2004. Residence time is the frequency that winds pass over a specific ge ographic area on the path to a Class I area. Separate residence time plots were generated using trajectories with 100m and 500m start heights.Georgia Regional Haze State Implementation Plan

67 of 124 As illustrated in Figure 7.5.2-1, winds in fluencing Cohutta Wilderness Area on the 20 percent worst days come from all directi ons, and there is no single predominant wind direction influencing the 20 percent worst visibility days.

Figure 7.5.2-1. Example residenc e time plot for 20 percent worst visibility days in 2000-2004 for Cohutta Wilderness Area. Based on trajectories with 100m start height.

7.5.3 SO2 Areas of Influence The next step was to develop sulfate extincti on weighted residence time plots to define the geographic area with highest probability of influencing the receptor on the 20 percent worst days in 2000-2004 that were domi nated by sulfate. Ea ch back trajectory was weighted by sulfate extinction for that day. This allows us to focus on the 20 percent worst days that are influenced by sulfate and place less importance on days influenced by organic carbon from fires. Su lfate-weighted back trajectories for the 20 percent worst days were comb ined for five years of data. The resulting sulfate extinction-weighted residence time plots we re used to define the geographic Area of Influence for sources of SO2 emissions. In Figure 7.5.3 the area representing 10 percent or greater residence time is out lined in red and the ar ea representing five percent or greater residence time is outlined in orange. The VISTAS states focused their analyses on the Area of Influence defin ed by five percent or greater sulfate extinction-weighted residence time.Georgia Regional Haze State Implementation Plan

68 of 124 Figure 7.5.3-1. Example SO2 Area of Influence plot for sulfate extinction weighted residence time for 20 percent worst visibility days in 2000-2004 fo r Cohutta Wilderness Area, Georgia. Based on trajectories with 100m start height.

7.5.4 Emissions Sources within SO2 Areas of Influence Residence time plots were then comb ined with geographically-gridded emission data based on the 2002 baseline and 2018 BaseG emi ssions inventories. Plots were generated for the Areas of In fluence defined by trajectori es with 100m and 500m start heights. As a way of incorporating the effects of transport, deposition, and chemical transformation of point source emissions along the path of the trajectories, these data were weighted by 1/d, where “d” was calcul ated as the distance, in kilometers, between the center of the grid cell in which a source is located a nd the center of the grid cell in which the IMPROVE monitor is located. The distance-weighted point source SO2 emissions are then combined with the gri dded extinction-weighted back-trajectory residence times at a spatial resolution of 36-km.

The final step was to combine the residenc e times and gridded emissions data in plots and data sets. The distance weighted (1/d) gridded point source SO2 emissions were multiplied by the total extinc tion-weighted back-trajectory residence times on a grid cell by grid cell basis. These results were t hen normalized by the domain-wide total and displayed as a percentage. The analysi s was done using both the 2002 and 2018 base year inventories.Georgia Regional Haze State Implementation Plan

69 of 124 Figures 7.5.4-1 illustrates 2002 and 2018 dist ance weighted gridded emissions “x” sulfate extinction weighted residence time plots for Cohutta Wilderness Area. These maps help visualize where the emissions reductions will be occurring between 2002 and 2018. The change in SO2 emissions between 2002 and 2018 can be seen by comparing emissions source st rengths in the two plots. Note the emissions from each source are normalized by the total emissions in the domain. Sources that reduce SO2 emissions by 2018 will show a lower contribut ion to emissions in the domain. On the 2018 map the grid cells with thes e sources will show a lighter color gradient than on the 2002 map. For example: SO2 reductions fr om EGUs in north and central Georgia can be seen by comparing the 2002 and 2018 maps. Because the total emissions in the domain are smaller in 2018, a source that does not change emissions between 2002 and 2018 may actually appear to increase in importance in 2018 compared to 2002.

Figure 7.5.4-1. Cohutta Wilderness Area 2002 a nd 2018 SO2 distance weighted emissions x SO4 extinction-weighted residence time plots.

Figure 7.5.4-2 illustrates gr idded SO2 distance weighted emission’s sulfate “x” extinction weighted residence time plots for 2018 emissions for Okefenokee Wilderness Area. The plot illustrates t he relative importance of Geor gia sources of SO2 compared to sources in neighboring st ates. Additional analyses, including 2002 and 2018 distance weighted emissions “x” residence time plots for the Class I areas in Georgia
are contained in Appendix H.Georgia Regional Haze State Implementation Plan

70 of 124 Figure 7.5.4-2. 2018 SO2 distance weighted emis sions x SO4 extinction-weighted residence time plot for Okefenokee, Georgia

.Georgia Regional Haze State Implementation Plan

71 of 124 Finally, Table 7.5.4-1 shows, the relative co ntributions of point source SO2 emissions from nearby states to Georgia Class I areas.

Table 7.5.4-1. 2018 SO2 Point Source Co ntribution (Using RTMax*Q/d) to Georgia Class I Areas by State

Georgia Class I Area
State OKEF COHU WOLF
Alabama 1.29% 19.04% 0.85% Delaware 0.29%

Florida 74.99% 38.05% Georgia 16.95% 36.72% 41.88%
Indiana 0.42 Kentucky 1.75% Maryland New Jersey North Carolina 0.11% 5.16% 3.01%
Ohio Pennsylvania South Carolina 6.66% 4.05% 15.81%

Tennessee 31.88%

Virginia 0.62% 0.12% West Virginia 0.36%

Total 100.00% 100.00% 100.00%Georgia Regional Haze State Implementation Plan

72 of 124 7.5.5 Specific Source Types in the Areas of Influence for Georgia Class I Areas The next step in the analysis was to review the emissions inventories to determine the source categories, as well as specific sources, found to have the greatest impact on visibility in Georgia Class I areas. List s of SO2 point source s within the Areas of Influence for each Class I area were developed using the Base G VISTAS 2002 base year and 2018 future year emissions. Fo r this purpose the Area of Influence was defined as the counties with maximum sulf ate extinction weighted residence time greater than five. For SO2 sources withi n each Area of Influence, the following attributes were defined for each individual unit:

• State, county, and source (plant), and industry identification codes;

• SO2 emissions for 2002 and 2018;

• 2018 control efficiency;

• Distance to Class I areas (defined by centroid of the Class I area);

• Emissions divided by distance (Q/d), a metric that acco unts for the dispersion of emissions over distance; and

• Maximum sulfate extinction wei ghted residence time (RTmax).

Our review was conducted in a top-down fash ion starting with an analysis of the major source categories in each SO2 Area of In fluence to determine which major categories had the highest residual contribution to the area in 2018. It was also important to identify reductions that ar e projected to occur between 2002 and 2018 within each category or at specific units. This allowed VISTAS States to determine if certain source categories or units that had yet to be contro lled under the future year base case had the potential for reduction. Once the highest sour ce types were identified, subcategories within those source types were reviewed. The contributions from major source categories to the 2018 Base G4 inventory for the SO2 Areas of Influence for the Georgia Class I areas are listed in T ables 7.5.5-1 thro ugh 7.5.5-3.Georgia Regional Haze State Implementation Plan

73 of 124 Table 7.5.5-1. 2018 Emissions Contributions from Majo r Source Categories in the Area of Influence for Cohutta Wilderness Area.

Table 7.5.5-2. 2018 Emissions Contributions from Major Source Categories in the Area of Influence for Okefenokee Wilderness Area. Tier VOC NOX CO SO2 PM-10 PM-2.5 NH3

Fuel Comb. Elec. Util. 0% 21% 1% 52% 9% 17% 1%
Fuel Comb. Industrial 1% 19% 2% 28% 3% 5% 0%
Fuel Comb. Other 5% 6% 3% 6% 5% 10% 1%
Chemical & Allied Product Mfg 2% 1% 0% 2% 1% 1% 1% Metals Processing 1% 1% 1% 3% 2% 5% 0%
Petroleum & Related
Industries 0% 0% 0% 1% 0% 0% 0%
Other Industrial
Processes 7% 6% 1% 5% 9% 11% 1%
Solvent Utilization 42% 1% 0% 0% 0% 1% 0% Storage & Transport 6% 0% 0% 0% 1% 1% 0% Waste Disposal & Recycling 4% 2% 4% 0% 5% 12% 0% Highway Vehicles 18% 25% 48% 0% 2% 2% 12% Off-highway 11% 18% 34% 1% 2% 4% 0%
Miscellaneous 2% 1% 7% 0% 61% 30% 83%

V ISTAS Total 100 % 100 % 100 % 100 % 100 % 100 % 100 %

Tier VOC NOX CO SO2 PM-10 PM-2.5 NH3
Fuel Comb. Elec. Util. 0% 22% 1% 51% 7% 12% 1%
Fuel Comb. Industrial 1% 16% 2% 25% 3% 5% 0%
Fuel Comb. Other 3% 4% 1% 6% 2% 4% 0%
Chemical & Allied Product Mfg 1% 1% 0% 4% 0% 1% 0% Metals Processing 0% 0% 0% 4% 0% 0% 0%
Petroleum & Related
Industries 0% 0% 0% 0% 0% 0% 0%
Other Industrial
Processes 7% 6% 1% 7% 8% 11% 2%
Solvent Utilization 39% 0% 0% 0% 0% 0% 0% Storage & Transport 7% 0% 0% 0% 0% 0% 0% Waste Disposal & Recycling 4% 3% 7% 0% 8% 16% 0% Highway Vehicles 18% 25% 38% 1% 1% 1% 10% Off-highway 14% 19% 29% 1% 2% 3% 0%
Miscellaneous 6% 4% 20% 1% 68% 46% 86%

VISTAS Total 100% 100% 100% 100 % 100% 100% 100%Georgia Regional Haze State Implementation Plan

74 of 124 Table 7.5.5-3. 2018 Emissions Contributions from Majo r Source Categories in the Area of Influence for Wolf Island.

These tables indicate that for all Georgia Class I areas, EGUs and industrial boilers are the two major source categories contributi ng to 2018 SO2 emission s in the Areas of Influence, even after implementation of t he CAMR and CAIR. Together these two source categories contribute 79-85 percent of the 2018 SO2 em issions for the Areas of Influence for the Georgia Class I areas. Ot her fuel combustion and other industrial processes comprise another 9-12 per cent of the 2018 SO2 emissions.

These tables can also be used to evaluate t he major source categories contributing to emissions of NOx, NH3, and PM emissions in 2018. For instance, highway vehicles and off-road vehicles are major sources of NO x emissions, in addition to electric utilities and industrial boilers. The source category “m iscellaneous” (which includes agricultural sources and fires) is the major contributor to NH3 and primary PM. The emissions sensitivities discussed in Section 7.4 indica ted very small benefits of controlling NOx, NH3, and primary PM emissions at the Georgia Class I areas , but if these emissions were of concern, different source categories would need to be addressed.

The contributions to SO2 emissions in 2018 from the three highest source categories, electric utilities, industrial boilers, and ot her fuel combustion have been further broken out into subcategories. Table 7.5.5-4 indica tes subcategories for the Areas of Influence for the Georgia Class I areas. Within elec tric utilities, all t he SO2 emissions are attributable to coal-fired pow er plants. Within industria l boilers, most emissions are attributable to coal-fired boilers with le sser contributions from oil and gas boilers. Commercial and institutional coal and o il boilers have smaller contributions. Tier VOC NOX CO SO2 PM-10 PM-2.5 NH3
Fuel Comb. Elec. Util. 0% 21% 1% 47% 7% 14% 1%
Fuel Comb. Industrial 1% 16% 2% 31% 3% 5% 0%
Fuel Comb. Other 3% 5% 2% 6% 3% 6% 1%

Chemical & Allied Product Mfg 1% 2% 0% 4% 0% 1% 1% Metals Processing 0% 0% 0% 3% 0% 0% 0%
Petroleum & Related
Industries 0% 0% 0% 0% 0% 0% 0%
Other Industrial Processes 6% 5% 1% 5% 7% 8% 2%
Solvent Utilization 39% 0% 0% 0% 0% 0% 0% Storage & Transport 7% 0% 0% 0% 0% 1% 0% Waste Disposal & Recycling 4% 3% 7% 1% 7% 16% 0% Highway Vehicles 19% 25% 40% 1% 1% 1% 10% Off-highway 15% 21% 32% 1% 2% 5% 0%
Miscellaneous 5% 3% 15% 1% 67% 43% 85%

V ISTAS Total 100 % 100 % 100 % 100 % 100 % 100 % 100 %Georgia Regional Haze State Implementation Plan

75 of 124 Table 7.5.5-4. 2018 SO2 Emissions Cont ributions from Major Source Categories in the Area of Influence for GA Class I areas.

Tier W OLF OKEF COHU
Fuel Com b. Elec. Util.-Coal 45% 49% 52%
Fuel Com b. Elec. Util.-Oil 0% 0% 0%
Fuel Com b. Elec. Util.-Gas 0% 0% 0%
Fuel Com b. Elec. Util.-Other 2% 2% 0%
Fuel Com b. E lec . Util.-Internal
Combustion 1% 0% 0%
Fuel Com b. Industrial-Coal 18% 14% 20%
Fuel Com b. Industrial-Oil 9% 8% 5%
Fuel Com b. Industrial-Gas 2% 1% 2%
Fuel Com b. Industrial-Other 2% 3% 1%
Fuel Com b. Industrial-Internal
Combustion 0% 0% 0%
Fuel Com b. OtherCom m erc ial/Institutional Coal 2% 2% 2%
Fuel Com b. OtherCom m erc ial/Institutional Oil 3% 3% 4%
Fuel Com b. OtherCom m erc ial/Institutional Gas 0% 0% 0%
Fuel Com b. Other-Misc. Fuel Comb. (Except Residential) 0% 0% 0%
Fuel Com b. Other-Residential
W ood 0% 0% 0%
Fuel Com b. Other-Residential
Other 0% 0% 1%

These analyses indicate that GA EPD should consider what additional control measures for electric utilities and industrial boilers are reasonable. GA EPD also determined that it was appropriate to also consider additional control measures from industrial sources
other than boilers that contributed to the sa me magnitude of visibility impairment as boilers. The lists of individual sources ar e also being used to determine if individual
sources in other sources cat egories are major contributors.

