Appendix H

i

Appendix H

Reasonable Progress Evaluation, BART

and Long-Term Strategy
 Appendix H

i

TABLE OF CONTENTS

LIST OF APPENDICES..................................................................................................... iv

LIST OF TABLES ...................................................................................................v

LIST OF FIGURES ................................................................................................vi

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.....................................................................................................................10

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

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

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

1.5 Summary of Emissions Projections.................................................................................... 14

2.0 UNIFORM RATE OF PROGRESS...............................................................16

3.0 GEORGIA TECH SENSITIVITIES .............................................................19

3.1 Evaluation for Cohutta Wilderness Area, Georgia ............................................................. 19

3.2 Evaluation for Okefenokee Wilderness Area, Georgia ...................................................... 20

4.0 REASONABLE PROGRESS EVALUATION .............................................21

4.1 Area of Influence Analyses................................................................................................. 21

4.2 Source Type Analyses ........................................................................................................ 23

4.3 Back Trajectory Analyses................................................................................................... 25

4.4 Area of Influence Data and Displays.................................................................................. 30

4.5 Importance of Pollutants Other Than Sulfate ..................................................................... 42

4.6 Summary of Emission Inventories Used in Cost Analysis................................................. 43

4.7 Process in Preparing Files for Cost Effectiveness Curve Development............................. 45

4.8 Application of AirControlNET Technologies .................................................................... 47

4.9 Development of AOI-Based Cost Curves........................................................................... 48

5.0 REASONABLE PROGRESS ASSESSMENT..............................................49

6.0 FOUR FACTOR ANALYSIS.........................................................................59

6.1 The Four Statutory Factors................................................................................................. 59

6.1.1 Cost of Compliance.......................................................................................................59

6.1.2 Time Necessary for Compliance...................................................................................59

6.1.3 Energy and Non-Air Quality Environmental Impacts of Compliance..........................60

6.1.4 Remaining Useful Life of the Source ...........................................................................60

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

Influence ............................................................................................................................. 60

6.2.1 Cost of Compliance.......................................................................................................61

6.2-2 Time Necessary for Compliance ..................................................................................61

6.2-3 Energy and Non-Air Environmental Impacts...............................................................62

6.2-4 Remaining Useful Life .................................................................................................62
 Appendix H

ii

6.3 Process of Applying Statutory Factors ............................................................................... 62

6.4 Evaluation of Four-factor Eligible Emissions Units and Recommendations..................... 64

6.4.1 GA Pacific Brunswick Cellulose, Power Boiler No. 4 (F1)........................................76

6.4.2 Georgia Pacific Brunswick Cellulose, Recovery Boiler No. 6 (M24).........................78

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)......................................80

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)........................................84

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

6.4.9 Georgia Power Plant Kraft, Steam Generator 1...........................................................85

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

6.4.11 Georgia Power Plant Kraft, Steam Generator 3.........................................................88

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

6.4.13 Georgia Power Plant Mitchell, Steam Generator 3....................................................91

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

6.4.15 Temple-Inland Rome Linerboard, No. 4 Power Boiler .............................................96

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 ................................................................116

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
 Appendix H

iii

10.3 Reasonable Progress Goals............................................................................................. 119

REFERENCES: ...................................................................................................120
 Appendix H

iv

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 - Basic Smoke Management Plan and Memorandum of Understanding Among

GADNR-EPD, GADNR-WRD, and GA Forestry Commission

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

v

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...................................... 23

Table 4-2. Source types 2018 Base G4 modeling OKEF – Percentage....................................... 24

Table 4-3. Source types 2018 Base G4 modeling WOLF – Percentage...................................... 24

Table 4-4. Back Trajectory Model Parameters Selected for VISTAS AOI Analysis.................. 25

Table 4-5. VISTAS 2002 Base Year Annual Emissions Summary (tons). ................................. 43

Table 4-6. 2018 Base Case Annual Emissions Summary (tons). ................................................ 44

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

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

Table 4-8. Emissions Weighted NETDC (MW) Association....................................................... 47

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

I areas............................................................................................................................................ 50

