Appendix H 

i

Appendix H 

Reasonable Progress Evaluation, BART 

and Long-Term Strategy 
 Appendix H 

ii
 Appendix H 

i

TABLE OF CONTENTS 

LIST OF APPENDICES ....................................................................................... iii

LIST OF TABLES ..................................................................................................iv

LIST OF FIGURES .................................................................................................v

1.0 BASE G CAA CONTROLS..............................................................................1

1.1 Point Source Controls ........................................................................................................... 2 

1.1.1 Electric Generating Units (EGUs) ..................................................................................3 

1.1.2 Non-EGUs.......................................................................................................................9 

1.2 Area Source Controls.......................................................................................................... 11 

1.3 Mobile Sources ................................................................................................................... 12 

1.4 Non-Road............................................................................................................................ 12 

2.0 UNIFORM RATE OF PROGRESS...............................................................15

3.0 GEORGIA TECH SENSITIVITIES .............................................................17

3.1 Evaluation for Cohutta Wilderness Area, Georgia ............................................................. 17 

3.2 Evaluation for Okefenokee Wilderness Area, Georgia ...................................................... 18 

4.0 REASONABLE PROGRESS EVALUATION .............................................19

4.1 Area of Influence Analyses................................................................................................. 19 

4.2 Source Type Analyses ........................................................................................................ 21 

4.3 Back Trajectory Analyses................................................................................................... 23 

4.4 Area of Influence Data and Displays.................................................................................. 28 

4.5 Importance of Pollutants Other Than Sulfate ..................................................................... 40 

4.6 Summary of Emission Inventories Used in Cost Analysis................................................. 41 

4.7 Process in Preparing Files for Cost Effectiveness Curve Development............................. 43 

4.8 Application of AirControlNET Technologies .................................................................... 44 

4.9 Development of AOI-Based Cost Curves........................................................................... 45 

5.0 REASONABLE PROGRESS ASSESSMENT..............................................46

6.0 FOUR FACTOR ANALYSIS .........................................................................58

6.1 The Four Statutory Factors ................................................................................................. 58 

6.1.1 Cost of Compliance.......................................................................................................58 

6.1.2 Time Necessary for Compliance...................................................................................58 

6.1.3 Energy and Non-Air Quality Environmental Impacts of Compliance..........................59 

6.1.4 Remaining Useful Life of the Source ...........................................................................59 

6.2 Evaluating Four Statutory Factors for Specific SO2 Emissions Sources in Each Area of 

Influence ............................................................................................................................. 59 

6.2.1 Cost of Compliance.......................................................................................................60 

6.2.2 Time Necessary for Compliance...................................................................................60 

6.2.3 Energy and Non-Air Environmental Impacts ...............................................................61 

6.2.4 Remaining Useful Life..................................................................................................61 

6.3 Process of Applying Statutory Factors ............................................................................... 61 

6.4 Evaluation of Four-factor Eligible Emissions Units and Recommendations ..................... 63 
 Appendix H 

ii

6.4.1 GA Pacific Brunswick Cellulose, Power Boiler No. 4 (F1) ........................................75 

6.4.2 Georgia Pacific Brunswick Cellulose, Recovery Boiler No. 6 (M24).........................77 

6.4.3 Georgia Pacific Cedar Springs, Power Boiler No. 1 (U 500) ......................................78 

6.4.4 Georgia Pacific Cedar Springs, Power Boiler No. 2 (U 501) ......................................79 

6.4.5 Georgia Pacific Cedar Springs, Recovery Boiler No. 3 (R402) ..................................80 

6.4.6 Georgia Pacific Savannah River Mill, No. 3 Boiler (B001)........................................82 

6.4.7 Georgia Pacific Savannah River Mill, No. 4 Boiler (B002)........................................83 

6.4.8 Georgia Pacific Savannah River Mill, No. 5 Boiler (B003)........................................84 

6.4.9 Georgia Power Plant Kraft, Steam Generator 1...........................................................84 

6.4.10 Georgia Power Plant Kraft, Steam Generator 2.........................................................86 

6.4.11 Georgia Power Plant Kraft, Steam Generator 3.........................................................87 

6.4.12 Georgia Power Plant McIntosh, Steam Generator 1..................................................89 

6.4.13 Georgia Power Plant Mitchell, Steam Generator 3....................................................90 

6.4.14 International Paper Savannah Mill, Power Boiler 13 ................................................92 

6.4.15 Temple-Inland Rome Linerboard, No. 4 Power Boiler .............................................95 

7.0 BART.................................................................................................................99

7.1 Background......................................................................................................................... 99 

7.2 Approach to Implementation of BART Requirements..................................................... 100 

7.3 Identification of BART-Eligible Sources ......................................................................... 100 

7.4 Contribution Threshold..................................................................................................... 104 

7.5 Exemption of Point Source Volatile Organic Compounds for BART Purposes .............. 105 

7.5.1 Method ........................................................................................................................106 

7.5.2 Conclusions.................................................................................................................107 

7.6 Treatment of Ammonia Emissions for BART Purposes .................................................. 107 

7.6.1 Method ........................................................................................................................108 

7.6.2 Conclusions.................................................................................................................109 

8.0 Explanation of BART Exemption Criteria..................................................109

8.1 Background....................................................................................................................... 109 

8.1.1 Exemption Modeling ..................................................................................................110 

8.1.2 Model Plant Criteria....................................................................................................111 

8.1.3 Accepting an Emissions Limit....................................................................................112 

8.2 Use of New IMPROVE Equation..................................................................................... 115 

9.0 BART Determination.....................................................................................116

9.1 BART Subject Sources ..................................................................................................... 116 

9.1.1 BART-eligible Units and Existing Control.................................................................117 

9.2 BART Determination Analysis and Conclusion............................................................... 117 

10.0 Final Long Term Strategy And Reasonable Progress Goals..................118

10.1 Long-Term Strategy........................................................................................................ 118 

10.2 What Additional Emissions Controls Were Considered as Part of the Long-Term Strategy 

for Visibility Improvement by 2018? ............................................................................... 119 

10.3 Reasonable Progress Goals............................................................................................. 120 

REFERENCES: ...................................................................................................122
 Appendix H 

iii

LIST OF APPENDICES 

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

Appendix H.2 - VISTAS Class I Statistics 

Appendix H.3 - VISTAS Control Options Spreadsheet 

Appendix H.4 - Letters to Facilities 

Appendix H.5 - Emissions and Q/d for Georgia's BART Eligible sources 

Appendix H.6 - BART VOC, NH3, and Primary PM Sensitivity Modeling 

Appendix H.7 - BART Modeling Protocols 

Appendix H.8 - BART Determination Submittals 

Appendix H.9 - Correspondence Regarding Use of New IMPROVE Equation 

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

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

iv

LIST OF TABLES 

Table 1-1. Adjustments to IPM Control Determinations Specified by S/L Agencies for the Base 

G 2009/2018 EGU Inventories. ...................................................................................................... 4 

Table 1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the Base G 

2009/2018 EGU Inventories. .......................................................................................................... 6 

Table 4-1. Source types 2018 Base G4 modeling COHU – Percentage...................................... 21 

Table 4-2. Source types 2018 Base G4 modeling OKEF – Percentage....................................... 22 

Table 4-3. Source types 2018 Base G4 modeling WOLF – Percentage...................................... 22 

Table 4-4. Back Trajectory Model Parameters Selected for VISTAS AOI Analysis.................. 23 

Table 4-5. VISTAS 2002 Base Year Annual Emissions Summary (tons). ................................. 41 

Table 4-6. 2018 Base Case Annual Emissions Summary (tons). ................................................ 42 

Table 4-7. IPM Post Processing Assigned Device Codes and Applied SO2 Control Efficiencies.

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

Table 4-8. Emissions Weighted NETDC (MW) Association....................................................... 44 

Table 5-1. Numbers and percentage of 2018 SO2 emission units that contribute to Georgia Class 

I areas............................................................................................................................................ 48 

Table 5-2. Cohutta Wilderness Area Q/d, Q/d^2, RTMax, and fractional contribution analysis. 48 

Table 5-3. Okefenokee Wilderness Area Q/d, Q/d^2, RTMax, and fractional contribution 

analysis.......................................................................................................................................... 50 

Table 5-4. Wolf Island Q/d, Q/d^2, RTMax, and fractional contribution analysis. ..................... 52 

Table 5-5. Non-Georgia Class I Areas Q/d, Q/d^2, RTMax, and fractional contribution analysis 

(Georgia sources only).................................................................................................................. 53 

Table 5-6. Facilities and emissions units eligible for 4-factor analysis....................................... 55 

Table 5-7. Units dropped from four-factor analysis ..................................................................... 56 

Table 6-1. Summary of Four-factor Analyses – South Georgia Facilities ................................... 66 

Table 6-2. Summary of Four-Factor Analyses - North Georgia Facilities ................................... 72 

Table 6.3. Explanatory Notes for Summary of Four-Factor Analyses and Metrics ................... 73 

Table 7-1. GA BART-Eligible Sources and Distances to Respective Class I Areas.................. 103 

Table 7-2. Major BART NH3 Sources in the VISTAS Region .................................................. 109 

Table 8-1. BART Exemption Modeling Results......................................................................... 112 

Table 8-2 Facilities that demonstrated BART exemption based on model plant criteria or by 

accepting a limit of 250 tpy for visibility causing pollutants...................................................... 115 

Table 9-1 BART determination analysis for both the subject-to-BART sources....................... 117 

Table 10-1. Georgia Reasonable Progress Goals – 20 percent Worst Days............................... 121 

Table 10-2. Georgia Reasonable Progress Goals – 20 percent Best Days.................................. 121 
 Appendix H 

v

 LIST OF FIGURES 

Figure 1-1. Annual NH3 emissions – Base G4............................................................................. 13 

Figure 1-2. Annual PM2.5 emissions – Base G4.......................................................................... 14 

Figure 1-3. Annual NOx emissions – Base G4............................................................................ 14 

Figure 1-4. Annual SO2 emissions – Base G4. ............................................................................ 15 

Figure 2-1. Uniform Rate of Progress at Cohutta Wilderness...................................................... 16 

Figure 2-2. Uniform Rate of Progress at Okefenokee Wilderness ............................................... 16 

Figure 3-1. Sources of various visibility-reducing pollutants – COHU summer using 2009 Base 

D emissions................................................................................................................................... 18 

Figure 3-2. Sources of various visibility-reducing pollutants – OKEF summer using 2009 Base 

D emissions................................................................................................................................... 19 

Figure 4-1. Average Extinction for 20% Worst Visibility Days in 2000-2004 using New 

IMPROVE Equation (data from VIEWS Sep 2006). ................................................................... 20 

Figure 4-2. Example 72-hour back trajectories for 20% worst visibility days in 2002 for Cohutta 

Wilderness Area............................................................................................................................ 26 

Figure 4-3. Example 72-hour back trajectories for 20% worst visibility days in 2002 for 

Okefenokee Wilderness Area ....................................................................................................... 27 

Figure 4-4. Linville Gorge SO4 extinction-weighted residence time plots for the period 2000-

2004............................................................................................................................................... 29 

Figure 4-5. Shining Rock SO4 extinction-weighted residence time plots for the period 2000-

2004............................................................................................................................................... 29 

Figure 4-6. Swanquarter SO4 extinction-weighted residence time plots for the period 2000-

2004............................................................................................................................................... 30 

Figure 4-7. Great Smoky Mountains SO4 extinction-weighted residence time plots for the period 

2000-2004. .................................................................................................................................... 30 

Figure 4-8. Okefenokee Wilderness Area SO4 extinction-weighted residence time plots for the 

period 2000-2004.......................................................................................................................... 31 

Figure 4-9. Cape Romain SO4 extinction-weighted residence time plots for the period 2000-

2004............................................................................................................................................... 31 

Figure 4-10. Cohutta SO4 extinction-weighted residence time plots for the period 2000-2004. 32 

Figure 4-11. Sipsey SO4 extinction-weighted residence time plots for the period 2000-2004... 32 

Figure 4-12. Wolf Island SO4 extinction-weighted residence time plots for the period 2000-

2004............................................................................................................................................... 33 

Figure 4-13. Annual point source SO2 emissions for the VISTAS region in tons/year. (2002 

BaseG)........................................................................................................................................... 34 

Figure 4-14. Annual point source SO2 emissions for the VISTAS region in tons/year. (2018 

BaseG)........................................................................................................................................... 34 
 Appendix H 

vi

Figure 4-15. Cohutta 2002 SO2 Emissions * SO4 extinction-weighted residence time plots. ... 36 

Figure 4-16. Okefenokee 2002 SO2 Emissions * SO4 extinction-weighted residence time plots.

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

Figure 4-17. Wolf Island 2002 SO2 Emissions * SO4 extinction-weighted residence time plots.

....................................................................................................................................................... 37 

Figure 4-18. Cohutta 2018 SO2 Emissions * SO4 extinction-weighted residence time plots. ... 37 

Figure 4-19. Okefenokee 2018 SO2 Emissions * SO4 extinction-weighted residence time plots.

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

Figure 4-20. Wolf Island 2018 SO2 Emissions * SO4 extinction-weighted residence time plots.

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

Figure 4-21. Cohutta 2002 vs. 2018 SO2 emissions multiplied by residence time..................... 39 

Figure 4-22. Okefenokee 2002 vs. 2018 SO2 emissions multiplied by residence time. ............. 39 

Figure 4-23. Wolf Island 2002 vs. 2018 SO2 emissions multiplied by residence time............... 40 

Figure 4-24. VISTAS Base G2 SO2 Emissions Contribution by Major Source Sector.............. 43 

Figure 7-1. GA BART-Eligible Sources and Class I Areas....................................................... 102 

Figure 7-2. Location of VISTAS BART-Eligible Sources........................................................ 105 

Figure 7-3. Maximum Point VOC Impact ................................................................................. 107 

Figure 7-4. Maximum NH3 Impact - Maximum contributions of all BART-eligible NH3 point 

sources in the VISTAS region to haze in Class I areas during the CMAQ-modeled periods. ... 108 
 Appendix H 

1 of 122 

1.0 BASE G CAA CONTROLS 

2009 and 2018 emissions projections include the following existing State and Federal 

regulations: 

• Clean Air Interstate Rule (CAIR): Utility projections are based on Integrated Planning 

Model. CAIR will permanently cap emissions of sulfur dioxide (SO2) and nitrogen 

oxides (NOx) in the eastern United States. 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. 

• Georgia Rule 391-3-1-.02 (2) (sss) (i.e., The Multipollutant Control for Electric Utility 

Steam Generating Units) was enacted in 2007. The effective date of the rule varies for 

various EGU units, but it will start being effective from December 31, 2008, and will be 

in place over all the rule-effected units by January 1, 2018. 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. 

• 1-hr Ozone SIPs (Atlanta/Birmingham/Northern Kentucky). The purpose of a State 

implementation plan (SIP) is to demonstrate attainment or maintenance of the 1-hour 

ozone National Ambient Air Quality Standard (NAAQS). States must determine which 

Clean Air Act requirements are applicable to their area and submit plans to EPA for 

public comment and approval. 

• Georgia Rule 391-3-1-.02(2)(yy) (e.g., 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., a source with potential to emit > 50 tons/yr) of NOx located in 

the13-county Atlanta non-attainment area should apply reasonably available control 

technology (RACT) in controlling NOx emissions. Georgia EPD has required full 

compliance with NOx RACT limits since July 31, 1995. 

• Heavy Duty Diesel (2007) Engine Standard. This standard is 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. It also includes standards for NOx and nonmethane 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). 
 Appendix H 

2 of 122 

• Tier 2 Tail pipe. 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 

NOx emissions below a specified value.

• Large Spark Ignition and Recreational Vehicle Rule. Sets emission standards for these 

categories of nonroad engines and vehicles. 

• Nonroad Diesel Rule. Implements a low sulfur fuel requirement that affects both future 

(CMV) Commercial Marine Vessels and locomotive emissions. 

• Industrial Boiler/Process Heater/RICE MACT. The Environmental Protection Agency 

(EPA) issued final rules to substantially reduce emissions of toxic air pollutants from 

industrial, commercial and institutional boilers, process heaters and from stationary 

reciprocating internal combustion engines (RICE). These rules 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 four percent for SO2 

and 40 percent for PM10 and PM2.5. [It should be noted that EPA’s industrial boiler 

MACT rules were vacated on June 8, 2007. The emissions reductions that were modeled 

to account for the industrial boiler MACT were 1,343.5 tons/year of SO2, 879.4 tons/year 

of PM2.5, 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 (Appendix H.1). 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. 

The following are source category specific controls used to project future-year emissions 

inventories: 

1.1 Point Source Controls 

Different approaches were used for the Electric Generating Unit (EGU) and the non-EGU sectors 

of the point source inventory: 
 Appendix H 

3 of 122 

• For the EGUs, the State relied primarily on the Integrated Planning Model® (IPM®) to 

project future generation, as well as to calculate the impact of future emission control 

programs, to include CAIR. The IPM results were adjusted based on State and local 

(S/L) agency knowledge of planned emission controls at specific EGUs. 

• For non-EGUs, we used recently-updated growth and control data consistent with the 

data used in EPA’s CAIR analyses and supplemented these data with available S/L 

agency input and updated fuel use forecast data for the U.S. Department of Energy. 

 

For both sectors, we generated 2009 and 2018 inventories for a combined on-the-books (OTB) 

and on-the-way (OTW) control scenario. The OTB/OTW control scenario accounts for post2002 emission reductions from promulgated and proposed Federal, State, local, and site-specific 

control programs as of July 1, 2004. 

1.1.1 Electric Generating Units (EGUs) 

S/L agencies specified a number of changes to the IPM results to better reflect current 

information on when and where future controls would occur. These changes to the IPM results 

primarily involved S/L agency addition or subtraction of future emission controls based on the 

best available data from State rules, enforcement agreements, compliance plans, permits, and 

discussions/commitments from individual companies. 

Table 1-1 lists adjustments to IPM control determinations as specified by S/L agencies for the 

Base G 2009/2018 EGU inventories. Table 1-2 lists other adjustments to IPM results specified 

by S/L agencies for Base G 2009/2018 inventories. 
 Appendix H 

4 of 122 

Table 1-1. Adjustments to IPM Control Determinations Specified by S/L Agencies 

for the Base G 2009/2018 EGU Inventories. 

State Plant Name Unit

IPM State IPM State IPM State IPM State

3 & 4 SCR 

during 

ozone 

season

SCR year 

round from 

Consent 

Decree

SCR 

during 

ozone 

season

SCR year 

round from 

Consent 

Decree

None Scrubber None Scrubber

1, 2, 3 None SNCR SCR SNCR None None None None

4 None SNCR SCR SNCR None None Scrubber None

5 None None SCR SCR None None Scrubber None

4-Jan SCR None SCR None None None Scrubber None

5 SCR SCR SCR SCR Scrubber None Scrubber None

6 & 7 None None None None None None None None

8 & 9 None None None None None Scrubber None Scrubber

10 SCR SCR SCR SCR None Scrubber Scrubber Scrubber

1 None None None None None Scrubber None Scrubber

2 & 3 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber

2BLR SCR SCR SCR SCR None Scrubber Scrubber

3BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber

4BLR SCR SCR SCR SCR Scrubber Scrubber Scrubber

2 SCR SCR SCR SCR None Scrubber Scrubber

1, 2 None None None None None None None None

3 None None SCR None None None None None

1 None None None None Scrubber Scrubber Scrubber Scrubber

2, 3 None None None None None None None None

4 – 7 None None SCR None None None Scrubber None

1 None None SCR SCR None Scrubber Scrubber Scrubber

2 None None SCR SCR None Scrubber Scrubber Scrubber

3 None None SCR SCR None Scrubber Scrubber Scrubber

4 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber

1 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber

2 None None SCR SCR None Scrubber Scrubber Scrubber

3, 4 None SCR SCR SCR None Scrubber Scrubber Scrubber

IPM had 

scrubbers 

but little 

emission 

reductions

KY Ghent 

ORISID=1356

James H. 

Miller 

ORISID=6002

None None None

GA

Wansley 

ORISID=6052

Kraft 

ORISID=733

McIntosh 

ORISID=6124

Yates 

ORISID=728

Hammond 

ORISID=708

Scrubber Scrubber Scrubber

1 None None SCR None None

1 SCR SCR SCR SCR

Gorgas 

ORISID=8

Charles R. 

Lowman 

ORISID=56

IPM had 

retrofit 

scrubbers 

but little 

emission 

reductions

Bowen 

ORISID=703

None Scrubber Scrubber

SCR 

during 

ozone 

season

SCR 

probable 

year round 

due to 

CAIR

SCR year 

round due 

to CAIR

Barry 

ORISID=3

None None None

1BLR SCR SCR SCR SCR

NOx Emission Controls SO2 Emission Controls

2009 2018 2009 2018

1 & 2 SCR 

during 

ozone 

season

AL None

E C Gaston 

ORISID=26
 Appendix H 

5 of 122 

Table 1-1 (continued) 

State Plant Name 

and ID

Unit

IPM State IPM State IPM State IPM State

C1 None None SCR SCR None Scrubber Scrubber Scrubber

C2 None None SCR SCR None Scrubber Scrubber Scrubber

C3 None None SCR SCR None Scrubber Scrubber Scrubber

H1 SCR SCR SCR SCR Scrubber Scrubber Scrubber Scrubber

H2 None SCR SCR SCR Scrubber Scrubber Scrubber Scrubber

1 None None None None None Scrubber None Scrubber

2 None None SCR SCR None Scrubber Scrubber Scrubber

3 None None SCR SCR None Scrubber Scrubber Scrubber

3 SCR None SCR None None None None None

4 None None None None None None None None

WAT1 SCR SCR SCR SCR None Scrubber None Scrubber

WAT2 SCR SCR SCR SCR None Scrubber Scrubber Scrubber

CAN1 None None None None None None None None

CAN2 None None None None None None None None

CAN3 None None None None None Scrubber None Scrubber

CT1A None SCR None SCR None None None None

CT1B None SCR None SCR None None None None

1 – 8 SCR SCR SCR SCR None None Scrubber Scrubber

9 None SCR SCR SCR None None Scrubber Scrubber

1 – 10 SCR None SCR SCR None None None None

2 SCR None SCR SCR Scrubber None Scrubber Scrubber

3-Jan SCR None SCR SCR Scrubber None Scrubber Scrubber

Jeffries 

ORISID=3319

Wateree 

ORISID=3297

Canadys 

ORISID=3280

Rainey 

ORISID=7834

Coleman 

ORISID=1381

HMP&L 

Station 2

KY

E W Brown 

ORISID=1355

NOx Emission Controls SO2 Emission Controls

2009 2018 2009 2018

Kingston 

ORISID=3407

Johnsonville 

ORISID=3406

Willow Island 

ORISID=3946

Kammer 

ORISID=3947

SC

TN

WV
 Appendix H 

6 of 122 

Table 1-2. Other Adjustments to IPM Results Specified by S/L Agencies for the 

Base G 2009/2018 EGU Inventories. 

State Plant Name and ID Units Nature of Update/Correction 

FL Central Power and Lime 

ORISID= 10333 

GEN1 Central Power and Lime (ORIS10333) is a duplicate entry. This is point 18 in 

Florida Crushed Stone (12-053-0530021). Removed IPM emissions for Central 

Power and Lime. 

 Cedar Bay Generating 

ORISID=10672 

GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this 

facility and the cogeneration facility should not grow faster than the underlying 

industry. Cedar Bay is connected to Stone Container (12-031-0310067). 

Replaced IPM emissions with 2002 emissions for Cedar Bay (12-031-0310337) 

times the growth factors for Stone Container. 

 Indiantown Cogeneration 

ORISID=50976 

GEN1 FLDEP disagrees with IPM projections - no knowledge of expansion of this 

facility and the cogeneration facility should not grow faster than the underlying 

industry. Indiantown is connected to Louis Dreyfus Citrus (12-085-0850002). 

Replaced IPM emissions with 2002 emissions for Indiantown (12-085-0850102) 

times the growth factors for Louis Drefus Citrus. 

GA Bowen 

ORISID=703 

1BLR 

2BLR 

3BLR 

4BLR 

IPM indicated retrofit scrubbers on all 4 units in 2009, but the IPM emissions 

showed little reductions from 2002 levels. Changed emissions to reflect 

scrubbers on 1BLR and 2BLR by 2009. 

 Wansley 

ORISID=6052 

1, 2 IPM indicated retrofit scrubbers on both units in 2009, but the IPM emissions 

showed little reductions from 2002 levels. Changed emissions to reflect one 

scrubber on Unit 1 by 2009. 

 Riverside 

ORISID=734 

4 All of plant Riverside was retired from service June 1, 2005; emissions set to 

zero in 2009 and 2018. 

 McIntosh 

ORISID=727 

CT10A 

CT10B 

CT11A 

CT11B 

The McIntosh Combined Cycle facility became commercial June 1, 2005. 

Added 346 tons of NOx and 121 tons of SO2 per unit to the 2009 and 2018 

inventories. 

 Longleaf Energy Station 1, 2 Longleaf Energy Station is being proposed by LS Power Development, Inc. GA 

specified that the emissions from this proposed plant be included in the 2018 

projections. Boilers 1 and 2 added 1,882 tons of NOx and 3,227 tons of SO2 per 

unit to the 2018 inventory. 

MS R D Morrow 

ORISID=6061 

1, 2 Revised the 2018 emissions to reflect controls not indicated by IPM. The SO2

emissions are much lower than IPM, but their expected NOx emissions are 

actually higher than IPM. The controls will be coming online 2009 or 2010, so 

the 2009 inventory did not change. 

 Jack Watson (2049) 

Victor J Daniel (6073) 

Chevron Oil (2047) 

All MS DEQ specified that the emission projections provided by the Southern 

Company for their units in Mississippi were to be used instead of the IPM 

results. 
 Appendix H 

7 of 122 

Table 1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

NC G G Allen (2718) 

Belews Creek (8042)1 

Buck (2720) 

Cliffside (2721) 

Dan River (2723) 

Marshall (2727) 

Riverbend (2732) 

All Replaced all IPM 2009 results with emission projections from Duke 

Power’s NC Clean Air Compliance Plan for 2006. Used IPM results for 

2018 

 Asheville (2706) 

Cape Fear (2708) 

Lee (2709) 

Mayo (6250) 

Roxboro (2712) 

Sutton (2713) 

Weatherspoon (2716) 

All Replaced all IPM 2009 results with emission projections from Progress 

Energy’s NC Clean Smokestacks Act Calendar Year 2005 Progress Report. 

Used IPM results for 2018 

 Dwayne Collier Battle 

Cogeneration Facility 

ORISID=10384 

GEN1 

GEN2 

Dwayne Collier Battle is a duplicate entry. This is Cogentrix of Rocky 

Mount (37-065-3706500146, stacks G-26 and G-27). Duplicate entries 

were removed both the 2009 and 2018 inventories. 

 Kannapolis Energy 

Partners 

ORISID=10626 

GEN2 

GEN3 

Kannapolis Energy emissions are being used as credits for another facility. 

IPM emissions from this facility (37-025-ORIS10626) were removed from 

the EGU inventory for 2009 and 2018. Emissions from Kannapolis Energy 

(37-025-3702500113) were carried forward in the 2009/2018. 

SC Cross 

ORISID=130 

1, 2 Unit 1: upgrade scrubber from 82 percent to 95 percent removal efficiency 

by June 30, 2006. Recalculate emissions based on upgrade in control 

efficiency. 

Unit 2: upgrade scrubber from 70 percent to 87 percent removal efficiency 

by June 30, 2006. Recalculate emissions based on upgrade in control 

efficiency. 

 Winyah 

ORISID=6249 

1 – 4 Unit 1: Install scrubber that meets 95 percent removal efficiency by Dec. 

31, 2008; Upgrade ESP from 0.38 to 0.03 lb/mmBTU by Dec. 31, 2008 

Unit 2: Replace scrubber with one that meets 95 percent removal efficiency 

from 45 percent by Dec. 31, 2008; Upgrade ESP from 0.10 to 0.03 

lb/mmBTU by Dec. 31, 2008 

Unit 3: Upgrade scrubber from 70 percent to 90 percent removal efficiency 

by Dec. 31, 2012; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 

2012 

Unit 4: Upgrade scrubber from 70 percent to 90 percent removal efficiency 

by Dec. 31, 2007; Upgrade ESP from 0.10 to 0.03 lb/mmBTU by Dec. 31, 

2007 

Recalculated SO2 and PM emissions based on upgrade in control 

efficiencies. 
 Appendix H 

8 of 122 

Table 1-2 (continued) 

 State Plant Name and ID Unit Nature of Update/Correction 

SC Dolphus Grainger 

ORISID=3317 

1, 2 Unit 1: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. 

Reduced PM10 and PM25 emissions in 2018 by 95 percent based on change in 

allowable emission rate 

Unit 2: Install low NOx burners that meet 0.46 lb/mmBTU from 0.9 by May 

1, 2004. Recalculated NOx emissions using 0.46/lbs/mmBtu and IPM heat 

input 

Unit 2: Upgrade ESP from 0.60 to 0.03 lb/mmBTU by Dec. 31, 2012. 

Reduced PM10 and PM25 emissions in 2018 by 95 percent based on change 

in allowable emission rate 

SC Jeffries 

ORISID=3319 

3, 4 Unit 3: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. 

Reduced PM10 and PM25 emissions in 2018 by 94.44 percent based on 

change in allowable emission rate 

Unit 4: Upgrade ESP from 0.54 to 0.03 lb/mmBTU by Dec. 31, 2012. 

Reduced PM10 and PM25 emissions in 2018 by 94.44 percent based on 

change in allowable emission rate 

 W S Lee 

ORISID=3264 

1, 2 IPM does not indicate that these units are installing SOFA NOx control 

technology by April 30, 2006 to meet 0.27 lb/mmBTU, down from 0.45 

lb/mmBtu. Calculated NOx emissions using IPM heat input and 0.27 

lbs/mmBtu 

 Generic Unit 

ORISID=900545 

All All predictions for generic units appear reasonable with the exception of 

Plant ID ORIS900545 Point ID GSC45 which was modeled in Georgetown 

County. It will be very difficult to add new generation this close to the 

Cape Romain Class I area. Santee Cooper has no plans for future 

generation in Georgetown County, but does have plans for new future 

generation in Florence County. This unit was moved to coordinates 

specified in Florence County. 