The next step was to identify emission reduc tions that have al ready occurred within each source category and at spec ific units. Unit level tabl es of emission comparisons from 2002 to 2018 were developed, allowing VIST AS States to review existing emission reductions. These tables assigned future-y ear control technology from IPM forecasting and State modification for EGUs and from c ontrol efficiency tables for Non-EGU point

sources.

Once emission control profiles for specific units were defined, the next step was to determine what, if any, additional control meas ures would feasibly be available and to
evaluate these controls to determine which are reasonable.Georgia Regional Haze State Implementation Plan

76 of 124 For EGUs, the 2018 IPM file used by VIST AS for EGU sources was obtained and matched to the 2018 base-case in ventory of EGU sources for most states. However, IPM assumptions for future controls were not consistent with t he emission controls required for EGUS by Georgia’s Multipol lutant Rule. The Georgia EGU emission
controls are documented in the emission inventory document s found in Appendix C.

7.6 Reasonable Progress Determinati ons for Individual Sources

The following summarizes the process for determining reasonable progress for Georgia sources and the results of t he determinations. This process was based on U.S. EPA’s “Guidance for Setting Reasonable Progress G oals Under the Regional Haze Program,” June of 2007 [Reasonable Progress guidance]. For a detailed discussion of the reasonable progress assessments for all emissi ons units contributing greater than half a percent of sulfate impact to any Class I area in Georgia or in neighboring states, see Appendix H.

7.6.1 Process for Determi ning Reasonable Progress

Step 1: Determine pollutants of concern.

VISTAS evaluated the species contribution on the 20 percent worst visibility days and concluded that sulfate account ed for greater than 70 percent of the visibility impairing pollution. The VISTAS States conclude d that controlling SO2 emissions was the appropriate step in addressing the reasonable progress a ssessment for 2018. The VISTAS findings were consistent with the fi ndings of SAMI. As stated previously, SAMI confirmed that sulfate particles account fo r the greatest portion of the haze affecting Class I areas in the Southern Appalachian regi on and that these sulf ates were produced in large part from SO2 emissi ons from coal combustion.

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

Since SO2 point source emissions in 2018 ar e projected to repres ent greater than 95 percent of the total SO2 emissions inventor y, the VISTAS states concluded that the focus should be on electric generating unit (EGU) and non-EGU point sources of SO2
emissions.Georgia Regional Haze State Implementation Plan

77 of 124 Step 3: Consideration of Emissions R eductions from State and Federal Control
Measures.

64 FR 35733 states that “In determining t he emissions and visibility improvement achieved during each implement ation period, states shoul d include all air quality improvements that will be achieved by other programs and activities under the CAA and any state air pollution control requirements. ” In keeping with this recommendation, Georgia, as part of its long-term reasonab le progress analysis to consider potential sources contributing to visibility impairment, examined other CAA requirements such as CAIR. Under Georgia’s CAIR rule for SO2 [391-3-1-.02(13)], SO2 emissions from Georgia EGUs will be capped at 149,140 tons in 2015, a 70 % reduction from 2002 actual emissions. In addition, a 70 % reduc tion of SO2 emissions is expected during this time period across all CAIR-affected EGUs in 28 eastern states. Through these programs between the present and 2018, EPD concluded t hat additional EGU control during this time period is not reasonable for sources that significantly contribute to visibility impairment at Class I areas that clear ly projected to meet the uniform rate of progress (URP) in 2018. However, for source s that significantly contribute to visibility impairment at Class I areas not clearly m eeting the URP (such as Okefenokee and Wolf Island), EPD did consider additional controls at CAIR-affected units.

For EGUs subject to CAIR, EPA evaluated a number of factors, in cluding the cost of compliance and time necessary for compliance. In the CAIR rule, EPA determined “that
the earliest reasonable deadline for compliance with the final highly cost effective control levels for reducing emission s was 2015...” (70 FR 25197 – 25198, May 12, 2005). The State believes t hat the cost of compliance and time necessary for compliance are the dominant factors for det ermining if additional reductions would be reasonable from CAIR-subject EGUs. The det ailed analyses in the preamble to the May 12, 2005, CAIR rule support a conclusi on that CAIR controls satisfy reasonable progress for SO2 for the first regional haze planning period ending in 2018.

The SO2 emission reductions that are pr edicted by the IPM to meet the CAIR requirements are not certain due to the current rule’s reliance on unchecked trading and the use of banked Title IV allowances. T he GA EPD intends to re-evaluate the IPM predictions of SO2 reductions for CAIR for EGUs at the time of the first five-year periodic report [40 CFR 51.308(g) ] to ensure that the reducti ons currently predicted by IPM for CAIR are in fact taking pl ace where they are expected and needed . The Cohutta Class I Area is expected, based on modeling, to clear ly meet the glide slope in 2018. GA EPD has therefore c oncluded that CAIR constitutes reasonable measures for Georgia EGUs that significantly impact visibility in Cohutta during this first assessment period (between bas eline and 2018). Because the Okefenokee, Wolf Island, and Saint Marks areas are not expected to clearly meet the g lide slope, controls required under CAIR have not been deemed to constitute reasonable measures for Georgia EGUs that significantly im pact visibility in these Class I areas.

Georgia Power Company, in anticipation of CAIR requirements, has committed to implementing SO2 emission r eduction measures on 22 of its EGUs. All of the 22Georgia Regional Haze State Implementation Plan

78 of 124 affected units are located in the northern hal f of the state and thei r predicted emissions reductions have been accounted for in the modeli ng used to predict 2018 visibility levels in this SIP. These reduction measures and the associated emissions reductions are summarized in Table 7.6.1-1.

Table 7.6.1-1. Projected 2018 SO2 emi ssion reductions associated with planned reduction measures at Georgia Power EGUs.

Facility Unit Annual SO2 Emissions, 2002 (tons) Reduction Measure Annual SO2 Emissions,
2018 (tons) * Annual SO2 Reductions,
2002 to 2018 (tons)

Hammond 1 3933 scrubber 269 3664

2 4092 scrubber 270 3822

3 4262 scrubber 267 3995

4 18088 scrubber 1728 16360
Wansley 1 38741 scrubber 3018 35723

2 36421 scrubber 3022 33399

Bowen 1 33050 scrubber 2415 30635
2 35266 scrubber 2432 32834

3 42900 scrubber 3056 39844
4 42634 scrubber 3147 39487
McDonough 1 13802 convert to natural gas 578 13224 2 13631 convert to natural gas 596 13035

Scherer 1 25286 scrubber 1313 23973

2 24966 scrubber 1304 23662

3 18149 scrubber 1387 16762

4 20771 scrubber 1331 19440

Branch 1 10837 scrubber 618 10219

2 13941 scrubber 748 13193

3 21211 scrubber 1158 20053

4 22342 scrubber 1133 21209
Yates 1 233 Existing scrubber (no additional reduction) 332 -99

2 3991 none 3547 444

3 3237 none 3916 -679

4 4842 none 6500 -1658

5 5009 none 6643 -1634

6 15175 scrubber 818 14357

7 14024 scrubber 826 13198

TOTAL (tons) 490385 52373 438012

* Emissions reflect VISTAS plan t utilization growth projections.Georgia Regional Haze State Implementation Plan

79 of 124 Step 4: Determine which emission units would be evaluated based on impact.

The GA EPD calculated the projected 2018 fr actional contribution from all emission units within the SO2 Area of Influence for a given Class I area, including contributions from EGUs after planned SO2 controls. EPD then identified those emission units with a contribution of half a perc ent or more to the sulfate visibi lity impairment at the specific Class I area. See section 5.0 of Appendix H for t he rationale for the selection of the one-half percent threshold for this analysis. As noted in Step 3, SO2 controls on EGUs that impact visibility at Cohutta, as r equired by CAIR, are deemed to be reasonable measures. Therefore, these units were ex empted from four-facto r evaluation even if their sulfate visibility impairments were half a percent or more.

Step 5: Evaluate the four factors.

Each emission unit identified in Step 4 above was evaluated using the following four statutory and regulator y factors of 1) cost of comp liance, 2) time necessary for compliance, 3) the energy and non-air quality environmental impacts of compliance, and 4) the remaining useful lif e of the emissions unit.

7.6.2 Sources Eligible for Four Factor Analysis in Georgia As part of the Regional Haze reasonable progress goal analysis, GA EPD initially identified 29 emission units for analysis of addi tional controls for meeting the reasonable progress requirements of the Regional Haze program in a ccordance with the above four statutory factors. The 29 units were selected based on analyses that indicated that each one’s contribution to total su lfate visibility impairment was at least 0.5% of the total sulfate visibility impairment at one or mo re Class I areas. The analysis for eligibility assumed that the units’ 2018 sulfate emissions were their VISTAS-projected emissions. The eligible units are listed below in Table 7.6.2-1. Details of the eligible unit selection process are presented in Se ction 5.0 of Appendix H.Georgia Regional Haze State Implementation Plan

80 of 124 Table 7.6.2-1. List of all facilities along with their uni ts eligible for 4-factor analysis

Four Factor Analysis – Eligible Sources Eligible Units Georgia Pacific Brunswick Cellulose Power Boiler No. 4 Georgia Pacific Brunswick Cellulose Recovery Boiler (M24) Georgia Pacific Cedar Springs Power Boiler U500 Georgia Pacific Cedar Springs Power Boiler U501 Georgia Pacific Cedar Springs Recovery Boiler R402 Georgia Pacific, Savannah River Mill Boiler B001 Georgia Pacific, Savannah River Mill Boiler B002 Georgia Pacific, Savannah River Mill Boiler B003 Georgia Power Plant Kraft Steam Generator 1 Georgia Power Plant Kraft Steam Generator 2 Georgia Power Plant Kraft Steam Generator 3 Georgia Power Plant Mitchell Steam Generator 3 Georgia Power Plant McIntosh Steam Generator 1 International Paper, Savannah Mill Power Boiler 13 Interstate Paper Power Boiler F1

Miller Brewing Boiler B001 Miller Brewing Boiler B002
Mount Vernon Mills Boiler E U 03
Mount Vernon Mills Boiler E U 04 Packaging Corporation of America C E Boiler Rayonier Performance Fibers, Jessup Mill Power Boiler 2 Rayonier Performance Fibers, Jessup Mill Power Boiler 3 Rayonier Performance Fibers, Jessup Mill Recovery Furnace 1 Rayonier Performance Fibers, Jessup Mill Recovery Furnace 4 Savannah Sugar Refinery Boiler U161 Southern States Phosphate and Fertilizer Sulfuric Acid Plant 2 Temple Inland Rome Linerboard Power Boiler No. 4
Mohawk Industries Boiler BL06
Mohawk Industries Boiler BL07

GA EPD requested four-factor analyses from t hese facilities. In response to this request, additional information regarding projec ted 2018 actual emissions was received from a number of sources. As a result of this revised information, seven units were removed from consideration for addition al controls based on an analysis that the emission units would not contribut e half a percent or greater of the total sulfate visibility impairment at any Class I area in 2018. Thos e seven units are listed below in Table 7.6.2-2.Georgia Regional Haze State Implementation Plan

81 of 124 Table 7.6.2-2. Units Removed from 4-F actor List Based on Facilities’ Updated 2018 Emission Estimates

Sources Units Miller Brewing Boiler B001 Miller Brewing Boiler B002
Mount Vernon Mills Boiler E U 03
Mount Vernon Mills Boiler E U 04 Savannah Sugar Refinery Boiler U161
Mohawk Industries Boiler BL06
Mohawk Industries Boiler BL07

In addition, three facilities requested and hav e received emission limits to reduce the sulfate visibility impairment from each emissions unit to le ss than 0.5%. Those facilities and the affected emission units are listed below in Table 7.6.2-3.

Table 7.6.2-3. Facilities Tha t Requested Emission Limits

Sources Units Rayonier Performance Fibers, Jessup Mill Power Boiler 2 Rayonier Performance Fibers, Jessup Mill Power Boiler 3 Rayonier Performance Fibers, Jessup Mill Recovery Furnace 1 Rayonier Performance Fibers, Jessup Mill Recovery Furnace 4 Southern States Phosphate and Fertilizer Sulfuric Acid Plant 2 Packaging Corporation of America C E Boiler

Furthermore, one of the emissions units is subj ect to Best Available Retrofit Technology (BART) Review under the Regional Haze Ru le. In accordance with EPA’s June 1, 2007 ”Guidance For Setting Reasonable Progress Goals under the Regional Haze Program” (pages 4-2 and 4-3), for emissions units subj ect to BART, the St ate will already have completed a BART analysis. Since t he BART analysis is based, in part, on an assessment of many of the same factors that must be addressed in establishing reasonable progress goals, it is reasonable to conclude that any control requirements imposed in the BART determination also sa tisfy the RPG-related requirements for source review in the first RPG planning period. (This exclusion does not include units at facilities that are exempt from BART review through screening modeling.) That
emissions unit is Interstate Paper – Power Boiler F1.

Therefore, 4-factor revi ews were conducted on the remaining 15 emission units.

7.6.3 Regional Haze Reasonable Progress Four-Factor Analysis The regional haze rule requires that st ates consider the following factors and demonstrate how these factors were taken into consideration in selecting the reasonable progress goal:

• Costs of compliance;

• Time necessary for compliance;Georgia Regional Haze State Implementation Plan

82 of 124 • Energy and non-air quality environment al impacts of compliance; and

• Remaining useful life of any potentially-affected sources.