Table 5-2. Cohutta Wilderness Area Q/d, Q/d^2, RTMax, and fractional contribution analysis. 51

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

analysis.......................................................................................................................................... 53

Table 5-4. Wolf Island Q/d, Q/d^2, RTMax, and fractional contribution analysis. ..................... 55

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

(Georgia sources only).................................................................................................................. 56

Table 5-6. Units dropped from four-factor analysis..................................................................... 58

Table 6-1. Summary of Four-factor Analyses – South Georgia Facilities ................................... 67

Table 6-2. Summary of Four-Factor Analyses - North Georgia Facilities................................... 73

Table 6.3. Explanatory Notes for Summary of Four-Factor Analyses and Metrics................... 74

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 lists Georgia’s Reasonable Progress Goals. ............................................................. 120

Table 10-2. Georgia Reasonable Progress Goals – 20 percent Best Days.................................. 120
 Appendix H

vi

 LIST OF FIGURES

Figure 1-1. Annual NH3 emissions – Base G4............................................................................. 14

Figure 1-2. Annual PM2.5 emissions – Base G4.......................................................................... 15

Figure 1-3. Annual NOx emissions – Base G4............................................................................ 16

Figure 1-4. Annual SO2 emissions – Base G4. ............................................................................ 16

Figure 2-1. Uniform Rate of Progress at Cohutta Wilderness...................................................... 17

Figure 2-2. Uniform Rate of Progress at Okefenokee Wilderness............................................... 18

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

D emissions................................................................................................................................... 20

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

D emissions................................................................................................................................... 21

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

IMPROVE Equation (data from VIEWS Sep 2006). ................................................................... 22

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

Wilderness Area............................................................................................................................ 28

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

Okefenokee Wilderness Area ....................................................................................................... 29

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

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

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

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

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

2004............................................................................................................................................... 32

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

2000-2004. .................................................................................................................................... 32

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

period 2000-2004.......................................................................................................................... 33

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

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

Figure 4-10. Cohutta SO4 extinction-weighted residence time plots for the period 2000-2004. 34

Figure 4-11. Sipsey SO4 extinction-weighted residence time plots for the period 2000-2004... 34

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

2004............................................................................................................................................... 35

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

BaseG)........................................................................................................................................... 36

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

BaseG)........................................................................................................................................... 36
 Appendix H

vii

Figure 4-15. Cohutta 2002 SO2 Emissions * SO4 extinction-weighted residence time plots. ... 38

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

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

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

....................................................................................................................................................... 39

Figure 4-18. Cohutta 2018 SO2 Emissions * SO4 extinction-weighted residence time plots. ... 39

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

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

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

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

Figure 4-21. Cohutta 2002 vs. 2018 SO2 emissions multiplied by residence time..................... 41

Figure 4-22. Okefenokee 2002 vs. 2018 SO2 emissions multiplied by residence time. ............. 41

Figure 4-23. Wolf Island 2002 vs. 2018 SO2 emissions multiplied by residence time............... 42

Figure 4-24. VISTAS Base G2 SO2 Emissions Contribution by Major Source Sector.............. 45

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 115

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. Note that on July 11, 2008, the U.S.

District Court of Appeals in the District of Columbia vacated the Clean Air Interstate

Rule. As of the date of writing of this SIP, the mandate for that decision has not been

issued. Should the vacatur of CAIR stand, the Division may need to revise this SIP.

• 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 115

• 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 115

• 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 115

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 115

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 115

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 115

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,
 Appendix H

8 of 115

2007

Recalculated SO2 and PM emissions based on upgrade in control

efficiencies.

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

9 of 115

ORISID=3797 5, 6 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.

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
 Appendix H

10 of 115

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

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;
 Appendix H

11 of 115

• 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

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.
 Appendix H

12 of 115

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

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
 Appendix H

13 of 115

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.

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

SIP narrative.
 Appendix H

14 of 115

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

15 of 115

Figure 1-2. Annual PM2.5 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

16 of 115

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

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

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

17 of 115

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 

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

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

18 of 115

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

19 of 115

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

20 of 115

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

21 of 115

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

22 of 115

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
 Appendix H

23 of 115

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.