VA AEP Clinch River 

ORISID=3775 

1, 2, 3 Replaced all 2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

 AEP Glen Lyn 

ORISID=3776 

51, 52, 6 Replaced all 2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

 Dominion Clover 

ORISID=7213 

1, 2 Replaced all 2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

 Dominion Bremo 

ORISID=3796 

3, 4 Replaced all 2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

 Dominion Chesterfield 

ORISID=3797 

3, 4, 

5, 6 

Replaced all 2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

 Dominion Yorktown 

ORISID=3809 

1, 2, 3 Units 1, 2: Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

Unit 3: IPM predicts zero heat input for this 880 MW #6 oil fired unit. IPM 

does not predict a retirement, just that the heat input is zero. Dominion 

plans to continue to operate Unit 3. Replaced all 2009/2018 IPM results 

using VADEQ’s growth and control estimates. 
 Appendix H 

9 of 122 

Table 1-2 (continued) 

State Plant Name and ID Unit Nature of Update/Correction 

VA Dominion Chesapeake 

ORISID=3803 

1 – 4 Replaced all 2009/2018 IPM results using VADEQ’s growth and control 

estimates. 

 Dominion Possum Point 

ORISID=3804 

3 & 4 

5 

6 

Unit 3&4: IPM had 137 tons of NOx for these units in 2009 and 111 tons in 

2018. VA DEQ specified that the permitted emission rates should be used, 

which equates to 3,066 tons in 2009 and 2018. 

Unit 5: IPM had zero heat input for this unit. Replaced all 2009/2018 IPM 

results using VADEQ’s growth and control estimates. 

Unit 6: Replaced all 2009/2018 IPM results using VADEQ’s growth and 

control estimates. 

 Potomac River 

ORISID=3788 

1 - 5 Units 1&2: IPM retired these units. Mirant has no plans at this time to 

retire any units. Replaced all 2009/2018 IPM results using VADEQ’s 

growth and control estimates. 

Units 3, 4, 5: Replaced all 2009/2018 IPM results using VADEQ’s growth 

and control estimates. 

WV Albright 

ORISID=3942 

1, 2 IPM predicted early retirement for these units. AEP indicated there are no 

for early retirement. For 2009, used 2002 emissions as these units are not 

likely to retire by 2009. For 2018, used IPM prediction of retirement. 

 Rivesville 

ORISID=3945 

7, 8 IPM predicted early retirement for these units. AEP indicated there are no 

for early retirement. For 2009, used 2002 emissions as these units are not 

likely to retire by 2009. For 2018, used IPM prediction of retirement. 

 Willow Island 

ORISID=3946 

1, 2 Unit 1: IPM predicted early retirement for these units. AEP indicated there 

are no for early retirement. For 2009, used 2002 emissions as these units 

are not likely to retire by 2009. For 2018, used IPM prediction of 

retirement. 

Unit 2: IPM predicted SCR and scrubber for 2009. These controls will not 

be in place by 2009. 

 North Branch Power 

Station 

ORISID=7537 

1A, 1B SO2 Permit Rate was corrected from 2.7 to 0.678 lb/MMBtu. Used SO2

Permit Rate of 0.678 lb/MMBtu and IPM predicted total fuel used to 

calculate SO2 emissions in 2009 and 2018 

 Mt. Storm 

ORISID=3954 

1, 2, 3 SO2 Permit Rate was corrected from 2.7 to 0.15 lb/MMBtu. Used SO2

Permit Rate of 0.15 lb/MMBtu and IPM predicted total fuel used to 

calculate SO2 emissions in 2009 and 2018 

1.1.2 Non-EGUs 

The general approach for assembling future-year data was to use recently-updated growth and 

control data consistent with the data used in EPA’s Clean Air Interstate Rule analyses, 

supplement these data with available stakeholder input, and provide the results for stakeholder 

review to ensure accuracy.

MACTEC (MACTEC, 2006) used the same control programs for both the 2009 and 2018 nonEGU point inventory. Two control scenarios were developed: on-the-books (OTB) controls and 
 Appendix H 

10 of 122 

on-the-way (OTW) controls. The OTB control scenario accounts for post-2002 emission 

reductions from recently-promulgated Federal, State, local, and site-specific control programs. 

The OTW control scenario accounts for proposed (but not final) control programs that are 

reasonably anticipated to result in post-2002 emission reductions. 

Maximum achievable control technology (MACT) requirements were also applied, as 

documented in the report entitled Control Packet Development and Data Sources, dated July 14, 

2004. The point source MACTs and associated emission reductions were derived 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. Emission reductions were applied only for MACT standards with an 

initial compliance date of 2002 or later. 

The final Phase II NOx SIP call rule was finalized on April 21, 2004. States had until April 21, 

2005, to submit SIPs meeting the Phase II NOx budget requirements. The Phase II rule applies to 

large IC engines, which are primarily used in pipeline transmission service at compressor 

stations. We identified affected units using the same methodology as was used by EPA in the 

proposed Phase II rule (i.e., a large IC engine is one that emitted, on average, more than one tonper-day during 2002). The final rule reflects a control level of 82 percent for natural gas-fired IC 

engines and 90 percent for diesel or dual fuel categories. Several S/L agencies provided more 

specific information on the anticipated controls at the compressor stations. This information was 

used instead of the default approach used by EPA in the proposed Phase II rule. 

A summary of Non-EGU point source control programs included in 2009/2018 

projection inventories include: 

• Atlanta/Northern Kentucky/Birmingham 1-hr Ozone Non-attainment SIPs; 

• Industrial Boiler/Process Heater/RICE MACT. EPA’s industrial boiler MACT rules 

were vacated on June 8, 2007. The emissions reductions that were modeled to account 

for the industrial boiler MACT were 1,343.5 tons/year of SO2, 879.4 tons/year of PM2.5, 

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; 

• NOx RACT in 8-hr Ozone NAA SIPs; 

• Petroleum Refinery Initiative (October 1, 2003 notice; MS & WV). This initiative 

addresses the most significant Clean Air Act compliance concerns affecting the 

petroleum refinery industry. Since December 2000, 17 global refinery settlements have 

been reached with refiners representing nearly 77 percent of domestic refining capacity. 

Three refineries in the VISTAS region are affected by two October 2003 Clean Air Act 

settlements under the EPA Petroleum Refinery Initiative. The refineries are: (1) the 
 Appendix H 

11 of 122 

Chevron refinery in Pascagoula, Mississippi; (2) the Ergon refinery in Vicksburg, 

Mississpipp; and (3) the Ergon refinery in Newell, West Virginia; 

• Reasonable Further Progress 3 percent plans where in place for 1-hour plans 

(Metropolitan Washington, DC, and Atlanta, Georgia); 

• VOC 2-, 4-, 7-, and 10-year MACT Standards. The point source MACTs and associated 

emission reductions were derived 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; 

• Combustion Turbine MACT. The projection inventories do not include the NOx cobenefit effects of the MACT regulations for Gas Turbines or stationary Reciprocating 

Internal Combustion Engines, which EPA estimates to be small compared to the overall 

inventory; and 

• NOx SIP Call (Phase II – remaining States & IC engines). 

For more information on the development of point source inventories, see Appendix C of the SIP 

narrative. 

1.2 Area Source Controls 

Controls (including control efficiency, rule effectiveness and rule penetration) provided by the 

States or originally developed for use in estimating projected emissions for U.S. EPA’s Heavy 

Duty Diesel (HDD) rulemaking emission projections and used in the Clean Air Interstate Rule 

(CAIR) projections were used to calculate controlled emissions. 

The controls obtained by MACTEC (MACTEC, 2006) for the HDD rulemaking were controls 

for the years 2007, 2020, and 2030. Since MACTEC was preparing 2009 and 2018 projections, 

control values for intermediate years were prepared using a straight-line interpolation of control 

level between 2007 and 2020. 

State-submitted controls had precedence over the U.S. EPA-developed controls. Control 

measures submitted by the Georgia Environmental Protection Division (GA EPD) include Stage 

I controls for gasoline dispensing facilities and open burning controls. 

As part of the air toxics program, Stage I controls for gasoline dispensing facilities was adopted 

by the State and became effective May 1990 with final compliance by January 1, 1994. Stage I 

is the vapor recovery technology on the underground storage tanks and reduces the emissions 

during the tank-filling operations at service stations. 

The GA EPD is responsible for going to all gasoline-dispensing facilities and testing the fuels to 

ensure that they meet the quality standards of the State. The GA EPD checks for Stage I controls 
 Appendix H 

12 of 122 

and proper maintenance of the control equipment. If a facility is not found to be properly 

maintaining the control equipment, then the GA EPD sends a notice of violation informing the 

facility that the controls are required and gives the facility time to correct the violation before 

fines are accessed. From this information, the rule effectiveness and rule penetration can be 

estimated. The rule effectiveness is the percentage of facilities complying with the rule, 

whereas, the rule penetration is the percentage of facilities requiring Stage I controls. Control 

efficiency is the expected percent reduction from this control technology. 

Open burning is treated as a means of waste disposal in rural areas. Materials burned generally 

include household trash, agricultural refuse, landscaping refuse, or scrap wood. The open 

burning emissions inventory includes SCC 2610030000, residential open burning of household 

waste and SCC 2610000100, and open burning of yard trimmings. Since it is illegal to burn 

within the corporate limits, the rural population in each county is used to estimate emissions. 

For more information on the development of area source inventories, see Appendix C of the SIP 

narrative. 

1.3 Mobile Sources 

Local controls included vehicle emissions inspection (i.e., I/M) programs, Stage II vapor 

recovery programs, anti-tampering programs, etc. By nature, the assumptions used for the 2002 

initial base-year inventory vary across the VISTAS region, but our presumption is that these data 

accurately reflected each State’s situation as it existed in 2002. If a State had no plans to change 

program requirements between 2002 and 2018, we proposed to maintain the 2002 program 

descriptions without change. However, if a State planned changes, we requested information on 

those plans. In the final implementation of the inventory, Stage II controls were exercised in the 

area source component of the inventory, since the units used to develop Stage II refueling 

estimates are different between MOBILE6 and the NONROAD models. 

For more information on the development of mobile source inventories, see Appendix C of the 

SIP narrative. 

1.4 Non-Road 

Using the 2002 base-year emissions inventory for aircraft, locomotives, and commercial marine 

vessels (CMV) prepared as described earlier in this document, corresponding emission 

projections for 2009 and 2018 were developed. Detailed inventory data (both before and after 

controls) for these same emission sources for 1996, 2010, 2015, and 2020 were obtained from 

the EPA's Clean Air Interstate Rule (CAIR) Technical Support Document. Using these data, 

combined growth and control factors for the period 2002-2009 and 2002-2018 were estimated 

using straight-line interpolation between 1996 and 2010 (for 2009) and 2015 and 2020 (for 

2018). This is done at the State-county-SCC-pollutant level of detail. According to EPA 

documentation, the CAIR baseline emissions include the impacts of the Tier 4 (T4) non-road 

diesel rulemaking, which implements a low-sulfur fuel requirement that affects both future CMV 

and locomotive emissions. 
 Appendix H 

13 of 122 

For more information on the development of non-road source inventories, see Appendix C of the 

SIP narrative. 

1.5 Summary of Emissions Projections 

Figures 1.1-1.4 depict pollutant totals for NH3, PM2.5, NOx, and SO2 for the various sectors by 

state for 2002, 2009, and 2018 Base G2 modeling. The totals are presented assuming the 

anticipated growth and implementation discussed in previous subsections. As can be seen in 

Figure 1-1 there is a gradual increase in the ammonia emissions. In Figure1-2, PM 2.5 emissions 

do not show any relative change in 2009 or 2018 as compared to 2002. Although, in Georgia, 

they are showing a slightly increasing trend. NOx and SO2 emissions in Figure 1-3 and 1-4, 

respectively, show a steep decrease in their 2018 emissions as compared to 2002. This decrease 

can be attributed to various Federal and State controls that will be in place on or before 2018. 

Figure 1-1. Annual NH3 emissions – Base G4. 

0

20

40

60

80

100

120

140

160

180

200

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NH3 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW
 Appendix H 

14 of 122 

Figure 1-2. Annual PM2.5 emissions – Base G4. 

Figure 1-3. Annual NOx emissions – Base G4. 

0

50

100

150

200

250

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual PM-2.5 (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

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual NOx (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW
 Appendix H 

15 of 122 

Figure 1-4. Annual SO2 emissions – Base G4. 

2.0 UNIFORM RATE OF PROGRESS 

The linear rate of improvement sufficient to attain natural conditions by 2064 is referred to as the 

“uniform rate of progress” or “glide path.” The baseline represents the starting point from which 

reasonable progress will be measured. There are two baseline values for each Class I area. 

Using 2000 - 2004 Interagency Monitoring of Protected Visual Environments (IMPROVE) 

monitoring data, the deciview values for the 20% best days in each year are averaged together, 

producing a single average deciview value for the best days. Similarly, the deciview values for 

the 20% worst days in each year are averaged together producing a single average deciview 

value for the worst days. Extinction from individual PM components is calculated from the 

IMPROVE equation (EPA, 2003; Hand and Malm, 2006). EPA defined target natural conditions 

in 2064 for each Class I area (EPA, 2003). For each VISTAS Class I area, a baseline visibility 

using 2000-2004 IMPROVE data and uniform rate of progress was established, using EPA 

default assumptions for calculating visibility and natural background. Most recently, the 

scientific community has reviewed the assumptions used to calculate current and natural 

background visibility and has agreed to revised methods (Hand and Malm, 2006, Pitchford, 

2006). VISTAS intends to present both the original and revised methods to calculate visibility 

and visibility improvement. Figures 2.1-2.2 illustrate the average 20% worst visibility days in 

the 2000-2004 baseline period for Cohutta Wilderness Area (COHU), and Okefenokee 

Wilderness Area (OKEF), the target natural condition in 2064 for the 20% worst days, and the 

incremental deciview changes assuming a uniform rate of progress between current and natural 

0

100

200

300

400

500

600

700

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW
 Appendix H 

16 of 122 

conditions in 2064, using the original method for calculating visibility. This is known as 

“glidepath.” 

Figure 2-1. Uniform Rate of Progress at Cohutta Wilderness 

Figure 2-2. Uniform Rate of Progress at Okefenokee Wilderness 

Uniform Rate of Reasonable Progress Glide Path

Okefenokee

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

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation

Uniform Rate of Reasonable Progress Glide Path

Cohutta

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

Year

Haziness Index (Deciviews)

Glide Path Natural Condition (Worst Days) Observation
 Appendix H 

17 of 122 

3.0 GEORGIA TECH SENSITIVITIES 

Georgia Tech performed emission sensitivities to examine the impact of emission 

reductions on regional haze, annual PM2.5, and 8-hour ozone concentrations using 

CMAQv4.4_SOA modifications on the VISTAS 12 km modeling domain, using the 2009 

OTW (on the way) BaseD emissions. Once the key pollutants contributing to visibility 

impairment at each Class I area were identified, the sources or source categories 

responsible for emitting these pollutants or pollutant precursors were determined. 

Emissions sensitivity analyses were conducted using CMAQ with 2009 Base D inventory 

and considering 30% reductions from major pollutants and source categories. The 

sensitivity runs were initially designed to consider pollutant contributions in 2009 to 

PM2.5 in urban areas; results were also considered for Class I areas even though the full 

benefit of controls anticipated by 2018 are not included in these sensitivity analyses. 

Results are qualitatively similar to previous sensitivity results using an earlier (Base A) 

2018 inventory. While the 2009 sensitivity analyses cannot be used to judge absolute 

contributions from each state or source sector, the results do indicate relative levels of 

responses among pollutants, sectors, and geographic areas. 

3.1 Evaluation for Cohutta Wilderness Area, Georgia 

Figure 3-1 shows the results of emissions sensitivity run for COHU for summer (since 

summer is when 20% worst days occur). CMAQ was run using 30% reductions from the 

2009 Base D inventory assumptions for implementing existing State and Federal 

regulations (listed on Page 2) for major source categories of SO2, NOx, VOC, and PM. 

The results identify geographic origins for visibility impairing pollutants, and serve as a 

good starting point when considering potential air quality benefits from additional 

controls for specific source sectors in VISTAS states or neighboring RPOs. The greatest 

benefits at COHU in 2009 are projected to come from further reducing SO2 from electric 

generating utilities (EGUs). Additional, smaller benefits are projected from additional 

SO2 emission reductions from non-utility, industrial point sources. Reductions of 

nitrogen oxide emissions from point sources (EGU and non-EGU) or ground-level 

sources (on road vehicles, off road engines, and area sources) and reductions of primary 

carbon from point- or ground-level sources are projected to be significantly less 

beneficial than reductions in SO2 emissions. Reductions in anthropogenic VOC 

emissions show no response in visibility, while a 30 percent reduction in biogenic VOC 

emissions result in a measurable improvement. However, controlling the VOCs from 

vegetation is not possible or appropriate. For this sensitivity run, further reducing SO2 

emissions from electricity-generating utilities in Alabama, Georgia, West Virginia, 

Tennessee, and North Carolina would have the greatest benefit for COHU; reductions 

from electric generating utilities in other VISTAS states would have additional but 

smaller benefits at COHU. 
 Appendix H 

18 of 122 

Figure 3-1. Sources of various visibility-reducing pollutants – COHU summer using 

2009 Base D emissions. 

3.2 Evaluation for Okefenokee Wilderness Area, Georgia 

Figure 3-2 shows the results of the emissions sensitivity run for OKEF for summer (since 

summer is when 20% worst days occur). CMAQ was run using 30% reductions from the 

2009 Base D inventory assumptions for implementing existing state and federal 

regulations (listed on page 4) for major source categories of SO2, NOx, and PM. The 

results identify geographic origins for visibility impairing pollutants, and serve as a good 

starting point when considering potential air quality benefits from additional controls for 

specific source sectors in VISTAS states or neighboring RPOs. The greatest benefits at 

OKEF in 2009 are projected to come from further reducing SO2 from electric generating 

utilities (EGUs). Additional, smaller benefits are projected from additional SO2 emission 

reductions from non-utility, industrial point sources. Reductions of nitrogen oxide 

emissions from point sources (EGU and non-EGU) or ground level sources (on road 

vehicles, off road engines, and area sources) and reductions of primary carbon from point 

or ground level sources are projected to be significantly less beneficial than reductions in 

SO2 emissions. Reductions in anthropogenic VOC emissions show no response in 

visibility, while a 30 percent reduction in biogenic VOC emissions result in a measurable 

improvement. However, controlling the VOCs from vegetation is not possible or 

appropriate. For this sensitivity run, further reducing SO2 emissions from electricity 

generating utilities in Alabama, Florida, and Georgia, would have the greatest benefit for 

OKEF. 
 Appendix H 

19 of 122 

Figure 3-2. Sources of various visibility-reducing pollutants – OKEF summer using 

2009 Base D emissions

4.0 REASONABLE PROGRESS EVALUATION 

4.1 Area of Influence Analyses

The objective of the VISTAS Area of Influence analysis is to identify the geographic 

source regions that are contributing to visibility impairment at the Class I areas on the 

20% worst visibility days. This information will be used by the State as part of the 

evaluation and demonstration of reasonable progress toward visibility improvement in 

Class I areas. 

VISTAS’ contribution assessment based on IMPROVE monitoring data (Brewer and 

Adlhoch, 2005) demonstrated that ammonium sulfate is the major contributor to PM2.5 

mass and visibility impairment at Class I areas in the VISTAS and neighboring states. As 

illustrated in Figure 4-1, on the 20% worst visibility days in 2000-2004, ammonium 

sulfate accounted for greater than 70% of the calculated light extinction at Class I areas in 

the Southern Appalachians and greater than 60% of the calculated light extinction for 
 Appendix H 

20 of 122 

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

CADI1

BRIG1

BRET1

MING1

HEGL1UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm -1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

0

50

100

150

200

250

300

SWAN1

ROMA1

OKEF1

EVER1

CHAS1

SAMA1DOSO1

SHEN1

JARI1

LIGO1

SHRO1

GRSM1

COHU1

SIPS1

MACA1

CADI1

BRIG1

BRET1

MING1

HEGL1UPBU1

CACR1

VISTAS coastal VISTAS inland non-VISTAS

Extinction (Mm -1)

Sea Salt

CM

Soil

EC

POM

Amm NO3

Amm SO4

Rayleigh

Figure 4-1. Average Extinction for 20% Worst Visibility Days in 2000-2004 using 

New IMPROVE Equation (data from VIEWS Sep 2006). 

coastal sites in the VISTAS states (excepting Everglades). In contrast, ammonium nitrate 

contributed less than 5% of the calculated light extinction at VISTAS Class I areas on the 

20% worst visibility days. (Nitrate has a somewhat larger contribution on 20% worst 

days at Class I areas in neighboring states to the VISTAS region.) Particulate organic 

matter (organic carbon) accounted for 10-20% of light extinction on 20% worst visibility 

days (except Everglades where organic carbon accounted for 40%). 

VISTAS emissions sensitivity analyses using the CMAQ regional air quality model 

project that reductions in SO2 emissions from Electric Generating Utilities (EGU) and 

non-EGU industrial point sources will result in the greatest improvements in visibility at 

VISTAS Class I areas. EGU and non-EGU industrial point sources comprise 95+% of 

the SO2 emissions inventory in the VISTAS states. The emissions sensitivity analyses 

also indicate that improvements in visibility from reductions in NOx or primary carbon 

emissions from ground-level sources or point sources would be small. Based on these 

analyses, VISTAS states chose to focus their reasonable progress evaluation for the first 

regional haze SIP on potential controls of SO2 emissions from EGU and non-EGU point 

sources. To select the specific point sources that would be considered for each Class I 

area, states first identified the geographic areas that most likely influence visibility in 

each Class I area and then identified the major SO2 point sources in that geographic area. 
 Appendix H 

21 of 122 

4.2 Source Type Analyses 

The following analyses are illustrative of an initial approach from September 2005 to 

evaluate potential control strategies. These analyses rely on the 200 km area 

surrounding the Class I area and use the Base F4 model run. 

VISTAS emissions inventory for the simplest area of influence, the 200 km concentric 

circle, indicated for COHU in 2018 that fuel combustion from electric utilities and 

industrial processes produces the majority of the remaining SO2 emissions (Table 4-1), 

with 86% of 2018 SO2 total coming from fuel combustion. 

Table 4-1. Source types 2018 Base G4 modeling COHU – Percentage. 

Annual 2018 BaseG2 Emissions (%) 

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%

VISTAS Total 100% 100% 100% 100% 100% 100% 100%

VISTAS emissions inventory for the simplest area of influence, the 200 km concentric 

circle, indicated for OKEF in 2018 that fuel combustion from electric utilities and 

industrial processes produces the majority of the remaining SO2 emissions (Table 4-2), 

with 82% of 2018 SO2 total coming from fuel combustion. 
 Appendix H 

22 of 122 

Table 4-2. Source types 2018 Base G4 modeling OKEF – Percentage. 

Annual 2018 BaseG2 Emissions (%) 

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 0% 0% 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%

VISTAS emissions inventory for the simplest area of influence, the 200 km concentric 

circle, indicated for WOLF in 2018 that fuel combustion from electric utilities and 

industrial processes produces the majority of the remaining SO2 emissions (Table 4-3), 

with 84% of 2018 SO2 total coming from fuel combustion. 

Table 4-3. Source types 2018 Base G4 modeling WOLF – Percentage. 

Annual 2018 BaseG2 Emissions (%) 

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%

VISTAS Total 100% 100% 100% 100% 100% 100% 100%
 Appendix H 

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4.3 Back Trajectory Analyses 

The GA EPD defined AOIs to identify source regions for which additional controls might 

be considered and that are likely to have the greatest impact on each Class I area. Initial 

focus on AOIs is on SO2 emissions because SO4 contributes greater than 60% of the 

calculated light extinction on the haziest days. In fact, figure 4-1 shows that for Cohutta 

(COHU), SO4 contributes roughly 80% to the calculated light extinction on the haziest 

days. To better understand the sources that should be considered in a four factor analysis 

for reasonable progress, VISTAS contracted ENVIRON to partner with VISTAS’s Data 

Analysis contractor, Air Resource Specialists (ARS), to provide SO2 Areas of Influence 

for each VISTAS and six neighboring Class I areas. ARS generated meteorological back 

trajectories for IMPROVE sites in VISTAS and neighboring states. Back trajectory 

analyses use interpolated measured or modeled meteorological fields to estimate the most 

likely central path of air masses that arrive at a receptor at a given time. The method 

essentially follows a parcel of air backward in hourly steps for a specified length of time. 

Back trajectories account for the impact of wind direction and wind speed on delivery of 

emissions to the receptor, but do not account for chemical transformation and dispersion 

of emissions. 

Trajectories were generated using the Hybrid-Single Particle Lagrangian Integrated 

Trajectory (HYSPLIT) model developed by the National Oceanic and Atmospheric 

Administration’s (NOAA) Air Resources Laboratory (ARL). HYSPLIT uses archived 3-

dimensional meteorological fields generated from observations and short-term forecasts. 

HYSPLIT can be run to generate forward or backward trajectories using several available 

meteorological data archives. 

The data archives used in this analysis were the National Weather Service's National 

Centers for Environmental Prediction Eta Data Assimilation System (EDAS). The EDAS 

fields are archived by the ARL across the continental U.S., including a buffer zone, at a 

horizontal resolution of 80 km before 2004, and at a horizontal resolution of 40 km 

starting in 2004. Detailed information regarding the trajectory model and these data sets 

can be found on NOAA’s Web site (http://www.arl.noaa.gov/ready/hysplit4.html). 

The major model parameters selected for this analysis include those listed in Table 4-4. 

Table 4-4. Back Trajectory Model Parameters Selected for VISTAS AOI Analysis 

Model Parameter Value 

Trajectory duration 72 hours backward in time 

Top of model domain 14,000 meters 

Vertical motion option used model data 

Meteorological Field EDAS 

End Times 0600, 1200, 1800 and 2400 EST 

End Heights 100 and 500 m 
 Appendix H 

24 of 122 

The choice of these parameters affects the trajectories generated and the final attribution 

analyses. In particular, trajectories tend to become increasingly uncertain the further 

back in time they are used. Vertical motion in the model is sometimes best represented 

by following actual vertical motion measurements (represented by model data), surfaces 

of constant entropy, or surfaces of constant pressure, depending on the meteorological 

conditions at a given location and time. The impact of receptor height (or end height) on 

an individual trajectory is also important. Low-ending trajectories represent air parcels 

nearer to ground-level and high-ending trajectories may represent more accurate 

boundary layer flow above the local terrain. 
 Appendix H 

25 of 122 

For the years 2000 – 2004, back trajectories were computed for the following IMPROVE 

sampling sites in and around the VISTAS region: 

1. Breton, LA (BRET1) 

2. Brigantine NWR, NJ (BRIG1) 

3. Cadiz, KY (CADI1) 

4. Caney Creek, AR (CACR1) 

5. Cape Romain National Wilderness Area, SC (ROMA1) 

6. Chassahowitzka National Wilderness Area, FL (CHAS1) 

7. Cohutta Wilderness, GA (COHU1) 

8. Dolly Sods Wilderness, WV (DOSO1) 

9. Everglades NP, FL (EVER1) 

10. Great Smoky Mountains NP, TN (GRSM1) 

11. Hercules-Glades, MO (HEGL1) 

12. James River Face Wilderness, VA (JARI1) 

13. Linville Gorge, NC (LIGO1) 

14. Mammoth Cave NP, KY (MACA1) 

15. Mingo, MO (MING1) 

16. Okefenokee Wilderness, GA (OKEF1) 

17. Shenandoah NP, VA (SHEN1) 

18. Shining Rock Wilderness, NC (SHRO1) 

19. Sipsy Wilderness, AL (SIPS1) 

20. St. Marks, FL (SAMA1) 

21. Swanquarter, NC (SWAN1) 

22. Upper Buffalo Wilderness, AR (UPBU1) 

23. Wolf Island Wilderness, GA (WOLF) 
 Appendix H 

26 of 122 

Figure 4-2 shows the 72-hour back trajectory analysis performed for Cohutta Wilderness 

area. 

Figure 4-2. Example 72-hour back trajectories for 20% worst visibility days in 2002 

for Cohutta Wilderness Area 

Back Trajectories for 2002 20% Worst Days 

Cohutta Wilderness Area 
 Appendix H 

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Figure 4-3. Example 72-hour back trajectories for 20% worst visibility days in 2002 

for Okefenokee Wilderness Area 

Based on the five years of individual back trajectories, ARS generated extinctionweighted residence time data for each IMPROVE site. Each hourly trajectory point was 

tagged with its associated sample (or end) date. Back trajectories with end dates 

corresponding to the 20% worst visibility days were weighted with calculated extinction 

values and summed into 1-degree horizontal grid cells of latitude and longitude. 

Extinction data is based on the IMPROVE Regional Haze Rule dataset, as available from 

the VIEWS website 

(http://vista.cira.colostate.edu/views/Web/IMPROVE/SummaryData.aspx) in November 

2005 and is calculated based on the original IMPROVE algorithm. For sites with less 

than three complete years of data, ARS developed and applied a data substitution 

protocol to fill missing data. Organic carbon and elemental carbon values were filled 

based on correlations to hydrogen and sulfate values for the same site. Other components 

were filled based on data from nearby sites. 

Trajectory data was weighted by total extinction and by extinction components including 

ammonium sulfate (AmmSO4), ammonium nitrate (AmmNO3), particulate organic 

material (POM), Light Absorbing Carbon (LAC), Soil, and Coarse Mass (CM). 

Weighting trajectories for the 20% worst days by sulfate extinction gave greater 

importance to days influenced by SO2 emissions and lesser importance to days 

influenced by organic carbon emissions. This allowed a geographic area of influence to 

be identified based on sulfate contributions and not skewed by contributions from fire. 

These data files were provided to ENVIRON. ENVIRON was charged with developing 

residence time plots to define the geographic area with highest probability of influencing 
 Appendix H 

28 of 122 

the receptor on the 20% worst days dominated by sulfate. Residence time over an area is 

indicative of general flow patterns, but since it does not account for emissions and 

removal processes, it does not necessarily imply specific areas contributed significantly 

to haze compounds at a receptor site. 