The general considerations taken into account in Georgia EPD’s 4-factor evaluations and the evaluations of the specific emissions units are presented below.

Costs of Compliance – General Considerations

GA EPD evaluated the cost of compliance using a variety of factors. Facilities provided data for various control options for each affe cted unit. The data typically included total capital costs and cost-per-ton of pollutant re moved ($/ton). GA EPD compared this data with similarly controlled units as well as AirControlNET estimates. Costs were presented in 2007 dollars for consistency. In addition, GA EPD conducted CMAQ modeling to determine the amount of visibility improvement re sulting from each ton of SO2 reduced from each unit subject to anal ysis. This cost-efficiency metric is expressed in dollar-per-inverse megameter ($/Mm -1 ) and was considered in addition to cost efficiency expressed in $/ton. This approach is similar to the approach used by Georgia EPD to evaluate cost efficien cy for other SIPS (e.g., ozone, PM2.5).

Time Necessary For Complianc e – General Considerations

GA EPD based the time necessary for comp liance on the installa tion and operation of controls by the beginning of the year 2012. Since the next Regional Haze SIP will be due December 17, 2017, a compliance date of 2012 will result in visibility improvement for all five years of monitoring data (2012, 2013, 2014, 2015, and 2016) that will be assessed to determine conformity with 2018 progress goals at t he time the next Regional Haze SIP is due. Any control optio ns that can be installed and operated prior to 2012 were determined to be timely. C ontrol options that cannot be installed and operated prior to 2012, but can be prior to 2018, would not result in the optimal amount of visibility improvement by the 2018 reasonable progress goal, but were still considered. Control options that could not be installed and operated until 2018 or after, were not considered for this Regional Haze SIP.

Energy And Non-Air Quality Environment al Impacts Of Compliance – General Considerations

Additional factors that were considered were the energy requirements of the control technology and the non-air impacts (that is, impacts on other environmental media). Energy impacts were generally included in the cost-efficiency estimates. Non-air impacts that were considered included so lid waste disposal, water withdrawal, and wastewater discharge. The review of cont rol strategies that were not eliminated because of excessive cost efficiencies and that involved water withdrawal and wastewater discharge were coordinated wit h GA EPD’s Watershed Protection Branch.Georgia Regional Haze State Implementation Plan

83 of 124 Remaining Useful Life – General Considerations

The remaining useful life of an affect ed emissions unit can potentially impact reasonableness of control strategies in two ways. If the remaini ng useful life of an affected emission unit did not extend past 2018, no controls would be considered for that unit. If the remaining us eful life of a unit was less than the amortization period for a particular control option, the shorter period was used in annualizing the capital costs of the control option when determining the cost efficiency. It should be noted that remaining useful life was not an issue for any of the control options reviewed by GA
EPD.

Results of Unit-Specific Analyses

As stated previously, GA EPD performed 4-fa ctor analyses for 15 emissions units. The
results are summarized below. For mo re details refer to Appendix H.

Georgia Pacific, Brunswick Ce llulose - Power Boiler U700 (F1) – This unit significantly contributes to the sulfate visibility impairment at two Class I areas (approximately 12.6% at Wolf Island and 3.9% at Okefenok ee). This is the highest level of visibility impairment cont ribution to any Class I Area caused by any single emissions unit of those analyzed. The baseline SO2 emissions were 1642 tons-per-year. However, the boiler had already reduced em issions to approximately 1099 tons-peryear due to a 2002 modification achieving higher efficiency.

The 4-factor analysis reviewed wet FGD, in-duc t sorbent injection, and a limitation on fuel oil usage coupled with lower fuel oil su lfur content (2.2% and 1.0%). It should be noted that the fuel oil usage limitation proposed by the com pany is representative of their current usage rate. Of these control measures, the fuel oil changes could take place prior to 2012 and the wet FGD and in-duc t sorbent injection could be installed before 2013. The remaining useful life of the unit extended past 2018 and the control equipment amortization period. The wet FGD had an impact on water usage and wastewater discharge and in-duct sorbent inje ction resulted in additional solid waste. There were no significant energy impacts addressed by the company.

Out of all of the control options considered, both in-duct sorbent injection and a switch to 1.0% fuel oil coupled with a five-millio n-gallon-per-year usage limit were considered reasonably cost effective ($3562/ton and $20.7MM/Mm -1 at Wolf Island for in-duct sorbent injection and $3228/ton and $18.8MM/Mm -1 at Wolf Island for 1.0% fuel oil). These were considered cost effective due to the relatively high visibility impact on two Class I areas and the fact that neither of these Class I areas were clearly meeting the uniform rate of progress. Both in-duct sorben t injection and 1.0% sulfur fuel oil achieve approximately the same amount of emissions reductions (769 tpy for sorbent injection and 731 tpy for 1.0% sulfur) from the current level of 1099 tons/year. Implementation of the less restrictive of thes e two options would reduce SO 2 emissions to 368 tons/12- consecutive months (1099 tpy – 731 tpy).Georgia Regional Haze State Implementation Plan

84 of 124 Supplemental information provided by the fac ility indicated that the two controls deemed to be reasonable would control emissions from oil combustion but would not affect SO2 emissions from combustion of wood waste and tire-derived fuel (TDF). The facility requested an allowance for an additional 200 t ons of emissions based on calculations of historical emissions from wood waste and TDF. This request was also supported by the facility’s assertion that the sulfur content of locally av ailable TDF may be above what has been burned historically. EPD concurred with the facility’s request and established an SO2 emissions limit for the power boiler of 568 tons (368 plus 200) for Regional Haze reasonable progress with a compliance date of 2012.

Georgia Pacific, Brunswick Ce llulose - Recovery Boiler R407 (M24) - This unit contributes about 1.3 % to the sulfate visibility impairment at Wolf Island. The baseline SO2 emissions were 193 tons/year. Georgi a Pacific’s four-factor submittal found combustion control and wet FG D (scrubber) to be the only tec hnically feasible control options. The company stated t hat emissions of SO2 of 38 ppm, as measured in a 2006 stack test, is too low of a load for effectiv e operation of a wet scrubber. Therefore, the company ruled out wet FGD based on cost effectiveness.

Combustion control, the other technically f easible control option, is already included in the boiler design. Due to the fa ct that this emission unit on ly contributes to visibility impairment at one Class I area and the relati vely low baseline emissions level, no additional controls are required for R egional Haze reasonable progress.

Georgia Pacific, Cedar Springs, Power Boiler U500 (Power Boiler 1) and Power Boiler U501 (Power Boiler 2) – These are two nearly identic al power boilers. Each of these units contribute about 1. 1% to the sulfate visibilit y impairment at Saint Marks Class I area. The baseline SO2 emissions were 1976 tons/year for each boiler.

The 4-factor analyses reviewed wet FGD, addi tion of spray towers and caustic to the existing venturi scrubbers, adding causti c to the existing scrubbers (79% SO2 reduction), in-duct sorbent injection, coal wa shing, and coal switching. In addition to these control measures, Georgia Pacific subm itted two control scenarios as part of their BART exemption modeling reques t (see section 7.7) that included the addition of lower amounts of caustic to their existing scrubbers (approximately 68% and 37% SO2 reduction). All of the control options could be installed pr ior to 2012 except the wet FGD which could be installed before 2013. All th ree of the scrubber options (wet FGD, adding spray towers to the existing scr ubbers, and adding caustic to the existing venturis) result in 15,000 tons/year of solid waste. There were no significant energy impacts addressed by the company. The re maining useful life of the unit extended past 2018 and the control equipment amortization period.

Out of all the control options considered, adding caustic to the existing venturi scrubber and in-duct sorbent injection were consider ed reasonably cost effective ($1675/ton andGeorgia Regional Haze State Implementation Plan

85 of 124 $849.2MM/Mm -1 at Saint Marks for adding causti c to the scrubber and $1663/ton and $843. 2MM/Mm -1 at Saint Marks for in-duct sorbent injection). These were considered cost effective due to the relatively lo w visibility impact on only one Class I area (although St. Marks is not clear ly meeting the uniform rate of progress.) Since the company submitted control optio ns for three different levels of caustic use (79%, 68%, and 37% SO2 reduction), GA EPD analyzed the information to determine which level of caustic use was considered reasonable (i n-duct sorbent injection achieves approximately 70% reduction, which is within t he range of control efficiencies for caustic scrubbing). As part of Georgi a Pacific’s BART exemption modeling, the company has proposed SO2 emission limits of 135 pounds each per hour from Power Boilers 1 and 2, along with additional limits of Recovery Boile r 3 (see section 7.7.2 for further discussion on these BART exemption limits). A limit of 135 lb/hr would result in maximum annual emissions of 591 tons/yr of SO2. This resu lts in a 70% reduction. The actual annual reduction should be even higher since the boiler would not be expected to emit SO2 at the maximum allowable level for an entire year . Therefore, the 70+ % reduction required by the BART exemption limit satisfies the requirement fo r reasonable progress. No additional limitations will be required.

Georgia Pacific, Cedar Springs, Recovery Boiler R402 (Recovery Boiler 3) - This unit contributes about 0.8 % to the sulfate vi sibility impairment at Saint Marks class I area. The baseline SO2 emissions were 1726 tons/year. (Although, Georgia-Pacific submitted 2006 and 2007 SO2 emissions signifi cantly lower than this baseline at 462 and 741 tons/year, respectively.

The 4-factor analyses reviewed switching from No. 6 fuel oil to No. 2 fuel oil (0.5 % sulfur), switching to 1% sulfur No. 6 fuel oil, and the installation of a new concentrator and new multi-level air system. The company did not provide any indications that any of the control options could not be installed pr ior to 2012. No negativ e energy impacts or non-air quality environmental impacts were addressed by the company. Remaining useful life of the units extended past 2018 and the cont rol equipment amortization periods.

Of all of the control options considered, none were consi dered reasonable, given the relatively low visibility impact on a single Cl ass I area. Therefore no additional controls will be required for Regional Haze Reasonable Progress.

Georgia Pacific, Savannah Rive r, Mill Boilers B001, B002, and B003 (Nos. 3, 4, and 5 Boilers) – These are three relatively simila r boilers, with B002 and B003 being almost identical. The units significantly impac t one class I area (approximately 1.1%, 0.9%, and 0.8% at Wolf Island for B001, B002, and B003, respectively). The baseline SO2 emissions for the three boilers are 1659 tons /yr, 1195 tons/yr, and 1190 tons/yr. Note that all three of these are re-circulating fluidized bed boile rs with limestone injection in the combustion chamber. B001 currently achieves approximat ely 87% SO2 removal and Boilers B002 and B003 achieve approximately 90% SO2 removal.Georgia Regional Haze State Implementation Plan

86 of 124 The 4-factor analyses reviewed wet FGD, ci rculating fluidized bed scrubber, switching from petroleum coke to 100% coal, increas ed limestone injection, and rotating opposed fire air. Out of all the proposed changes, only increased limestone injection could occur prior to 2012. All other control measur es could not be installed until after 2012, although estimated control dates were not prov ided. Wet FGD controls would result in increased water use and wastewater discharges . No significant energy impacts were addressed by the company. Remaining usef ul life of the units extended past 2018 and the control equipment amortiza tion periods. Increased limest one injection would result in increased solid waste generation. Geor gia-Pacific conducted tr ial operations with increased limestone injection rates and found t hat SO2 removal could only be increased by an additional two percent (from 87% to 89% for B001 and from 90% to 92% for B002 & B003). Revised cost estimates were also derived from t he trial operations.

Of all of the control options considered, none were consid ered reasonable, given the resulting control efficiencies and the relative ly low visibility impact on a single Class I area. Therefore no additional controls will be required for Regional Haze Reasonable Progress.

Georgia Power, Plant Kraft, St eam Generators 1, 2, and 3 – These are three coalfired steam generating units (i .e., boilers) rated at 50, 54, and 104 MW, respectively. Units 1 and 2 each impact Wolf Island Class I area by approximately 0.5%. Unit 3 was initially determined to impact three Class I ar eas (approximately 3.3% at Wolf Island, 0.9% at Okefenokee, and 0.8% at Cape Romain). Ho wever, with the projected reduction in SO2 emissions by 2018, t he impact on Okefenokee and Cape Romain should drop below the 0.5% threshold and th e impact at Wolf Island should drop below 2%. The 2018 baseline SO2 emissions for units 1 through 3 were initially estimated by VISTAS at 691 tpy, 704 tpy, and 4474 tpy, re spectively. As part of the supporting documentation for the 4-factor analyses, Georgia Power pr ovided projected heat input through 2018 for these units. Those projections indicate that SO2 emissions will be 632 tpy, 889 tpy, and 2455 tpy, respectively. Wh ile the heat inputs provided by Georgia Power for units 1 and 2 are similar to t he VISTAS 2018 projections, Georgia Power’s projection for Unit 3 represent s a 45 percent reduction in heat input and SO2. This was explained by Georgia Power as the resu lt of additional capacity coming on line somewhere else between 2010 and 2017. The reduc tion in heat input for Plant Kraft is expected to occur by around 2015. GA EPD has utilized these revised heat inputs in conducting the 4-factor analyses.

GA EPD can verify the heat input reducti on during development of the next Regional Haze SIP (due in 2017).