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

24 of 115

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

26 of 115

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

27 of 115

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

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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

30 of 115

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

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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

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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

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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

34 of 115

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

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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

36 of 115

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

37 of 115

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

38 of 115

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

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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

40 of 115

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

41 of 115

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

42 of 115

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

43 of 115

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

45 of 115

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 future0

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

46 of 115

year 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

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
 Appendix H

47 of 115

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

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

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

48 of 115

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

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.
 Appendix H

49 of 115

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

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
 Appendix H

50 of 115

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

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%
 Appendix H

51 of 115

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 Attachment H-1

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 INLAND PAPERBOARD

& PACKAGING, INC. -

LIN

F2 1,148 4 87.55 13.11 0.15 78.87 0.0137

GEORGIA INLAND PAPERBOARD

& PACKAGING, INC. -

LIN

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

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
 Appendix H

52 of 115

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

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
 Appendix H

53 of 115

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

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
 Appendix H

54 of 115

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

55 of 115

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

STATE PLANT

POIN

(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

56 of 115

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 INLAND PAPERBOARD

& PACKAGING

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. 

The GA EPD reviewed the sources for which the Four Factor Analysis was to be

conducted. The first review was of existing permit and compliance files, pending permit

applications and information provided by EPD permitting staff. As a result, three

emissions units were determined to have permanently ceased operation and were thus

removed from the list. These three sources were: Inland Paperboard I Packaging Inc. –

Unit F2; and Mohawk Industries, South Hamilton Street – Units BL06 and BL07.

GA EPD then requested site-specific information for use in the Four Factor Analyses

from each source on March 21, 2007. As a result of this inquiry, updated projected 2018

emissions were received from some facilities. Other facilities requested emission limits
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to reduce the percentage of an emission unit’s contribution to sulfate visibility impact on

the nearest Class I area to less than the threshold value of 0.5%. Table 5-6 gives a list of

the units that were removed as a result of updated emission projections or emission

limitations.

Table 5-6. 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, resulting into

lowering of sulfate visibility impact to less than 0.5 %

GEORGIA MOUNT VERNON

MILLS, INC., APPAREL

FABRIC

EU04 Facility updated their 2018 emission information, resulting into

lowering of sulfate visibility impact to less than 0.5 %

GEORGIA JESUP MILL, RAYONIER

PERFORMANCE FIBERS

PB02 Facility took voluntary limit on units eligible for four factor

analyses, resulting into lowering of sulfate visibility impact to

GEORGIA JESUP MILL, RAYONIER less than 0 5 %

PERFORMANCE FIBERS

PB03 Facility took voluntary limit on units eligible for four factor

analyses, resulting into lowering of sulfate visibility impact to

GEORGIA JESUP MILL, RAYONIER less than 0 5 %

PERFORMANCE FIBERS

RF01 Facility took voluntary limit on units eligible for four factor

analyses, resulting into lowering of sulfate visibility impact to

GEORGIA JESUP MILL, RAYONIER less than 0 5 %

PERFORMANCE FIBERS

RF04 Facility took voluntary limit on units eligible for four factor

analyses, resulting into lowering of sulfate visibility impact to

GEORGIA SOUTHERN STATES less than 0 5 %

PHOSPHATE &

FERTILIZER C

SA02 Facility took voluntary limit on units eligible for four factor

analyses, resulting into lowering of sulfate visibility impact to

GEORGIA SAVANNAH SUGAR less than 0 5 %

REFINERY

U161 Facility updated their 2018 emission information, resulting into

lowering of sulfate visibility impact to less than 0.5 %

GEORGIA PACKAGING

CORPORATION OF

AMERICA

CE Facility took voluntary limit on units eligible for four factor

analyses, resulting into lowering of sulfate visibility impact to

GEORGIA MILLER BREWING B001 less than 0 5 % Facility updated their 2018 emission information, resulting into

lowering of sulfate visibility impact to less than 0.5 %

GEORGIA MILLER BREWING B002 Facility updated their 2018 emission information, resulting into

lowering of 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 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 AirControNET 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. 