4.4 Area of Influence Data and Displays 

The primary objective of the Area of Influence (AOI) displays and data sets are to assist 

the State in focusing its reasonable progress analysis on those geographic regions and 

source categories which most impact a particular Class I Area. The sources of data used 

in these analyses include back-trajectory residence time data provided by ARS and 

described above and the VISTAS 2002 and 2018 36-km gridded emissions data (Base G, 

August 2006 inventory version). 

Extinction weighted back-trajectory residence time plots were provided by ARS for all 

Class I Areas in the VISTAS region as well as for the surrounding, neighboring states. 

These trajectories were processed on an un-projected (i.e., geodetic lat/lon 1 degree by 1 

degree) grid and transferred to ENVIRON for further GIS processing and analysis. Backtrajectories were run for 100-meter and 500-meter start heights. Because the backtrajectories were to be combined with gridded emissions data, the first step in the analysis 

and GIS processing involved re-projecting the data to the Inter-RPO Unified Lambert 

Conformal Projection domain. Once the data was re-projected, the data was mapped to 

the 36-km grid cells in the RPO projection using an area-weighted mapping routine. The 

re-projected extinction weighted back-trajectory residence times were then plotted on the 

VISTAS 12-km modeling domain. As sulfate is the primary visibility-impairing 

component of the total extinction in the Southeast, the SO4-weighted residence time 

trajectories were chosen as the basic data set for display. For clarity, these data are scaled 

by the maximum value of the total extinction-weighted residence time within the 

modeling domain. The 100-km and 200-km distances from the Class I area were labeled. 

Using the trajectories with the 100-m start height, the State has defined the SO2 Areas of 

Influence as the area with grid cells showing 5% (area shaded in yellow in following 

plots) or greater residence time (the frequency that winds pass over that area on the way 

to the Class I area on the 20% worst days dominated by sulfate) for the period 2000-

2004. Residence time over an area is indicative of general flow patterns, but since it does 

not account for emissions and removal processes, it does not necessarily imply specific 

areas contributed significantly to haze compounds at a receptor site. The following 

figures, 4-4 through 4-11, are extinction-weighted residence time plots for LIGO, SHRO, 

SWAN, GRSM, OKEF, COHU, ROMA and SIPS for 100-m and 500-m trajectory start 

heights. 
 Appendix H 

29 of 122 

SO2 Area of Influence for Linville Gorge, NC

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

M ax B ext V alue = 5 4353 9

M ax V alu e = 84%

Figure 4-4. Linville Gorge SO4 extinction-weighted residence time plots for the 

period 2000-2004. 

SO 2 Area of Influence for S hining Rock, NC

Green circles indicate 100-km and 2 00-km ra dii from Class I area .

Red line perimete r indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influe nce with Residence Time > 5%.

Max Bext V alue = 79 3133

Max Valu e = 85 %

Figure 4-5. Shining Rock SO4 extinction-weighted residence time plots for the 

period 2000-2004. 
 Appendix H 

30 of 122 

SO2 Area of Influence for Swanquarter, NC

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Max B ext V alue = 26 3144

Max V alue = 75%

Figure 4-6. Swanquarter SO4 extinction-weighted residence time plots for the 

period 2000-2004. 

SO2 Area of Influence for Great Smoky Mountains, NC-TN

Green circles indicate 100-km and 200-km radii f rom Class I area.

R ed line perimeter indicate Area of Influence with Residence Time > 10%.

Orange line perimeter indic ate Area of Inf luenc e with Residence Time > 5%.

M a x B e x t V a l u e = 7 2 4 55 8

M a x V a lu e = 8 4 %

Figure 4-7. Great Smoky Mountains SO4 extinction-weighted residence time plots 

for the period 2000-2004. 
 Appendix H 

31 of 122 

Figure 4-8. Okefenokee Wilderness Area SO4 extinction-weighted residence time 

plots for the period 2000-2004. 

SO2 Area of Influence for Cape Romain, SC

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10% (weighted by

sulfate extinction and normalized by total extinction).

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Figure 4-9. Cape Romain SO4 extinction-weighted residence time plots for the 

period 2000-2004. 
 Appendix H 

32 of 122 

SO2 Area of Influence for Cohutta, GA

Green circles indicate 100-km and 200-km radii from Class I area.

Red line perimeter indicate Area of Influence with Residence Time > 10% (weighted by

sulfate extinction and normalized by total extinction).

Orange line perimeter indicate Area of Influence with Residence Time > 5%.

Figure 4-10. Cohutta SO4 extinction-weighted residence time plots for the period 

2000-2004. 

Figure 4-11. Sipsey SO4 extinction-weighted residence time plots for the period 

2000-2004. 
 Appendix H 

33 of 122 

Figure 4-12. Wolf Island SO4 extinction-weighted residence time plots for the 

period 2000-2004. 

As an aid to the analysis, all regions with scaled residence time values greater than 5% 

and greater than 10% were noted on the display. Finally, county boundaries were 

overlaid to identify those counties and 36-km modeling grid cells for which the 

extinction-weighted residence time back-trajectories exceeded 5% and 10%. This data 

was then exported as comma-delimited ASCII data files for further analyses. These 

residence time displays are used primarily to determine the regions (counties and/or grid 

cells) impacting each Class I Area. The next step in the analysis is to determine the 

potential impact from emission sources within the regions identified from the extinctionweighted back-trajectory residence time displays and analyses. 

Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory 

analyses have indicated that SO4 is the largest contributor to haze on the 20% worst 

visibility days and that electric generating utilities and industrial point sources are the 

largest contributors to SO4 levels at the Class I areas. These two source categories make 

up 95% of the VISTAS SO2 inventory. Therefore these two source categories were 

identified as the highest priority for evaluation of reasonable progress in 2018 at the Class 

I areas. The potential impacts of SO2 point source emissions for each Class I Area are 

determined by combining gridded emissions data and weighted back-trajectory residence 

times for the 36-km grid cells. The analysis was carried out with both the 2002 and 2018 

base-year emission inventories. Figures 4-13 and 4-14 display the gridded point source 

SO2 emissions from the VISTAS modeling databases, for 2002 and 2018, respectively. 

This data was processed by summing all vertical layers for each grid column and then 

summing across all days to obtain a total annual emission for each grid cell. 
 Appendix H 

34 of 122 

Figure 4-13. Annual point source SO2 emissions for the VISTAS region in 

tons/year. (2002 BaseG) 

Figure 4-14. Annual point source SO2 emissions for the VISTAS region in 

tons/year. (2018 BaseG) 

As a way of incorporating the effects of transport, deposition, and chemical 

transformation of point source emissions along the path of the trajectories, the data was 
 Appendix H 

35 of 122 

weighted by 1/d, where d was calculated as the distance between grid cell centers, in 

kilometers. For the grid cell containing the Class I Area monitor, a weighting of 1/9 was 

applied. The distance-weighted point source SO2 emissions are then combined with the 

gridded extinction-weighted back-trajectory residence times at a spatial resolution of 36-

km. 

The final step in the development of the displays and datasets involve the combination of 

the residence times and gridded emission data. The distance weighted (1/d) gridded point 

source SO2 emissions are multiplied by the total extinction-weighted back-trajectory 

residence times [SO2 * Bext-weighted RT * (1/d)] on a grid cell by grid cell basis. These 

results are then normalized by the domain-wide total and displayed as a percentage 

(Appendix H.2). The analysis is carried out for both the 2002 and 2018 base year 

inventories. Figures 4-15 through 4-23 display the result of this final analysis step. Note 

that the outlined regions (in red and light orange) represent the extent of the >10% and 

>5% sulfate extinction-weighted residence times determined from the first step in the 

analysis (see Figures 4-3 through 4-11). As with the residence time analysis, the results 

of the combined distance-weighted SO2 emissions and extinction-weighted residence 

times are overlayed with county boundaries and exported to comma-delimited ASCII 

data files for further analyses of emissions and control options for specific sources. 
 Appendix H 

36 of 122 

Figure 4-15. Cohutta 2002 SO2 Emissions * SO4 extinction-weighted residence time 

plots.

Figure 4-16. Okefenokee 2002 SO2 Emissions * SO4 extinction-weighted residence 

time plots. 
 Appendix H 

37 of 122 

Figure 4-17. Wolf Island 2002 SO2 Emissions * SO4 extinction-weighted residence 

time plots. 

The following sets of plots show the 2018 SO2 Emissions multiplied by the SO4 

extinction-weighted residence time plots. These were produced the same way as the 

previous plots, only using 2018 emissions instead of 2002 emissions. 

Figure 4-18. Cohutta 2018 SO2 Emissions * SO4 extinction-weighted residence time 

plots. 

Wolf Island, GA 
 Appendix H 

38 of 122 

Figure 4-19. Okefenokee 2018 SO2 Emissions * SO4 extinction-weighted residence 

time plots. 

 

Figure 4-20. Wolf Island 2018 SO2 Emissions * SO4 extinction-weighted residence 

time plots. 

Wolf Island, GA 
 Appendix H 

39 of 122 

To understand how emissions have changed by 2018, the following plots, 4-21 – 4-23, 

compare 2002 and 2018 SO2 multiplied by residence time. 

Figure 4-21. Cohutta 2002 vs. 2018 SO2 emissions multiplied by residence time. 

Figure 4-22. Okefenokee 2002 vs. 2018 SO2 emissions multiplied by residence time. 
 Appendix H 

40 of 122 

Figure 4-23. Wolf Island 2002 vs. 2018 SO2 emissions multiplied by residence time. 

VISTAS states evaluated these plots of residence time weighted by sulfate extinction 

plots of gridded SO2 emissions and defined the SO2 Areas of Influence as those areas 

with residence time greater than 10%, based on trajectories with start height of 100m and 

4 start times per day. 

Extinction-weighted residence plots for Class I areas indicate that the areas of probable 

influence for sulfate contribution to visibility impairment are similar to those for nitrate 

contribution even though the visibility impact of nitrate is an order of magnitude smaller 

than that of sulfate. From these plots we can initially conclude that it is appropriate to 

focus on sources that contribute to sulfate concentrations and that sources near a Class I 

area are more likely to contribute to visibility impairment than more distant sources. 

Gridded SO2 emissions for the sulfate extinction-weighted residence time plots indicate 

that large emissions sources at great distance from the Class I area can contribute to 

visibility impairment on some 20% worst days. 

4.5 Importance of Pollutants Other Than Sulfate 

For completion, the following is a brief discussion of the importance of other PM 

components and contributing source categories. If NOx controls are considered, 54% of 

NOx is from point sources, 23% is from highway vehicles, and 20% is from nonroad 

engines. Elevated organic carbon (OC) and elemental carbon (EC) are indicators of fire. 

Some states may need to consider emissions from residential wood burning, forest fires 

Nitrate (NH4NO3) levels in winter can be significant and are dependent on availability of 

NH3; 88% of NH3 is from area sources (e.g. agriculture). However, given that sulfate 

contributes almost 60% at OKEF and greater than 70% at COHU on the 20% worst 
 Appendix H 

41 of 122 

visibility days, the GAEPD believes it is appropriate to focus on SO2 reductions in this 

first Regional Haze SIP. 

4.6 Summary of Emission Inventories Used in Cost Analysis 

A necessary component of control strategy design is a thorough review of the emission 

inventories that are used in the modeling of the future year base case. These inventories 

can shed light on the residual emissions from sources or source categories defined to be 

within areas of transport or impact of a Class I area. We used the most current (BaseG 

fall 2006) VISTAS future year (2018) base case and 2002 base year emissions to conduct 

this control cost analysis. For purposes of listing sources within the Area of Influence, 

data were provided for all sources with emissions over distance (Q/d) greater than 5 and 

maximum residence time (RTmax) greater than 5. States independently defined the 

criteria for selecting which sources from this list would be considered for reasonable 

control measures. 

The NIF formatted and SMOKE-ready modeling files for both 2002 and 2018 base year 

and base cases were obtained from VISTAS emissions development and modeling 

contractors and converted to annual emissions and summed for the geography and 

domain of interest. 

Tables 4-5 and 4-6 present the State breakdown of these emissions for the entire VISTAS 

domain. Because the SMOKE-ready files were used in this analysis, the particulate 

matter transport factor (0.90 times inventory values) is included in the PM emission 

summaries. This factor is applied to account for the removal of a substantial portion of 

fugitive dust emissions near a source by surrounding vegetation and structures when such 

emissions are used in regional scale modeling analyses. 

Table 4-5. VISTAS 2002 Base Year Annual Emissions Summary (tons). 

State VOC NOx CO SO2 PM-10 PM-2.5 NH3

AL 455986.6 508186.18 2639729.125 589958.722 229647.3855 102441.48 68365.2496

FL 1336653 1029414.61 7973550.506 597069.646 394623.2101 194814.88 61707.8367

GA 758324.4 676086.152 4640051.048 653870.886 346056.1024 141583.09 98059.1961

KY 298654.1 553437.753 1887662.518 591941.591 152553.0869 54788.97 57652.5317

MS 310938 315509.534 1283278.075 113148.074 182518.1506 45115.861 63991.004

NC 679631.8 668399.482 4410127.923 549402.424 183096.9552 87817.724 173832.4682

SC 393472.3 356431.368 2186195.351 289105.501 166503.9202 79326.939 35637.6515

TN 490647.5 588121.105 2813567.115 450018.744 168682.1637 78674.286 43281.8017

VA 464505.2 499762.38 3256848.719 421145.767 112841.3165 49843.365 55614.3642

WV 140149.3 378559.602 859397.9753 570885.53 48974.9782 28313.253 12468.711

Total 5328963 5573908.16 31950408.35 4826546.89 1985497.269 862719.84 670610.8147
 Appendix H 

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Table 4-6. 2018 Base Case Annual Emissions Summary (tons). 

State VOC NOx CO SO2 PM-10 PM-2.5 NH3

AL 327,243 269,679 1,976,259 295,593 249,430 106,872 84,746

FL 990183.7 467164.541 6003566.751 318293.487 447956.9962 193995 74420.0253

GA 562557.3 346853.445 3373857.236 212461.783 412358.7798 157692.4 123465.3064

KY 239819.6 281504.202 1422317.011 316508.674 165239.7959 57042 64504.0178

MS 249234.7 186848.555 865445.2111 48997.5324 203073.9879 52586.703 76272.3655

NC 428356 280996.238 2789482.511 175581.317 201461.5264 94657.988 197515.9242

SC 301998.5 196269.879 1585057.47 164409.353 186931.0623 86491.75 43361.5571

TN 389063 253040.352 1802311.755 207667.049 187913.2215 85495.927 48448.8788

VA 316675.2 279807.32 2103008.414 267852.827 129835.5692 56201.147 65077.764

WV 107982.3 152446.79 596152.6817 181085.221 46698.516 25158.089 15034.6498

Total 3,913,114 2,714,610 22,517,458 2,188,450 2,230,899 916,193 792,847

Our review was conducted in a top down fashion starting with an analysis of the major 

source categories in the domains of interest to determine which major categories had the 

highest residual contribution to the area. Once the highest source types were identified, 

subcategories within those source types were reviewed. Again, a ranking of the highest 

residual sub source types was performed and additional analyses on these categories were 

conducted. Using the extinction weighted analysis, these emission reviews and 

summaries like those presented in Figure 4-24, VISTAS made a decision to further 

review only point source controls in increment to the Clean Air Act scenario. 

In addition to reviewing the residual emission categories in the future-year base, it was 

important to identify reductions that had already occurred within each category or at 

specific units. This allowed VISTAS States to determine if certain source categories that 

had yet to be controlled under the future-year base case had the potential for reduction or 

if source types already reduced have reached the full cost potential. 

Finally, once each subcategory was identified, unit-level tables of emission comparisons 

from 2002 to 2018 were developed allowing VISTAS States to review existing emission 

reductions and providing the ability to assign new cost-effective controls to units using 

the best control for the scenario. These tables presented comparisons of 2002 and 2018 

emission levels for SO2 and future-year control technology assignment (by IPM 

forecasting and State modification) for EGUs. Georgia EPD then used the processes 

described in Section 5.0 to identify additional reasonable controls for these units. 

Ultimately, the final control strategy decisions will include the application of BART 

subject source reductions in the future-year base case. 
 Appendix H 

43 of 122 

Figure 4-24. VISTAS Base G2 SO2 Emissions Contribution by Major Source 

Sector. 

Note: Sections 4.7 through 4.9 discuss the use of AirControlNET to determine cost 

efficiencies of possible control measures. Georgia EPD relied upon site-specific cost 

efficiencies supplied by each source to identify cost-efficient control strategies. Results 

of AirControlNET analyses were used for comparison with source supplied information 

when evaluating control strategies. 

4.7 Process in Preparing Files for Cost Effectiveness Curve Development 

The 2018 IPM file used by VISTAS for EGU sources (RPO 2.1.9) was obtained and 

matched to the 2018 base-base inventory of EGU sources. This step was conducted to 

ensure that incremental controls assigned to these source types did not duplicate existing 

base-case assumptions. Because IPM does not assign a control efficiency with each 

control device applied to SO2 and NOX, we made some assumptions, based on IPM 

documentation, as to what pollutant-specific level of reduction was applied in the futureyear base case runs. These assumptions, by primary and secondary control device code 

combinations for SO2, are presented in Table 4-7. 

Since many of the control-technology-control-cost equations within AirControlNET 

require additional unit-level characteristic data, we also made matches of the SMOKE 

IDA files to VISTAS NIF, EPA NEI, or EPA CAMD CEM data sets to obtain these 

variables when missing. Unit-level boiler capacity (MMBtu/hr) or NETDC (MW) values 

0

100

200

300

400

500

600

700

Alabama

Florida

Georgia

Kentucky

Mississippi

North Carolina

South Carolina

Tennessee

Virginia

West Virginia

Annual SO2 (Thousand Tons)

Miscellaneous

Nonroad

Onroad

Industrial

Other Fuel Combustion

EGU

2002 Typical

2009 OTW

2018 OTW
 Appendix H 

44 of 122 

are required for capital, operating and maintenance cost calculations for many of the SO2 

applied technologies. In cases where these nameplate capacity values could not be 

identified, emission-weighted capacities (based on the final EPA 2002 NEI) were 

assigned to boilers using a primary (highest emitting) SCC. Table 4-8 presents these 

weighted capacities. Additionally, stack flow, sulfur content, and primary SCC 

assignment were necessary to cross-reference available incremental control technologies 

to the base-case emissions inventory data. These variables were obtained where matches 

could be found in priority order of VISTAS, CAMD, and other EPA datasets, 

respectively. 

Table 4-7. IPM Post Processing Assigned Device Codes and Applied SO2 Control 

Efficiencies. 

Primary Device Code Secondary Device Code Description CE RE 

0 0 No Control 0 0 

119 0 Dry Scrubber 90 100 

141 0 Wet Scrubber 90 100 

Table 4-8. Emissions Weighted NETDC (MW) Association.

4.8 Application of AirControlNET Technologies 

AirControlNET is a control technology analysis tool developed to support the US EPA in 

its analyses of air pollution policies and regulations (Pechan, 2005). The tool provides 

SCC Description NETDC (MW)

10100201 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Wet 

Bottom (Bituminous Coal) 200

10100202 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom (Bituminous Coal) 500

10100203 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace 

(Bituminous Coal) 200

10100212 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom (Tangential) (Bituminous Coal) 500

10100215 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cell Burner 

(Bituminous Coal) 1300

10100218 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Atmospheric Fluidized 

Bed Combustion: Circulating Bed (Bitum. Coal) 200

10100222 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom (Subbituminous Coal) 400

10100223 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Cyclone Furnace 

(Subbituminous Coal) 400

10100226 

External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry 

Bottom Tangential (Subbituminous Coal) 500

10100401 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Normal Firing 400

10100404 External Combustion Boilers; Electric Generation; Residual Oil; Grade 6 Oil: Tangential Firing 500

10100501 External Combustion Boilers; Electric Generation; Distillate Oil; Grades 1 and 2 Oil 400

10100601 

External Combustion Boilers; Electric Generation; Natural Gas; Boilers > 100 Million Btu/hr except 

Tangential 400

10100701 External Combustion Boilers; Electric Generation; Process Gas; Boilers > 100 Million Btu/hr 200

10100801 External Combustion Boilers; Electric Generation; Petroleum Coke; All Boiler Sizes 600

10101204 External Combustion Boilers; Electric Generation; Solid Waste; Tire Derived Fuel : Shredded 200

10300811 External Combustion Boilers; Commercial/Institutional; Landfill Gas; Landfill Gas 200

20100101 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine 200

20100109 Internal Combustion Engines; Electric Generation; Distillate Oil (Diesel); Turbine: Exhaust 200

20100201 Internal Combustion Engines; Electric Generation; Natural Gas; Turbine 200

 

 All other boilers 100
 Appendix H 

45 of 122 

data on emission sources, potential pollution control measures and emission reductions 

and the costs of implementing those controls. 

The core of AirControlNET is a relational database system in which control technologies 

are linked to sources within EPA emissions inventories. The system contains a database 

of control measure applicability, efficiency, and cost information for reducing the 

emissions contributing to ambient concentrations of ozone, PM10, PM2.5, SO2, NOX, as 

well as visibility impairment (regional haze) from point, area, and mobile sources. PM10

and PM2.5 as included in AirControlNET represent primary emissions of PM. The 

control measure data file in AirControlNET includes not only the technology's control 

efficiency, and calculated emission reductions for that source, but also estimates the costs 

(annual and capital) for application of the control measure. 

Since available versions of AirControlNET contain the preprocessed application of 

control technologies to a predetermined set of EPA emission inventories, direct use of the 

model in this analysis was not possible. However, Alpine received approval from EPA’s 

Innovative Strategies and Economics Group (ISEG) to modify the AirControlNET 

Version 4.1 source code (Sorrels, 2006) and data tables in order to make it useful to this 

study. The results of the application of this modified version of the code still retain the 

applicability, efficiency, and cost information from the unmodified version of the source 

code, but were applied to the VISTAS modeling inventories with updated price index 

scalars to reflect control costs in 2005 dollars. 

Using the modified inventories identified above, we ran every available SO2 control 

strategy in AirControlNET against the EGU and non-EGU point source inventories to 

develop a master list of available, incremental control strategies for the entire VISTAS 36 

km domain necessary for VISTAS states to design command-and-control or costeffectiveness-based control strategies by source or domain. 

4.9 Development of AOI-Based Cost Curves 

Each Class I area in the VISTAS modeling domain had an associated AOI as identified 

earlier in this document. In order to best determine where emission reduction has the 

greatest benefit, this geography was designed to limit the available source type list from 

including all sources within the entire domain. 

These marginal cost curves include the application of all available control measures to all 

applicable point sources within the AoI. The curves will allow VISTAS States to 

determine if, based on the generic application of SO2 control technologies from the 

associations originally developed in AirControlNET and improved upon with stakeholder 

input will help attain reasonable progress emission reduction objectives while presumably 

minimizing the number and type of controlled sources in each AOI. 

Using a geocoded county list from these AOIs, we parsed the master list of incremental 

control measures from all point sources located within the boundaries of the AOIs. This 

parsed list was then sorted by incremental cost-effectiveness (marginal cost) basis to 
 Appendix H 

46 of 122 

determine the most cost-effective control suite available to attain emission reduction 

targets for SO2 within each AOI. Each individual source had its own cost-effectiveness 

curve generated. 

In aggregate, the results of these applications are SO2 emission cost curves for all EGU 

and non-EGU point sources within the geographic domain of the AOI. Incremental 

controls on area and mobile sources were not considered in this analysis. An illustrative 

example of the steps involved with the cost-effectiveness curve design can be found in 

the Attachment H-1a of this document. 

With each AOI’s cost curve, additional metrics, calculated for the distance from the 

emission release point to the Class I area IMPROVE monitor (in km), the 2018 residual 

emissions and distance (Q/d) or squared distance (Q/d^2), and the normalized 2018 SO2 

point source emissions times distance-weighted residence time (RTMax) values for the 

county in which the emission release point was located, were calculated for incremental 

review and consideration. The GA EPD used these values to further determine control 

strategy development for individual Class I areas. 

5.0 REASONABLE PROGRESS ASSESSMENT 

The State concluded that SO2 emissions from EGU and non-EGU point sources in 

geographic Areas of Influence (AOIs) are sources to consider for further controls. 

VISTAS developed source matrices for SO2 AOIs for each Class I area, using data 

delivered by ENVIRON for 2002 and 2018 SO2 emissions multiplied by SO4 extinctionweighted residence time plots.

Spreadsheets were developed for each Class I area with: 

• Plant name 

• Point ID 

• Tons of SO2 projected for 2018 

• Q (tons) 

• Current control efficiency, CE (%) 

• Stationary source distance to Class I area [d (km)] 

• Analysis of emissions per distance from source [Q/d and Q/d2] 

• RT Max, the maximum percentage of time that winds pass over that area on the 

way to the Class I area on the 20 worst days 

The ranking refers to the source rank by Q/d when sources from all states are included.

In an analysis of emissions-per-distance from source, Q/d2

 is more representative when d 

is less than 20 km because plumes are still dispersing in two dimensions. After about 100 

km, plumes only disperse in one dimension. The distance calculation is based on a single 

stack at a unit (when more than one are represented in the inventory) and is calculated in 

distance in km to the IMPROVE monitor at each Class I area. The residence time for the 
 Appendix H 

47 of 122 

county where the source is located was reviewed. It was generally agreed that states 

would focus on those sources where RT max was equal to or greater than 10%. A second 

matrix for sources in the SO2 AOI was developed for sources with a 2018 Q/d > 5 when 

d was greater than 100 km, Q/d2

 > 0.03 when d was less than 20 km, and Q/d > 5 or Q/d2

> 0.03 when d was 20-100 km (these values were chosen to limit the number of sources 

on the list and focus on those that are most influential). 

Next, the GA EPD elected to focus on those units that contributed at least half a percent 

to sulfate visibility impairment at a given Class I area for several reasons. First, the units 

with the larger contribution toward visibility impairment would likely show an 

environmental benefit under a control evaluation, and GA EPD would be able to use that 

environmental benefit to require controls on a given unit. Secondly, there are several 

regulatory programs that use a higher threshold than half a percent for evaluation 

thresholds. 

1. The BART rule specifies that a maximum impact of 0.5 dv is an acceptable threshold 

for establishing significance. This threshold equates to roughly a five percent change in 

visible perception. This same significance level is used in the Prevention of Significant 

Deterioration/New Source Review program for the visibility air quality related value. 

2. For the CAIR rule, a PM contribution of 0.2 ug/m3 was used to demonstrate a 

significant impact, which is 1.3% of the annual PM2.5 standard of 15 ug/m3. 

3. Lastly, when human health standards are proposed (NAAQS), significant impact 

levels are assigned which allow sources to determine their significance on air quality in 

the area around their facilities. Sources that demonstrate that their "contribution" from 

the new or modified sources is less than these significance levels do not have to complete 

any further modeling. The SILS represent a percentage of the NAAQS. 

After looking at all averaging periods for the criteria pollutants, GA EPD determined that 

the one half of one percent (0.5%) threshold proposed for reasonable progress was as 

protective or more protective than the significant impact levels. The most restrictive 

threshold identified was for NOx, which has a NAAQS of 100 ug/m3 and a significance 

level of 1 ug/m3, which represents one percent of the total. 

Finally, GA EPD considered available resources to evaluate the sources in the each Class 

I area’s sulfate AOI. GA EPD recognized that there was neither sufficient time nor 

resources available to evaluate all units within a given AOI. Therefore, a threshold 

needed to be established to determine which units would be evaluated. Table 5-1 shows 

that half a percent contribution threshold captures greater than 70% percent of the total 

point source SO2 contribution to two of Georgia’s three Class I areas while requiring an 

evaluation of 30 or more units. At the remaining area, Cohutta Wilderness Area, the half 

a percent threshold represents 69 percent of the total contribution, while requiring an 

evaluation of 38 units. In order to capture a significant percentage of the total 

contribution, the next increment would involve an evaluation of many more units. GA 

EPD believes that half percent threshold is appropriate, given the contribution to the total 
 Appendix H 

48 of 122 

visibility impairment at each Class I area and the limited resources available to conduct 

the unit-by-unit evaluation for reasonable progress. 

Table 5-1. Numbers and percentage of 2018 SO2 emission units that contribute to 

Georgia Class I areas. 

Georgia Class I Area Non-Georgia class I areas 

COHU OKEF WOLF SAMA JOKI ROMA 

# Units Contributing > 

0.5% 

38 31 29 51 17 36 

Percentage of total 

contribution 

69% 83.16% 73.39% 86.74% 42.91% 83.61% 

# Units Contributing > 

0.1%, but < 0.5% 

121 90 95 70 46 72 

Percentage of total 

contribution 

31.61% 26.09% 29.4% 17.73% 14.2% 22.95% 

# Units Contributing < 

0.1% 

119 43 46 7 26 106 

Percentage of total 

contribution 

6.3% 2.57% 2.72 0.48% 1.31% 4.92% 

The following three tables, 5-2 through 5-4, show the analysis for COHU, OKEF, 

WOLF, and non-Georgia Class I Areas for sources that met the above criteria. The full 

spreadsheets containing all VISTAS Class I area results can be found in Appendix H.2. 

Table 5-2. Cohutta Wilderness Area Q/d, Q/d^2, RTMax, and fractional 

contribution analysis. 