The same control measures were analyzed for the four statutory fa ctors for all three units: wet FGD, coal switching, and coal wa shing. Wet FGD could not be installed until 2016 because of required control device in stallations scheduled up until 2015 in Georgia Power’s system. The company did not address the im plementation time for theGeorgia Regional Haze State Implementation Plan

87 of 124 other control options. All three control optio ns would require additional energy usage. Wet FGD and coal washing would result in increased water usage and wastewater discharges as well as additional solid waste gener ation. The remaining useful life of the units extended past 2018 and the control equipment amortization periods. The costs of wet FGD and coal switching were relati vely high ($3216 to $8161/ton and $56.9MM to $144.5MM/Mm -1 for wet FGD and $4041to $4306/ton and $71.5MM/Mm -1 for coal switching). Coal washing was relatively cost effective ($1839 to $1847/ton and $32.5 to $32.7/Mm -1 ) but the control efficiency is only 6%. Regarding non-air environmental impacts, the company indicated that coal switching could possibly reduce boiler efficiency, would use up to 7500 gallons (at Unit 3) per day of water, would result in acidic wastewater requiring treat ment, and would result in coal refuse in the amount of approximately 5% of the total coal consumption. This control efficiency is projected to achieve low extinction reductions (which are visibility improvements) at Wolf Island. Based on the relatively low control effici ency of this option, the negative non-air environmental impacts, and the relatively low visibility impact, coal washing was determined not to be reasonable. Based on the above considerations, no additional controls will be required for any of the Plant Kraft units.

Georgia Power, Plant McIn tosh, Steam Generator 1 – This coal-fired steamgenerating unit (i.e., boiler) is rated at 178 MW . This unit was initially determined to impact five Class I areas (appr oximately 4.1% at Wolf Is land, approximately 1.2% at Okefenokee, approximately 0.6% at Saint Mar ks, approximately 1. 5% at Cape Romain, and approximately 0.7% at Swanquarter). Ho wever, with the proj ected reduction in SO2 emissions by 2018, the impact on all of these except Wolf Island should drop below the 0.5% threshold and the impact at Wo lf Island should drop to close to 1%. The 2018 baseline SO2 emissions were initially estimated by VISTAS at 7015 tpy. As part of the supporting documentat ion for the 4-factor analyse s, Georgia Power provided projected heat input through 2018 for this unit. Those proj ections indicate that SO2 emissions will drop to 1860 tpy by 2018. G eorgia Power’s projection represents a 73 percent reduction in heat input and SO2. This was explained by Georgia Power as a result of additional capacity coming on li ne somewhere else between 2010 and 2017. The reduction in heat input for Plant Mc Intosh is to occur between around 2011 and 2016. GA EPD has utilized this revised SO2 emission rate in conducting the 4-factor analyses. GA EPD can verify the heat i nput reduction during development of the next Regional Haze SIP (due in 2017).

Georgia Power analyzed the following control m easures: wet FGD, coal switching, and coal washing. Wet FGD could not be in stalled until 2016 because required control device installations scheduled up until 2015 in Georgia Power’s system. The company did not address the implementati on time for the other control options. All three control options would require additio nal energy usage. Wet FGD and coal washing would result in increased water usage and wastewater discharges as well as additional solid waste generation. The remaining useful life of the units ex tended past 2018 and the control equipment amortization periods. T he cost effectiveness of all the control operations were relatively high ($7131/ton and $118.5MM/Mm -1 for wet FGD, $4306/tonGeorgia Regional Haze State Implementation Plan

88 of 124 and $71.5MM/Mm -1 for coal switching, and $5334/ton and $91.9MM/Mm -1 for coal washing). Based on these factors, no additional controls wil l be required Plant McIntosh.

Georgia Power, Plant Mitchell, Steam Generator 3 – This coal-fired steam-generating unit (i.e., boiler) is rated at 163 MW. (Note t hat this is the only remaining operational boiler at Plant Mitchell.) This unit was in itially determined to impact two Class I areas (approximately 0.8% at Ok efenokee and approximately 2.7% at Saint Marks). However, with the project ed reduction in SO2 emissions by 2018, the impact on Okefenokee should drop below the 0.5% threshold and the impact on Saint Marks should drop to below 1%. The 2018 baseline SO2 emissions were initially estimated by VISTAS at 4930 tpy. As part of the supporti ng documentation for the 4-factor analyses, Georgia Power provided proj ected heat input through 2 018 for this unit. Those projections indicate that SO2 emissions wi ll drop to 1189 tpy by 2018. Georgia Power’s projection represents a 76 perc ent reduction in heat input and SO2. This was explained by Georgia Power as a result of additio nal capacity coming online somewhere else starting in 2010. The reduction in heat inpu t for Plant Mitchell is to occur between around 2008 and 2010. GA EPD has utilized this revised SO2 emission rate in conducting the 4-factor analyses. GA EPD ca n verify the heat input reduction during the Regional Haze mid-cour se review in 2012.

Georgia Power analyzed the following control measures: wet FGD and coal switching. Wet FGD could not be installed until 2016 bec ause required control device installations scheduled up until 2015 in Georgia Power’s syst em. The company did not address the implementation time for coal switching. Bo th control options would require additional energy usage. Georgia Power did not indi cate any additional water use, wastewater discharge, or solid waste generation issues for any of the control options. The remaining useful life of the units ex tended past 2018 and the control equipment amortization periods. The cost effectiv eness for wet FGD was high ($9119/ton and $148.5MM/Mm -1 ). The cost effectiveness for coal switching was more reasonable ($2347/ton and $38.2MM/Mm -1 ), but the control efficiency wa s relatively low at 43%. Based on these factors, including the project ed significant utilizatio n drop within the next few years, no additional controls will be required for Plant Mitchell.

International Paper, S avannah, Power Boiler 13 – This is a 1280 MMBtu/hr coal, oil, and woodwaste fired boiler. It also com busts both low-volume high-concentration (LVHC) and high-volume low-concentrati on (HVLC) non-condensable gases from the pulping process and stripper off-gas (SOG) from the stripper used to control HAP emissions from wastewater streams. Baseline emissi ons are 8578 tons/year with approximately 1944 tons/yr of this coming from the combustion of LVHC, HVLC, and SOG. This unit significantly c ontributes to the sulfate visibi lity impairment at five Class I areas (approximately 6.4% at Wolf Island, approximat ely 1.7% at Okefenokee, approximately 0.7% at Saint Marks, appr oximately 1.6% at Cape Romain, and approximately 0.9% at Swanqu arter). This is the highest number of Class I areas significantly impacted by any single emissions unit of all those reviewed.Georgia Regional Haze State Implementation Plan

89 of 124 The 4-factor analysis reviewed wet FGD (pa cked tower), FGD (wet limestone spray tower), semi-dry lime spray towe r, fuel switching to natural gas, dry sorbent injections, and a stand-alone RTO with SO2 scrubbing for the control of LVHC, HVLC, and SOG (this control option was pres ented as three different comb inations of LVHC, HVLC, and SOG combustion). Also, Inte rnational Paper (IP) later suggested an SO2 reduction of 2000 tons/year as a control option that would provide maximum flexibility for compliance. Except for the 2000 ton/year r eduction alternative, all of these control options could be implemented by 2012. International Paper requested a 2016 compliance date for the 2000 ton/yr reduction al ternative. This compliance date is necessary in order for the company to take into consideration any reductions that will occur as a result of the Boiler MACT and th e uncertainty surrounding that standard. The remaining useful life of the unit extended past 2018 and the control equipment amortization period. The wet FGD and a ll three RTO options had an impact on water usage and wastewater discharge. GA EPD Air Branch checked with GA EPD Watershed Protection Branch (WPB) personnel to discuss the potential water usage and wastewater discharges associated with thes e controls. WPB associates indicated that they would not be a pr oblem as long as there was not additional BOD load on the Savannah River. Based on the type of chemic als that would be a ssociated with effluent from a wet FGD, WPB associates stated that the controls shoul d not result in additional BOD load. However, because of the current problem with dissolved oxygen in the Savannah River (there are stri ct limitations and perhaps a moratorium on any additional DO load to the river), any projects that could possibly increase DP load were not considered reasonable at this time. FGD (wet limestone spray tower, semi-dry lime spray tower, and dry sorbent injection) resu lted in additional solid waste generation. There were energy impacts associated with a ll but the fuel switching options. These energy costs were factored into the ov erall control cost efficiency.

Regarding the company’s cost efficiency estimate s, EPD’s review indicated that the cost estimates for a packed tower wet FGD and we t limestone spray tower were higher than expected based on a number of metrics (cost per ACFM is about four times higher than other units of comparable size, company’s es timate is three to eight times higher than EPA cost estimation software, and Internati onal Paper used an admittedly conservative retrofit factor) plus the company used a cost estimation model not recommended by EPA. In a letter to IP on 12/21/2007, GA EPD requested site-specific cost analyses for these control options. In that letter, GA EPD stated that if site-specific estimates were not provided, that control option recommendations would be made with the understanding that the cost estimates may be overstated. In response, International Paper chose not to provide site-specific cost estimates as requested. However, despite the possibly high cost effectiveness number s the FGD - wet limestone spray tower ($4391/ton) was determined not to be cost effe ctive. Wet FGD – packed tower, was not considered reasonable because of the possi ble impact on DO load to the Savannah River. Fuel switching to natural gas ($9506 /ton), and dry sorbent injection ($5223/ton)
were determined not to be reasonable bec ause of cost effective.Georgia Regional Haze State Implementation Plan

90 of 124 The next most effective control option is a 6758 tons per year emission limit. However, since the option was proposed by the company, it had to be considered cost-effective. No specific emission reduction methodologies we re associated with this control option, however, there are certain control methodol ogies that are under consideration (see Appendix H for details). The 6758 ton per year limit was determined by reducing the projected 2018 SO2 emissions baseline of 8758 tons per year by 2000 tons. EPD reviewed recent SO2 emissions data and determined that the 8758 tons per year baseline is a reasonable and not over-inflated baseline. A compliance date of 2016 was proposed in order to take into consideratio n any controls that will be required under the Boiler MACT currently under development. The Boiler MACT has been vacated and remanded to EPA, and EPA is developing a proposed boiler MACT rule. A 2016 compliance date should provide sufficient time for the MACT to be proposed and promulgated, provide the three years requir ed for compliance with the standard, and provide time to determine an appropriate method for complying with the 6758 SO2 emissions limit from Power Boiler 13 followi ng compliance with the MACT standard.

Out of all of the control options consider ed, a 2000 tons per year reduction alternative was considered reasonably cost effe ctive. This results in an emission limit of 6758 tons per year. The baseline SO2 emissions ar e 8578 tons/yr. A review of past CERR reports SO2 emissions from PB13 at 7620 to 7699 tpy from 2002-2005 and increasing to 8974 tpy in 2006. The increase in 2006 may be due to the compliance date for phase II of the “Cluster Rule” MA CT standard that required collection and treatment of emissions from pulp mill condensate beginni ng in 2006. This would have resulted in increased sulfur emission from SOG which we re then combusted in PB13 to form SO2. Therefore, the 8578 ton/ year estimate is a good basel ine for determining allowable
emissions based on a selected control technol ogy. A 2000 tons per year reduction results in an emission limit of 6578 tons/year . This limit will include SO2 emissions resulting from the combustion of LVHC, HV LC, and SOG, whether they are combusted in Power Boiler 13 or some other combustion dev ice. In order to provide flexibility for the facility, an emission lim it of 6578 tons/12-consecutiv e months will be required for Power Boiler 13 as a requirement of Regional Haze reasonable progress with a compliance date of 2016.

Temple-Inland Rome Linerboard, No. 4 Power Boiler - This is a 565 MMBtu/hr coal and oil fired boiler. This unit significantly c ontributes to the sulfat e visibility impairment at two Class I areas (approxim ately 4.4% at Cohutta and appr oximately 1.0% at Joyce Kilmer/Slickrock).Georgia Regional Haze State Implementation Plan

91 of 124 The 4-factor analysis reviewed two wet FG D configurations [m agnesium enhanced lime (MEL) and limestone forced oxidation (LSF O)], dry FGD (lim e absorbent), fuel switching, and dry sorbent injection. All of these control options could be implemented by 2012. The remaining useful life of the unit extended past 2018 and the control equipment amortization period. The wet FGD options had an impact on water usage. GA EPD Air Branch checked with GA EPD Watershed Protection Branch personnel to discuss the potential water usage and was inform ed that the mill had sufficient capacity within their currently permitted water withdr awal permit to easily handle the increased water use associated with wet FGD. All of t he control options result ed in additional solid waste generation. There were energy impacts associated with all of the control options. These energy costs were factored into the ov erall control cost efficiency. None of the control options considered had a cost effe ctiveness that was determined reasonable at this time. Of all of the control options considered, none were considered reasonable at this time. The fact that t he affected Class I areas impacted by this unit are predicted to meet the Uniform Rate of Progress in 2018 wit h controls that are already on the books was a key factor in determining what was considered “reasonable” for reasonable progress requirements for this source. This determination may be re visited at the midcourse review or when determining future Regional Haze reasonable progress goals (i.e., future Regi onal Haze SIPs).

7.6.4 Required Controls for Sources Subject to Four-Factor Analysis in Georgia

Table 7.6.4-1 provides a summary of t he required emission limits for the sources subject to 4-factor analysis in Georgia. The final determinations were based on the 4- factor analyses and reviews and are detailed in Appendix H. GA EPD decided on limits that would be consistent with controls that were reasonably cost effective. Reasonable costs were based on the number of Class I ar eas impacted, the m agnitude of visibility impact on Class I area, progress of the impacted Class I area rela tive to the glide slope, and cost effectiveness. Once the control or controls were dete rmined to be reasonable, an emission limit was applied based on the expected emission reduction from the control technology or technologies to allow the facility flexibility in meeting the limit. The control technology was not required. Th is approach was determined to be an effective means of obtaining reasonable emission reductions.

Note that this table presents four-factor dat a only for controls that were deemed to be reasonable and cost-effective. Table 6.1 of Appendix H incl udes four-factor data on control options that were deemed not cost-effective.