The Georgia EPD evaluated the amount of SO2 reduction from the EGU sector resulting

from the implementation of Georgia Rule 391-3-1-.02(2)(sss) - Multipollutant Control for

Electric Utility Steam Generating Units, CAIR, and other enforceable mechanisms as

reported by other VISTAS states. The EGUs in Georgia are expected to reduce their SO2

emissions by greater than 90 percent by 2018. This reduction is the result of Georgia

Rule 391-3-1-.02(2)(sss). This rule requires the installation and operation of specific

control equipment on specific EGUs in Georgia by specific deadlines. In contrast, the

SO2 emission reductions outside of Georgia that are predicted by IPM to meet the CAIR

requirements are not as certain due to CAIR’s reliance on unchecked trading and the use

of banked Title IV allowances (with certain exceptions such as North Carolina’s Clean

Smokestacks Act and controls required by consent agreements). The Georgia EPD

intends to re-evaluate the IPM predictions of SO2 reductions for CAIR outside of

Georgia at the time of our next periodic report in 2012 to ensure that the reductions

currently predicted by IPM for CAIR are in fact taking place where they are expected and

needed. 

Based on the controls required by Georgia Rule 391-3-1-.02(2)(sss), and predicted by

IPM under CAIR for EGUs outside of Georgia, and the fact that the expected visibility

improvement resulting from these requirements will clearly meet the glide slope (see

Figure 7.2.4.1 of narrative) we have concluded that at this time these existing regulatory

programs constitute reasonable progress for Georgia EGUs affecting visibility at Cohutta

Wilderness Area. Note, however, that on July 11, 2008, the U.S. District Court of

Appeals in the District of Columbia vacated the Clean Air Interstate Rule. As of the date

of writing of this SIP, the mandate for that decision has not been issued. Should the

vacatur of CAIR stand, the Division may need to revise this conclusion regarding

reasonable progress for the Cohutta Wilderness Area. However, these same existing

controls do not predict that the visibility improvement at Okefenokee or Wolf Island will

clearly meet the glide slope (see Figures 7.2.4.2 and 7.2.4.3 of Narrative). Therefore, we

have determined that CAIR does not satisfy the requirements for reasonable progress for

those EGUs impacting Okefenokee Wilderness Area and Wolf Island. 
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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

Temple Inland Rome

Class I Area: Cohutta Wilderness Area
 Appendix H

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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

Table 6.1 and 6.2 show the summary of assessment of 4-factor analysis for each of the

emission units. Abbreviations and color codes are listed below Table 6.2.

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 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. The following

subsections provide details of the 4-factor analysis and decision process for each eligible

unit.
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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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 Appendix H

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 Appendix H

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 Appendix H

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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 NotesClass I sulfateimpact fraction

P&SModelingunit

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 escrubber 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. 

ControlTechnology

company Control, deemed technically feasible by the facilty, evaluated for reduction of 

ControlEffectiveness

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 ControlNet

The estimated annual cost from a query of EPA’s Air Control Net database. Tcame from queries which found matches for the applicable technology at the sfacility. 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 toACNet

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 fivisibility data will be collected for the 2018 Regional Haze progress report. Tlife of all of the emissions units is 2018 or later. The expected useful life of alunits also exceeds the project life (i.e., amortization period) of all control optio

VisibilitySensitivity:Tons SO2/Mm-1

P&SModelingunit

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.

VisibilitySensitivity:$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. Th

dollars per ton ($/ton) was used in evaluating cost efficiency.

VisibilitySensitivity: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. 
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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

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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

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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. 

No control options were provided by the company. 

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.

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
 Appendix H

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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

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
 Appendix H

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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.

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. 
 Appendix H

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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 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

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 Sytem. 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
 Appendix H

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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.

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

 

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

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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

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
 Appendix H

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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

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.
 Appendix H

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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;

2. Coal swithching; 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.
 Appendix H

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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.

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.
 Appendix H

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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.

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.
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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;

2. Coal swithching; 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
 Appendix H

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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 realatively 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.

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.
 Appendix H

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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 swithching; 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

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.
 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 $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

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%)].
 Appendix H

92 of 115

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.