STATE PLANT POINT 

ID 

(2018 G) CE 

(%)* 

DIST (KM) Q/D Q/D^2 RT 

MAX** 

FRACTION

GEORGIA TEMPLE INLAND ROME 

LINERBOARD (THIS 

UNIT IS PERMENTLY 

SHUT DOWN) 

F2 1,148 4 87.55 13.11 0.15 78.87 0.0137 

GEORGIA TEMPLE INLAND ROME 

LINERBOARD 

F4 3,696 4 87.55 42.22 0.48 78.87 0.0442 

GEORGIA MOHAWK INDUSTRIES 

- SOUTH HAMILTON 

STREE 

BL06 200 0 31.93 6.28 0.20 83.31 0.0069 

GEORGIA MOHAWK INDUSTRIES 

- SOUTH HAMILTON 

STREE 

BL07 200 0 31.93 6.28 0.20 83.31 0.0069 

GEORGIA MOUNT VERNON 

MILLS, INC., APPAREL 

FABRIC 

EU03 351 4 67.72 5.18 0.08 78.87 0.0054 

GEORGIA MOUNT VERNON 

MILLS, INC., APPAREL 

FABRIC 

EU04 828 4 67.72 12.22 0.18 78.87 0.0128 

TENNESSEE A.E. STALEY 

MANUFACTURING 

COMPANY 

005 2,982 4 109.35 27.27 0.25 38.49 0.0139 

TENNESSEE ALUMINUM COMPANY 

OF AMERICA - SOUTH 

PLAN 

16 2,370 0 125.75 18.85 0.15 33.77 0.0084 
 Appendix H 

49 of 122 

TENNESSEE ALUMINUM COMPANY 

OF AMERICA - SOUTH 

PLAN 

17 2,320 0 125.75 18.45 0.15 33.77 0.0083 

TENNESSEE BOWATER NEWSPRINT 

& DIRECTORY - 

CALHOUN 

015 5,871 4 58.30 100.71 1.73 82.90 0.1107 

TENNESSEE E. I. DU PONT DE 

NEMOURS AND 

COMPANY 

0002 1,173 0 67.08 17.48 0.26 83.31 0.0193 

TENNESSEE 

EASTMAN CHEMICAL 

COMPANY 

021520 16,729 4 270.21 61.91 0.23 8.43 0.0069 

TENNESSEE INTERTRADE 

HOLDINGS, INC. 

001 2,530 4 32.47 77.92 2.40 82.90 0.0857 

TENNESSEE U.S. DEPARTMENT OF 

ENERGY, Y-12 PLANT 

002 2,336 4 137.55 16.99 0.12 24.66 0.0056 

GEORGIA GEORGIA POWER 

COMPANY, BOWEN 

STEAM-ELECT 

SG03 3,056 95 78.34 39.01 0.50 44.32 0.0233 

GEORGIA GEORGIA POWER 

COMPANY, HAMMOND 

STEAM-ELE 

SG04 1,728 95 88.75 19.47 0.22 78.87 0.0207 

GEORGIA GEORGIA POWER 

COMPANY, BOWEN 

STEAM-ELECT 

SG02 2,432 95 78.34 31.05 0.40 44.32 0.0185 

GEORGIA GEORGIA POWER 

COMPANY, BOWEN 

STEAM-ELECT 

SG01 2,415 95 78.34 30.83 0.39 44.32 0.0184 

ALABAMA TVA - WIDOWS CREEK 008 10,185 90 103.54 98.37 0.95 20.39 0.0270 

GEORGIA GEORGIA POWER 

COMPANY, YATES 

STEAM-ELECT 

SG05 6,643 0 149.41 44.46 0.30 39.91 0.0239 

GEORGIA GEORGIA POWER 

COMPANY, YATES 

STEAM-ELECT 

SG04 6,500 0 149.41 43.50 0.29 39.91 0.0234 

TENNESSEE TVA BULL RUN FOSSIL 

PLANT 

001 8,657 90 144.05 60.10 0.42 24.66 0.0199 

ALABAMA TVA - WIDOWS CREEK 009 6,712 90 103.54 64.83 0.63 20.39 0.0178 

GEORGIA GEORGIA POWER 

COMPANY, YATES 

STEAM-ELECT 

SG03 3,916 0 149.41 26.21 0.18 39.91 0.0141 

ALABAMA TVA - WIDOWS CREEK 005 4,839 0 103.54 46.73 0.45 20.39 0.0128 

ALABAMA TVA - WIDOWS CREEK 004 4,828 0 103.54 46.63 0.45 20.39 0.0128 

ALABAMA TVA - WIDOWS CREEK 002 4,821 0 103.54 46.56 0.45 20.39 0.0128 

GEORGIA GEORGIA POWER 

COMPANY, YATES 

STEAM-ELECT 

SG02 3,547 0 149.41 23.74 0.16 39.91 0.0127 

ALABAMA TVA - WIDOWS CREEK 006 4,707 0 103.54 45.46 0.44 20.39 0.0125 

ALABAMA TVA - WIDOWS CREEK 003 4,625 0 103.54 44.67 0.43 20.39 0.0122 
 Appendix H 

50 of 122 

ALABAMA TVA - WIDOWS CREEK 007 4,550 0 103.54 43.95 0.42 20.39 0.0121 

SOUTH 

CAROLINA 

DUKE ENERGY:LEE 003 7,274 0 201.57 36.09 0.18 22.06 0.0107 

ALABAMA ALABAMA POWER 

COMPANY - GORGAS 

004 9,854 0 268.85 36.65 0.14 13.76 0.0068 

SOUTH 

CAROLINA 

DUKE ENERGY:LEE 001 4,347 0 201.61 21.56 0.11 22.06 0.0064 

SOUTH 

CAROLINA 

DUKE ENERGY:LEE 002 4,140 0 201.57 20.54 0.10 22.06 0.0061 

ALABAMA ALABAMA POWER 

COMPANY - GORGAS 

005 8,091 0 268.85 30.09 0.11 13.76 0.0056 

ALABAMA ALABAMA POWER 

COMPANY - E C 

GASTON 

006 7,542 90 240.83 31.32 0.13 11.99 0.0051 

Table 5-3. Okefenokee Wilderness Area Q/d, Q/d^2, RTMax, and fractional 

contribution analysis 

STATE PLANT POINT 

ID 

(2018 G) CE 

(%)* 

DISTANCE 

(KM) 

Q/D Q/D^2 RT 

MAX** 

FRACTION 

GEORGIA JESUP MILL, 

RAYONIER 

PERFORMANCE 

PB02 624 4 106.37 5.87 0.06 71.58 0.0094 

GEORGIA JESUP MILL, 

RAYONIER 

PERFORMANCE 

PB03 1,597 4 106.27 15.03 0.14 71.58 0.0240 

GEORGIA JESUP MILL, 

RAYONIER 

PERFORMANCE 

RF01 333 0 106.22 3.14 0.03 71.58 0.0050 

GEORGIA JESUP MILL, 

RAYONIER 

PERFORMANCE 

RF04 334 0 105.88 3.15 0.03 71.58 0.0050 

FLORIDA ANCHOR GLASS 

CONTAINER 

CORPORATION 

3 206 0 59.04 3.49 0.06 65.70 0.0051 

FLORIDA ANCHOR GLASS 

CONTAINER 

CORPORATION 

4 212 0 59.04 3.60 0.06 65.70 0.0053 

FLORIDA CEDAR BAY 

GENERATING 

COMPANY L P 

GEN1 2,227 0 61.17 36.41 0.60 65.70 0.0534 

FLORIDA GEORGIA-PACIFIC 

CORP. PULP/PAPER 

MILL 

15 4,329 0 125.55 34.48 0.27 22.94 0.0177 

FLORIDA GEORGIA-PACIFIC 

CORP. PULP/PAPER 

MILL 

16 1,581 4 125.55 12.59 0.10 22.94 0.0064 

FLORIDA IFF CHEMICAL 

HOLDINGS, INC. 

3 733 0 56.66 12.94 0.23 65.70 0.0190 

FLORIDA JEFFERSON SMURFIT 

CORPORATION (US) 

15 3,639 4 64.58 56.35 0.87 71.58 0.0900 
 Appendix H 

51 of 122 

FLORIDA JEFFERSON SMURFIT 

CORPORATION (US) 

6 300 0 64.42 4.66 0.07 71.58 0.0074 

FLORIDA MILLENNIUM 

SPECIALTY 

CHEMICALS 

5 269 0 60.46 4.45 0.07 65.70 0.0065 

FLORIDA MILLENNIUM 

SPECIALTY 

CHEMICALS 

6 590 0 60.46 9.76 0.16 65.70 0.0143 

FLORIDA PROGRESS ENERGY 

FLORIDA, INC. 

CRYSTAL RI 

1 13,537 0 205.80 65.78 0.32 5.47 0.0080 

FLORIDA PROGRESS ENERGY 

FLORIDA, INC. 

CRYSTAL RI 

2 15,241 0 205.80 74.06 0.36 5.47 0.0090 

FLORIDA RAYONIER 

PERFORMANCE 

FIBERS LLC 

6 1,256 0 63.34 19.83 0.31 71.58 0.0317 

FLORIDA SAINT JOHNS RIVER 16 5,882 90 65.12 90.33 1.39 65.70 0.1325 

FLORIDA SAINT JOHNS RIVER 17 7,420 90 65.12 113.9

5 

1.75 65.70 0.1671 

FLORIDA SEMINOLE ELECTRIC 

COOPERATIVE, INC. 

1 6,779 95 121.83 55.64 0.46 22.94 0.0285 

FLORIDA SEMINOLE ELECTRIC 

COOPERATIVE, INC. 

2 6,508 95 121.83 53.42 0.44 22.94 0.0274 

FLORIDA WHITE SPRINGS 

AGRICULTURAL 

CHEMICALS,INC 

66 1,496 0 69.96 21.39 0.31 48.81 0.0233 

FLORIDA WHITE SPRINGS 

AGRICULTURAL 

CHEMICALS,INC 

67 1,308 0 69.96 18.69 0.27 48.81 0.0204 

GEORGIA SAVANNAH 

ELECTRIC: MCINTOSH 

STEAM - ELEC 

SG01 7,015 0 201.59 34.80 0.17 15.51 0.0124 

FLORIDA PROGRESS ENERGY 

FLORIDA, INC. 

CRYSTAL RI 

2 15,241 0 205.80 74.06 0.36 5.47 0.0093 

GEORGIA SAVANNAH 

ELECTRIC: KRAFT 

STEAM - ELECTRI 

SG03 4,474 0 182.45 24.52 0.13 15.53 0.0088 

GEORGIA GEORGIA POWER 

COMPANY, MITCHELL 

STEAM-EL 

SG03 4,930 0 206.79 23.84 0.12 14.43 0.0079 

SOUTH 

CAROLINA 

SCE&G:CANADYS 001 5,203 0 295.33 17.62 0.06 16.79 0.0068 

SOUTH 

CAROLINA 

SCE&G:CANADYS 002 5,144 0 295.35 17.42 0.06 16.79 0.0067 
 Appendix H 

52 of 122 

Table 5-4. Wolf Island Q/d, Q/d^2, RTMax, and fractional contribution analysis. 

STATE PLANT POIN

T ID 

(2018 G) CE 

(%)* 

DISTANCE 

(KM) 

Q/D Q/D^2 RT 

MAX*

FRACTION 

GEORGIA GEORGIA-PACIFIC 

BRUNSWICK 

F1 1,842 4 28.39 64.89 2.29 73.01 0.1255 

GEORGIA GEORGIA-PACIFIC 

BRUNSWICK 

M24 193 0 28.39 6.80 0.24 73.01 0.0131 

GEORGIA GEORGIA-PACIFIC 

CORP SAVANNAH 

BO01 1,844 90 109.91 16.78 0.15 25.08 0.0111 

GEORGIA GEORGIA-PACIFIC 

CORP SAVANNAH 

BO02 1,415 90 109.95 12.87 0.12 25.08 0.0086 

GEORGIA GEORGIA-PACIFIC 

CORP SAVANNAH 

BO03 1,282 90 109.99 11.66 0.11 25.08 0.0077 

GEORGIA INTERNATIONAL 

PAPER - SAVANNAH 

PB13 8,578 4 85.82 99.96 1.16 25.08 0.0664 

GEORGIA INTERSTATE PAPER 

LLC

F1 188 0 44.67 4.20 0.09 46.19 0.0051 

GEORGIA SAVANNAH 

ELECTRIC: KRAFT 

SG01 691 0 90.18 7.66 0.08 25.08 0.0051 

GEORGIA SAVANNAH 

ELECTRIC: KRAFT 

SG02 704 0 90.18 7.80 0.09 25.08 0.0052 

GEORGIA SAVANNAH 

ELECTRIC: KRAFT 

SG03 4,474 0 90.18 49.62 0.55 25.08 0.0330 

GEORGIA SAVANNAH 

ELECTRIC: MCINTOSH 

SG01 7,015 0 112.72 62.24 0.55 25.08 0.0413 

GEORGIA SAVANNAH SUGAR 

REFINERY 

U161 997 4 89.65 11.13 0.12 25.08 0.0074 

GEORGIA SOUTHERN STATES 

PHOSPHATE &

SA02 808 0 83.92 9.62 0.11 25.08 0.0064 

SOUTH 

CAROLINA 

GIANT CEMENT CO 005 3,893 0 222.58 17.49 0.08 14.78 0.0068 

SOUTH 

CAROLINA 

HOLCIM:HOLLY HILL 002 4,074 0 235.40 17.31 0.07 12.19 0.0056 

SOUTH 

CAROLINA 

MEADWESTVACO 

CORPORATION INC

006 2,706 0 213.39 12.68 0.06 24.20 0.0081 

SOUTH 

CAROLINA 

SANTEE COOPER 

CROSS

002 3,380 87 244.36 13.83 0.06 14.73 0.0054 

SOUTH 

CAROLINA 

SANTEE COOPER 

CROSS

3 3,835 0 244.36 15.69 0.06 14.73 0.0061 

SOUTH 

CAROLINA 

SANTEE COOPER 

JEFFERIES

003 6,761 0 244.62 27.64 0.11 14.73 0.0108 

SOUTH 

CAROLINA 

SANTEE COOPER 

JEFFERIES

004 6,609 0 244.62 27.02 0.11 14.73 0.0105 

SOUTH 

CAROLINA 

SCE&G:CANADYS 001 5,203 0 201.47 25.83 0.13 24.20 0.0166 

SOUTH 

CAROLINA 

SCE&G:CANADYS 002 5,144 0 201.47 25.53 0.13 24.20 0.0164 

FLORIDA SAINT JOHNS RIVER 17 7,420 90 105.18 70.55 0.67 50.75 0.0976 

FLORIDA SAINT JOHNS RIVER 16 5,882 90 105.18 55.92 0.53 50.75 0.0774 

FLORIDA CEDAR BAY 

GENERATING

GEN1 2,227 0 107.25 20.77 0.19 50.75 0.0287 

FLORIDA SEMINOLE ELECTRIC 

COOPERATIVE, INC.

1 6,779 95 182.71 37.10 0.20 15.88 0.0161 

FLORIDA SEMINOLE ELECTRIC 

COOPERATIVE, INC.

2 6,508 95 182.71 35.62 0.19 15.88 0.0154 
 Appendix H 

53 of 122 

Table 5-5. Non-Georgia Class I Areas Q/d, Q/d^2, RTMax, and fractional 

contribution analysis (Georgia sources only) 

STATE PLANT POINT 

ID 

(2018 G) CE 

(%)* 

DISTANCE 

(KM) 

Q/D Q/D^2 RT 

MAX** 

FRACTION

SAINT MARKS 

GEORGIA GEORGIA PACIFIC 

CORPORATION, 

CEDAR SPRINGS 

U500 2428 4 149.70 16.22 0.11 12.89 0.0108 

GEORGIA GEORGIA PACIFIC 

CORPORATION, 

CEDAR SPRINGS 

U501 2533 4 149.70 16.92 0.11 12.89 0.0113 

GEORGIA GEORGIA PACIFIC 

CORPORATION, 

CEDAR SPRINGS 

R402 1726 0 149.78 11.53 0.08 12.89 0.0077 

GEORGIA GEORGIA POWER 

COMPANY, PLANT 

MITCHELL 

SG03 4930 0 150.49 32.76 0.22 16.16 0.0274 

GEORGIA INTERNATIONAL 

PAPER SAVANNAH 

MILL 

PB13 8578 4 366.31 23.42 0.06 5.81 0.0070 

GEORGIA SAVANNAH 

ELECTRIC, PLANT 

MCINTOSH 

SG01 7015 0 380.33 18.44 0.05 5.81 0.0055 

GEORGIA MILLER BREWING CO B0011 1073 0 164.59 6.52 0.04 15.16 0.0054 

GEORGIA PACKAGING 

CORPORATION OF 

AMERICA 

1017 653 0 105.83 6.17 0.06 15.90 0.0051 

JOYCE KILMER/SLICKROCK 

GEORGIA TEMPLE INLAND 

ROME LINERBOARD 

F4 3696 4 175.7 21.04 0.12 29.12 0.0099 

CAPE ROMAIN 

GEORGIA INTERNATIONAL 

PAPER SAVANNAH 

MILL 

PB13 8578 4 165.98 51.68 0.31 31.04 0.0155 

GEORGIA SAVANNAH 

ELECTRIC, PLANT 

MCINTOSH 

SG01 7089 0 155.93 44.99 0.29 31.04 0.0135 

GEORGIA SAVANNAH 

ELECTRIC, PLANT 

KRAFT 

SG03 3992 0 165.25 27.08 0.16 31.04 0.0081 

SHINING ROCK 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO3 27,735 0 276.79 100.2 0.36 8.61 0.0071 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO4 26,616 0 276.79 96.16 0.35 8.61 0.0068 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO1 26,264 0 276.79 94.89 0.34 8.61 0.0067 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO2 26,075 0 276.79 94.20 0.34 8.61 0.0067 

 

1

 Note that Boiler B002 at Miller Brewing Company is identical to B002 and was 

originally included in Georgia’s 4-factor list along with B001. 
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GEORGIA GEORGIA POWER, 

PLANT YATES 

SG07 16,530 0 290.63 56.88 0.20 12.35 0.0058 

GEORGIA GEORGIA POWER, 

PLANT YATES 

SG06 16,367 0 290.63 56.31 0.19 12.35 0.0057 

SIPSEY 

GEORGIA GEORGIA POWER, 

PLANT YATES 

SG07 16,530 0 245.30 67.39 0.27 15.03 0.0111 

GEORGIA GEORGIA POWER, 

PLANT YATES 

SG06 16,367 0 245.30 66.72 0.27 15.03 0.0110 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO3 27,735 0 356.99 77.69 0.22 6.86 0.0059 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO4 26,616 0 356.99 74.56 0.21 6.86 0.0056 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO1 26,264 0 356.99 73.57 0.21 6.86 0.0056 

GEORGIA GEORGIA POWER, 

PLANT SCHERER 

SGO2 26,075 0 356.99 73.04 0.20 6.86 0.0055 

SWANQUARTER 

GEORGIA INTERNATIONAL 

PAPER SAVANNAH 

MILL 

PB13 8578 4 587.64 14.60 0.02 24.37 0.0086 

GEORGIA SAVANNAH 

ELECTRIC, PLANT 

MCINTOSH 

SG01 7089 0 573.33 12.24 0.02 24.36 0.0072 

Note that only units located within Georgia are listed in Table 5.5. Since Georgia EPD is 

only responsible for Four Factor Analyses for sources located in Georgia that impact nonGeorgia Class I areas, units outside of Georgia that exceed the threshold value of 0.5% 

are not included. 

Spreadsheets were developed for each Class I area source with Q/d > 3 or Q/d2

 > 0.03, 

indicating the plant name, industry description, emissions projections for 2018, current 

control efficiency (CE%), distance from Class I area, Q/d, Q/d2

, RT average, RT 

maximum, Q/d*RT, the fraction a single source contributes to the total Q/d*RT for a 

Class I area. 

Using the process described above, GA EPD initially identified 27 emissions units for 

analysis of additional controls in accordance with the four statutory factors. The 27 units 

were selected based on analyses that indicated that each one’s contribution to total sulfate 

visibility impairment was at least 0.5% of the total sulfate visibility impairment at one or 

more Class I areas. The eligible units are listed below in Table 5-6. 
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Table 5-6. Facilities and emissions units eligible for 4-factor analysis 

Facility Eligible Unit(s) 

Georgia Pacific, Brunswick Cellulose Power Boiler No. 4 

Recovery Boiler (M24) 

Power Boiler U500 

Power Boiler U501 

Georgia Pacific, Cedar Springs 

Recovery Boiler R402 

Boiler B001 

Boiler B002 

Georgia Pacific, Savannah River Mill 

Boiler B003 

Georgia Power, Plant Kraft Steam Generator 1 

 Steam Generator 2 

 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 

Boiler B002 

Mount Vernon Mills Boiler E U 03 

Boiler E U 04 

Packaging Corporation of America C E Boiler 

Power Boiler 2 

Power Boiler 3 

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 

GA EPD reviewed the sources for which the Four Factor Analysis was to be conducted. 
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The first review was of existing permit and compliance files, pending permit applications 

and information provided by EPD permitting staff. As a result, one emissions unit 

(Temple Inland Corrugated Container Plant – Unit F2) was determined to have 

permanently ceased operation and was thus removed from the requirement for reasonable 

progress determination. According to correspondence from Temple Inland, the last day of 

operation of the Corrugated Container Plant (in Rome, Georgia) was November 11, 

2008. Georgia EPD revoked permit number 2653-115-088-V-02-0 on April 15, 2009. 

GA EPD requested a Four Factor Analysis from each of the remaining reasonable 

progress facilities on March 21, 2007. As a result of this inquiry, updated projected 2018 

emissions were received from some facilities. Other facilities requested emission limits 

to reduce the emission unit’s contribution to sulfate visibility impact on the nearest Class 

I area to less than the threshold of 0.5%. Table 5-7 gives a list of the units that were 

removed from the requirement for four-factor analysis as a result of updated emission 

projections or emission limitations. 

Table 5-7. Units dropped from four-factor analysis 

STATE PLANT POINT 

ID 

REASON FOR REMOVING UNIT FROM FOUR FACTOR 

ANALYSIS 

GEORGIA MOUNT VERNON 

MILLS, INC., APPAREL 

FABRIC 

EU03 Facility updated their 2018 emission information, lowering 

sulfate visibility impact to less than 0.5 % 

GEORGIA MOUNT VERNON 

MILLS, INC., APPAREL 

FABRIC 

EU04 Facility updated their 2018 emission information, lowering 

sulfate visibility impact to less than 0.5 %

GEORGIA JESUP MILL, RAYONIER 

PERFORMANCE FIBERS 

PB02 Facility took limit on units eligible for four factor analyses, 

lowering sulfate visibility impact to less than 0.5 % 

GEORGIA JESUP MILL, RAYONIER 

PERFORMANCE FIBERS 

PB03 Facility took limit on units eligible for four factor analyses, 

lowering sulfate visibility impact to less than 0.5 %

GEORGIA JESUP MILL, RAYONIER 

PERFORMANCE FIBERS 

RF01 Facility took limit on units eligible for four factor analyses, 

lowering sulfate visibility impact to less than 0.5 %

GEORGIA JESUP MILL, RAYONIER 

PERFORMANCE FIBERS 

RF04 Facility took limit on units eligible for four factor analyses, 

lowering sulfate visibility impact to less than 0.5 %

GEORGIA SOUTHERN STATES 

PHOSPHATE & 

FERTILIZER C 

SA02 Facility took limit on units eligible for four factor analyses, 

lowering sulfate visibility impact to less than 0.5 %

GEORGIA SAVANNAH SUGAR 

REFINERY 

U161 Facility updated their 2018 emission information, resulting in 

lowering of sulfate visibility impact to less than 0.5 %

GEORGIA PACKAGING 

CORPORATION OF 

AMERICA 

CE Facility took limit on units eligible for four factor analyses, 

lowering sulfate visibility impact to less than 0.5 %

GEORGIA MILLER BREWING B001 Facility updated their 2018 emission information, lowering 

sulfate visibility impact to less than 0.5 %
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GEORGIA MILLER BREWING B002 Facility updated their 2018 emission information, lowering 

sulfate visibility impact to less than 0.5 %

GEORGIA INTERSTATE PAPER 

LLC 

F1 Facility subject to full BART determination analysis. Exempt 

from 4-factor analysis per EPA guidance. 

GEORGIA MOHAWK INDUSTRIES BL06 Facility updated their 2018 emission information, lowering 

sulfate visibility impact to less than 0.5 % 

GEORGIA MOHAWK INDUSTRIES BL07 Facility updated their 2018 emission information, lowering 

sulfate visibility impact to less than 0.5 % 

Georgia EPD conducted Four Factor Analyses on the remaining Georgia Sources on the 

lists. For Non-Georgia units whose percentage contribution to sulfate visibility impact on 

a Georgia Class I area of 0.5% or greater, Georgia EPD requested, in writing, that the 

state that the unit is located in conduct a Four Factor Analysis on the unit to determine 

and require reasonable control measures. A copy of the letter sent to those states is found 

in Appendix J of the SIP narrative. 
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6.0 FOUR FACTOR ANALYSIS 

Section 169A(g)(1) of the Clean Air Act (CAA) and 40 CFR 51.308(d)(1)(i)(A). 

Four statutory factors that are outlined have been identified as mandatory for purposes of 

establishing a reasonable progress goal for any mandatory Class I area within a State: 

cost of compliance, time necessary for compliance, energy and non-air quality 

environmental impacts of compliance, and remaining useful life of any existing source 

subject to such requirements. These statutory factors would be specific to the sources 

being considered for additional controls. 

 

6.1 The Four Statutory Factors 

6.1.1 Cost of Compliance 

The “cost of compliance” is a factor used to determine whether compliance costs for 

sources are reasonable compared to the emission reduction and visibility improvement 

they will achieve. Note that visibility improvement is not only related to tons of pollutant 

removed, but also involves how the pollutant or chemical compound affects the 

extinction coefficient in each Class I area. For example, on a pound-to-pound 

comparison, sulfate particulate impairs visibility greater than coarse particulate. Costs 

should be determined for one-time capital costs, as well as ongoing annual operation and 

maintenance. 

6.1.2 Time Necessary for Compliance

The “time necessary for compliance” factor may be used to adjust the reasonable 

progress goals to reflect the degree of improvement achievable within the long-term 

strategy period, as opposed to the improvement expected at full implementation of a 

control measure, if the time needed for full compliance exceeds the length of the longterm strategy period. For instance, if implementation of a control measure could not be 

completed within the schedule outlined by the control strategy, the RPG should reflect 

what visibility improvement could be expected within the strategy period. 

For example, if construction labor availability constraints preclude the installation of 

controls at all sources of a particular category within the LTS period, the RPG should 

reflect the visibility improvement anticipated from installation of controls at the 

percentage of sources that could be controlled within the strategy period. (The SIP could 

still include control strategies that extend beyond the 2018 milestone. In the above 

example, the visibility improvement anticipated from installation of controls at the 

percentage of sources that could not be controlled within the first strategy period would 

have to be counted in a later SIP.) 
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6.1.3 Energy and Non-Air Quality Environmental Impacts of Compliance 

The “energy and non-air quality environmental impacts of compliance” factor is meant to 

consider whether the energy requirements of the control technology result in energy 

penalties or benefits. For example, controls on diesel engines may decrease the overall 

efficiency and require a significant increase in diesel fuel consumption. The State should 

also consider any significant or unusual non-air environmental impacts such as a waste 

stream that may be generated by a particular control technology. 

6.1.4 Remaining Useful Life of the Source 

The statutory factor of the “remaining useful life of the source” is applicable only to 

those measures which would require retrofitting of control devices (or possibly 

production changes) at existing sources. In such cases, this factor should be treated as 

one element of the overall cost analysis. For purposes of this analysis, the remaining 

useful life is the difference between the year of the reasonable progress analysis and the 

date the facility permanently stops operations. The remaining useful life of a source 

affects the annualized costs of retrofit controls. 

6.2 Evaluating Four Statutory Factors for Specific SO2 Emissions Sources in Each 

Area of Influence 

The next step was to identify emission reductions that have already occurred within each 

source category and at specific units. Unit-level tables of emission comparisons from 

2002 to 2018 were developed, allowing VISTAS States to review existing emission 

reductions. These tables assigned future-year control technology from IPM forecasting 

and State modification for EGU and from control-efficiency tables for non-EGU point 

sources. 

Once emission control profiles for specific units were defined, the next step is to 

determine what, if any, additional control measures would feasibly be available, and to 

assign costs to those control measures. 

For EGUs, the 2018 IPM file used by VISTAS for EGU sources was obtained and 

matched to the 2018 base-case inventory of EGU sources. This step was conducted to 

ensure that incremental controls assigned to these source types did not duplicate existing 

base-case assumptions. 

For non-EGUs, VISTAS used EPA’s AirControlNET database, modified for the VISTAS 

emission inventories. The core of AirControlNET is a relational database system in 

which control technologies are linked to sources within EPA emissions inventories. The 

system contains a database of control measure applicability, efficiency, and cost 

information for reducing emissions. The control measure data file in AirControlNET 

includes not only the technology's control efficiency and calculated emission reductions 
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for that source, but also estimates the costs (annual and capital) for application of the 

control measure. 

Using the modified inventories identified above, VISTAS ran every available SO2 

control strategy in AirControlNET against the EGU and non-EGU point source 

inventories to develop a master list of incremental control strategies for each unit in the 

VISTAS 36 km domain.

For the sources within the AOIs for each Georgia Class I area, Georgia requested sitespecific analysis from the affected facilities. Data obtained from AirControlNet 

(Appendix H.3) was used for comparison with site-specific analyses to identify possible 

control options that need to be evaluated and to determine possible over-estimation or 

under-estimation of cost efficiencies. 

 

The Regional Haze Rule requires that states consider the following factors and 

demonstrate how these factors were taken into consideration in selecting the reasonable 

progress goal: 

• the costs of compliance, 

• the time necessary for compliance, 

• the energy and non-air quality environmental impacts of compliance, and 

• the 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. 

6.2.1 Cost of Compliance 

Georgia EPD evaluated cost of compliance using a variety of factors. Facilities provided 

data for various control options for each affected unit. The data typically included total 

capital costs and cost-per-ton of pollutant removed ($/ton). Georgia EPD compared this 

data with similarly-controlled units as well as AirControlNET estimates. Costs were 

presented in 2007 dollars for consistency. In addition, Georgia EPD conducted CMAQ 

modeling to determine the amount of visibility improvement resulting from each ton of 

SO2 reduced from each unit subject to analysis. 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 efficiency for other SIPS (e.g., ozone and PM2.5). 

6.2.2 Time Necessary for Compliance 

Georgia EPD based the time necessary for compliance on the installation 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 the time the next Regional 
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Haze SIP is due. Any control options that can be installed and operated prior to 2012 

were determined to be timely. Control 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. 

6.2.3 Energy and Non-Air Environmental Impacts 

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 solid waste disposal, water withdrawal, and wastewater 

discharge. The review of control strategies that were not eliminated because of excessive 

cost efficiencies and that involved water withdrawal and wastewater discharge were 

coordinated with Georgia EPD’s Watershed Protection Branch. 