The required emission limits wil l be implemented by adding them as permit conditions (see Appendix M) to the Title V operating permits of the affected facilities. Recordkeeping, monitoring, and testing r equirements will be included to demonstrate compliance with the limits. These requirements will be cons istent with Georgia EPD’s Procedures for Testing and Monitoring Source s of Air Pollutants (PTM) and must meetGeorgia Regional Haze State Implementation Plan

92 of 124 the requirements of Compliance Assurance Monitoring (40 CFR Part 64) or Periodic Monitoring [40 CFR 70.6(3 )(i)(B)], as appropriate.Georgia Regional Haze State Implementation Plan93 of 124Table 7.6.4-1. Summary of Required Emissions Limits for Sources Subject to Four-Factor AnalysesFacilityEmissionsunit2018 SO2emissionsestimate,uncontrolled(tpy)1% of sulfatevisibilityimpact atClass I areaReasonablecosteffectivecontroloptions2,4Annualcost($/ton)1,4Cost/visibilityat nearestClass I($106/Mm-1)4Life ofunitNon-airenvironmentalimpacts4Requiredemissionlimit(tons/12consecutivemonths)1642 Oil limit andin-duct sorbentinjection3562 20.7 8000 tons/yr ofsolid wastePower BoilerNo. 4 (F1)1099312.55 WOLF3.89 OKEFOil limit andfuel switch to S= 1.0%3228 18.8Beyond2018None568GA PacificBrunswickCelluloseRecoveryBoiler No. 6(M24)193 VISTAS 1.31 WOLF No costeffectivecontrolsNo costeffectivecontrolsNo costeffectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredAdd caustic toexisting venturiscrubber1675 849.2Power BoilerU5001976 1.08 SAMAIn-Ductsorbentinjection1663 843.2Beyond201815000 tons/yr ofsolid wasteBARTexemptionmodelinglimit of 135lb/hrAdd caustic toexisting venturiscrubber1675 849.2Power BoilerU5011976 1.13 SAMAIn-Ductsorbentinjection1663 843.2Beyond2018Not Provided BARTexemptionmodelinglimit of 135lb/hrGA PacificCedarSpringsRecoveryBoiler R4021726 VISTAS 0.77 SAMA No costeffectivecontrolsNo costeffectivecontrolsNo costeffectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredGeorgia Regional Haze State Implementation Plan94 of 124Table 7.6.4-1. Summary of Four-Factor Analyses (continued)FacilityEmissionsunit2018 SO2emissionsestimate,uncontrolled(tpy)1% of sulfatevisibilityimpact atClass I areaReasonablecosteffectivecontroloptions2,4Annualcost($/ton)1,4Cost/visibility atnearest Class I($106/Mm-1)4Life ofunitNon-airenvironmentalimpacts4Requiredemission limit(tons/12consecutivemonths)Boiler B001 1659 1.11 WOLF No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredBoiler B002 1195 0.86 WOLF No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredGA Pacific –Savannah R.MillBoiler B003 1190 0.77 WOLFNo costeffectivecontrolsNo costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredSteamGeneratorSG01632 0.51 WOLF No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredGA PowerCompany PlantKraftSteamGeneratorSG02889 0.52 WOLFNo costeffectivecontrols.Facilityforecastscapacityutilizationdrops, around2015, to 23%,34%, and 50%(SG01, SG02,SG03).No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredGeorgia Regional Haze State Implementation Plan95 of 124FacilityEmissionsunit2018 SO2emissionsestimate,uncontrolled(tpy)1% of sulfatevisibilityimpact atClass I areaReasonablecosteffectivecontroloptions2,4Annualcost($/ton)1,4Cost/visibility atnearest Class I($106/Mm-1)4Life ofunitNon-airenvironmentalimpacts4Requiredemission limit(tons/12consecutivemonths)GA PowerCompany PlantKraftSteamGeneratorSG032455 3.30 WOLF0.85 OKEF0.81 ROMANo costeffectivecontrols.Facilityforecastscapacityutilizationdrops, around2015, to 23%,34%, and 50%(SG01, SG02,SG03No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredGA PowerCompany PlantMitchellSteamGeneratorSG031189 2.74 SAMA0.77 OKEFNo additionalcontrols arerequired sincethe facilityforecasts acapacityutilizationdrop to 11 %by 2018No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredGA PowerCompany PlantMcIntoshSteamGeneratorSG011860 4.13 WOLF1.20 OKEF0.55 SAMA1.35 ROMA0.72 SWANNo additionalcontrols arerequired sincethe facilityforecasts acapacityutilizationdrop to 24 %by 2018No costeffectivecontrolsNo cost-effectivecontrolsBeyond2018No cost-effectivecontrolsNot RequiredFacilityEmissionsunit2018 SO2emissionsestimate,uncontrolled% of sulfatevisibilityimpact atClass I areaReasonablecosteffectivecontrolAnnualcost($/ton)1,4Cost/visibility atnearest Class I($106/Mm-1)4Life ofunitNon-airenvironmentalimpacts4Requiredemission limit(tons/12consecutiveGeorgia Regional Haze State Implementation Plan96 of 124(tpy)1options2,4months)International Paper– Savannah MillPower BoilerPB 138578 6.64 WOLF1.66 OKEF0.70 SAMA1.55 ROMA0.86 SWAN6578 tons peryear emissionlimit5Notprovided5Not provided5Beyond2018Not provided56578Temple-InlandRome LinerboardPower BoilerF43837 4.42 COHU0.99 JOKINo additionalcontrols werecost effectiveNo costeffectivecontrolsNo cost-effectivecontrolsBeyond2018Reduction of powergeneration, waterconsumption, andgypsum generationNot Required(1) from facility-provided data, unless indicated otherwise(2) in the case of multiple options, each option wouldprovide approximately the samelevel of SO2 reductions(3) revised estimate, based on 2002 modification to boiler to increase efficiency; lowered typical oil usage to 5 million gal/yr or less(4) See Appendix H, Table 6.1, for four-factor data on control options thatwere deemed not cost-effective.(5) Control options evaluated for International Paper PB 13 are documented in Appendix H. Several options are capable ofachieving a reduction to 6578 tons/year.Class I Areas:WOLF Wolf Is. SWAN Swan QuarterOKEF Okefenokee COHU CohuttaSAMA St. Marks JOKI Joyce KilmerROMA RomainGeorgia Regional Haze State Implementation Plan

97 of 124 Three facilities, due to resource limitati ons and/or uncertainty regarding future operations, requested limits on their affected emissions units in lieu of performing fourfactor analyses: Rayonier Performance Fiber s, Packaging Corporation of America, and Southern States Phosphate and Fertilizer. The required limit s dropped the sulfate contributions of these units bel ow 0.5 percent of the total sulfate impact on any affected Class I areas.

Table 7.6.4-2 lists the limits and compliance dat es for the four-facto r and the four-factor exempted units. In addition the estimated tons reduced with the new limits are presented. Limits for the four-factor units are on actual emissions as currently stated, but this could change if additional conditi ons are added during the permit amendment process. The limits for the four-factor exem pted units are based on actual (rather than potential) emissions, as the permit conditi ons do not depend solely on fuel sulfur content or on equipment capacit ies. Note that the permi t limits for PB02, RF01, and RF04 at Rayonier Performance Fiber s are on fuel usage and on stack SO2 concentrations (RF01 and RF04 only) that ha ve been calculated to achieve the ton-peryear limits shown in the table. T he limit on RF01 becomes effective upon the completion of the Plant’s Phase 1 projects , which include the addi tion of SO2 control (staged air combustion). The limit on RF04 becomes effective upon the completion of the Plant’s Phase 2 projects, which includ e the addition of SO2 control (staged air combustion). The permitting of Phases 1 and 2 allows for increased production and burning of black liquor solids, but only after the emissions controls are installed. At the time of this SIP submittal, the projec ts were suspended due to depressed market conditions in 2009.

Figure 7.6.4-1 shows the locati ons of facilities with emission units eligible for 4-factor analysis. In addition, the basis for reductions (control or exemption) is indicated for those facilities at which reductions are required.Georgia Regional Haze State Implementation Plan

98 of 124 Table 7.6.4-2. Permit Li mits for Implementation of Reasonable Progress Emissions Reductions

Facility Emissions
Unit Permit limit (tpy of SO2, except as noted) Estimated
Tons
Reduced

GA Pacific –
Brunswick
Cellulose F1
Pwr. Boiler 4 Not more than 568 tons SO2 per 12 consecutive months, compliance date of January 1, 2012 1 1074

Power Boiler
U500 135 pound SO2 per hour (same as BART exemption modeling limit) 1385 Georgia Pacific – Cedar Springs
Power Boiler
U501 135 pound SO2 per hour (same as BART exemption modeling limit) 1385

International Paper – Savannah Pwr. Boiler 13, including
combustion of process organic
emissions Not more than 6758 tons SO2 per 12 consecutive months, compliance date of January 1, 2016 2 2000

Packaging Corp.
of America 3 CE Power
Boiler Not more than 600 tons SO2 per 12 consecutive months, compliance date of January 1, 2012 1 53

PB02
Pwr. Boiler 2 Not more than 318 tons SO2 per 12 consecutive months, compliance date of June 4, 2008 4 306

PB03
Pwr. Boiler 3 Not more than 149 tons SO2 per 12 consecutive months, compliance date of June 4, 2008 4 1448

RF01
No. 5 Rec.
Furn. Not more than 194 tons SO2 per 12 consecutive months, compliance date tied to facility modification 5 139 Rayonier Perf.
Fibers 3

RF04
No. 6 Rec.
Furn. Not more than 307 tons SO2 per 12 consecutive months, compliance date tied to facility modification 5 27

Southern States Phosphate and
Fertilizer 3 SA02
Acid Plant 2 Not more than 580 tons SO2 per 12 consecutive months, compliance date of January 1, 2014 6 228

(1) start of record-keeping; first 12 mont hs will be January 1 – December 31, 2012 (2) start of record-keeping; first 12 mont hs will be January 1 – December 31, 2016 (3) These facilities took limits on the respective uni ts in order to be exempt from submitting fourfactor analyses (4) start of record-keeping; first 12 months will be June 4, 2008, through June 3, 2009 (5) The actual limits on RF01 and RF04 are stac k concentrations of 15 ppm or less SO2 and 19 ppm or less SO2, respectively. The limit on RF01 becomes effective upon the completion of the Plant’s Phase 1 projects, which include the addition of SO2 control (staged air combustion). The limit on RF04 becomes effective upon the comple tion of the Plant’s Phase 2 projects, which include the addition of SO2 control (staged air combustion). (6) start of record-keeping; first 12 mont hs will be January 1 – December 31, 2014Georgia Regional Haze State Implementation Plan

99 of 124 Figure 7.6.4-1. Locations Of Fac ilities With Emission Units Eligible For Four-Factor AnalysisGeorgia Regional Haze State Implementation Plan

100 of 124 7.7 Control Determinations Representing Best Available Retrofit Technology (BART) for Individual Sources

Section 169A of the CAA directs States to assess certain large, older emission sources for additional controls in order to address visibility impacts. St ates are directed to conduct BART determinations for such sources in specific source categories and which contribute to visibility impairm ent in Class I areas. The 1999 r egional haze rule includes the BART requirement, and directs States to in clude BART in their regional haze SIPs. On July 6, 2005, US EPA publis hed a revised final rule, in cluding Appendix Y to 40 CFR Part 51, the Guidelines for BART Determinations Under the Regional Haze Rule (the “BART Guidelines”) that provides direction to states on determining which of these sources should be subject to BART, and how to determine BART for each source.

A BART-eligible source is one which has the potential to emit 250 tons or more of a visibility-impairing air pollutant, one which was put in place between August 7, 1962, and August 7, 1977, and one whose operations fall within one or more of 26 specifically listed source categories. Under the CAA, BART is required for any BART-eligible source that a State determines ‘‘emits any air pollutant which may reasonably be anticipated to cause or contribute to any im pairment of visibility in any such area.’’

For those sources subject to BART, Section 169A(g)(7) of the CAA r equires that States must consider the following factors in ma king BART determinations: (1) the costs of compliance, (2) the energy and non-air quality environmental impacts of compliance, (3) any existing pollution control technology in us e at the source, (4) the remaining useful life of the source, and (5) the degree of impr ovement in visibility which may reasonably be anticipated to result from the use of such technology.Georgia Regional Haze State Implementation Plan

101 of 124 7.7.1 BART-Eligible Sources in Georgia

Table 7.7.1-1. Facilities with BART-eligible sources in Georgia

BART –Eligible Sources

Chemical Products Corporation DSM Chemicals, North America Georgia Pacific – Cedar Springs

Georgia Power – Plant Bowen Georgia Power Plant Branch Georgia Power – Plant Hammond Georgia Power – Plant McDonough

Georgia Power – Plant Mitchell Georgia Power – Plant Scherer Georgia Power – Wansley

Georgia Power – Yates International Paper – Augusta International Paper – Savannah Interstate Paper, LLC Koch Cellulose (Georgia Pacific – Br unswick / Brunswick Pulp & Paper) Lafarge Building Materials (Blue Circle Cement – Atlanta Plant) Owens Corning PCA –Valdosta (Tenneco Packaging, Inc.) PCS Nitrogen Prayon, Inc. Rayonier (Rayonier ITT, Inc.)
Savannah Electric – Plant Kraft
Savannah Electric – Plant McIntosh

Tronox (Kerr – McGee / Kemira)

BART-eligible sources were identified usi ng the methodology in the BART Guidelines:Georgia Regional Haze State Implementation Plan

102 of 124 • One or more emissions units at the fa cility fit within one of the 26 categories listed in the BART Guidelines;

• The emission unit(s) were in exis tence on August 7, 1977, and began operation at some point on or after August 7, 1962; and

• The limited potential emissions from all emission units i dentified in the previous two bullets emission units were greater t han 250 tons or more per year of any of these visibility-impairing pollu tants: SO2, NOx, and PM10.