 

6.2.4 Remaining Useful Life 

The remaining useful life of an affected emissions unit can potentially impact 

reasonableness of control strategies in two ways. If the remaining useful life of an 

affected emission unit did not extend past 2018, no controls would be considered for that 

unit. If the remaining useful 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 Georgia 

EPD. 

6.3 Process of Applying Statutory Factors 

The Georgia EPD has completed the reasonable progress assessment for the first regional 

haze SIP. This process was based on U.S. EPA’s “Guidance for Setting Reasonable 

Progress Goals Under the Regional Haze Program,” June of 2007 [Reasonable Progress 

guidance]. The following was Georgia EPD’s Process on reasonable progress assessment 

for the current time period (from the present to 2018): 

Step 1: Determine pollutants of concern.

VISTAS evaluated the species contribution on the 20 percent worst visibility days and 

concluded that sulfate accounted for greater than 70 percent of the visibility-impairing 

pollution. The VISTAS States concluded that controlling SO2 emissions was the 

appropriate step in addressing the reasonable progress assessment for 2018. The 

VISTAS findings were consistent with the findings of the Southern Appalachian 

Mountain Initiative (SAMI). As you may recall, SAMI confirmed that sulfate particles 

account for the greatest portion of the haze affecting Class I areas in the Southern 
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Appalachian region and that these sulfates were produced in large part from SO2 

emissions from coal combustion. 

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

Since SO2 point source emissions in 2018 are projected to represent greater than 95 

percent of the total SO2 emissions inventory, the VISTAS States concluded that the focus 

should be on electric generating unit (EGU) and non-EGU point sources of SO2 

emissions. 

Step 3: Consideration of Emissions Reductions from State and Federal Control Measures. 

64 FR 35733 states that “In determining the emissions and visibility improvement 

achieved during each implementation period, states should 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 reasonable 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 % reduction 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 that additional EGU control during this 

time period is not reasonable. 

For EGUs subject to CAIR, EPA evaluated a number of factors, including 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 emissions was 2015...” (70 FR 25197 – 25198, May 12, 2005). The 

State believes that the cost of compliance and time necessary for compliance are the 

dominant factors for determining if additional reductions would be reasonable from 

CAIR-subject EGUs. The detailed analyses in the preamble to the May 12, 2005 CAIR 

rule support a conclusion that CAIR controls satisfy reasonable progress for SO2 for the 

first regional haze planning period ending in 2018. 

The SO2 emission reductions that are predicted 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. The GA EPD intends to re-evaluate the IPM 

predictions of SO2 reductions for CAIR for EGUs at the time of the first 5-year periodic 

report [40 CFR 51.308(g)] to ensure that the reductions currently predicted by IPM for 

CAIR are, in fact, taking place where they are expected and needed. 

The Cohutta Class I Area is expected, based on modeling, to clearly meet the glide slope 

in 2018. GA EPD has therefore concluded that CAIR constitutes reasonable measures for 

Georgia EGUs that significantly impact visibility in Cohutta during this first assessment 

period (between baseline and 2018). Because the Okefenokee, Wolf Island, and Saint 
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Marks areas are not expected to clearly meet the glide slope, controls required under 

CAIR have not been deemed to constitute reasonable measures for Georgia EGUs that 

significantly impact visibility in these Class I areas. 

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

Georgia EPD calculated the fractional contribution from all emission units within the 

SO2 Area of Influence for a given Class I area and identified those emission units with a 

contribution of half of a percent or more. 

Step 5: Evaluate the four factors. 

Each emission unit identified in Step 4 above was evaluated using the statutory and 

regulatory factors of 1) cost of compliance, 2) time necessary for compliance, 3) the 

energy and non-air quality environmental impacts of compliance, and 4) the remaining 

useful life of the emissions unit. Georgia EPD believes that the cost of compliance is 

typically the dominant factor in whether a source will be required to install controls. 

Therefore, much emphasis was placed on cost of control as part of this reasonable 

progress assessment, as compared to the other three statutory factors. 

 

6.4 Evaluation of Four-factor Eligible Emissions Units and Recommendations 

The Georgia EPD focused the reasonable progress assessments on specific units at the 

following non-EGU and EGU facilities in the State: 

Georgia Pacific Brunswick Cellulose 

Class I Areas: Wolf Island, Okefenokee Area 

Units (Wolf Island): F-1 (Power Boiler), M-24 (Recovery Boiler) 

Units (Okefenokee Wilderness Area): F-1 (Power Boiler) 

Georgia Pacific Cedar Springs 

Class I Area: St. Marks Area, Florida 

Units: U-500 (Power Boiler), U-501 (Power Boiler), R-402 (Recovery Boiler) 

Georgia Pacific Savannah River 

Class I Area: Wolf Island 

Units: B001, B002, B003 

International Paper Savannah Mill 

Class I Area: Wolf Island, Okefenokee, St. Marks, Florida, Swanquarter, North 

Carolina, Cape Romain, South Carolina 

Units: PB-13 

Interstate Paper 

 Class I Area: Wolf Island 

 Units: Power Boiler F1 
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Temple Inland Rome 

Class I Area: Cohutta Wilderness Area 

Units: Power Boiler 4 

Georgia Power Plant Kraft 

Class I Area: Wolf Island, Okefenokee Wilderness Area, and Cape Romain, SC 

NC 

Units: SG01, SG02 and SG03 

Georgia Power Plant McIntosh 

Class I Area: Wolf Island, Okefenokee , St. Marks Wilderness Area, FL, Cape 

Romain, SC, Swanquarter, NC 

Units: SG01 

Georgia Power Plant Mitchell 

Class I Area: Okefenokee and St. Marks, NC 

Units: SG03 

In March of 2007, Georgia EPD requested 4-factor analyses from affected facilities for 

each of their emissions units that were deemed eligible (Appendix H.4). In May 2007, 

EPD sent a follow-up letter extending the deadline for submission of the 4-factor 

analyses and providing further guidance on the compliance deadline for any controls 

determined to be reasonable. As discussed in the narrative, eligible units were those 

emissions units likely to contribute more than 0.5% to the total visibility impairment 

caused by sulfate at any Class I area in 2018. Facilities were requested to evaluate the 

feasibility of additional SO2 controls on these units based on the four statutory factors 

required to be analyzed in the setting of reasonable progress goals: 

1) The costs of compliance; 

2) The time necessary for compliance; 

3) The energy and non-air-quality environmental impacts of compliance; and 

4) The remaining useful life of existing sources that contributes to visibility 

impairment. 

The first step was to screen each unit using the fourth factor: remaining useful life of the 

source. If the remaining useful life extended beyond 2018, EPD requested that the other 

three statutory factors be analyzed using a “top-down” approach as follows: 

Step 1: Identification of all control technologies; 

Step 2: Elimination of technically-infeasible options; 
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Step 3: Ranking of remaining control technologies (top down) by control effectiveness; 

Step 4: Application of the first three statutory factors (cost of compliance, time necessary 

for compliance, energy and non air quality environmental impacts) to the control 

technologies identified in Step 3 and documentation of the results; and 

Step 5: Selection of control technology. 

 

In general, the cost estimates provided in the facilities’ submittals followed the methods 

outlined in EPA’s Air Pollution Control Cost Manual (EPA/452/B-02-001). Company 

cost estimates were typically prepared as study-level estimates, which are presumed to be 

accurate to within +/- 30 percent. Study-level estimates are appropriate for the 4-factor 

analysis. 

EPD reviewed the four-factor analyses received from the facilities to determine what, if 

any, controls may be reasonable to implement. Additional information was requested as 

needed. After reviewing all of the analyses, a list of emissions units was developed along 

with information regarding the four factors for all technically-feasible controls identified 

(see Table FF-1). EPD identified emissions units and associated controls that were 

deemed to be “reasonable” and then met with staff from affected facilities for discussion 

of controls, further communication of the reasonable progress goals, and verification of 

facility data. 

Georgia EPD used a number of factors to determine what should be considered 

“reasonable” for each emissions unit on a case-by-case basis. Included in these factors 

were the magnitude of the contribution to visibility impairment at the nearest Class I area, 

the number of Class I areas for which the emissions unit contributed to sulfate visibility 

impairment above the 0.5% “threshold,” the impact on PM2.5 non-attainment areas, 

existing SO2 controls, and cross-comparison of facility cost estimates to an EPA database 

(Air Control Net) and to other facility’s estimates (for comparably-sized control 

equipment). 

The following subsections provide details of the 4-factor analysis and decision process 

for each eligible unit. The results of the 4-factor analysis and review process are 

summarized for each eligible unit in Tables 6.1 and 6.2. An entry of “below threshold” 

means that the sulfate-related visibility impairment to the specific Class I area was below 

0.5 %. Table 6.3 provides explanatory notes for the various fields (columns) in Tables 

6.1 and 6.2. Summaries of the four-factor analyses submitted by the facilities are 

presented in Appendix H.10. 
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Table 6-1. Summary of Four-factor Analyses – South Georgia Facilities 
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 Appendix H 

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Table 6-2. Summary of Four-Factor Analyses - North Georgia Facilities 
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Table 6.3. Explanatory Notes for Summary of Four-Factor Analyses and Metrics 

Column Source Notes Class I sulfate impact fraction 

P&S Modeling unit 

This is the impact of sulfate emissions from the specific emissions unit on visispecified Class I area, expressed as a fraction of the combined sulfate impacts impacting facilities. The impact given is based on the VISTAS SO2 projected Threshold for inclusion in 4-factor analysis was impact of 0.005 (0.5 %) or mo

4F baseline SO2 company The baseline emissions used by the facility in the 4-factor submittal. In the ca

U501 at GA Pacific Cedar Springs, the number represents emissions after an e

scrubber with water scrubbant (they estimate 30% SO2 control). In the case oSavannah River, all 3 emissions units currently perform limestone injection fo

Baseline basis company In many instances the company used a different baseline emissions level than 

projected value. A blank field means that the company did not provide a full ethe VISTAS value has been inserted into the baseline field. 

Control Technology 

company Control, deemed technically feasible by the facility, evaluated for reduction of 

Control Effectiveness 

company Percent reduction as presented in the facility’s 4-factor analysis. In cases whe

not list a control effectiveness, this was back-calculated from the tons of reduc

Annual cost, company 

company Company cost estimates were typically prepared as study-level estimates, accu

30 percent. The costs are assumed to be in 2007 dollars (some companies statThe annual cost is the sum of the annual operation and maintenance cost and t

cost (capital cost), annualized over the life of the project. Project lives ranged 

years, interest rates from 7% to 10%, and capital recovery factors from 0.094 

Cost/ton calculation The annual cost divided by the tons reduced from the 4F baseline. Annual Cost, ACNet 

Air Control Net 

The estimated annual cost from a query of EPA’s Air Control Net database. T

came from queries which found matches for the applicable technology at the s

facility. The queries provide estimates in 2004 dollars. This number was then dollars using the Chemical Engineering Plant Cost Index. 
 Appendix H 

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Cost ratio, company to ACNet 

calculation Comparison of company estimate to ACNet estimate. Yellow cell indicates a 

than 1.3. 

Statutory factors Company A “0” indicates that the submittal provided no information pertaining to the sp

blue cell indicates that the company has indicated that the option could be impJan. 1, 2012. This would allow the control measure to be in place during all fi

visibility data will be collected for the 2018 Regional Haze progress report. T

life of all of the emissions units is 2018 or later. The expected useful life of al

units also exceeds the project life (i.e., amortization period) of all control optio

Visibility Sensitivity: Tons SO2/Mm-1

P&S Modeling unit 

The tons of SO2 required to effect a reduction of 1 Mm-1 (inverse megameter) Class I area. This value is independent of the control technology. 

Visibility Sensitivity: $106/Mm-1

Calculation The cost, based on the specific technology, to effect a reduction of 1 Mm-1 (in

in the applicable Class I area. This is the product of $/ton and ton/ Mm-1. Thdollars per ton ($/ton) was used in evaluating cost efficiency. 

Visibility Sensitivity: Tons SO2/Mm-1

Calculation The extinction reduction (visibility improvement) in Mm-1 that would be achie

applicable Class I area by implementation of the specific control. An orange cextinction reduction of greater than 0.010 and less than 0.100. A light green c

extinction reduction of greater than 0.100. 
 Appendix H 

75 of 122 

6.4.1 GA Pacific Brunswick Cellulose, Power Boiler No. 4 (F1) 

Georgia Pacific’s Brunswick Cellulose facility is located in Glynn County, near the 

Georgia coast. Power Boiler No. 4 is an 800 MMBtu/hr boiler that burns primarily No. 6 

fuel oil and wood waste, including bark. It is also permitted to burn tire-derived fuel and 

wastewater treatment sludge. The sulfur content of the fuel oil is 3% or less. Particulate 

emissions are controlled by an electrostatic precipitator (ESP). The baseline SO2 

emissions reported by the company were 1642 tons, based on the 2002 emissions report. 

In the course of communications with Georgia Pacific, it was learned that a boiler 

modification in 2002 had resulted in increased production efficiency when burning oil. 

The increased efficiency had reduced typical annual oil consumption to less than five 

million gallons-per-year. 

 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit had the highest contribution to visibility impact on a 

Class I area (12.55 at Wolf Island) of any other Georgia emission unit subject to the 4-

factor analysis. EPD also took into consideration that this unit significantly contributed 

to two Class I areas that were predicted to clearly not meet the Uniform Rate of Progress 

(glide slope) in 2018 based on “on the books” controls. 

Georgia Pacific’s original submittal identified the following control technologies, from 

most effective to least effective as being technically feasible: 

1. Wet scrubbing with caustic (wet flue gas desulfurization) 

2. Dry scrubbing with limestone injection 

3. In-duct sorbent injection 

4. Cleaner fuels 

5. Wet scrubbing with water only 

As noted above, a boiler modification in 2002 resulted in increased production efficiency 

when burning oil. Therefore, EPD added a 5 million gallon oil limit as a control option 

for evaluation and also combined the oil limit with other control technologies (in-duct 

sorbent injection and cleaner fuels) for evaluation. 

Wet flue gas desulfurization. Wet flue gas desulfurization (FGD) would achieve an 

SO2 reduction of approximately 95% and could be implemented before 2013. The cost 

metrics are $5449 per ton of SO2 reduced and $31.7 million and $35.7 million per 

inverse megameter (Mm-1) of visibility improvement (at Wolf Island and Okefenokee 

Class I areas, respectively). Regarding energy and non-air environmental impacts, this 

option would consume approximately 98 million gallons of water and generate an 

estimated 34 million gallons per year of wastewater. This control efficiency is projected 

to achieve light extinction reductions (which are visibility improvements) of 0.27 and 

0.24 Mm-1 at Wolf Island and Okefenokee, respectively. The cost effectiveness of this 

control option was determined not to be reasonable. 
 Appendix H 

76 of 122 

Dry scrubbing with limestone injection. Georgia Pacific installed dry scrubbing with 

limestone injection at its Port Hudson, LA, facility in 2007. The Port Hudson design was 

for a unit comparable in size to Brunswick’s Power Boiler No. 4. The total installed cost 

of the Port Hudson equipment was more than twice the estimated installed cost for wet 

FGD at Brunswick. Because the typical removal efficiencies of wet FGD and dry 

scrubbing are approximately the same, dry scrubbing was not considered further in the 

Brunswick four-factor submittal due to its high expected cost. The cost effectiveness of 

this control option was determined not to be reasonable. 

Five million gallon oil limit and in-duct sorbent injection. A five million gallon oil 

limit combined with in-duct sorbent injection was evaluated. This could be implemented 

before 2013 and would reduce allowable SO2 emissions to approximately 330 tons 

(accounting for 70% control efficiency applied to 1100 tons of emissions). The cost 

metrics are $3562 per ton of SO2 reduced and $20.7 million and $23.4 million per 

inverse megameter (Mm-1) of visibility improvement (at Wolf Island and Okefenokee 

Class I areas, respectively). Regarding energy and non-air environmental impacts, this 

option would generate an estimated 8000 tons per year of solid waste. This control 

option is projected to achieve light extinction reductions of 0.13 and 0.12 Mm-1 at Wolf 

Island and Okefenokee, respectively. This control option is considered to be reasonable 

due to cost-effectiveness, the relatively high visibility impact on two Class I areas and the 

fact that neither of these Class I areas is clearly meeting the uniform rate of progress. 

Five million gallon oil limit and fuel switch to 1.0 % sulfur oil. A five million gallon 

oil limit combined with switching to 1.0 % sulfur oil was evaluated. This could be 

implemented before 2012 and would reduce allowable SO2 emissions to approximately 

368 tons (accounting for 67% SO2 reduction applied to 1100 tons of emissions). The 

cost metrics are $3228 per ton of SO2 reduced and $18.8 million and $21.2 million per 

inverse megameter (Mm-1) of visibility improvement (at Wolf Island and Okefenokee 

Class I areas, respectively). No energy or non-air environmental impacts were 

documented. This control option is projected to achieve light extinction reductions of 

0.13 and 0.11 Mm-1 at Wolf Island and Okefenokee, respectively. This control option is 

considered to be reasonable due to cost-effectiveness, the relatively high visibility impact 

on two Class I areas and the fact that neither of these Class I areas is clearly meeting the 

uniform rate of progress. 

Five million gallon oil limit. Implementing a five million gallon limit on burning oil 

with the existing sulfur percentage would mimic typical operation since the improvement 

to boiler efficiency. This could be implemented immediately and would reduce 

allowable SO2 emissions to approximately 1100 tons, a 33% reduction from 1642 tons. 

There is no cost associated with this control, and there would be no energy or non-air 

environmental impacts. This control option is projected to achieve light extinction 

reductions of 0.093 and 0.083 Mm-1 at Wolf Island and Okefenokee, respectively. This 

control option has a lower control efficiency than other options that are considered 

reasonable. 
 Appendix H 

77 of 122 

Five million gallon oil limit and fuel switch to 2.2% sulfur oil. This could be 

implemented before 2012 and would reduce allowable SO2 emissions to approximately 

805 tons (accounting for 27% SO2 reduction applied to 1100 tons of emissions). This 

control option has a lower control efficiency than other options that are considered 

reasonable. 

Wet scrubbing with water only. This control option has a lower control efficiency 

(30%) than other options that are considered reasonable. 

Conclusion. In-duct sorbent injection and fuel-switching to 1% sulfur oil, both including 

the five million gallon per year oil consumption limit, were identified as reasonable 

controls. This was based on reasonable costs/ton, very low costs/visibility improvement, 

and timeliness of implementation. In addition, the visibility improvements at Wolf Island 

and Okefenokee would be relatively large. Implementation of the less restrictive of these 

two options would reduce SO2 emissions to 368 tons/12-consecutive months, as 

discussed above. 

Supplemental information provided by the facility 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 tons 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 available 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.

6.4.2 Georgia Pacific Brunswick Cellulose, Recovery Boiler No. 6 (M24) 

Recovery Boiler No. 6 burns black liquor with a 72% solids concentration. Particulate 

emissions are controlled by an electrostatic precipitator (ESP). The baseline SO2 

emissions estimated by VISTAS were 193 tons per year, contributing about 1.3% to the 

sulfate visibility impairment at Wolf Island. 

Georgia Pacific’s four-factor submittal found combustion control and wet FGD 

(scrubber) to be the only technically-feasible control options. The company stated that 

emissions of SO2 of 38 ppm, as measured in a 2006 stack test, is too low of a load for 

effective operation of a wet scrubber. Therefore, the company ruled out wet FGD based 

on cost effectiveness. Combustion control, the other technically-feasible control option, 

is already included in the boiler design. 

Conclusion. Due to the fact that this emission unit only contributes to visibility 

impairment at one Class I area and the relatively low baseline emissions level, Georgia 

EPD will not require any additional controls for Regional Haze Reasonable Progress. 
 Appendix H 

78 of 122 

6.4.3 Georgia Pacific Cedar Springs, Power Boiler No. 1 (U 500) 

Georgia Pacific’s Cedar Springs facility is located in Early County in the southwest 

corner of the state. Power Boiler No. 1 is a 784 MMBtu/hr boiler that burns primarily 

bituminous coal, wood waste, and fuel oil. The sulfur content of the fuel oil is typically 

1%. A venturi scrubber (water) controls particulate emissions and also provides some 

control of SO2 emissions estimated at 30%. The baseline SO2 emissions reported by the 

company were 1976 tons based on 2006 CEMS data. 

 

Georgia Pacific’s original submittal identified the following control technologies, from 

most effective to least effective, as being technically feasible: 

1. New wet FGD with caustic; 

2. Addition of spray towers and caustic to existing venturi scrubber; 

3. Addition of caustic to existing venturi scrubber; 

4. Duct sorbent injection; 

5. Cleaner coal; and 

6. Coal washing. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit had a relatively low visibility impact on only one 

Class I area (St. Marks, although it is not clearly meeting the uniform rate of progress). 

EPD also took into consideration that this unit is BART-eligible and that the facility 

desired to take reductions for the unit to be exempt from BART. 

New wet FGD with caustic. This option would achieve an SO2 reduction of 

approximately 93% and could be implemented before 2013. The cost metrics are $2725 

per ton of SO2 reduced and $1391.2 million per inverse megameter (Mm-1) of visibility 

improvement (at Saint Marks Class I area). Regarding energy and non-air environmental 

impacts, this option would generate approximately 15,000 tons per year of solid waste. 

This control is projected to achieve a light extinction reduction of 0.0036 Mm-1 at Saint 

Marks. This option was not considered cost effective. 

Addition of spray towers and caustic to existing venture scrubber. This option would 

achieve an SO2 reduction of approximately 86% and could be implemented before 2012. 

The cost metrics are $2952 per ton of SO2 reduced and $1497.0 million per inverse 

megameter (Mm-1) of visibility improvement (at the Saint Marks Class I area). 

Regarding energy and non-air environmental impacts, this option would generate 

approximately 15,000 tons per year of solid waste. This control is projected to achieve a 

light extinction reduction of 0.0033 Mm-1 at Saint Marks. This option was not 

considered cost effective. 

Addition of caustic to existing venturi scrubber. This option would achieve an SO2 

reduction of approximately 79% (total control, in lieu of existing 30%) and could be 

implemented before 2012. The cost metrics are $1675 per ton of SO2 reduced and $849 

million per inverse megameter (Mm-1) of visibility improvement (at Saint Marks Class I 
 Appendix H 

79 of 122 

area). Regarding energy and non-air environmental impacts, this option would generate 

approximately 15,000 tons per year of solid waste. This control is projected to achieve a 

light extinction reduction of 0.0031 Mm-1 at Saint Marks. The cost efficiencies (in both 

$/ton and $/Mm-1), the energy and non-environmental impacts were determined not to be 

unacceptable, and the controls could be installed in time for the full benefit to be realized 

during all five years in which the 2018 Regional Haze progress report will be based. 

Therefore, this control option is determined to be reasonable. 

Duct sorbent injection. This option would achieve an SO2 reduction of approximately 

70% (upstream of and in conjunction with the 30% scrubber removal) and could be 

implemented before 2012. The cost metrics are $1663 per ton of SO2 reduced and $843 

million per inverse megameter (Mm-1) of visibility improvement (at the Saint Marks 

Class I area). No energy or non-air environmental impacts were documented. This 

control is projected to achieve a light extinction reduction of 0.0027 Mm-1 at Saint 

Marks. The cost efficiencies (in both $/ton and $/Mm-1), the energy and nonenvironmental impacts were determined not to be unacceptable, and the controls could be 

installed in time for the full benefit to be realized during all 5 years in which the 2018 

Regional Haze progress report will be based. Therefore, this control option is determined 

to be reasonable. 

Cleaner coal. This control option was not considered because the SO2 control efficiency 

(25%) is lower than other options that are considered reasonable. 

Cleaner washing. This control option was not considered because the SO2 control 

efficiency (15%) is lower than other options that are considered reasonable. 

Conclusion. Addition of caustic to the existing venturi scrubber and duct sorbent 

injection were determined to be reasonable because of their relatively low costs per unit 

of visibility improvement. The other options had higher costs per visibility improvement 

and coal washing and coal switching also had lower total visibility improvements. As 

part of Georgia Pacific’s BART exemption modeling, the company has proposed SO2 

emission limits of 135 pounds per hour from Power Boiler. A limit of 135 lb/hr would 

result in maximum annual emissions of 591 tons/yr of SO2. This is a 70% reduction 

from baseline emissions. 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 for reasonable progress. No additional limitations will be required. 

6.4.4 Georgia Pacific Cedar Springs, Power Boiler No. 2 (U 501) 

Power Boiler No. 2 is the same size, burns the same fuels, and has the same estimated 

SO2 emissions as Power Boiler 1. The 4-factor analysis and recommendations are 

identical to those for Power Boiler No. 1. 
 Appendix H 

80 of 122 

6.4.5 Georgia Pacific Cedar Springs, Recovery Boiler No. 3 (R402) 

Recovery Boiler No. 3 burns black liquor and has a capacity of 769 MMBtu/hr. 

Particulate emissions are controlled by an electrostatic precipitator (ESP). The baseline 

SO2 emissions estimated by VISTAS were 1726 tons per year, which contributes about 

0.77 % to the sulfate visibility impairment at Saint Marks. 

Georgia Pacific’s original submittal did not contain any control measures for 4-factor 

analysis. However, the company did include control scenarios as part of the company’s 

BART exemption modeling request that included modifications to Recovery Boiler 3. 

Scenario 1 included repaired concentrator sets. This should result in a decrease of peak 

SO2 emissions. However, the company could not estimate the annual reduction in 

emissions from this control option. Therefore, it is assumed to be zero. Scenario 2 

included new concentrator sets and a new multi-level air system for the recovery boiler. 

This control measure would reduce SO2 emissions to 919.8 tons/yr. The Division 

requested cost analysis information for a new concentrator/multi-level air system and 

received this information on July 31, 2008. This submittal also contained further 

information regarding SO2 emissions from Recovery Boiler 3 and regarding the cost 

effectiveness of switching to 1% sulfur fuel oil. After reviewing this information, the 

Division requested information regarding the cost-effectiveness of switching from no. 6 

fuel oil to no. 2 fuel oil and received this information on August 15, 2008. 

Based on the information received from Georgia-Pacific, the recovery boiler has two 

operating modes. The normal operating mode is when the recovery boiler is burning 

black liquor (and at times co-firing fuel oil) at which time the furnace is operating in a 

reducing mode and thus has relatively low SO2 emissions (20-30 ppm). The other 

operating mode is when there is no black liquor being fired, but the mill is burning fuel 

oil in the recovery boiler in order to produce steam needed for the mill processes. During 

these periods, SO2 emissions are emitted uncontrolled (approximately 400-500+ ppm). 

The company provided information for 2006-2007 regarding SO2 emissions during each 

of these operating modes. Recovery Boiler 3 emitted 184 and 169 tons of SO2 per year 

in 2006 and 2007, respectively, when burning black liquor. Recovery Boiler 3 emitted 

278 and 571 tons of SO2 per year in 2006 and 2007, respectively, when burning only fuel 

oil. 

 

The control options reviewed for Recovery Boiler 3, ranked from most effective to least 

effective, are: 

1. Switching from no. 6 to no. 2 fuel oil with 0.5% sulfur; 

2. Switching from no. 6 fuel oil with 1.8 % sulfur [typical max)] to no. 6 fuel oil 

with 1% sulfur; 

3. New concentrator and new multi-level air system for high solids firing 
 Appendix H 

81 of 122 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit had a relatively low visibility impact on only one 

Class I area (St. Marks, although it is not clearly meeting the uniform rate of progress). 

New Concentrator and New Multi-Level Air System. This option would only reduce 

SO2 emissions when black liquor is fired in the recovery boiler. This is the normal 

operating mode of the recovery boiler. This conversion is estimated to reduce SO2 

emissions by 22% when firing black liquor. The company provided SO2 emissions 

information for periods when black liquor was being fired in the recovery boiler. This 

amount is 184 tons in 2006 and 169 tons in 2007. The cost metrics are $149,000 per ton 

of SO2 reduced and $75,500 million per inverse megameter (Mm-1) of visibility 

improvement (at Saint Marks Class I area). These high cost figures are logical 

considering that this control option would only be effective when SO2 emissions from 

the recovery boiler are already low. The company did not provide any indication that the 

control measure could not be operated prior to 2012 nor that there would be any energy 

or non-air quality environmental impacts. This option was not considered cost effective. 

Switching to 1% Fuel Oil . This option would only reduce SO2 emissions when only 

fuel oil is being fired in the recovery boiler. This sulfur content of fuel oil burned in this 

unit is limited to 3%. The company stated that the actual sulfur content ranged from 

0.7% to 1.8%. 1.8% sulfur fuel oil is used as the basis for this cost estimate. Conversion 

to 1% fuel oil would reduce SO2 emissions by 44% when burning fuel oil. The cost 

metrics are $12,000 per ton of SO2 reduced and $6116 million per inverse megameter 

(Mm-1) of visibility improvement (at Saint Marks Class I area). The company did not 

provide any indication that the control measure could not be operated prior to 2012 nor 

that there would be any energy or non-air quality environmental impacts. This option 

was not considered cost effective. 

Switching from no. 6 to no. 2 Fuel Oil . This option would reduce SO2 emissions only 

when fuel oil is being fired in the recovery boiler. The recovery boiler currently burns 

no. 6 fuel oil and the company stated that the actual sulfur content ranged from 0.7% to 

1.8%. 1.8% sulfur fuel oil is used as the basis for this cost estimate. The sulfur content 

for no. 2 fuel oil is defined as 0.5%. Conversion to no. 2 fuel oil would reduce SO2 

emissions by 72% when burning fuel oil. The cost metrics are $22,900 per ton of SO2 

reduced and $11,594 million per inverse megameter (Mm-1) of visibility improvement 

(at Saint Marks Class I area). The company did not provide any indication that the 

control measure could not be operated prior to 2012 nor that there would be any energy 

or non-air quality environmental impacts. This option was not considered cost effective.

Conclusion. None of the control options were considered reasonable given the high-cost 

efficiencies (in both $/ton and $/Mm-1), and the relatively low-visibility impact on a 

single Class I area. Georgia EPD, therefore, will not require any additional controls be 

required for Regional Haze reasonable progress. 
 Appendix H 

82 of 122 

6.4.6 Georgia Pacific Savannah River Mill, No. 3 Boiler (B001) 

Georgia Pacific’s Savannah River facility is located in Effingham County, northwest of 

the City of Savannah. The No. 3 Power Boiler is a re-circulating fluidized bed 422 

MMBtu/hr boiler that burns petcoke (6.1 % sulfur2) and bituminous coal (1.55 % sulfur). 

Under current operation, petcoke is the primary fuel. Limestone injection into the 

combustion chamber provides control (approximately 90%) of SO2 emissions. The 

facility’s current Title V permit limits SO2 emissions from this unit to 2152 tons. The 

baseline level of SO2 emissions reported by the company was 1659 tons, based on 2005 

CEMS data. This compares with the VISTAS estimated baseline of 1844 tons. 

Georgia Pacific’s original submittal identified the following control technologies, from 

most effective to least effective, as being technically feasible: 

1. Wet FGD with caustic; 

2. Circulating fluidized bed scrubber; 

3. Switch to 100 % coal firing; 

4. Increased limestone injection; and 

5. Rotating opposed fire air combustion control. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit had a relatively low visibility impact on only one 

Class I area (1.1% of the sulfate impact at Wolf Island, although it is not clearly meeting 

the uniform rate of progress). Another consideration was that this unit has an existing 

control (approximately 90%) for SO2. 

Wet FGD with caustic. This option would achieve an SO2 reduction of approximately 

95% and could be implemented after 2012 (a specific date was not provided). The cost 

metrics are $2430 per ton of SO2 reduced and $ 602.2 million per inverse megameter 

(Mm-1) of visibility improvement (at the Wolf Island Class I area). Regarding energy 

and non-air environmental impacts, this option would use 20 million gallons-per-year of 

water and increased the dissolved solids load to their wastewater treatment system. This 

control is projected to achieve a light extinction reduction of 0.0006 Mm-1 at Wolf 

Island. This option was not considered cost effective. 

Circulating fluidized bed scrubber. This option would achieve an SO2 reduction of 

approximately 95% and could be implemented after 2012 (a specific date was not 

provided). The cost metrics are $4504 per ton of SO2 reduced and $1116.3 million per 

inverse megameter (Mm-1) of visibility improvement (at the Wolf Island Class I area). 

No energy and non-air environmental impacts were reported. This control is projected to 

 

2

 The sulfur content of petcoke is allowed to exceed the 3 percent limit set by rule 

Georgia Air Quality Rule 391-3-1-.02(2)(g)2. because the boilers are equipped with flue 

gas desulfurization and thus qualifies for the provisions of 391-3-1-.02(2)(g)3. 
 Appendix H 

83 of 122 

achieve a light extinction reduction of 0.0006 Mm-1 at Wolf Island. This option was not 

considered cost effective. 

Switch to 100% coal firing. This option would achieve an SO2 reduction of 

approximately 65% and could be implemented after 2012 (a specific date was not 

provided). The cost metrics are $4451 per ton of SO2 reduced and $1103.0 million per 

inverse megameter (Mm-1) of visibility improvement (at the Wolf Island Class I area). 

No energy and non-air environmental impacts were reported. This control is projected to 

achieve a light extinction reduction of 0.0004 Mm-1 at Wolf Island. This option was not 

considered cost effective. 

Rotating opposed fire air. This option would achieve an SO2 reduction of 

approximately 30% and could be implemented after 2012 (a specific date was not 

provided). The cost metrics are $2150 per ton of SO2 reduced and $532.7 million per 

inverse megameter (Mm-1) of visibility improvement (at Wolf Island Class I area). No 

energy and non-air environmental impacts were reported. This control is projected to 

achieve a light extinction reduction of 0.0002 Mm-1 at Wolf Island. This option was not 

considered cost effective. 

Increased limestone injection. Georgia-Pacific conducted trial operations with 

increased limestone injection rates and found that overall SO2 removal could only be 

increased by an additional two percent (from 87% to 89%) resulting in an additional SO2 

reduction of approximately 15%. This option could be implemented prior to 2012. The 

cost metrics are $7223 per ton of SO2 reduced and $1792.4 million per inverse 

megameter (Mm-1) of visibility improvement (at Wolf Island Class I area). Regarding 

energy and non-air environmental impacts, this option would result in 24,000 to 60,000 

tons per year of solid waste. This control is projected to achieve a light extinction 

reduction of 0.0001 Mm-1 at Wolf Island. This option was not considered cost effective. 

Conclusion. None of the control options were considered reasonable given the resulting 

control efficiencies, the time delay to implementation (with the exception of increased 

limestone injection), the high-cost efficiencies (in both $/ton and $/Mm-1), and the 

relatively low-visibility impact on a single Class I area. Georgia EPD, therefore, will not 

require any additional controls be required for Regional Haze reasonable progress. 

6.4.7 Georgia Pacific Savannah River Mill, No. 4 Boiler (B002) 

The No. 4 Power Boiler is also a re-circulating fluidized bed boiler that is the same size, 

burns the same fuels, and has the same SO2 controls as the No. 3 Boiler. The facility’s 

current Title V permit limits SO2 emissions from this unit to 1671 tons. The baseline 

level of SO2 emissions reported by the company was 1195 tons based on 2005 CEMS 

data. This compares with the VISTAS estimated baseline of 1415 tons. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit had a relatively low visibility impact on only one 

Class I area (0.86% of the sulfate impact at Wolf Island although it is not clearly meeting 
 Appendix H 

84 of 122 

the uniform rate of progress). Another consideration was that this unit has a required 

minimum 90% control efficiency for SO2 as specified in NSPS Subpart Db. 

The four-factor submittal identified the same control options as for the No. 3 Boiler. For 

the same reasons as listed for the No. 3 Boiler, Georgia EPD will not require any 

additional controls be required. 

6.4.8 Georgia Pacific Savannah River Mill, No. 5 Boiler (B003) 

The No. 5 Power Boiler is also a re-circulating fluidized bed boiler that is the same size, 

burns the same fuels, and has the same SO2 controls as the No. 3 and No. 4 Boilers. The 

facility’s current Title V permit limits SO2 emissions from this unit to 1671 tons. The 

baseline level of SO2 emissions reported by the company was 1190 tons based on 2005 

CEMS data. This compares with the VISTAS estimated baseline of 1282 tons. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit had a relatively low visibility impact on only one 

Class I area (0.77% of the sulfate impact at Wolf Island although it is not clearly meeting 

the uniform rate of progress). Another consideration was that this unit has a required 

minimum 90% control efficiency for SO2 as specified in NSPS Subpart Db. 

The four-factor submittal identified the same control options as for the No. 3 and No. 4 

Boilers. For the same reasons as listed for the No. 3 Boiler, Georgia EPD will not require 

any additional controls be required. 

6.4.9 Georgia Power Plant Kraft, Steam Generator 1 

Georgia Power’s Plant Kraft is located in Chatham County, near the Georgia coast. 

Steam Generator Unit 1 is a 50 Megawatt coal-fired electric utility boiler. The sulfur 

content of the coal is limited to 3% or less and currently burns relatively low-sulfur coal 

(0.62% S). Particulate emissions are controlled by an electrostatic precipitator (ESP). 

The 2018 baseline SO2 emissions reported by the company were 632 tons which is close 

to the 2018 emissions projected by VISTAS using an IPM of 691 tons. 632 tons per year 

was used as the baseline SO2 emissions used in this analysis. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributed to only one Class I area 

(Wolf Island) by a relatively low amount (0.51%; EPD’s “threshold” for significant 

contribution was 0.5%). EPD also took into consideration that this unit significantly 

contributed to a Class I area that was predicted to not clearly meet the Uniform Rate of 

Progress (glide slope) in 2018 based on “on the books” controls. 

Georgia Power’s submittal identified the following control technologies, from most 

effective to least effective, as being technically feasible: 

1. Wet flue gas desulfurization; 
 Appendix H 

85 of 122 

2. Coal switching; and 

3. Coal washing. 

Wet flue gas desulfurization. Wet flue gas desulfurization (FGD) would achieve an 

SO2 reduction of approximately 95% and could be implemented by January 2016. The 

cost efficiencies are $8161 per ton of SO2 reduced and $144.5 million per inverse 

megameter (Mm-1) of visibility improvement (at the Wolf Island Class I area). 

Regarding energy and non-air environmental impacts, this option would reduce energy 

production by approximately 2% (1000 k), consume approximately 90 gallons of water 

per Mwh, discharge 30 gallons of wastewater per Mwh, and generate 2.7 tons of gypsum 

per ton of SO2 removed. This control efficiency is projected to achieve light extinction 

reductions (which are visibility improvements) of 0.03 Mm-1 at Wolf Island. The cost 

effectiveness of this control option was determined not to be reasonable. 

Coal Switching. Switching to 0.38 percent coal would achieve an SO2 reduction of 

approximately 39%. No data was submitted regarding the time to implement, thus it was 

assumed that coal washing could be achieved by January 1, 2012. The cost efficiencies 

are $4041 per ton of SO2 reduced and $71.5 million per inverse megameter (Mm-1) of 

visibility improvement (at the Wolf Island Class I area). Regarding energy and non-air 

environmental impacts, the company indicated that this option could possibly reduce 

boiler efficiency, but did not provide a quantitative amount. Non-air quality 

environmental impacts were not reported. This control efficiency is projected to achieve 

light extinction reductions (which are visibility improvements) of 0.01 Mm-1 at Wolf 

Island. The cost effectiveness of this control option was determined not to be reasonable. 

Coal Washing. Coal washing would achieve an SO2 reduction of approximately 6%. 

No data was submitted regarding the time to implement, thus it was assumed that coal 

switching could be achieved by January 1, 2012. The cost efficiencies are $1839 per ton 

of SO2 reduced and $32.5 million per inverse megameter (Mm-1) of visibility 

improvement (at the Wolf Island Class I area). The annualized cost of this control was 

only about 30% of the cost predicted by AirControlNET, indicating that, if anything, the 

costs provided by the company may be underestimated. Regarding energy and non-air 

environmental impacts, the company indicated that this option could possibly reduce 

boiler efficiency, would use 4400 gallons per day of water, would result in acidic 

wastewater requiring treatment, and would result in coal refuse in the amount of 

approximately 5% of the total coal consumption. This control efficiency is projected to 

achieve light extinction reductions (which are visibility improvements) of 0.002 Mm-1 at 

Wolf Island. Based on the relatively low control efficiency of this option, the negative 

non-air environmental impacts, and the relatively low visibility impact, this control 

option was determined not to be reasonable. 

Conclusion. No additional controls will be required for Plant Kraft Steam Generator 1. 
 Appendix H 

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6.4.10 Georgia Power Plant Kraft, Steam Generator 2 

Georgia Power’s Plant Kraft is located in Chatham County, near the Georgia coast. 

Steam Generator Unit 1 is a 54 Megawatt coal-fired electric utility boiler. The sulfur 

content of the coal is limited to 3% or less and currently burns relatively low-sulfur coal 

(0.62% S). Particulate emissions are controlled by an electrostatic precipitator (ESP). 

The 2018 baseline SO2 emissions reported by the company were 889 tons, which is 

higher, but relatively close, to the 2018 emissions projected by VISTAS using an IPM of 

704 tons. 889 tons per year was used as the baseline SO2 emissions used in this analysis. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributed to only one Class I area 

(Wolf Island) by a relatively low amount (0.52%; EPD’s “threshold” for significant 

contribution was 0.5%.) EPD also took into consideration that this unit significantly 

contributed to a Class I area that was predicted to not clearly meet the Uniform Rate of 

Progress (glide slope) in 2018 based on “on the books” controls. 

Georgia Power’s submittal identified the following control technologies, from most 

effective to least effective, as being technically feasible: 

1. Wet flue gas desulfurization; 

2. Coal switching; and 

3. Coal washing. 

Wet flue gas desulfurization. Wet flue gas desulfurization (FGD) would achieve an 

SO2 reduction of approximately 95% and could be implemented by January 2016. The 

cost efficiencies are $6039 per ton of SO2 reduced and $106.9 million per inverse 

megameter (Mm-1) of visibility improvement (at the Wolf Island Class I area). 

Regarding energy and non-air environmental impacts, this option would reduce energy 

production by approximately 2% (1000 k), consume approximately 90 gallons of water 

per Mwh, discharge 30 gal of wastewater per Mwh, and generate 2.7 tons of gypsum per 

ton of SO2 removed. This control efficiency is projected to achieve light extinction 

reductions (which are visibility improvements) of 0.05 Mm-1 at Wolf Island. The cost 

effectiveness of this control option was determined not to be reasonable. 

Coal Switching. Switching to 0.38 percent coal would achieve an SO2 reduction of 

approximately 39%. No data was submitted regarding the time to implement, thus it was 

assumed that coal switching could be achieved by January 1, 2012. The cost efficiencies 

are $4041 per ton of SO2 reduced and $71.5 million per inverse megameter (Mm-1) of 

visibility improvement (at the Wolf Island Class I area). Regarding energy and non-air 

environmental impacts, the company indicated that this option could possibly reduce 

boiler efficiency, but did not provide a quantitative amount. There were not reported 

non-air quality environmental impacts. This control efficiency is projected to achieve 

light extinction reductions (which are visibility improvements) of 0.02 Mm-1 at Wolf 

Island. The cost effectiveness of this control option was determined not to be reasonable. 
 Appendix H 

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Coal Washing. Coal washing would achieve an SO2 reduction of approximately 6%. 

No data was submitted regarding the time to implement, thus it was assumed that coal 

washing could be achieved by January 1, 2012. The cost efficiencies are $1847 per ton 

of SO2 reduced and $32.7 million per inverse megameter (Mm-1) of visibility 

improvement (at the Wolf Island Class I area). The annualized cost of this control was 

only about 30% of the cost predicted by AirControlNET, indicating that, if anything, the 

costs provided by the company may be underestimated. Regarding energy and non-air 

environmental impacts, the company indicated that this option could possibly reduce 

boiler efficiency, would use 4600 gallons per day of water, would result in acidic 

wastewater requiring treatment, and would result in coal refuse in the amount of 

approximately 5% of the total coal consumption. This control efficiency is projected to 

achieve light extinction reductions (which are visibility improvements) of 0.003 Mm-1 at 

Wolf Island. Based on the relatively low control efficiency of this option, the negative 

non-air environmental impacts, and the relatively low visibility impact, this control 

option was determined not to be reasonable. 

Conclusion. No additional controls will be required for Plant Kraft Steam Generator 2. 

6.4.11 Georgia Power Plant Kraft, Steam Generator 3 

Georgia Power’s Plant Kraft is located in Chatham County, near the Georgia coast. 

Steam Generator Unit 1 is a 104 Megawatt coal-fired electric utility boiler. The sulfur 

content of the coal is limited to 3% or less and currently burns relatively low-sulfur coal 

(0.62% S). Particulate emissions are controlled by an electrostatic precipitator (ESP). 

The 2018 baseline SO2 emissions reported by the company were 2455 tons, which is 

significantly lower than the 2018 emissions projected by VISTAS using an IPM of 4474. 

Georgia Power provided information dated September 7, 2007, indicating that utilization 

of the boiler will drop significantly in 2015 as a result of new generation coming on-line 

about that same time. EPD used a baseline SO2 emission rate of 2455 tons in this 

analysis. EPD can review the actual utilization of Unit 3 when the next Regional Haze 

SIP is developed to ensure that the assumption of reduced utilization has actually 

occurred. If not, analysis of additional controls can be re-analyzed during development 

of that SIP. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributed to three Class I areas [Wolf 

Island (3.3%), Okefenokee (0.9%), and Cape Roman (0.8%).] EPD also took into 

consideration that this unit significantly contributed to two Class I areas (Wolf Island and 

Okefenokee) that were predicted to not clearly meet the Uniform Rate of Progress (glide 

slope) in 2018 based on “on the books” controls. 

Georgia Power’s original submittal identified the following control technologies, from 

most effective to least effective, as being technically feasible: 

1. Wet flue gas desulfurization; 
 Appendix H 

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2. Coal switching; and 

3. Coal washing. 

Wet flue gas desulfurization. Wet flue gas desulfurization (FGD) would achieve an SO2 

reduction of approximately 95% and could be implemented by January 2016. The cost 

efficiencies are $3216 per ton of SO2 reduced and $56.9 and $58.2 million per inverse 

megameter (Mm-1) of visibility improvement at Wolf Island and Okefenokee Class I 

areas, respectively. Regarding energy and non-air environmental impacts, this option 

would reduce energy production by approximately 2% (2000 k), consume approximately 

90 gallons of water per Mwh, discharge 30 gal of wastewater per Mwh, and generate 2.7 

tons of gypsum per ton of SO2 removed. This control efficiency is projected to achieve 

light extinction reductions (which are visibility improvements) of 0.13 Mm-1 at both 

Wolf Island and Okefenokee. Taking into account the cost effectiveness and non-air 

quality environmental impacts, this option was determined not to be reasonable. 

Coal Switching. Switching to 0.38 percent coal would achieve an SO2 reduction of 

approximately 39%. No data was submitted regarding the time to implement, thus it was 

assumed that coal switching could be achieved by January 1, 2012. The cost efficiencies 

are $4042 per ton of SO2 reduced and $71.5 and $73.2 million per inverse megameter 

(Mm-1) of visibility improvement at Wolf Island and Okefenokee Class I areas, 

respectively. Regarding energy and non-air environmental impacts, the company 

indicated that this option could possibly reduce boiler efficiency, but did not provide a 

quantitative amount. Non-air quality environmental impacts were not reported. This 

control efficiency is projected to achieve light extinction reductions (which are visibility 

improvements) of 0.05 Mm-1 at both Wolf Island and Okefenokee. The cost 

effectiveness of this control option was determined not to be reasonable. 

Coal Washing. Coal washing would achieve an SO2 reduction of approximately 6%. 

No data was submitted regarding the time to implement, thus it was assumed that coal 

washing could be achieved by January 1, 2012. The cost efficiencies are $1845 per ton 

of SO2 reduced and $32.7 and $33.4 million per inverse megameter (Mm-1) of visibility 

improvement at Wolf Island and Okefenokee Class I areas, respectively. The annualized 

cost of this control was only about 50% of the cost predicted by AirControlNET, 

indicating that, if anything, the costs provided by the company may be underestimated. 

Regarding energy and non-air environmental impacts, the company indicated that this 

option could possibly reduce boiler efficiency, would use 7500 gallons per day of water, 

would result in acidic wastewater requiring treatment, and would result in coal refuse in 

the amount of approximately 5% of the total coal consumption. This control efficiency is 

projected to achieve light extinction reductions (which are visibility improvements) of 

0.01 Mm-1 at both Wolf Island and Okefenokee. Based on the relatively low control 

efficiency of this option, the negative non-air environmental impacts, and the relatively 

low visibility impact, this control option was determined not to be reasonable. 

Conclusion. No additional controls will be required for Plant Kraft Steam Generator 3. 

However, this conclusion may be revised should the reduction in utilization and SO2 

emissions reported by the company not be realized. 
 Appendix H 

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6.4.12 Georgia Power Plant McIntosh, Steam Generator 1 

Georgia Power’s Plant McIntosh is located in Effingham County, near the Georgia coast 

about 10-15 miles north of Plant Kraft. Steam Generator Unit 1 is a 178 megawatt coalfired electric utility boiler. The sulfur content of the coal is limited to 3% or less and 

currently burns relatively low-sulfur coal (0.62% S). Particulate emissions are controlled 

by an electrostatic precipitator (ESP). The 2018 baseline SO2 emissions reported by the 

company were 1860 tons, which is significantly lower than the 2018 emissions projected 

by VISTAS using an IPM of 7015. Georgia Power provided information dated 

September 7, 2007, indicating that utilization of the boiler will drop significantly between 

2011 and 2015 as a result of new a generation coming on-line about that same time. EPD 

used a baseline SO2 emission rate of 1860 tons in this analysis. EPD can review the 

actual utilization of McIntosh Unit 1 when the next Regional Haze SIP is developed to 

ensure that the assumption of reduced utilization has actually occurred. If not, analysis of 

additional controls can be re-analyzed during development of that SIP. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributed to five class I areas [Wolf 

Island (4.1%), Okefenokee (1.2%), Saint Marks (0.6%), Cape Romain (1.4%), and 

Swanquarter (0.7%)], the highest number of all of the units (except International Paper 

Power Boiler 13, which also impacts the same five class I areas) reviewed by EPD. EPD 

also took into consideration that this unit significantly contributed to three Class I areas 

(Wolf Island, Okefenokee, and Saint Marks) that was predicted to not clearly meet the 

Uniform Rate of Progress (glide slope) in 2018, based on “on the books” controls. 

However, should utilization and SO2 emissions by approximately 75%, as reported by 

the company, the visibility impairment will reduce to less than the 0.5% threshold for 

four of these Class I areas and will be significantly less on the remaining one (Wolf 

Island (1.1%). 

Georgia Power’s submittal identified the following control technologies, from most 

effective to least effective, as being technically feasible: 

1. Wet flue gas desulfurization; 

2. Coal switching; and 

3. Coal washing. 

Wet flue gas desulfurization. Wet flue gas desulfurization (FGD) would achieve an SO2 

reduction of approximately 95% and could be implemented by January 2016. The cost 

efficiencies are $7131 per ton of SO2 reduced and $118.5, $132.6 and $411.0 million per 

inverse megameter (Mm-1) of visibility improvement at Wolf Island, Okefenokee, and 

St. Marks Class I areas, respectively. Regarding energy and non-air environmental 

impacts, this option would reduce energy production by approximately 1-2%, consume 

approximately 80-110 gallons of water per MWh and generate 2.7 tons of gypsum per ton 

of SO2 removed. This control efficiency is projected to achieve light extinction 

reductions (which are visibility improvements) of 0.11 Mm-1 at Wolf Island, 0.09 Mm-1 
 Appendix H 

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at Okefenokee, and 0.03 Mm-1 at St. Marks. The cost effectiveness of this control option 

was determined not to be reasonable. 

Coal Switching. Switching to 0.38 percent coal would achieve an SO2 reduction of 

approximately 39%. No data was submitted regarding the time to implement, thus it was 

assumed that coal switching could be achieved by January 1, 2012. The cost efficiencies 

are $4306 per ton of SO2 reduced and $71.5, $80.1, and $248.2 million per inverse 

megameter (Mm-1) of visibility improvement at Wolf Island, Okefenokee, and St. Marks 

Class I areas, respectively. Regarding energy and non-air environmental impacts, the 

company indicated that this option could possibly reduce boiler efficiency, but did not 

provide a quantitative amount. Non-air quality environmental impacts were not reported. 

This control efficiency is projected to achieve light extinction reductions (which are 

visibility improvements) of 0.04 Mm-1 at both Wolf Island and Okefenokee, and 0.01 

Mm-1 at St. Marks. The cost effectiveness of this control option was determined not to 

be reasonable. 

Coal Washing. Coal washing would achieve an SO2 reduction of approximately 6%. 

No data was submitted regarding the time to implement, thus it was assumed that coal 

washing could be achieved by January 1, 2012. The cost efficiencies are $5534 per ton 

of SO2 reduced and $91.9, $102.9, and $319.0 million per inverse megameter (Mm-1) of 

visibility improvement at Wolf Island, Okefenokee, and St. Marks Class I areas, 

respectively. The annualized cost of this control was only about 25% of the cost 

predicted by AirControlNET, indicating that, if anything, the costs provided by the 

company may be underestimated. Regarding energy and non-air environmental impacts, 

the company indicated that this option would use 163,000 gallons per day of water, 

would result in acidic wastewater requiring treatment, and would result in coal refuse in 

the amount of approximately 5% of the total coal consumption. Energy impacts were not 

reported and are thus assumed to be minimal. This control efficiency is projected to 

achieve light extinction reductions (which are visibility improvements) of 0.002 Mm-1 at 

both Wolf Island and Okefenokee, and 0.0006 Mm-1 at St. Marks. The cost effectiveness 

of this control option was determined not to be reasonable. 

Conclusion. No additional controls will be required for Plant McIntosh Steam Generator 

1. However, this conclusion may be revised should the reduction in utilization and SO2 

emissions reported by the company not be realized. 

6.4.13 Georgia Power Plant Mitchell, Steam Generator 3 

Georgia Power’s Plant Mitchell is located in Dougherty County, in southwest Georgia. 

Steam Generator Unit 3 is a 163 Megawatt coal-fired electric utility boiler. The sulfur 

content of the coal is limited to 3% or less and currently burns relatively low-sulfur coal 

(1% S) and employs coal washing, which slightly reduces SO2 emissions. Particulate 

emissions are controlled by an electrostatic precipitator (ESP). The 2018 baseline SO2 

emissions reported by the company were 1189 tons, which is significantly lower than the 

2018 emissions projected by VISTAS using IPM of 4930. Georgia Power provided 

information dated September 7, 2007, indicating that utilization of the boiler will drop 
 Appendix H 

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significantly between 2008 and 2010 as a result of new a generation coming on-line about 

that same time. EPD used a baseline SO2 emission rate of 1189 tons in this analysis. 

EPD can review the actual utilization of McIntosh Unit 1 during the mid-course review to 

ensure that the assumption of reduced utilization has actually occurred. If not, analysis of 

additional controls can be re-analyzed during development of that SIP. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributed to two Class I areas (Saint 

Marks (2.7%) and Okefenokee (0.8%). EPD also took into consideration that this unit 

significantly contributed to two Class I areas that were predicted to not clearly meet the 

Uniform Rate of Progress (glide slope) in 2018, based on “on the books” controls. 

However, should utilization and SO2 emissions drop by approximately 75%, as reported 

by the company, the visibility impairment will reduce to less than the 0.5% threshold for 

Okefenokee and will be significantly less on the remaining one [Saint Marks (0.7%)]. 

Georgia Power’s submittal identified the following control technologies, from most 

effective to least effective, as being technically feasible: 

1. Wet flue gas desulfurization; and 

2. Coal switching. 

Wet flue gas desulfurization. Wet flue gas desulfurization (FGD) would achieve an SO2 

reduction of approximately 95% and could be implemented by January 2016. The cost 

efficiencies are $9119 per ton of SO2 reduced and $148.5, and $299.4 0 million per 

inverse megameter (Mm-1) of visibility improvement at Okefenokee and St. Marks Class 

I areas, respectively. Regarding energy and non-air environmental impacts, this option 

would reduce energy production by approximately 1-2% (1250-2500 kw). No non-air 

quality environmental impacts were reported. This control efficiency is projected to 

achieve light extinction reductions (which are visibility improvements) of 0.07 Mm-1 at 

Okefenokee and 0.03 Mm-1 at St. Marks. The cost effectiveness of this control option 

was determined not to be reasonable. 

Coal Switching. Switching to 0.38 percent coal would achieve an SO2 reduction of 

approximately 47%. No data was submitted regarding the time to implement, thus it was 

assumed that coal switching could be achieved by January 1, 2012. The cost efficiencies 

are $2347 per ton of SO2 reduced and $38.2 and $77.1 million per inverse megameter 

(Mm-1) of visibility improvement at Okefenokee and St. Marks Class I areas, 

respectively. Regarding energy and non-air environmental impacts, the company 

indicated that this option could possibly reduce boiler efficiency. No non-air quality 

environmental impacts were reported. This control efficiency is projected to achieve 

light extinction reductions (which are visibility improvements) of 0.03 Mm-1 at 

Okefenokee, and 0.02 Mm-1 at St. Marks. Based on the relatively low visibility 

impairment resulting from significant reductions in SO2 emissions from this unit, the cost 

effectiveness of this control option was not low enough to be considered reasonable. 
 Appendix H 

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Conclusion. No additional controls will be required for Plant Mitchell Steam Generator 

3. However, this conclusion may be revised should the reduction in utilization and SO2 

emissions reported by the company not be realized. 

6.4.14 International Paper Savannah Mill, Power Boiler 13 

 

International Paper’s Savannah Mill is located in Chatham County, on Georgia’s coast at 

the border with South Carolina. Power Boiler 13 (PB 13) is a 1280 MMBtu/hr boiler that 

burns bituminous coal (primary fuel), bark, and wood fines. The sulfur content of the 

coal is typically 0.69 % or less. In addition, the boiler controls (by combustion) waste 

gas emissions from the pulping process: low-volume high-concentration (LVHC) noncondensable gases, high-volume low-concentration (HVLC) non-condensable gases, and 

stripper off-gases (SOG). These waste gases contribute approximately 35% of the total 

sulfur load to the boiler. An electrostatic precipitator controls particulate emissions. The 

baseline SO2 emissions level used by the company was the VISTAS estimate of 8578 

tons with approximately 1944 tons/yr of this coming from the combustion of LVHC, 

HVLC, and SOG. 

 

International Paper provided two 4-factor analyses in separate submittals. The second 

submittal was in response to a request from EPD and it identified controls specifically for 

the pulping waste gas emissions (options 7, 8, and 9 below). Also, facility 

representatives later suggested an SO2 reduction of 2000 tons/year as a control option 

that would provide maximum flexibility for compliance (i.e., a 6758 ton per year 

emission limit). The submittals identified the following control technologies, from most 

effective to least effective, as being technically feasible: 

1. Wet FGD (packed tower); 

2. FGD, wet limestone spray tower; 

3. Semi-dry lime spray tower; 

4. Fuel switching to natural gas; 

5. Dry sorbent injection; 

6. 6758 ton/year emission limit 

7. Regenerative thermal oxidizer (RTO) with scrubber: control HVLC ; 

8. Regenerative thermal oxidizer (RTO) with scrubber: control LVHC and SOG; 

and 

9. Regenerative thermal oxidizer (RTO) with scrubber: control HVLC, LVHC, 

and SOG. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributes to the sulfate visibility 

impairment at five Class I areas (approximately 6.4% at Wolf Island, approximately 1.7% 

at Okefenokee, approximately 0.7% at Saint Marks, approximately 1.6% at Cape 

Romain, and approximately 0.9% at Swanquarter). This is the highest number of Class I 

areas significantly impacted by any single emissions unit of all those reviewed. 
 Appendix H 

93 of 122 

Wet FGD, packed tower. This option would achieve an SO2 reduction of 

approximately 95% and could be implemented before 2012. The cost metrics are $4896 

per ton of SO2 reduced and $72.3 million per inverse megameter (Mm-1) of visibility 

improvement (at Wolf Island, the closest of the Class I areas). Regarding energy and 

non-air environmental impacts, this option would consume 2210 kW of power and 

approximately 212 million gallons of water per year. It would generate approximately 

161 million gallons of wastewater per year. This control is projected to achieve a light 

extinction reduction of 0.55 Mm-1 at Wolf Island. Based on information received from 

EPD’s Watershed Protection Branch, the Savannah River (into which this mill 

discharges) currently had a restriction on increased dissolved oxygen (DO) demand to the 

river. Although the Division did not receive sufficient information to determine whether 

this control option would result in actual DO load to the river, the potential for this to 

happen was sufficient for EPD to consider an option that did not result in increased 

wastewater load. 