The BART Guidelines recommend addressing t hese visibility-impairi ng pollutants: SO 2 , NO x , and particulate matter, and suggest that States use their best judgment in determining whether to address VOC or am monia emissions. GA EPD addressed SO2 and NOx, and used particulate matter le ss than 10 microns in diameter (PM 10 ) as an indicator for particulate matte r to identify BART-eligible uni ts, as the BART guidelines recommend. As discussed in detail in Appendix H, VISTAS m odeling demonstrated that VOCs and ammonia from po int sources are not visibility -impairing pollutants. For this reason GA EPD did not evaluate em issions of VOCs and ammonia in BART
determinations.

7.7.2 Determination of Sources Subject to BART in Georgia

Under the BART Guidelines, GA EPD may c onsider exempting some sources from BART if we find that they do not cause or contribute to vi sibility impairment in a Class I area. In accordance with the BART guidel ines, GA EPD chose to perform sourcespecific analyses to determine which sources c ause or contribute to visibility impairment using the CALPUFF model. The CALPUFF modeling protocol used for determining which facilities are subject to BART is include d in Appendix H.7. In accordance with the Guidelines, a contribution threshold of 0. 5 deciviews was used for determining which sources were subject to BART.

All of Georgia’s BART-eligible sources s ubmitted exemption modeling demonstrations. Twenty-two of the twent y-four sources were able to dem onstrate exemptio n. Additional details including BART modeling protocols and exemption reports submitted by the facilities are available in Appendix H. S upporting files and databases that would be impracticable to print are available elec tronically, both on the s ubmitted CD-R and via permanent EPD web links. In addition, files are permanently archived on EPD computer networks. To request access to any of these files pleas e contact the Georgia EPD Air Protection Branch at (404) 363-7000. Facilities found to be subject to BART must complete a BART analysis.

Table 7.7.2-1 represents the facilities that were able to demonstrate exemption from BART based on CALPUFF modeling conducted using the VISTAS modeling protocol. All the listed facilities used old IMPRO VE equation except Georgia Pacific Cedar Springs which used new IMPR OVE equation to demonstrate it s exemption from BARTGeorgia Regional Haze State Implementation Plan

103 of 124 Table 7.7.2-1 Exemption modeling results for BART-eligible sources.

Facility Class 1 Areas Impacted Grid Resolution DeltaDeciviews
Cohutta Wilderness Area 4 km 0.442 Great Smoky Mountains National Pa r 4 km 0.173 Joyce-Kilmer Wilderness Area 4 km 0.197 Sipsey Wilderness Area 4 km 0.127 Chemical
Products Corporation

Shining Rock Wilder ness Area 4 km 0.090 Cape Romain Wilderness Area 12 km 0.094
Cohutta Wilderness Area 12 km 0.112 Great Smoky Mountains National
Park 12 km 0.072

Joyce-Kilmer Wilderness Area 12 km 0.036
Okefenokee Wilderness Area 12 km 0.063 Shining Rock Wilder ness Area 12 km 0.069 DSM Chemicals,
North America

Wolf Island Wilderness Area 12 km 0.114
Okefenokee Wilderness Area 4 km 0.306 Georgia Pacific – Cedar Springs* St. Marks Wilderness Area 4 km 0.499
Cohutta Wilderness Area 4 km 0.17 Great Smoky Mountains National
Park 4 km 0.11

Joyce-Kilmer Wilderness Area 4 km 0.09
Okefenokee Wilderness Area 4 km 0.12 Shining Rock Wilder ness Area 4 km 0.09 Georgia Power –
Plant Branch

Wolf Island Wilderness Area 4 km 0.11
Cohutta Wilderness Area 4 km 0.29 Great Smoky Mountains National
Park 4 km 0.08

Joyce-Kilmer Wilderness Area 4 km 0.09 Shining Rock Wilder ness Area 4 km 0.05 Georgia Power –
Plant Hammond

Sipsey Wilderness Area 4 km 0.06
Cohutta Wilderness Area 4 km 0.19 Great Smoky Mountains National
Park 4 km 0.07

Joyce-Kilmer Wilderness Area 4 km 0.07 Shining Rock Wilder ness Area 4 km 0.05 Georgia Power – Plant McDonough

Sipsey Wilderness Area 4 km 0.04
Okefenokee Wilderness Area 4 km 0.04
St. Marks Wilderness Area 4 km 0.05 Georgia Power –
Plant Mitchell
Wolf Island Wilderness Area 4 km 0.02Georgia Regional Haze State Implementation Plan

104 of 124 Cohutta Wilderness Area 4 km 0.08 Great Smoky Mountains National
Park 4 km 0.07

Joyce-Kilmer Wilderness Area 4 km 0.07
Okefenokee Wilderness Area 4 km 0.08 Shining Rock Wilder ness Area 4 km 0.06 Georgia Power – Plant Scherer

Wolf Island Wilderness Area 4 km 0.05 Georgia Power – Plant Wansley Cohutta Wilderness Area 4 km 0.44

Great Smoky Mountains National Pa r 4 km 0.17 Joyce-Kilmer Wilderness Area 4 km 0.18 Sipsey Wilderness Area 4 km 0.14 Georgia Power – Plant Wansley

Shining Rock Wilder ness Area 4 km 0.12
Cohutta Wilderness Area 4 km 0.15 Great Smoky Mountains National Pa r 4 km 0.05 Joyce-Kilmer Wilderness Area 4 km 0.06 Sipsey Wilderness Area 4 km 0.05 Georgia Power –
Plant Yates

Shining Rock Wilder ness Area 4 km 0.03 Cape Romain Wilderness Area 4 km 0.211
Cohutta Wilderness Area 4 km 0.114 Great Smoky Mountains National
Park 4 km 0.093

Joyce-Kilmer Wilderness Area 4 km 0.086 Linville Gorge Wilderness Area 4 km 0.103
Okefenokee Wilderness Area 4 km 0.157 Shining Rock Wilder ness Area 4 km 0.127 International Paper – Augusta

Wolf Island Wilderness Area 4 km 0.148 Cape Romain Wilderness Area 4 km 0.092
Okefenokee Wilderness Area 4 km 0.282
St. Marks Wilderness Area 4 km 0.055 Koch Cellulose (GP – Brunswick, Brunswick Pulp and Paper Wolf Island Wilderness Area 4 km 0.447
Cohutta Wilderness Area 12 km 0.119 Great Smoky Mountains National Pa r 12 km 0.051 Joyce-Kilmer Wilderness Area 12 km 0.056 Sipsey Wilderness Area 12 km 0.054 Owens Corning

Shining Rock Wilder ness Area 12 km 0.072
Chassahowitzka Wilder ness Area 12 km 0.197
Okefenokee Wilderness Area 12 km 0.349
St. Marks Wilderness Area 4 km 0.190 PCA- Valdosta

Wolf Island Wilderness Area 12 km 0.181Georgia Regional Haze State Implementation Plan

105 of 124 Cape Romain Wilderness Area 4 km 0.359
Cohutta Wilderness Area 12 km 0.409 Great Smoky Mountains National
Park 12 km 0.163

Joyce-Kilmer Wilderness Area 12 km 0.175 Linville Gorge Wilderness Area 12 km 0.393
Okefenokee Wilderness Area 12 km 0.393 Shining Rock Wilder ness Area 12 km 0.220 PCS Nitrogen

Wolf Island Wilderness Area 12 km 0.294 Cape Romain Wilderness Area 12 km 0.009
Cohutta Wilderness Area 12 km 0.004 Great Smoky Mountains National
Park 12 km 0.002

Joyce-Kilmer Wilderness Area 12 km 0.002 Linville Gorge Wilderness Area 12 km 0.005
Okefenokee Wilderness Area 12 km 0.007 Shining Rock Wilder ness Area 12 km 0.003 Prayon, Inc.

Wolf Island Wilderness Area 12 km 0.005 Cape Romain Wilderness Area 12 km 0.132
Okefenokee Wilderness Area 12 km 0.254
St. Marks Wilderness Area 12 km 0.151 Rayonier

Wolf Island Wilderness Area 12 km 0.319 Cape Romain Wilderness Area 4 km 0.18
Okefenokee Wilderness Area 4 km 0.18 Savannah Electric – Plant Kraft
Wolf Island Wilderness Area 4 km 0.21 Cape Romain Wilderness Area 4 km 0.04
Okefenokee Wilderness Area 4 km 0.03 Savannah Electric
– Plant McIntosh
Wolf Island Wilderness Area 4 km 0.03 Cape Romain Wilderness Area 12 km 0.134
Okefenokee Wilderness Area 12 km 0.213Tronox (KerrMcGee/Kemira)
Wolf Island Wilderness Area 12 km 0.246
* Note: All sources used the old IMPRO VE equation except Georgia Pacific – Cedar Springs, which used the new IMPROVE equation.

Table 7.7.2-2 represents the facilities that were able to demonstrate exemption from BART based on model plant criteria or by accepting emissions limits for visibility causing pollutants.Georgia Regional Haze State Implementation Plan

106 of 124 Table 7.7.2-2. Facili ties exempted from BART via other methods

Facility Name Pollutant Potential Emissions Pre- limit (tpy) PTE 2002 SO2+NOx+ PM of BART - Eligible Equipment (tpy) Min distance to Nearest Class 1
Area (km) Potential Emissions Post – limit (tpy) Effective Date

Georgia Pacific – Cedar Springs SO2 8506.2 17684 137.1 Power Boilers No. 1 and No. 2 have limits of 135lbs/hr
each. This equates to 591 tpy.

Recovery Boiler No. 3 has a limit of 350 ppm on a dry basis corrected to 8 percent oxygen as a 24-hour average when firing black liquor
solids. This equates to 3600 tpy.

Facility wide limits are equivalent to 4782.36 tpy. July 30, 2011.

LaFarge Building Materials* -- 540 114.3 No limit. Facility Exempt via Model Plant Exemption. --

International Paper – Savannah -- 51.4 83.6 No limit. Facility Exempt via Model Plant Exemption. --

*Note: After this analysis was completed, Lafarge Building Materials shut down and removed BART-eligible equipment resulting in a reduction of 531.4 tons of potential emissions of SO2 + NOx + PM effectively eliminating t heir eligibility to BART.Georgia Regional Haze State Implementation Plan

107 of 124 Georgia Pacific Cedar Springs was able to demonstrate exemption from BART by accepting SO2 emissions limits on Power Boilers 1 and 2 (135 lb/hr each) and on Recovery Boiler 3 (350 ppm). These limits re sult in 0.499 deciview impact at St. Marks and a 0.306 deciview impact at Okefenokee NWR. The permit will be issued with Federally-enforceable limits and a Federally- enforceable c ondition that requires the facility to monitor their emissions and to not ify EPD if they exceed the BART exemption
limit.

EPA established specific exempt ion thresholds or criteria based on CALPUFF modeling conducted for a model plant. The criteria th at sources must meet include potential emissions of SO2 and NOx combined of less than 500 tons per year and a distance of greater than 50km from any Class I area, or combined potential emissions less than 1000 tons per year with a distance greater than 100km from any Class I area. In
situations where combined SO2 and NOx emissions are le ss than 500 or 1000 tons per year, but PM emissions are greater than 15 t ons per year, the emissions of SO2, NOx and PM may be combined using weighting fa ctors (Appendix P) and compared to 500 or 1000 tons. Both Lafarge Building Mate rials and International Paper – Savannah meet the model plant exemption criteria. Please see Table 7.7.2-2 for emissions and distances from Class I areas.

One of Georgia’s BART-eligibl e sources is an EGU. This Georgia power plant Bowen is subjected to CAIR. US EPA has determined that, as a whole, the CAIR cap-and-trade program improves visibility more than im plementing BART for individual sources in states affected by CAIR. A State that opts to participate in the CAIR program under Part 96 AAA-EEE need not require an affected BAR T-eligible EGU to install, operate, and maintain BART for SO2 or NOx emissions. Since Georgia is participating in CAIR and accepts US EPA’s overall finding that CA IR “substitutes” for BART for NOx and SO2, Georgia’s EGUs were allowed to submit BART exemption modeling demonstrations for PM emissions only. All EGUs other than Georgia Power-Plant Bowen demonstrated that they do not contribute to visibility impairment in any Class I

area.

In total, twenty-two of G eorgia’s twenty-four BART-eligible sources were able to demonstrate that they did not cause or contribute to visibility impairment in any Class I area within 300 km of the source.

7.7.3 BART Determination fo r Subject-to-BART Sources

Two sources, Interstate Paper in Riceboro, Georgia, and Georgia Power Plant Bowen in Cartersville, Georgia, were unable to demonstrate a contribut ion of less than 0.5 dv at all Class I areas within 300 km from their BA RT-eligible sources. These two sources are considered to be “subject to BART” and were required to do a complete BART determination containing thei r evaluation of potential BA RT options and accordingly submit permit applications. Interstate Paper failed to perform a BART determination, therefore the analysis was performed by EPD and the results presented are thoseGeorgia Regional Haze State Implementation Plan

108 of 124 determined by EPD. Their BART determination results are give in table 7.7.3-1, for a more detailed discussion of the BART det erminations, please s ee Appendix H.8.

Table 7.7.3-1 BART determination r esults for subject-to BART sources

Source Unit Required Control Option Control Efficiency Cost of Control ($/ton)

Power Boiler (F1) Combustion of natural gas only

except during

periods of
curtailment 99% 370

Recovery

Boiler No cost effective control options Available Not required Not required Interstate

Paper

Lime Kiln No cost effective control options Available Not required Not required

Boiler 1
Boiler 2
Boiler 3 Georgia

Power Company –
Plant Bowen Boiler 4 No cost effective control options Available Not required Not required

Figure 7.7.3-1 shows the loca tions of facilities with emission units eligible for BART analysis. In addition, the basis for reduction or no reduction is indicated for each facility.