FGD, wet limestone spray tower. This option would achieve an SO2 reduction of 

approximately 90% and could be implemented before 2012. The cost metrics are 

$4391/ton reduced and $64.8 million/Mm-1 at Wolf Island. Regarding energy and non-air 

environmental impacts, this option would consume 2210 kW of power and generate 

approximately 22,000 tons of solid waste per year. No additional water use or 

wastewater discharge was reported. This control is projected to achieve a light extinction 

reduction of 0.52 Mm-1 at Wolf Island. Based on cost estimates from other sources (i.e., 

the company’s capital cost estimate was 8.37 times that derived from AirControlNet), the 

company’s cost estimates may be high. EPD requested that a more precise site-specific 

cost analysis be performed by the company, but the company chose not to do so. 

However, despite the possibly high cost estimated, this control option is not considered 

reasonable at this time. This determination may be revisited at the mid-course review or 

when determining future Regional Haze reasonable progress goals (i.e., future Regional 

Haze SIPs.) 

Semi-dry lime spray tower. A semi-dry lime spray dryer would achieve an SO2 

reduction of approximately 85% and could be implemented by before 2012. The cost 

efficiencies are $4869 per ton of SO2 reduced and $71.9 million per inverse megameter 

(Mm-1) of visibility improvement at Wolf Island. Regarding energy and non-air 

environmental impacts, this option would reduce energy production by 780 kw, would 

generate 19,300 tons per year of solid waste and approximately 114 million gallons of 

wastewater per year. The company reported no water withdrawal for this option. This 

control is projected to achieve a light extinction reduction of 0.49 Mm-1 at Wolf Island. 

Based on information received from EPD’s Watershed Protection Branch, the Savannah 

River (into which this mill discharges) currently had a restriction on increased dissolved 

oxygen (DO) demand to the river. Although the Division did not receive sufficient 

information to determine whether this control option would result in actual DO load to 

the river, the potential for this to happen was sufficient for EPD to consider an option that 

did not result in increased wastewater load. 
 Appendix H 

94 of 122 

Fuel switching to natural gas. Switching from coal to natural gas would achieve an 

SO2 reduction of approximately 65% and could be implemented before 2012. The cost 

metrics are $9506/ton reduced and $140.4 million/Mm-1 at Wolf Island. No negative 

energy or non-air environmental impacts were reported. This control is projected to 

achieve a light extinction reduction of 0.38 Mm-1 at Wolf Island. This control option 

results in a lower control efficiency and has a higher cost efficiency than others 

determined not to be cost effective at this time. Therefore, this option is not considered 

reasonable. 

 

Dry sorbent injection. Dry sorbent injection would achieve an SO2 reduction of 

approximately 25% and could be implemented before 2012. The cost metrics are 

$5223/ton reduced and $77.1 million/Mm-1 at Wolf Island. Regarding energy and non-air 

environmental impacts, this option would reduce energy production by 280 kw and 

would generate 7900 tons per year of solid waste. No water or wastewater impacts were 

reported. This control is projected to achieve a light extinction reduction of 0.15 Mm-1 

at Wolf Island. This control option results in a lower control efficiency and has a higher 

cost efficiency than others determined not to be cost effective at this time. Therefore, this 

option is not considered reasonable. 

6758 ton per year emission limit: The company has proposed to reduce SO2 emissions 

from this unit by 2000 tons per year from the projected 2018 baseline emissions of 8578 

tons/year. This results in an emission limit of 6578 tons per year. This reduction could 

be accomplished by 2016. The need for a 2016 compliance date is due to uncertainty 

regarding controls that would be installed in response to the Boiler MACT. At this point, 

the Boiler MACT has been vacated and remanded to EPA. EPA is currently in the 

process of developing a proposed boiler MACT. A 2016 compliance date should provide 

sufficient time for the MACT to be proposed and promulgated, provide the three years 

required for compliance with the standard, and provide time to determine what the SO2 

emissions from this unit will be following compliance with this standard. This control 

option would achieve SO2 reductions of approximately 23%. The company did not 

specify how the reductions would be accomplished. Possible measures to reduce SO2 

from the power boiler would include increased bark combustion and reduced coal 

combustion, installation of a second white liquor scrubber to reduce TRS compounds in 

the non-condensible gases prior to combustion in the boiler, and installation of an RTO 

and scrubber for the control of HVLC, LVHC, and/or SOG (see control option below). 

Since this control option was proposed by the company, it is assumed to have no 

unacceptable energy or non-air environmental impacts. This control is projected to 

achieve a light extinction reduction of 0.14 Mm-1 at Wolf Island. The proposed limit of 

6758 tons/year is based on a projected 2018 baseline SO2 emission rate of 8578 tons per 

year. EPD reviewed recent emission inventory data to determine if this 2018 baseline is 

reasonable. The 2002 (the inventory baseline year) through 2007 (the most recent year of 

available data) actual emissions from Power Boiler 13 were 7643, 7699, 7620, 7728, 

8974, and 8761 tons/year. This data indicates that a 2018 future baseline of 8578 

tons/year is reasonable, given that it is lower than the most two recent years of actual 

emissions. Also, the proposed 6758 ton/year emission limit is lower than any past actual 
 Appendix H 

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emission since 2002. Although no cost-effectiveness information was provided by the 

company, this control option is determined to be reasonable at this time. 

Regenerative thermal oxidizer (RTO) with scrubber controlling HVLC, LVHC, and 

SOG: This control option would involve routing a portion of the mill’s non-condensible 

gases or NCGs [in this case the high-volume low-concentration stream (HVLC), lowvolume high-concentration stream (LVHC), and the stripper off-gas stream (SOG)] 

which contain sulfur-bearing compounds to a stand-alone RTO equipped with a scrubber 

(95% SO2 removal) to remove resulting SO2 emissions instead of using Power Boiler 13 

to combust the NCGs. This control option was not considered because the SO2 control 

efficiency (approximately 22%) is lower than other options that are considered 

reasonable. 

Regenerative thermal oxidizer (RTO) with scrubber controlling LVHC and SOG: 

This control option would involve routing a portion of the mill’s non-condensible gases 

or NCGs (in this case LVHC and SOG) which contain sulfur bearing compounds to a 

stand-alone RTO equipped with a scrubber (95% SO2 removal) to remove resulting SO2 

emissions instead of using Power Boiler 13 to combust the NCGs. This control option 

was not considered because the SO2 control efficiency (approximately 18%) is lower 

than other options that are considered reasonable. 

Regenerative thermal oxidizer (RTO) with scrubber controlling HVLC: This control 

option would involve routing a portion of the mill’s non-condensible gases or NCGs (in 

this case HVLC) which contain sulfur-bearing compounds to a stand-alone RTO 

equipped with a scrubber (95% SO2 removal) to remove resulting SO2 emissions instead 

of using Power Boiler 13 to combust the NCGs. This control option was not considered 

because the SO2 control efficiency (approximately 4%) is lower than other options that 

are considered reasonable. 

Conclusion. Of the control options considered, an emission limit of 6578 tons per year 

was considered reasonable. To allow the facility flexibility in selection and 

implementation of a control, Georgia EPD will establish a permit limit of 6578 tons of 

SO2 per 12 months, including emissions from the pulping process. 

6.4.15 Temple-Inland Rome Linerboard, No. 4 Power Boiler 

The Temple-Inland Rome Linerboard facility is located in Floyd County, in northwest 

Georgia. The No. 4 Power Boiler is a 565 MMBtu/hr coal and oil fired boiler. The unit 

is also permitted to burn a relatively small amount of sawdust. The sulfur content of the 

coal and oil are limited by permit condition to 1.29% and 0.5%, respectively. There are 

hourly and annual SO2 permit limits of 1,130.0 pounds per hour and 3837 tons per 12-

month period for the boiler. The permit also limits the combustion of fuel oil to 

35,352,857 gallons per 12-month period. The pound per hour SO2 limit is a PSD limit. 

All of the others are for PSD avoidance. Particulate emissions are controlled by a 

multiclone followed by an electrostatic precipitator (ESP). The 2018 baseline SO2 

emissions reported by the company were 3837 tons (the same as the permit limit). The 
 Appendix H 

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VISTAS 2018 projected emissions were 3696, relatively close to the permit limit. 3837 

tons per year was used as the baseline SO2 emissions used in this analysis. Review of 

data submitted under the Consolidated Emissions Reporting Rule showed 3293 tons 

emitted in 2002, 3404 tons in 2003, 3396 tons in 2004, 2533 tons in 2005, and 2839 tons 

in 2006. Because a maximum permit limit is used as the 2018 baseline emissions in this 

review, the appropriate 2018 baseline may be over-estimated, but not by a significant 

amount. As a result, the amount of SO2 reduced by any particular control strategy may 

be slightly overestimated. 

In determining what control options should be considered “reasonable” for this unit, EPD 

took into consideration that this unit significantly contributed to two Class I areas 

[Cohutta (4.4%) and Joyce Kilmer (1.0%)]. EPD also took into consideration that this 

unit significantly contributed to Class I areas that were predicted to clearly meet the 

Uniform Rate of Progress (glide slope) in 2018, based on “on the books” controls. EPD 

also took into consideration that this unit is located within a PM2.5 non-attainment area 

(Floyd County) and within a county adjacent to another PM2.5 non-attainment area 

(Atlanta.) 

Temple-Inland’s submittal identified the following control technologies, from most 

effective to least effective, as being technically feasible: 

1. Wet flue gas desulfurization – magnesium enhanced lime (wet FGD MEL); 

2. Wet flue gas desulfurization – limestone forced oxidation (wet FGD LSFO); 

3. Dry flue gas desulfurization (dry FGD); 

4. Fuel Switching to Powder River Basin coal (i.e., subbituminous coal); and 

5. Duct Lime Sorbent Injection. 

The company reported the control efficiency of both wet FGD MEL and wet FGD LSFO 

as equivalent. Cost estimates for the five control technologies were prepared as studylevel estimates (which are not site-specific) in the company’s original four-factor 

submittal. The company subsequently prepared and submitted to EPD a site-specific cost 

estimate for the wet FGD LSFO option. No site-specific analysis was presented for wet 

FGD MEL, but the submittal stated that the capital and operating costs for MEL 

technology would be approximately the same as LSFO. Costs from the site-specific 

analysis are presented in this SIP since these are expected to be more accurate than those 

from the study-level estimate. 

It should also be noted that the company submitted a report dated April 3, 2008, 

proposing that EPD should establish thresholds of direct PM2.5 emissions within Floyd 

County and require RACT and/or RACM analyses in lieu of controlling SO2 emissions 

from No. 4 Power Boiler. However, the report did not propose or analyze any specific 

direct PM2.5 control measures from either No. 4 Power Boiler or any other source at the 

mill. Furthermore, EPD has determined for this particular Regional Haze SIP that 

reducing SO2 emissions from EGU and non-EGU point sources in the VISTAS states 

would have the greatest visibility benefits for the Georgia Class I areas. 
 Appendix H 

97 of 122 

Wet flue gas desulfurization – magnesium enhanced lime. Wet FGD MEL would 

achieve an SO2 reduction of approximately 90 % and could be implemented by before 

2012. The cost efficiencies are $2027 per ton of SO2 reduced and $39.5 million per 

inverse megameter (Mm-1) of visibility improvement (at the Cohutta Class I area). 

Regarding energy and non-air environmental impacts, this option would reduce energy 

production by 450 kw, consume 37 million gallons of water per year, and generate 

16,000 tons of gypsum per year. The electrical usage was taken into account with the 

economic analysis. EPD’s Watershed Protection Branch has indicated that mill had 

sufficient capacity within its currently permitted water withdrawal permit to easily handle 

the increased water use associated with wet FGD. This control efficiency is projected to 

achieve light extinction reductions (which are visibility improvements) of 0.17 Mm-1 at 

Cohutta. The cost effectiveness of this control option was determined not to be 

reasonable at this time. This determination may be revisited at the mid-course review or 

when determining future Regional Haze reasonable progress goals (i.e., future Regional 

Haze SIPs.) 

Wet flue gas desulfurization – limestone forced oxidation. Wet FGD LSFO would 

achieve an SO2 reduction of approximately 90 % and could be implemented by before 

2012. The cost efficiencies are $2027 per ton of SO2 reduced and $39.5 million per 

inverse megameter (Mm-1) of visibility improvement (at the Cohutta Class I area). 

Regarding energy and non-air environmental impacts, this option would reduce energy 

production by 450 kw, consume 37 million gallons per year, and generate 16,000 tons of 

gypsum per year. The electrical usage was taken into account with the economic 

analysis. EPD’s Watershed Protection Branch has indicated that mill had sufficient 

capacity within its currently permitted water withdrawal permit to easily handle the 

increased water use associated with wet FGD. This control efficiency is projected to 

achieve light extinction reductions (which are visibility improvements) of 0.17 Mm-1 at 

Cohutta. The cost effectiveness of this control option was determined not to be 

reasonable at this time. This determination may be revisited at the mid-course review or 

when determining future Regional Haze reasonable progress goals (i.e., future Regional 

Haze SIPs.) 

Dry flue gas desulfurization. Dry FGD would achieve an SO2 reduction of 

approximately 80% and could be implemented before 2012. The cost efficiencies are 

$1857 per ton of SO2 reduced and $36.2 million per inverse megameter (Mm-1) of 

visibility improvement (at the Cohutta Class I area). Regarding energy and non-air 

environmental impacts, this option would reduce energy production by 650 kw and 

would generate 10,000 tons of gypsum per year. The company reported no water or 

wastewater impacts. This control efficiency is projected to achieve light extinction 

reductions (which are visibility improvements) of 0.16 Mm-1 at Cohutta. This control 

option results in a lower control efficiency and has a similar cost efficiency than other 

control options determined not to be cost effective at this time. Therefore, this option is 

not considered reasonable. 

Fuel switching. Switching to lower sulfur fuels would achieve an SO2 reduction of 

approximately 65% and could be implemented before 2012. The cost efficiencies are 
 Appendix H 

98 of 122 

$2807 per ton of SO2 reduced and $54.6 million per inverse megameter (Mm-1) of 

visibility improvement (at the Cohutta Class I area). Regarding energy impacts, this 

option would reduce energy production by 650 kw. The company reported no non-air 

quality environmental impacts from this control option. This control efficiency is 

projected to achieve light extinction reductions (which are visibility improvements) of 

0.13 Mm-1 at Cohutta. This control option results in a lower control efficiency and has a 

higher cost efficiency than others determined not to be cost effective at this time. 

Therefore, this option is not considered reasonable. 

Duct lime sorbent injection. Duct sorbent injection would achieve an SO2 reduction of 

approximately 45% and could be implemented before 2012. The cost efficiencies are 

$1943 per ton of SO2 reduced and $37.8 million per inverse megameter (Mm-1) of 

visibility improvement (at the Cohutta Class I area). Regarding energy impacts, this 

option would reduce energy production by 650 kw. The company reported no non-air 

quality environmental impacts from this control option. This control efficiency is 

projected to achieve light extinction reductions (which are visibility improvements) of 

0.11 Mm-1 at Cohutta. This control option has a relatively low control efficiency and has 

a similar cost efficiency than other control options determined not to be cost effective at 

this time. Therefore, this option is not considered reasonable. 

Conclusion. No additional controls will be required for Temple-Inland Rome No. 4 

Power Boiler Plant. However, this determination may be revisited at the mid-course 

review or when determining future Regional Haze reasonable progress goals (i.e., future 

Regional Haze SIPs.) Furthermore, Temple-Inland Rome is located within a PM2.5 

nonattainment area (Floyd County) and is near two other PM2.5 nonattainment areas 

(Atlanta and Chattanooga). Further evaluation of controls for this unit may be included 

in attainment plans for these nonattainment areas. 
 Appendix H 

99 of 122 

7.0 BART 

7.1 Background

As required by the CAA, EPA included in the final regional haze rule a requirement for 

Best Available Retrofit Technology (BART) for certain large stationary sources that were 

placed in operation between 1962 and 1977. The BART-eligible sources are those 

sources which have the potential to emit 250 tons or more of a visibility-impairing air 

pollutant, were placed in operation between August 7, 1962, and August 7, 1977, and 

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 impairment of visibility in any such area.’’ Accordingly, for stationary sources 

meeting these criteria, States must address the BART requirement when they develop 

regional haze SIPs. EPA has set guidance for identifying BART-eligible sources in 40 

CFR Part 51 Appendix Y. 

A BART-eligible source that is responsible for a 0.5 deciview (dv) change or more is 

considered to “cause” visibility impairment. Although the appropriate threshold may 

vary, the guidelines state that the contribution threshold used for BART applicability 

should not be higher than 0.5 deciviews. Thus a BART-eligible source that is responsible 

for a 0.5 dv change or more is considered to “contribute” to visibility impairment. Any 

source determined to cause or contribute to visibility impairment in any Class I area is 

subject to BART. 

The guidelines direct that States should include SO2, NOX, and direct particulate matter 

(PM) emissions, including both PM10 and PM2.5, in determining whether sources cause 

or contribute to visibility impairment. States may use their best judgment to determine 

whether VOC or ammonia emissions are likely to have an impact on visibility in an area.

To determine which BART-eligible sources are subject to BART, states have several 

options. A state may consider all BART-eligible sources subject to BART; may perform 

analysis showing that the full group of BART-eligible sources in a State cumulatively 

may not be reasonably anticipated to cause or contribute to any visibility impairment in 

any Class I areas; or may consider the individualized contribution of a BART-eligible 

source to determine whether a specific BART-eligible source is subject to BART. 

Sources that are subject to BART must undergo a BART determination. Section 

169A(g)(7) of the CAA requires that States must consider the following factors in 

making 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 use at the source, (4) the remaining useful life of the source, and (5) the 

degree of improvement in visibility which may reasonably be anticipated to result from 

the use of such technology.
 Appendix H 

100 of 122 

To demonstrate the degree of improvement in visibility from various BART control 

options, the States may run CALPUFF or another appropriate dispersion model to predict 

visibility impacts. Scenarios would be run for the pre-controlled and post-controlled 

emission rates for each of the BART control options under review. The maximum 24-

hour emission rates would be modeled for a period of three or five years of 

meteorological data. States have the flexibility to develop their own methods to evaluate 

model results. 

7.2 Approach to Implementation of BART Requirements 

Georgia has used a multi-faceted approach to implementation of the federal regional haze 

rule BART requirements. The approach consists of source identification efforts, use of a 

permitting process to establish any resulting BART limits for inclusion in the SIP 

submittal as well as participation in the VISTAS BART subgroup to resolve technical 

issues spanning states in the VISTAS region, and ongoing consultation with affected 

sources, and EPA and FLMs throughout the BART process. 

EPA’s Best Available Retrofit Technology (BART) applies to sources that have the 

potential to emit 250 tons or more of a visibility impairing pollutant, those that were in 

existence on August 7, 1977 and began operation after August 7, 1962, and those that fall 

within one of the 26 industrial source categories listed in 40 CFR Part 51 Appendix Y 

guidelines. The rule allows affected sources to demonstrate that the source does not 

contribute to visibility impairment and should be exempted. Non-exempt sources are 

required to undergo a determination of best available retrofit technology. BART controls 

are required to be installed and begin operating by January 1, 2012. 

7.3 Identification of BART-Eligible Sources 

EPA provided guidance for identifying BART-eligible sources in 40 CFR Part 51 

Appendix Y. Georgia followed this guidance in identifying its BART-eligible sources. 

The Georgia 2002 air emissions inventory was reviewed to determine the population of 

potential BART-eligible sources. The data was initially queried for any sources emitting 

SO2, NOx, PM-10, VOC, or ammonia. The data set was refined based on emissions, 

whether emission units fit in any of the twenty-six listed source categories for BART, and 

available date information obtained through review of permit and inspection reports and 

discussion with permitting and compliance staff familiar with the facilities. 

An information packet on BART was sent to and additional information was collected 

from the remaining sources regarding potential emissions and BART eligibility from the 

standpoint of source category and date criteria. Through this iterative review process, the 

list of potential BART-eligible sources was pared down to the 24 BART-eligible sources 

listed below. For more details on emissions and Q/d at these facilities, see Appendix H.5. 

These include one cement manufacturing facility, six pulp and paper facilities, ten 

electric utilities, two chemical manufacturers, two packaging facilities, one phosphoric 

acid manufacturer, one asphalt manufacturer, and one nitrogen fertilizer manufacturer. 
 Appendix H 

101 of 122 

Georgia BART Eligible Sources 

FACILITY NAME 

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 – Brunswick / 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)

Georgia BART-eligible sources were presumed to be subject to BART but were provided 

the opportunity to submit modeling demonstrations showing that they did not contribute 

to visibility impairment (i.e., had less than 0.5 deciviews (dv) impact on any Class I area 

within 300 km and thus could be exempt). 
 Appendix H 

102 of 122 

Figure 7-1. GA BART-Eligible Sources and Class I Areas. 

Georgia BART-Eligible Sources 
 Appendix H 

103 of 122 

Table 7-1. GA BART-Eligible Sources and Distances to Respective Class I Areas 

Distance From Class I Area 

Facility Name WOLF 

ISLAND 

Okefenokee Cohuttta Cape 

Romain 

Linville 

Gorge 

Joyce 

Killmer 

Shinning 

Rock 

St. 

Marks 

Great Smoky 

Mountains 

Sipsey Bardw

Bay 

Georgia Power-Plant Bowen* 

Georgia Power-Plant Branch 274.4 254.8 218.6 247.4 242.5 250.5 

Georgia Power-Plant Hammond 93.7 174.8 252.4 187.5 183 

Georgia Power-Plant McDonough 113.7 176.9 221.8 189.8 269 

Georgia Power-Plant Mitchell 265.4 163.4 141.7 

Georgia Power-Plant Scherer 299.4 263.1 211.8 256.3 268.3 265.3 

Georgia Power-Plant Wansley 163.8 237.5 289.9 250.9 235 

Georgia Power-Plant Yates 156.3 228.2 278.3 241.5 240 

Savannah Electric-Plant Kraft 87 159 161.7 

Savannah Electric-Plant McIntosh 110.5 177.1 152.6 

Chemical Products Corp 

DSM Chemicals North America 236.9 266 288.7 219.2 266.7 281.5 2276 

Koch Cellulose (GP Brunswick, Brunswick Pulp & Paper) 26 100 130 280 

Georgia-Pacific Cedar Springs Operations 244 112 

International Paper – Augusta 226 254 294 219 275 289 236 

International Paper - Savannah (Union Camp Corp.) 83.6 156.9 162.5 

Interstate Paper, LLC 41 103 207 295 

Kerr-McGee Pigments, Inc. (Kemira) 90 180 210 

Lafarge Building Materials (Blue Circle Cement – Atlanta Plant) 114.3 177.3 221.9 190.2 269 

Owens Corning 146.4 212.3 255.6 225.3 267 

PCA (Tenneco Packaging, Inc.) 201 73.1 89.1 128.5 

PCS Nitrogen Fertilizer, LP – Augusta 238 267 288 220 265 280 225 

Prayon, Inc. (Solutia, Inc.)* 

Rayonier (ITT Rayonier, Inc.) 58 76 246 264 

 *Note: Georgia Power - Plant Bowen and Prayon Inc. do not have distances fro

Exempt Source applicable Class I areas listed in the table because exemptionmodeling 

 not performed on these sources. 

Non-Exempt Source Exempt Utility Non-Exempt Utility 
 Appendix H 

104 of 122 

7.4 Contribution Threshold 

Determining whether a source causes or contributes to visibility impairment is one step in 

the BART review process. The Guidelines for BART Determinations Under the Regional 

Haze Rule3 states “a single source that is responsible for a 1.0 deciview change or more 

should be considered to ‘cause’ visibility impairment.” The guideline document also 

states that “the appropriate threshold for determining whether a source ‘contributes to 

visibility impairment’ may reasonably differ across states,” but, “as a general matter, any 

threshold that you use for determining whether a source ‘contributes’ to visibility 

impairment should not be higher than 0.5 deciviews.” The rationale for these instructions 

is provided in the preamble to the BART guidance in the statement, “if ‘causing’ 

visibility impairment means causing a humanly perceptible change in visibility in 

virtually all situations (i.e. a 1.0 deciview change), then ‘contributing’ to visibility 

impairment must mean having some lesser impact on the conditions affecting visibility 

that need not rise to the level of human perception.”4

 The guidance document itself also 

states that, “States remain free to use a threshold lower than 0.5 deciviews if they 

conclude that the location of a large number of BART-eligible sources within the State 

and in proximity to a Class I area justify this approach.” 

EPA’s documents strive to set these thresholds in the context of the human perception of 

visibility change. As noted above, the EPA considers a 1.0-deciview change in visibility 

to be humanly perceptible “in virtually all situations.” Also, the preamble to the BART 

guidance5 cites an analysis in an appendix of a NAPAP (National Acid Precipitation 

Assessment Program) report, which asserts that “changes in light extinction of 5 percent 

will evoke just noticeable changes in most landscapes.” 6 (A 5% change is approximately 

0.5 dv.) But, as noted above, the preamble also states that perceptibility is not a 

prerequisite for choosing a contribution threshold. Putting all this together, it appears 

that “causing” visibility impairment means having a humanly perceptible impact (for 

which EPA considers the practical threshold to be 1.0 dv) while “contributing” to 

visibility impairment means having a smaller impact (for which EPA considers the 

threshold to be 0.5 dv or some smaller value) that may or may not be perceptible. 

The EPA argues that a contribution threshold of less than 0.5-dv-impact-per-source is 

appropriate when multiple sources contribute, in order to limit the combined effect of 

these sources. As an example, EPA asserts that if there were 100 sources, each affecting 

visibility by 0.1 dv (presumably an imperceptible amount), their total impact would be 10 

dv (which can be expected to be quite perceptible).7

 The point remains that multiple 

sources can cause a larger impact than a single one. For BART purposes, visibility 

 

3

 40 CFR 51, Appendix Y, Section III.A.1 

4

 70 FR 39120. Footnote 31 

5

 70 FR 39119. Footnote 28 

6

 “The Quadratic Detection Model” by W. Malm. Appendix D in Acidic Deposition: State of 

Science and Technology, Report 24, Visibility: Existing and Historical Conditions -- Causes and 

Effects. National Acid Precipitation Assessment Program, Washington, DC. 1990. 

7

 70 FR 39121. 1st column 
 Appendix H 

105 of 122 

impacts are calculated as 24-hour averages of 1-hour plume impacts, so if the plumes 

from the various sources each impact the point of interest at some time during a 24-hour 

period (not necessarily all at the same hour) then the 24-hour average will reflect their 

combined impact. 

Georgia EPD concluded that the EPA-suggested contribution threshold of 0.5 dv was 

appropriate in this situation since there are a limited number of sources that impact the 

various Class I areas in the State. 

Figure 7-2. Location of VISTAS BART-Eligible Sources 

7.5 Exemption of Point Source Volatile Organic Compounds for BART Purposes 

The State of Georgia has determined through modeling that volatile organic compounds 

(VOCs) from point sources are not anticipated to cause or contribute significantly to any 

impairment of visibility in Class I areas and should be exempt for BART purposes. 
 Appendix H 

106 of 122 

7.5.1 Method 

The State of Georgia determined through modeling that VOCs from point sources are not 

anticipated to cause or contribute significantly to any impairment of visibility in Class I 

areas. 

Modeling was conducted through The Visibility Improvement State and Tribal 

Association of the Southeast (VISTAS). VISTAS is a collaborative effort of State 

governments, tribal governments, and various Federal agencies established to initiate and 

coordinate activities associated with the management of regional haze, visibility and 

other air quality issues in the Southeastern United States. VISTAS contracted with 

Georgia Institute of Technology to perform model sensitivity runs to determine the 

impact of point source VOCs on visibility in Class I areas. 

Georgia Tech performed emission sensitivities to examine the impact of emission 

reductions on regional haze, annual PM2.5, and 8-hour ozone concentrations using 

CMAQv4.4_SOAmods on the VISTAS 12-km modeling domain, using the 2009 OTW 

(on the way) BaseD emissions. One such sensitivity run reduced anthropogenic, point 

source VOCs by 100%. The purpose was to quantify the impact of VOC emissions from 

VISTAS BART sources on Class I areas. Two episodes were examined: June 1-July 10, 

2002 and November 19 – December 19, 2002. The approach included calculating the 

extinction coefficient in dv (deciviews), then determining the maximum impact of point 

source VOCs. The chart below shows the impact on the following twenty-two Class I 

areas within the VISTAS domain (Appendix H.6).

BRET = Breton, LA 

BRIG = Brigantine NWR, NJ 

CACR = Caney Creek, AR 

CHAS = Chassahowitzka, FL 

COHU = Cohutta, GA 

DOSO = Dolly Sods, WV 

EVER = Everglades, FL 

GRSM = Great Smoky Mountains National Park 

HEGL = Hercules Glade, MO 

JARI = James River Face, VA 

LIGO = Linville Gorge, GA 

MACA = Mammoth Cave, KY 

MING = Mingo, MO 

OKEF = Okefenokee, GA 

ROMA = Cape Romain, SC 

SAMA = Saint Marks, FL 

SHEN = Shenandoah, VA 

SHRO = Shining Rock, GA 

SIPS = Sipsey Wilderness, AL 

SWAN = Swanquarter, GA 

UPBU = Upper Buffalo Wilderness, AR 
 Appendix H 

107 of 122 

Figure 7-3. Maximum Point VOC Impact 

7.5.2 Conclusions 

The results show that the maximum impact from eliminating all point source VOC 

emissions in the VISTAS 12 km domain is less than a 0.5 dv for all Class I areas in the 

VISTAS domain. The expected impact of controlling VOCs from all BART sources in 

Georgia would be much less than the 0.5 dv threshold since the VOCs from BART 

sources are only a fraction of the total VOCs. VISTAS and the State of Georgia conclude 

that VOCs from point sources are not a visibility-impairing pollutant for BART purposes 

and that BART-eligible sources do not need to consider VOC emissions. 

7.6 Treatment of Ammonia Emissions for BART Purposes 

Similar to its treatment of VOCs, EPA guidance allows States the discretion to decide 

whether or not ammonia emissions are to be considered for BART purposes based on 

evaluations of the contributions of the emissions to haze at Class I areas in their areas of 

influence. One approach a State can use to determine whether applying BART will be 

needed is to evaluate the haze impacts of all current emissions from all BART-eligible 

sources in the State. If the impact from all sources in the state is less than the 

contribution threshold established by the State, 0.5 dv for Georgia, then source-by-source 

analysis for BART is not needed. 

The State of Georgia has determined through modeling that ammonia (NH3) emissions 

from point sources are not anticipated to cause or contribute significantly to any 

impairment of visibility in Class I areas and should be exempt for BART purposes. 

Maximum Point VOC Impact

Maximum VOC Impact

0.0

0.1

0.2

0.3

0.4

0.5

0.6

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV
 Appendix H 

108 of 122 

7.6.1 Method 

The State of Georgia determined through modeling that ammonia emissions from point 

sources are not anticipated to cause or contribute significantly to any impairment of 

visibility in Class I areas with the exception of one large point source in close proximity 

to one Georgia Class I area. 

VISTAS contracted with Georgia Institute of Technology to perform model sensitivity 

runs to determine the impact of point source ammonia on visibility in Class I areas. 

Georgia Tech performed emission sensitivities to examine the impact of emission 

reductions on regional haze using CMAQv4.5 with SOA models on the VISTAS 12 km 

modeling domain using the VISTAS 2009 OTW (on the way) Base F4 emissions. One 

such sensitivity run reduced BART-eligible source, ammonia, by 100%. The purpose 

was to quantify the impact of ammonia emissions from VISTAS BART sources on Class 

I areas. Two episodes were examined: June 1-July 10, 2002, and November 19 – 

December 19, 2002. The approach included calculating the extinction coefficient in dv 

(deciviews), then determining the maximum impact of BART-eligible source ammonia. 

The chart below, taken from the VISTAS report BART in the VISTAS Region: Sensitivity 

to VOC, NH3, and Primary PM Emissions (included as Appendix H.6) shows the impact 

on the following 22 Class I areas within the VISTAS domain.

Figure 7-4. Maximum NH3 Impact - Maximum contributions of all BART-eligible 

NH3 point sources in the VISTAS region to haze in Class I areas during the CMAQmodeled periods. 

The chart shows the largest haze impact in delta dv over the two timeframes at each Class 

I area. These delta dv changes represent the haze contribution of all BART source 

Maximum NH3 Impact

0.0

0.5

1.0

1.5

BRET

BRIG

CACRCHAS

COHU

DOSO

EVER

GRSM

HEGL

JARI

LIGO

MACA

MING

OKEF

ROMA

SAMA

SHEN

SHRO

SIPS

SWAN

UPBU

WOLF

ΔdV
 Appendix H 

109 of 122 

ammonia emissions relative to assumed natural haze levels. The natural haze levels are 

based on EPA-default annual average natural concentrations for the East and monthlyvarying “climatologically-representative” relative humidity at each Class I area. 

During the periods modeled, the ammonia emissions from all BART-eligible sources 

contributed more than 0.5 dv to haze at Mammoth Cave National Park (MACA), 

Kentucky; Mingo Wilderness (MING), Missouri, Cape Romain National Wildlife Refuge 

Area (ROMA) South Carolina, and Swanquarter National Wildlife Refuge (SWAN), 

North Carolina. 

The majority of ammonia emissions in the VISTAS region come from four sources as 

shown in Table 7-2 below. 

Table 7-2. Major NH3 Sources in the VISTAS Region 

Facility State NH3 Emissions 

(tpy) 

Distance to Nearest 

Class 1 Area (km) 

MeadWestvaco Corp. SC 174 30 

PCS Phosphate – 

Savannah Ammonia 

Terminal* 

GA 206 31 

PCS Nitrogen TN 1252 180 

PCS Nitrogen GA 1765 220 

*Note: Although PCS Phosphate was included in the ammonia analysis; the facility is not subject to BART 

because it is a minor source for all pollutants. 

7.6.2 Conclusions 

The BART requirements of the regional haze rule allow states to determine whether or 

not ammonia is to be considered a visibility-impairing pollutant to be addressed for 

BART purposes. NH3 emissions from BART sources may impair visibility; however, 

the majority of NH3 emissions in the VISTAS region are from only a few sources. 

Removal of the large NH3 emission sources results in minimal impact on visibility at 

Class I areas in the VISTAS region. Furthermore, ammonia emissions from all sources 

contributed less than 0.5 dv to the Class I areas in Georgia [Cohutta Wilderness (COHU), 

Okefenokee Wilderness (OKEF), and Wolf Island Wilderness (WOLF)]. Therefore, the 

State of Georgia concludes that ammonia from point sources does not need to be 

considered for BART purposes. 

 

8.0 Explanation of BART Exemption Criteria 

8.1 Background 

 

Georgia opted to consider its BART-eligible sources subject to BART unless the source 

demonstrated exemption via any of the following three options: 1) Exemption modeling 

2) Meeting the specifically-listed model plant criteria for emissions and distance from 
 Appendix H 

110 of 122 

the; nearest class I area; and 3) accepting an emissions limit of less than 250 tpy of the 

visibility-impairing pollutant. 

8.1.1 Exemption Modeling 

BART-eligible sources can be excluded from BART determinations by demonstrating 

that the source cannot be reasonably expected to cause or contribute to visibility 

impairment in a Class I area. The threshold for determining that a source causes visibility 

impairment is set at 1.0-dv change from natural conditions over a 24-hour averaging 

period. The BART guidelines also propose that the threshold at which a source may 

“contribute” to visibility impairment should not be higher than 0.5 deciviews; however, 

depending on factors affecting a specific Class I area, it may be set lower than 0.5 

deciviews. 

As stated in the BART regulation, EPA’s preferred approach for determining cause or 

contribution is an assessment with an air quality model such as CALPUFF or other 

appropriate model followed by comparison of the estimated 24-hour visibility impacts 

against a threshold above estimated natural conditions to be determined by the State. 

EPA recommends that the 98th percentile value from the modeling be compared to the 

State’s chosen contribution threshold to determine if a source does not contribute to 

visibility impairment and, thus, is not subject to BART. Comparison of the 98th

percentile value to the threshold must be made for each Class I area. For an annual 

period, this implies the 8th highest 24-hour value at a particular Class I area is compared 

to the contribution threshold. For a 3-year modeling period, the 98th percentile value may 

be interpreted as the highest of the three annual 98th percentile values at a particular Class 

I area or the 22nd highest value in the combined 3-year record, whichever is more 

conservative. 

Georgia worked with the regional planning organization (RPO) VISTAS on development 

of the VISTAS Protocol for the Application of the CALPUFF Model for Analyses of Best 

Available Retrofit Technology (BART) (Appendix H.7). The common protocol was 

established to provide the basis for a common understanding among the organizations 

performing BART analyses or reviewing BART modeling results in the VISTAS region. 

The VISTAS protocol describes common procedures for carrying out air quality 

modeling to support BART determinations that are consistent with the 40 CFR Part 51 

Appendix Y guidelines. The protocol provides a consistent model, CALPUFF, and 

modeling guidelines for BART determinations, clearly delineated modeling steps, a 

common CALPUFF configuration, guidance for site-specific modeling, and common 

expectations for reporting model results. Details of the CALPUFF system can be found 

in Chapter 3 of the VISTAS protocol, specific recommendations for its application for 

BART purposes are found in Chapter 4, and specific information that should be included 

in site-specific protocols is found in Chapter 5. 

VISTAS contracted Earth Tech to develop a version of the CALPUFF model appropriate 

for BART purposes. The VISTAS version of the CALPUFF model is CALPUFF 

Version 5.754 and CALMET Version 5.7. 
 Appendix H 

111 of 122 

For BART modeling purposes VISTAS made publicly available 12-km CALMET output 

files for the entire VISTAS modeling domain (eastern United States) and provided 

CALMET output files for five 4-km grid sub domains covering the VISTAS states and 

VISTAS Class I areas. To generate the CALMET input files, the VISTAS contractor 

used the MM5 databases developed by EPA for 2001, VISTAS for 2002, and Midwest 

RPO for 2003. For the 12-km grid, large domain covering the entire VISTAS region, the 

No-Obs setting was used. For the 4-km grid, available surface and upper air observations 

were used in addition to MM5 meteorological model outputs. Specific model settings 

were provided with the CALMET files and via the CALPUFF website so that work could 

be replicated. 

For CALPUFF modeling, source emissions were to be defined using the maximum 24-

hour actual emission rate during normal operation for the most recent three or five years. 

If maximum 24-hour actual emissions were not available, continuous emission data, 

permit allowable emissions, potential emissions, and emission factors from AP-42 source 

profiles could be used as available. 

Key points on specific CALPUFF, CALPOST, and POSTUTIL configuration that were 

to be used for BART modeling are: 

• After running CALPUFF for an individual facility, NO3 should be 

repartitioned in POSTUTIL. 

• Ozone data from non-urban monitors should be used as the background ozone 

input. 

• The Pasquill-Gifford dispersion method should be used. 

• In CALPOST, Method 6 with monthly average RH for calculating extinction 

as recommended by EPA should be used. 

• EPA default calculations of light extinction under current and natural 

background conditions should be used. In addition a source may also 

calculate visibility using the recently-revised IMPROVE algorithm. 

Additional discussion of the CALPUFF model and VISTAS recommended settings can 

be found in the VISTAS protocol in Attachment H-7. 

8.1.2 Model Plant Criteria 

In its final BART rule, EPA included mechanisms for exempting sources from BARTdetermination requirements. Under one approach, EPA established specific exemption 

thresholds based on CALPUFF modeling conducted for a model plant. BART eligible 

sources meeting specifically-listed model plant criteria for emissions and distance from 

the nearest Class I area can be exempted from BART determination requirements. The 

criteria that must be met are that sources must have potential emissions of sulfur dioxide 

(SO2) and nitrogen oxides (NOx) combined of less than 500 tons and be greater than 50 

km from any Class I area or have combined potential emissions less than 1000 tons and 
 Appendix H 

112 of 122 

be greater than 100 km from any Class I area. Sources must also have potential 

emissions of particulate matter (PM) of less than 15 tons-per-year to be exempted without 

some form of modeling. In situations where a source’s combined SO2 and NOx 

emissions are less than 500 or 1000 tons, but PM emissions are greater than 15 tons, the 

emissions of SO2, NOx, and PM may be combined and compared to 500 or 1000 tons. 

8.1.3 Accepting an Emissions Limit 

If a facility is willing to take a facility-wide limit of 250 tpy on all BART eligible 

equipment for each pollutant for which the facility is BART eligible, then the facility is 

exempt from BART requirements. The facility must submit an application to this effect 

and such limits must be incorporated into an enforceable permit. 

Table 8-1 below provides a summary of the exemption modeling results. 

Table 8-1. BART Exemption Modeling Results 

Facility Class 1 Areas Impacted Delta-Deciviews 

PCS-Nitrogen Okefenokee Wilderness Area 0.393 

 Cohutta Wilderness Area 0.409 

 Wolf Island 0.294 

 Cape Romain 0.359 

 Great Smoky Mountains 0.163 

 Joyce Kilmer 0.175 

 Shining Rock Wilderness 0.220 

 Linville Gorge 0.393 

 Shinning Rock Wilderness 0.220 

Rayonier Wolf Island 0.319 

 Okefenokee Wilderness Area 0.254 

 Cape Romain 0.132 

 St. Marks 0.151 

Georgia Power-Plant Wansley Cohutta Wilderness Area 0.44 

 Great Smoky Mountains 0.17 

 Joyce Kilmer 0.18 

 Shining Rock Wilderness 0.12 

 Sipsey 0.14 

DSM Chemicals North America Cape Romain 0.094 

 Cohutta Wilderness Area 0.112 

 Great Smoky Mountains 0.072 

 Joyce Kilmer 0.036 
 Appendix H 

113 of 122 

 Okefenokee Wilderness Area 0.063 

 Shining Rock Wilderness 0.069 

 Wolf Island 0.114 

International Paper Augusta Cohutta Wilderness Area 0.114 

 Cape Romain National Wildlife Refuge 0.211 

 Great Smoky Mountains 0.093 

 Joyce Kilmer 0.086 

 Linville Gorge 0.103 

 Okefenokee Wilderness Area 0.157 

 Shining Rock Wilderness 0.127 

 Wolf Island 0.148 

Georgia Power-Plant Branch Cohutta Wilderness Area 0.17 

 Great Smoky Mountains 0.11 

 Joyce Kilmer 0.09 

 Shining Rock Wilderness 0.09 

 Okefenokee Wilderness Area 0.12 

 Wolf Island 0.11 

Georgia Power-Plant Hammond Great Smoky Mountains 0.08 

 Joyce Kilmer 0.09 

 Cohutta Wilderness Area 0.29 

 Shining Rock Wilderness 0.05 

 Sipsey 0.06 

Savannah Electric-Plant Kraft Cape Romain National Wildlife Refuge 0.18 

 Okefenokee Wilderness Area 0.18 

 Wolf Island 0.21 

Georgia Power-Plant 

McDonough Great Smoky Mountains 0.07 

 Joyce Kilmer 0.07 

 Cohutta Wilderness Area 0.19 

 Shining Rock Wilderness 0.05 

 Sipsey 0.04 

Savannah Electric-Plant 

McIntosh Cape Romain National Wildlife Refuge 0.04 

 Okefenokee Wilderness Area 0.03 

 Wolf Island 0.03 

Georgia Power-Plant Mitchell Okefenokee Wilderness Area 0.04 

 Wolf Island 0.02 

 St. Marks 0.05 
 Appendix H 

114 of 122 

Georgia Power-Plant Scherer Okefenokee Wilderness Area 0.08 

 Wolf Island 0.05 

 Joyce Kilmer 0.07 

 Cohutta Wilderness Area 0.08 

 Shining Rock Wilderness 0.06 

 Great Smoky Mountains 0.07 

Georgia Power-Plant Yates Cohutta Wilderness Area 0.15 

 Great Smoky Mountains 0.05 

 Shining Rock Wilderness 0.03 

 Joyce Kilmer 0.06 

 Sipsey 0.05 

Koch Cellulose (GP Brunswick, 

Brunswick Pulp & Paper Okefenokee Wilderness Area 0.282 

 Wolf Island 0.447 

 St. Marks 0.055 

 Cape Romain National Wildlife Refuge 0.092 

PCA Valdosta Chassahowitzka (12 km) 0.197 

 Okefenokee Wilderness Area (12 Km) 0.349 

 Wolf Island (12 Km) 0.181 

 St. Marks (4 Km) 0.190 

Kerr-McGee (Tronox) Okefenokee Wilderness Area 0.213 

 Wolf Island 0.246 

 Cape Romain National Wildlife Refuge 0.134 

Prayon Okefenokee Wilderness Area 0.007 

 Wolf Island 0.005 

 Cape Romain National Wildlife Refuge 0.009 

 Cohutta Wilderness Area 0.004 

 Great Smoky Mountains 0.002 

 Shining Rock Wilderness 0.003 

 Joyce Kilmer 0.002 

 Linville Gorge 0.005 

Owens Corning Cohutta Wilderness Area 0.119 

 Great Smoky Mountains 0.051 

 Shining Rock Wilderness 0.072 

 Joyce Kilmer 0.056 

 Sipsey 0.054 

Georgia Pacific Cedar Springs Okefenokee Wilderness Area 0.306 
 Appendix H 

115 of 122 

 St. Marks 0.499 

Chemical Products Corporation Cohutta Wilderness Area 0.442 

 Great Smoky Mountains 0.173 

 Shining Rock Wilderness 0.090 

 Joyce Kilmer 0.197 

 Sipsey 0.127 

Table 8-2 below provides a list of facilities exempted from BART on the basis of model 

plant criteria or by acceptance of a limit of 250 tpy for visibility-causing pollutants. 

Table 8-2 Facilities that demonstrated BART exemption based on model plant 

criteria or by accepting a limit of 250 tpy for visibility causing pollutants 

BART Eligible Sources Basis of Exemption 

 

International Paper - Savannah Total potential Emissions of visibility impairing 

pollutants is lesser than 500 tons and distance from the 

nearest Class I area is greater than 50 Km 

Lafarge Building Materials 

(Blue Circle Cement –Atlanta 

Plant) 

Total potential Emissions of visibility impairing 

pollutants is lesser than 1000 tons and distance from 

the nearest Class I area is greater than 100 Km 

8.2 Use of New IMPROVE Equation 

During the regional haze SIP development process, the IMPROVE Steering Committee 

made recommendations for a new IMPROVE equation. Among other things, the new 

equation includes components that take into account the effects of sea salt and sitespecific Rayleigh scattering (Appendix H.11). These are important issues to consider for 

coastal and mountainous sites. Additional discussion of the new IMPROVE equation can 

be found in Appendix B of the SIP narrative. 

VISTAS contracted Dr. Ivar Tombach to develop a postprocessor to allow CALPOST 

outputs to be used with the new IMPROVE equation. Georgia EPD submitted to EPA 

Region IV a request for approval to use the new IMPROVE equation and postprocessor 

developed by Dr. Tombach in BART modeling. A discussion of the rationale for use of 

the new IMPROVE equation follows. 

Rationale for Use of New IMPROVE Equation

The new IMPROVE equation is a much better representation of the effects of particulate 

matter on light extinction than the old equation and takes into account the latest scientific 

understanding of several parameters. 
 Appendix H 

116 of 122 

1. The new algorithm overcomes biases of the old algorithm on the haziest days and 

the clearest days as demonstrated by comparing the measured light extinction 

from nephelometers at Class I areas to light extinction calculated using each of 

the equations. 

2. The new algorithm recognizes spatial and temporal variation in light extinction as 

size distribution of the aerosol changes by increasing extinction efficiency as 

sulfate, nitrate and organic concentrations increase. 

3. The new algorithm incorporates a term to reflect the contribution of fine sea salt 

and its hygroscopic growth with increasing relative-humidity-recognizing 

research findings showing that fine sea salt can be an important contributor to 

light extinction in coastal areas. 

4. The new algorithm reflects research finding that the mass concentration of 

particulate organic matter in rural areas is greater than represented by the old 

equation. 

5. The new algorithm includes an NO2 term to represent times when light absorption 

by NO2 is a meaningful contributor to light extinction. 

6. The new algorithm incorporates site-specific Rayleigh scattering values to better 

represent sites close to sea level or with very hot or cold climates. 

With this combination of revisions to the IMPROVE equation, the resulting 

apportionment of extinction to various components is more accurate on the haziest and 

clearest days. This is important for development of emission control strategies since the 

benefits of control of concentrations of each species will be represented more correctly 

with the new algorithm. 

GA EPD submitted a request for approval to the use of the new IMPROVE equation 

instead of the original IMPROVE equation. This request also contains the new 

IMPROVE postprocessor and its instructions. Region 4 EPA granted this request to use 

the new IMPROVE equation (Appendix H.9). 

9.0 BART Determination 

For those facilities subject to BART, the state must determine what constitutes BART 

controls for the source by considering various control options and selecting the best 

alternative taking into consideration any pollution control equipment in use at the source, 

the costs of compliance with control options, the remaining useful life of the facility, the 

energy and non air-quality environmental impacts of compliance, and the degree of 

improvement in visibility that may reasonably be anticipated to result from the use of 

such technology. Under Georgia’s approach, facilities subject to BART were requested 

to propose BART considering these factors. 

9.1 BART Subject Sources 
 Appendix H 

117 of 122 

Only two BART-eligible sources in Georgia emit any air pollutant which may reasonably 

be anticipated to cause or contribute to any impairment of visibility in any Class I area. 

The two facilities, Interstate Paper in Riceboro, Georgia, and Georgia Power Company 

Plant Bowen, in Cartersville, Georgia, were unable to demonstrate less than a 0.5 dv 

impact on one or more Class I areas and, thus, are subject to BART. 

9.1.1 BART-eligible Units and Existing Control 

Georgia Power Plant Bowen has four BART-eligible emission units that comprise the 

BART-eligible source. These units are coal fired electric generating units 1,2,3 and 4. 

The above-mentioned units are BART eligible for their PM emissions. Each of these 

EGU’s PM emissions are already controlled by electrostatic precipitators (ESPs) and wet 

flue gas desulfurization scrubbers (Wet FGD). 

Interstate Paper has three BART-eligible emission units that comprise the BART-eligible 

source. These units are recovery boiler, power boiler and lime kiln. Each of these units 

is BART eligible for PM10, SO2 and NOx. The recovery boiler has a venturi scrubber as 

an existing control for PM10 emissions, staged combustion and combustion control as an 

existing control strategy for NOx and SO2 respectively. The lime kiln has a wet scrubber 

as an existing control for both PM10 and SO2. 

9.2 BART Determination Analysis and Conclusion 

In accordance to 40 CFR Part 51, Regional Haze Regulations and Guidelines for Best 

Available Retrofit Technology (BART) Determinations; Final Rule the state is responsible 

for determining BART for all the subject-to-BART sources. Georgia EPD requested the 

two facilities to do a detailed BART determination analysis. Interstate Paper in Riceboro, 

Georgia failed to respond to the above-mentioned request hence, Georgia EPD did a 

complete detailed BART analysis for the facilities BART eligible units. Table 9.1 gives a 

summary of the BART determination analysis for the two facilities. A complete BART 

determination analysis for both of the subject-to-BART sources are given in Appendix 

H.8. 

Table 9-1 BART determination analysis for both the 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 

Interstate Paper 99% 370 

Recovery 

Boiler 

No cost effective 

control options 

Available 

Not 

required 

Not required 
 Appendix H 

118 of 122 

 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 

The required permit conditions to incorporate the BART determination for Interstate 

Paper Power Boiler F1 will be incorporated into the Title V permit as discussed in 

Section 7.7.2 of the narrative. The Power Boiler will be required to combust only natural 

gas except during a period of curtailment. Curtailment occurs during periods of high 

natural gas demand where the supplier begins restricting the supply starting with 

industrial sources. The facility has no control over curtailment. Curtailment occurs very 

infrequently, if at all, once per year during the coldest winter months (typically January). 

Additionally, the Power Boiler (and Multi-fuel Boiler MFB1) is permitted to combust 

TRS containing waste gas streams when the associated Lime Kiln, LM01, is not 

operating. Operational records have demonstrated that this scenario has not occurred; 

however, Georgia EPD will modify the Title V permit to restrict the combustion of waste 

gas in the Power Boiler only when both the lime kiln and multi-fuel boiler are not 

operational. 

10.0 Final Long Term Strategy And Reasonable Progress Goals 

The regional haze rule requires States to establish reasonable progress goals, expressed in 

deciviews, for visibility improvement at each affected Class I area covering each 

(approximately) 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 covering the 

period from the baseline until 2018. This section discusses development of Georgia’s 

long-term strategy. 

10.1 Long-Term Strategy 

Ammonium sulfate is the most important contributor to visibility impairment and fine 

particle mass on the 20 percent worst and 20 percent best visibility days at all of the 

Georgia Class I areas. Sulfate levels on the 20 percent worst days account for 60-70 

percent of the visibility impairment. Across the VISTAS region, sulfate levels are higher 

at the Southern Appalachian sites than at the coastal sites. On the 20 percent clearest 

days, sulfate levels are more uniform across the region. Reduction of SO2 emissions 

would be the most effective means of reducing ammonium sulfate. Ninety-five percent 

of SO2 emissions in Georgia are attributable to electric generating facilities and industrial 

point sources. Thus, the long-term strategy for this first Regional Haze SIP focused on 

reductions in SO2 emissions. When fully implemented, Georgia Rule (sss) will reduce 

SO2 emissions by about 90 percent, NOx emissions by approximately 85 percent and 

mercury emissions by approximately 79 percent. 
 Appendix H 

119 of 122 

Such large SO2 reductions are predicted to result in significant improvements in 

visibility. Visibility improvements at all of the VISTAS mountain Class I areas and most 

of the coastal Class I areas are projected to be better than the uniform rate of progress. 

The percentage of the target reduction achieved for the Georgia Class I areas using the 

new IMPROVE equation is 90-160 percent. 

In addition to improving visibility on the 20 percent worst visibility days, states are also 

required to protect visibility on the 20 percent best days at the Class I areas. Visibility on 

the 20 percent best days is projected to improve in 2018 at all VISTAS Class I areas as a 

result of the 2018 Base G2 emissions reductions. The percentage of the 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 Georgia EPD completed a reasonable progress assessment after modeling the Clean 

Air Act controls discussed previously. The assessment did not identify any cost-effective 

control measures for the SO2 EGU units that contributed greater than half a percent to 

visibility impairment at any of the Class I areas in Georgia or in neighboring States. The 

Georgia EPD did an in-depth 3-factor analysis and has proposed reasonable controls for 

some non-EGUs that contribute more than half a percent to visibility impairment at any 

of the Class I areas in Georgia or in neighboring States. 

The Georgia EPD reviewed the BART determination from Georgia Power Plant Bowen, 

which is one of the two Georgia facilities that were determined to be subject to BART. 

From its review, Georgia EPD concluded that no cost-effective BART reductions are 

possible. Georgia EPD also did a BART determination analysis for Interstate Paper and 

concluded that burning of natural gas except during curtailment periods would be costeffective BART control for the facility. 

10.2 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. 

Elemental carbon (sources include agriculture, prescribed wildland fires, and wildfires) is 

a relatively minor contributor to visibility impairment 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 the Georgia Department of Natural Resources Wildlife 

Resources Division adopting a smoke management 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). 
 Appendix H 

120 of 122 

Georgia’s Rules for Air Quality Control include requirements for precautions to prevent 

fugitive dust from becoming airborne and also limit the opacity of fugitive emissions to 

less than 20 percent. The requirements of Rule 391-3-1-.02(n) include preventive 

measures for construction activities and are deemed adequate to satisfy the directive in 

Section 308(d)(3)(v)(B) of the Regional Haze rule. The current version of Georgia’s air 

rules is available on the Georgia EPD web site. 

10.3 Reasonable Progress Goals 

The Regional Haze Rule at 40 CFR Section 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 natural visibility. In addition, 

EPA released guidance on June 7, 2007, to use in setting reasonable progress goals. The 

goals must provide improvement in visibility for the most impaired days, and ensure no 

degradation in visibility for the least impaired days over the State Implementation Plan 

(SIP) period. The state must also provide an assessment of the number of years it would 

take to attain natural visibility conditions if improvement continues at the rate represented 

by the reasonable progress goal. 

In accordance with the requirements of 40 CFR §51.308(d)(1), this Regional Haze 

Implementation Plan establishes reasonable progress goals for each Class I area in 

Georgia. To calculate the rate of progress represented by each reasonable progress goal, 

Georgia EPD compared baseline visibility conditions 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 Georgia EPD will summarize 

expected visibility improvements under existing Federal and State regulations, BART 

determinations in Georgia and neighboring states, and any additional control measures 

found to be reasonable to implement in this review period. These controls will be 

modeled in CMAQ as part of the long-term strategy. The modeling results will be used 

to set the reasonable progress goal. At this time, Georgia EPD knows that the reasonable 

progress goals will be at least as stringent as the Base G4 modeling results and will likely 

be more stringent when BART and reasonable measures are taken into account. VISTAS 

has already demonstrated that the 2018 Base G4 control scenario provides for an 

improvement in visibility better than the uniform rate of progress for all Georgia Class I 

areas for the most impaired days over the period of the implementation plan and ensures 

no degradation in visibility for the least impaired days over the same period. In addition, 

we expect that IMPROVE monitoring results for 2018 will, at that time, be used to 

establish a new baseline for the next planning period. Tables 10-1 and 10-2 list Georgia’s 

Reasonable Progress Goals. 
 Appendix H 

121 of 122 

 Table 10-1. 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] 

 

Table 10-2. 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] 

Class I Area Baseline 

Visibility 

(dv, 20 

percent Best 

Days) 

Reasonable 

Progress Goal 

(Expected Visibility 

Improvement (dv) 

by 2018, 20 percent 

Best Days) 

Deciview 

Improvement 

Needed 2018-

2064 (20 percent 

Best Days) 

Cohutta Wilderness Area 13.77 2.02 7.43 

Okefenokee Wilderness Area 15.23 1.31 8.61 

Wolf Island 15.23 1.31 8.61 
 Appendix H 

122 of 122 

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1. Boylan, J., 2006, VISTAS Joint Tech Analysis-Planning Call. Power Point 

Presentation: Summary BART_VOC_NH3_PM.ppt. 

2. Brewer, P.F.; and Adloch, J.P., 2005, Trends in Speciated Fine Particulate Matter 

and Visibility across Monitoring Networks in the Southeastern United States. J 

Air and Waste Management Association, 55, 1663-1674. 

3. Federal Register / Vol. 70, No. 128 / Wednesday, July 6, 2005 / Rules and 

Regulations. 

4. Hand, J.L.; and Malm, W.C.,2006, Review of the IMPROVE Equation for 

Estimating Ambient Light Extinction Coefficients - Final Report. March 2006. 

Prepared for Interagency Monitoring of Protected Visual Environments 

(IMPROVE), Colorado State University, Cooperative Institute for Research in the 

Atmosphere, Fort Collins, CO. 

5. MACTEC, 2006, Documentation of the Base G 2002 Base Year, 2009 and 2018, 

Emissions Inventory VISTAS. 

6. Pechan, E.H., and Associates, Inc., 2005, AirControlNET User Guide. 

7. Pitchford, Marc., 2006, Natural Haze Levels II: Application of the New 

IMPROVE Algorithm to Natural Species Concentrations Estimates. Final Report 

of the Natural Haze Levels II Committee to the RPO Monitoring/Data Analysis 

Workgroup. Sep 2006. 

8. Sorrels, Larry, 2006, AirControlNET 4.1 Software; US EPA, OAQPS, Research 

Triangle Park, NC. 

9. U.S. Environmental Protection Agency. (2003). Guidance for Tracking Progress 

under the Regional Haze Program; EPA-54/B-03-004, 2003.