The required operational restrictions will be implemented by adding them as permit conditions to the Title V operating permit of Interstate Paper (see Appendix M). Georgia EPD has notified Interstate Paper in writing of the intent to revise its air permit. Recordkeeping, monitoring, and testing r equirements will be included to demonstrate compliance with the limits. These requirements will be cons istent with Georgia EPD’s Procedures for Testing and Monitoring Source s of Air Pollutants (PTM) and must meet the requirements of Compliance Assurance Monitoring (40 CFR Part 64) or Periodic Monitoring [40 CFR 70.6(3 )(i)(B)], as appropriate.Georgia Regional Haze State Implementation Plan

109 of 124 Figure 7.7.3-1. Locations of facilit ies with BART-eligible emission units.Georgia Regional Haze State Implementation Plan

110 of 124 7.8 What Additional Emissions Controls Were Considered as Part of the LongTerm Strategy for Visibility Improvement by 2018?

Section 308(d)(3)(v) of the regional haze rule lists several factors that must be addressed in each SIP. These factors include smoke management techniques for agricultural and forestry management purposes and measures to mitigate emissions from construction activities.

As discussed in Section 2.4 and demonstrat ed in Figures 2.4-1 and 2.4-2, elemental carbon (sources include agriculture, prescri bed wildland fires, and wildfires) is a relatively minor contributor to visibility im pairment at the Class I areas in Georgia. However, on July 11, 2008, GA EPD entered into a memorandum of understanding with the Georgia Forestry and Geor gia Department of Natural Re sources Wildlife Resources Division adopting a smoke managem ent plan that addresses the issues laid out in US EPA’s 1998 draft guidance for smoke management plans. This plan is sufficient to satisfy the directive in section 308(d)(3 )(v)(E). A copy of the current smoke management plan can be obtained from Georgi a EPD, or it can be viewed on the Georgia EPD web page.

Georgia’s Rules for Air Qualit y Control include r equirements for precautions to prevent fugitive dust from becoming airborne and also limit the opacit y of fugitive emissions to less than 20 percent. The requirements of ru le 391-3-1-.02(n) include preventive measures for construction activities and ar e deemed adequate to satisfy the directive in Section 308(d)(3)(v)(B) of the Regional Haze rule. The curr ent version of Georgia’s air rules is available on the Georgia EPD web site.Georgia Regional Haze State Implementation Plan

111 of 124 

### 8.0 REASONABLE PROGRESS GOALS

The Regional Haze Rule at 40 CFR secti on 51.308(d)(1) requires States to establish reasonable progress goals for each Class I area within the state (expressed in deciviews) that provide for reasonable progress towards achieving natur al visibility. In addition, US EPA released guidance on June 1, 2007, to use in setting reasonable progress goals. The goals must provide improv ement in visibility for the most impaired days, and ensure no degradation in visibility fo r the least impaired days over the State Implementation Plan (SIP) period. The stat e must also provide an assessment of the number of years it would take to attain nat ural visibility conditions if improvement continues at the rate represent ed by the reasonable progress goal.

In accordance with the requirements of 40 CFR §51.308(d)(1), this Regional Haze Implementation Plan establishes reasonabl e progress goals for each Class I area in Georgia. To calculate the rate of pr ogress represented by each reasonable progress goal, GA EPD compared baseline visibility conditi ons to natural visibility conditions in each Class I area and determined the uniform rate of visibility improvement (in deciviews) that would need to be maintained during each implementation period in order to attain natural visibility conditions by 2064. The GA EPD summarized expected visibility improvements under existing Federal and State regulations, BART determinations in Georgia and neighboring states, and any addi tional control measures found to be reasonable to implement in this review period. These controls were modeled in CMAQ as part of the long-term strategy (Appendix E) and the reasonable progress goals were then adjusted for additiona l controls in Georgia (Appendix N).

VISTAS has demonstrated that the 2018 Base G4 control scenario provides for a significant improvement in visibility better t han the uniform rate of progress for at least one of the three Georgia Class I areas and t he other two falling short by less than 10 percent for the most impaired days over the period of the implementation plan and ensures no degradation in visibility at any of the three Georgia Cl ass I areas for the least impaired days over the same period. Implementation of Georgia’s reasonable progress goals in the form of BART and 4-fa ctor analyses controls will give further visibility improvement by 0. 02 dV (0.088%) at Cohutta Wilderness Area and 0.05 dV (0.21%) at Okefenokee Wilder ness area and Wolf Island. These reductions can be seen in Figure 8.0-1 and 8.0-2. Since there is not an IMPR OVE monitor located at Wolf Island, the Okefenokee uniform rate of pr ogress glide slope and reasonable progress goals are being used as a surrogate for Wolf Island. Since the Okefenokee Wilderness and Wolf Island reasonable progress goals show a slower rate of improvement in visibility than the rate that would be needed to attain natural conditions by 2064 (uniform rate of progress glide slope), it has been estimated that an additional 6-7 years are need to attain natural conditions.

Note that GA EPD has not taken into a ccount any reductions that will result from Florida’s reasonable progress analysis as r equired 40 CFR 51.308(d)(1). Florida DEP has proposed requiring submittal of applic ations to address Reasonable Progress Control Technology no later than January 31, 2012. As explained in Appendix H, pointGeorgia Regional Haze State Implementation Plan

112 of 124 sources in Florida have a larger impact on visibility impairment at Okefenokee than Georgia sources and have a signif icant impact on Wolf Island. SO2 controls at Florida Sources can, therefore, have a signi ficant impact on reasonable progress at Okefenokee and Wolf Island. Because the r easonable controls r equired of Florida sources are not yet available, they hav e not been taken into account in setting reasonable progress goals for Okefenokee or Wolf Island.

Table 8.0-1. Georgia Reasonable Pr ogress Goals – 20 percent Worst Days

Class I

Area 2004 Baseline Visibility (dv) 2018 Reasonable Progress Goal (dv)

[2004 – 2018

decrease] 2018 Uniform Rate of Progress Glide Slope (dv)

[2004 – 2018 decrease to meet uniform progress] Natural Visibility (dv)

[2018-2064

decrease needed from

2018 goal]

Cohutta
Wilderness 30.25 22.78 [7.47] 25.71 [4.54] 10.78 [12.00]

Okefenokee
Wilderness 27.13 23.77 [3.36] 23.42 [3.71] 11.21 [12.56]

Wolf Island 27.13 23.77 [3.36] 23.42 [3.71] 11.21 [12.56]

Table 8.0-2. Georgia Reasonable Pr ogress Goals – 20 per cent Best Days

Class I

Area 2004 and 2018 Baseline Visibility (dv) 2018 Reasonable Progress Goal (dv) [2004 – 2018 improvement goal]
Cohutta
Wilderness 13.77 11.75 [2.02]
Okefenokee
Wilderness 15.23 13.92 [1.31]
Wolf Island 15.23 13.92 [1.31]Georgia Regional Haze State Implementation Plan

113 of 124 Figure 8.0-1. CMAQ 2018 Base G4 results compared to Uniform Rate of Progress at Cohutta Wilderness Area with GA Reasonable Progress Goals

Figure 8.0-2. CMAQ 2018 Base G4 results compared to Uniform Rate of Progress at Okefenokee Wilderness Area with GA Reasonable Progress Goals Uniform Rate of Progress Glide Path Cohutta - Worst 20% Data Days New IMPROVE Equation

30.25 28.63

25.71

22.46

19.22

15.97

12.73
10.78 27.05

22.78

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model Prediction

Uniform Rate of Progress Glide Path Okefenokee - Worst 20% Data Days New IMPROVE Equation

27.13 25.81

23.42

20.76

18.11

15.45

12.80 11.21 25.38 23.77

0 5 10 15 20 25 30 35

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064

YearHaziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation Model PredictionGeorgia Regional Haze State Implementation Plan

114 of 124 

### 9.0 MONITORING STRATEGY

The State Implementation Plan is to be a ccompanied by a strat egy for monitoring regional haze visibility impairm ent. Specifically, the Regional Haze Rule states at 40 CFR 51.308(d)(4):

“(4) Monitoring strategy and other im plementation plan requirements. The State must submit with the implementation plan a monitoring strategy for measuring, characterizing, and reporting of regiona l haze visibility impairment that is representative of all mandat ory Class I Federal areas within the State. This monitoring strategy must be coordinated wi th the monitoring strategy required in §51.305 for reasonably attributable visibi lity impairment. Compliance with this requirement may be met through participat ion in the IMPROVE network. The implementation plan must also provide for the following:

(i) The establishment of any additi onal monitoring sites or equipment needed to assess whether reasonable progr ess goals to address regional haze for all mandatory Class I Federal areas within the State are being
achieved.

(ii)-(vi) [Other implementation plan r equirements that pertain to reporting and use of monitoring data and an emission inventory.]”

Such monitoring is intended to provide t he data needed to satisfy four objectives:

1. Track the expected vi sibility improvements resu lting from emissions reductions identified in this SIP; 2. Better understand the atmospheric pr ocesses of importance to haze; 3. Identify chemical species in the ambient particulate matter an d relate them to emissions from sources; and
4. Evaluate regional air quality models for haze and construct relative response factors (RRFs) for using those models.

The primary monitoring network for regional haze is the IMPROVE network. Given that IMPROVE monitoring data from 2000-2004 serve as the baseline for the regional haze program, the future r egional haze monitoring strategy mu st necessarily be based on, or directly comparable to, IMPROVE. The IMPROVE measurements provide the only long-term record available for tracking visi bility improvement or degradation and, therefore, Georgia in tends to rely on the IMPROVE network for complying with the regional haze monitoring require ment in the Regional Haze Rule. There are currently two IMPROVE sites in the State.Georgia Regional Haze State Implementation Plan

115 of 124 Table 9.0-1. Class I areas in Georgia and IMPROVE monitors that represent conditions at each of them.

Class I Area IMPROVE Site Designation

Cohutta Wilderness Area COHU1

Okefenokee Wilderness Area OKEF1

GA EPD will use South Eastern Aerosol Re search and Characterization (SEARCH) data from the sites illustrated below for further the understanding of both PM2.5 and visibility formation and trends in Georgia. The SEARCH monitors pr ovides the following data related to the nature of am bient fine particulate matter:

• 24-hr PM2.5 filter samples, analyzed for ma ss, ions (sulfate, nitrate, ammonium), organic carbon (OC), elemental (black) ca rbon (EC or BC), and elements as measured by X-ray fluorescence (XRF);

• 24-hr PM coarse mass, ions, and XRF elements;

• 24-hr gaseous ammonia as co llected with an annular denuder;

• Continuous (minute to hourly) PM2.5 ma ss, OC, EC, ammoni um, nitrate, and sulfate; light scatteri ng and light absorption;

• Continuous gaseous ozone, nitric oxide, ni trogen dioxide, total oxidized nitrogen (NOy), nitric acid, carbon m onoxide, and sulfur dioxide; and

• Continuous 10-m meteorol ogical parameters: wind speed, wind direction, precipitation, temperatur e, barometric Pressure, relative humidity and solar radiation.

The Clean Air Status and Trends Network (CAST Net) provides atmospheric data on the dry deposition component of total acid deposition, gr ound-level ozone and other forms of atmospheric pollution. All measurements utilize a 1-week sample period and include sulfur dioxide, particulate sulfate, particulate nitrate, nitric acid, particulate ammonium, particulate calcium, particulate sodium, par ticulate magnesium, particulate potassium, and ozone. In addition, GA EPD operates a fa irly comprehensive PM 2.5 network of the filter-based Federal reference method (F RM) monitors, conti nuous mass monitors (TEOMs), filter-based speciated monitors (S TN) and the continuous speciated monitors described above. A map of the various locati ons around the State is included in Figure 9.0.1. These PM2.5 measurements help GA EPD characterize air pollution levels in areas across the state, and, t herefore, aid in the analysis of visibility improvement in and near the Class I areas.Georgia Regional Haze State Implementation Plan

116 of 124 Figure 9.0-1. PM2.5 Monitoring Network in Georgia

The IMPROVE measurements ar e central to Georgia’s regional haze monitoring strategy, and it is difficult to visualize how the objectives listed above could be met without the monitoring provided by IMPROVE. Any reduction in the scope of the IMPROVE network in Georgi a would jeopardize the Stat e’s ability to demonstrate reasonable progress toward visibility improvem ent in some of its Class I areas. In particular, Georgia’s regional haze strategy relies on emissi on reductions that will on different timelines and will most likely not be spatially uniform.

Because each of the current IMPROVE moni tors in Georgia represents a different airshed, reduction of the IMPROVE network by shutting down one of these monitoring sites impedes tracking progress at reducing ha ze at the affected Class I area. In the event this occurs, Georgia, in consultation with the US EPA and relevant Federal Land Managers, will develop an alter native approach for meeting the tracking goal, perhapsGeorgia Regional Haze State Implementation Plan

117 of 124 by seeking contingency funding to carry out lim ited monitoring or by relying on data from nearby urban monitoring sites to dem onstrate trends in speciated PM 2.5 mass.

Data produced by the IMPRO VE monitoring network will be used nearly continuously for preparing the 5-year progress reports and th e 10-year SIP revisions, each of which relies on analysis of the preceding five year s of data. Consequen tly, the monitoring data from the IMPROVE sites needs to be readi ly accessible and to be kept up to date. Presumably, IMPROVE wil l continue to process informati on from its own measurements at about the same pace and with the same att ention to quality as it has shown in the recent past. The VIEWS web site has been maintained by VISTAS and the other Regional Planning Organizations (RPOs) to pr ovide ready access to the IMPROVE data and data analysis tools. G eorgia is encouraging VISTAS and the other RPOs to maintain VIEWS or a similar data managemen t system to facilitate analysis of the IMPROVE data.Georgia Regional Haze State Implementation Plan

118 of 124 

### 10.0 INTERSTATE CONSULTATION

The VISTAS states have jointly developed the technical analyses to define the visibility improvement by 2018 under existing Federal and State regulations compared to the uniform rate of progress, SO2 Areas of In fluence for each Class I area, and methods to prioritize contributions from individual sour ces within the Areas of Influence. The states collectively accept the conc lusions of these analyses.

In December of 2006, the VIST AS State Air Directors held thei r first formal consultation meeting to review the Ba se G modeling results and t he SO2 Areas of Influence analyses. The Air Directors agreed to look at reasonable control measures for sources on the lists for the SO2 Areas of Influence. Each state would c onsider sources within their state and would identify sour ces in neighboring states that they would like to have that neighboring state consider. States acknowledged t hat the review process would differ among states since some Class I areas are projected to see visibility improvements near the uniform rate of progre ss while most Class I areas are projected to have greater improvements than uniform rate of progress.

In May of 2007, the VISTAS State Air Directo rs met for their second formal interstate consultation. States shared their lists of sources in their stat e and neighboring states for each Class I area. They also shared their criteria for listing sources and their plans for further interstate consultation.

The GA EPD received consultation letters an d evaluated the impact of Georgia sources on Class I areas in neighboring states and i dentified sources that were likely to contribute 0.5% or more to the total visibility impairment. Such sources were considered for additional reasonable contro l measures that should be implemented to mitigate impacts in Class I areas in neighboring states.

Based on the VISTAS Area of Influence (AOI) electronic spreadsheet that includes Q/d, RTMax, and percent contributi on from each Georgia point sour ce to each Class I area, the following seven nearby Class I areas outside of Georgia showed impacts greater than or equal to 0.5%: Joyce Kilmer-Slickrock (NC), Shining Rock (NC), Great Smoky Mountains (NC/TN), Sipsey Wildernesses (AL), Cape Ro main (SC), Swanquarter (NC), and St. Marks (FL). All other Class I areas s howed contributions fr om Georgia point sources of less than 0.5%. For details on specific percent contri bution from each Georgia point source to each Class I area, see Appendix H.2. For a list of po llution reductions that are anticipated at each source before 2018, see Section 7.6.1.Georgia Regional Haze State Implementation Plan

119 of 124 Table 10-1: Georgia point source contribution to Joyc e Kilmer-Slickrock (NC).
Plant Point ID Percent Contribution GEORGIA POWER COMPANY, YATES STEAM-ELECT SG07 1.879% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG06 1.861% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG03 1.559% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG04 1.496% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG01 1.476% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG02 1.466% GEORGIA POWER COMPANY, BOWEN STEAM-ELECT SG04 1.100% GEORGIA POWER COMPANY, BOWEN STEAM-ELECT SG03 1.068% INLAND PAPERBOARD & PACKAGING, INC. -LIN F4 0.995% GEORGIA POWER COMPANY, HAMMOND STEAM-ELE SG04 0.924% GEORGIA POWER COMPANY, BOWEN STEAM-ELECT SG02 0.850% GEORGIA POWER COMPANY, BOWEN STEAM-ELECT SG01 0.844% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG05 0.755% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG04 0.739%

Table 10-2: Georgia point source c ontribution to Shining Rock (NC).
Plant Point ID Percent Contribution
GEORGIA POWER COMPAN Y, SCHERER STEAM-ELE SG03 0.712%

GEORGIA POWER COMPAN Y, SCHERER STEAM-ELE SG04 0.683%

GEORGIA POWER COMPAN Y, SCHERER STEAM-ELE SG01 0.674%

GEORGIA POWER COMPAN Y, SCHERER STEAM-ELE SG02 0.669% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG07 0.580% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG06 0.574%

Table 10-3: Georgia point s ource contribution to Great Smoky Mountains (NC/TN).
Plant Point ID Percent Contribution GEORGIA POWER COMPANY, YATES STEAM-ELECT SG07 0.688% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG06 0.681% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG03 0.636% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG04 0.610% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG01 0.602% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG02 0.598%

Table 10-4: Georgia point source c ontribution to Swanquarter (NC).
Plant Point ID Percent Contribution INTERNATIONAL PAPER - SAVANNAH MILL PB13 0.859%
SAVANNAH ELECTRIC: MCINTOSH STEAM - ELEC SG01 0.720%Georgia Regional Haze State Implementation Plan

120 of 124 Table 10-5: Georgia point source contribution to Sipsey Wildernesses (AL).
Plant Point ID Percent Contribution GEORGIA POWER COMPANY, YATES STEAM-ELECT SG07 1.115% GEORGIA POWER COMPANY, YATES STEAM-ELECT SG06 1.104% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG03 0.587% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG04 0.563% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG01 0.555% GEORGIA POWER COMPANY, SCHERER STEAM-ELE SG02 0.551%

Table 10-6: Georgia point source c ontribution to Cape Romain (SC).
Plant Point ID Percent Contribution INTERNATIONAL PAPER - SAVANNAH MILL PB13 1.553%
SAVANNAH ELECTRIC: MCINTOSH STEAM - ELEC SG01 1.352%
SAVANNAH ELECTRIC: KRAFT STEAM - ELECTRI SG03 0.814%

Table 10-7: Georgia point source contribution to St. Marks (FL).
Plant Point ID Percent Contribution GEORGIA POWER COMPANY, MITCHELL STEAM-EL SG03 2.737% LONGLEAF ENERGY STATION BOIL1 1.392%
LONGLEAF ENERGY STATION BOIL2 1.392% GEORGIA PACIFIC CORPORATION, CEDAR SPRIN U501 1.128% GEORGIA PACIFIC CORPORATION, CEDAR SPRIN U500 1.081% GEORGIA PACIFIC CORPORATION, CEDAR SPRIN R402 0.768% INTERNATIONAL PAPER - SAVANNAH MILL PB13 0.704% SAVANNAH ELECTRIC: MCINTOSH STEAM - ELEC SG01 0.554%

The GA EPD also sent consultation letters to Florida, South Carolina and Tennessee regarding the impact of their sources on Geor gia’s Class I areas. These consultation letters are present in Appendix J.

Analyses of impacts from G eorgia and potential controls are discussed in greater detail in Appendix H.

The MANE-VU states of Maine, New Jersey , New Hampshire, and Vermont sent letters to Georgia in the Spring of 2007 stat ing that, based on 2002 emissions, Georgia contributed to visibility impairment to Class I areas in those states. MANE-VU states have asked the GA EPD to participate in fu rther consultation with these states during the Summer of 2007. The GA EPD has res ponded to those letters and has participated in conference calls with these states. The final Regional Ha ze SIP will reflect the results of those letters and calls. The letters from these states, and res ponses from GA EPD, are included as attachments to Appendix J.Georgia Regional Haze State Implementation Plan

121 of 124 

### 11.0 COMPREHENSIVE PERIODIC IMPLEMENTATION PLAN

REVISIONS

40 CFR Section 51.308(f) r equires the GA EPD to revise its regional haze implementation plan and submit a plan revisi on to US EPA by July 31, 2018, and every ten years thereafter. In a ccordance with the requirements listed in Section 51.308(f) of the Federal rule for regional haze, Georgia commits to re vising and submitting this regional haze implementation plan by July 31, 2018, and every ten years thereafter.

In addition, Section 51.308(g) requires periodic reports ev aluating progress towards the reasonable progress goals establis hed for each mandatory Class I area. In accordance with the requirements listed in Se ction 51.308(g) of the Federal rule for regional haze, the GA EPD commits to s ubmitting a report on reasonable progress to US EPA every five years following the initial submittal of the SIP. The report will be in the form of a SIP revision. The reasonable progress report will evaluate the progress made towards the reasonable progress goal for each mandatory Class I area located within Georgia and in each m andatory Class I area located outside Georgia which may be affected by emissions from within Georgia

.

The requirements listed in 51. 308(g) include the following:

1. Description of the st atus of implementation; 2. Summary of emission reductions achiev ed thus far, including especially the status of implementation of the CAIR compliance plans for EGUs compared to
the control assumed in t he modeling. [The GA EPD recognizes that the 2018 projections of EGU controls from the IPM runs repres ent one solution to how the CAIR requirements will be met. By the time of the first periodic report, the GA EPD anticipates that the actual comp liance strategy for the various utility companies will be much more defined. An assessment of those actual compliance plans will be done for the first periodic report.] 3. Assessment of changes in visibility c onditions at each Class I area (current vs. baseline), expressed as 5-year averages of annual values for 20 percent best and worst days; 4. Analysis of emission changes over the 5-year period identif ied by source or activity; 5. Analysis of any significant changes in or out of the Stat e which have impeded

progress; 6. Assessment of the sufficiency of t he implementation plan to meet RPGs;

7. Review and any modifications to G eorgia’s visibility monitoring plan.

All requirements listed in 51.308(g) shall be addressed in the SIP revision for reasonable progress.Georgia Regional Haze State Implementation Plan

122 of 124 There are several technical improvement s that are recommended in the emissions inventory and air quality models that are used to support regulatory decisions for regional haze. These reco mmended improvements, as fundi ng is available, will be implemented to support the next long-term st rategy. Appendix K contains a more detailed discussion of possible technical im provements. The following is an overall

summary:

First and foremost, continued improv ements are needed in the integrated oneatmosphere air quality models that are us ed to project air quality responses to emissions reductions. As our underst anding of partitioning between gaseous and aerosol phases improves, this understanding needs to be reflected in the models. Improvements can also be made in how t he models handle indivi dual pollutants. Sulfate performance for the CMAQ regional ai r quality model is good overall. However sulfate deposition is frequently overestimated in the models, particularly in the summer months. At the coastal sites, when winds are blowing from the Gulf of Mexico or Atlantic Ocean, CMAQ underestimates measur ed sulfate at the m onitors. CMAQ’s processes also should be reviewed for sulf ate formation over water. Nitrate is overestimated by the model in the winte r and underestimated in the summer, although summer monitored values of ni trates are very low. Addi tional improvements in seasonal allocation of ammonia emissions would impr ove model estimates of ammonium nitrate formation. Organic carbon is generally underestimated in the summer months. Improvements are needed in the characteriza tion of both primary carbon emissions and formation of secondary organic carbon.

Other improvements needed include better t ools for organic carbon source apportionment, and more consistent measur ement techniques between rural and urban monitoring networks. To im prove our understanding of the c ontribution of fire from natural forest fires, prescribed burning, l and clearing, and agricul tural burning, states need improved record keeping. Additional improvements to international emissions inventory are also needed, to improve our understanding of boundary conditions for our modeling domain and of the cont ributions from international emissions to pollutant concentrations at the VISTAS Class I areas.Georgia Regional Haze State Implementation Plan

123 of 124 

### 12.0 DETERMINATION OF ADEQ UACY OF THE EXISTING PLAN

Depending on the findings of t he 5-year progress report, G eorgia commits to taking one of the actions listed in 40 CFR section 51.308( h). The findings of the 5-year progress report will determine which action is appropriate and necessary.

List of Possible Actions – 40 CFR Section 51.308(h)

1) GA EPD determines that the existing SI P requires no further substantive revision in order to achieve established goals. GA EPD provides to the Administrator a negative declaration that further revision of the SIP is not needed at this time.

2) GA EPD determines that the ex isting SIP may be inadequate to ensure reasonable progress due to emissions from other states which participated in the regional planning process. GA EPD provides notification to the Administrator and the states that participated in regional planning. GA EP D collaborates with states through the regional planning process to address the SIP’s deficiencies.

3) GA EPD determines that the cu rrent SIP may be inadequate to ensure reasonable progress due to emissions from another country. GA EPD provides notification, along with available in formation, to the Administrator.

4) GA EPD determines that the existi ng SIP is inadequate to ensure reasonable progress due to emissions within the state. GA EPD will revise its SIP to address the plan’s deficiencies within one year.



### 13.0 COORDINATION WITH FEDERAL LAND MANAGERS

As required by 40 CFR §51.308(i), the regional haze SIP must include procedures for continuing consultation between the States and Federal Land Managers (FLMs) pertaining to visibility protection. The FL Ms responsible for Class I areas in Georgia

are:

· Fish and Wildlife Service (FWS), under U.S. Department of Interior · National Park Service (NPS), under U.S. Department of Interior · Forest Service (FS), under U. S. Department of Agriculture

The requirements for ongoing State and FLMs consultation and how Georgia will comply with the requirements are de scribed in the following paragraphs.

40 CFR 51.308(i)(2) requires the State to pr ovide the FLMs with an opportunity for consultation, in person and at least 60 days prior to holding a public hearing on a SIP
revision. The consultation must include the opportunity for the FLMs to discuss their:Georgia Regional Haze State Implementation Plan

124 of 124 · assessment of visibility impai rment in the Class I area; and · recommendations on the development of the reasonable progress goal and on the development and implementation of strategies to address visibility impairment.

Records of Georgia EPD’s consultations with the FLMs on the first Regional Haze SIP are included in Appendix O.

40 CFR 51.308(i)(3) requires the State to inco rporate into any SIP or SIP revision a description of how it addressed comments provided by the FLMs. The comments on the SIP and the description of how they were addressed have been included in Appendix O.

40 CFR 51.308(i)(4) requires the plan (or pl an revision) to include procedures for continuing consultation between the State and Federal Land Managers on the implementation of the visibi lity protection program, includi ng development and review of implementation plan revisions and 5-year pr ogress reports, and on the implementation of other programs having the potential to contribute to impairment of visibility in mandatory Class I Federal areas. GA EPD will offer the Federal Land Managers an opportunity for consultation on a yearly bas is, including the opportunity to discuss the implementation process and t he most recent IMPROVE monitoring data and VIEWS data. Records of annual consultations and progress report consultations will be maintained in Georgia EPD’s Regional Haze files.