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
 Appendix H

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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 6, 7, and 8 below). 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. Regenerative thermal oxidizer (RTO) with scrubber: control HVLC ;

7. Regenerative thermal oxidizer (RTO) with scrubber: control LVHC and SOG;

and

8. Regenerative thermal oxidizer (RTO) with scrubber: control HVLC, LVHC,

and SOG.

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). This control option could be implemented by 2016.

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.

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.
 Appendix H

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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 sitespecific cost analyis 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.

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
 Appendix H

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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. This control option would achieve SO2 reductions of

approximately 23%. The company did not specify how the reductions would be

accomplished. 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. Although no costeffectiveness 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.
 Appendix H

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

Temple-Inland Rome in Floyd County, in northwest Georgia. 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 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
 Appendix H

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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.

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
 Appendix H

98 of 115

$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 opstions 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

$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 results in a lower control efficiency and has a

similar cost efficiency than other control opstions 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 115

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 115

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

In order to meet the SIP submittal deadline, 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 115

Georgia BART Eligible Sources

FACILITY NAME

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-Plant Wansley

Georgia Power-Plant Yates

Savannah Electric-Plant Kraft

Savannah Electric-Plant McIntosh

Chemical Products Corp

DSM Chemicals North America

Koch Cellulose (GP Brunswick, Brunswick Pulp & Paper)

Georgia-Pacific Cedar Springs Operations

International Paper – Augusta

International Paper - Savannah (Union Camp Corp.)

Interstate Paper, LLC

Kerr-McGee Pigments, Inc. (Kemira)

Lafarge Building Materials (Blue Circle Cement – Atlanta Plant)

Owens Corning

PCA (Tenneco Packaging, Inc.)

PCS Nitrogen Fertilizer, LP – Augusta

Prayon, Inc. (Solutia, Inc.)

Rayonier (ITT Rayonier, Inc.)

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 115

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

Georgia BART-Eligible Sources
 Appendix H

103 of 115

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

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

Exempt SourceNon-Exempt SourceExempt UtilityNon-Exempt Utility

Distance From Class I Area

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

104 of 115

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 115

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 out of state 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 115

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 115

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 0.3 dv threshold. 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

∆dV
 Appendix H

108 of 115

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

∆dV
 Appendix H

109 of 115

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 BARTeligible sources as shown in Table 7-2 below.

Table 7-2. Major BART 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 GA 206 31

PCS Nitrogen TN 1252 180

PCS Nitrogen GA 1765 220

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 a few BART 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 BARTeligible 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

do 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

the; nearest class I area; and 3) accepting an emissions limit of less than 250 tpy of the

visibility-impairing pollutant.
 Appendix H

110 of 115

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 EarthTech 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 115

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

be greater than 100 km from any Class I area. Sources must also have potential
 Appendix H

112 of 115

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

Okefenokee Wilderness Area 0.063

Shining Rock Wilderness 0.069
 Appendix H

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Wolf Island 0.114

International Paper Agusta 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

Georgia Power-Plant Scherer Okefenokee Wilderness Area 0.08

Wolf Island 0.05

Joyce Kilmer 0.07
 Appendix H

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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

St. Marks 0.499

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.
 Appendix H

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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

Chemical Products Corp. Facility has taken a 250 tpy limit on BART Eligible

Equipment

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.

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.
 Appendix H

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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

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.
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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

Efficeincy

Cost of

Control

($/ton)

Power Boiler

(F1)

Combustion of natural

gas only except during

periods of curtailment

99% 370

Recovery

Boiler

No cost effective

control options

Available

Not

required

Not required

Interstate Paper

Lime Kiln No cost effective

control options

Available

Not

required

Not required

Boiler 1

Boiler 2

Boiler 3

Georgia Power

Company –

Plant Bowen

Boiler 4

No cost effective

control options

Available

Not

required

Not required

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. Additionally, the Power Boiler (and Multi-fuel Boiler
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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 to 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. 

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
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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 indepth 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 the role of fire at Class I areas and status of State

planning for smoke management, the role of dust and fine soil at Class I areas and status

of State plans to mitigate emissions from construction activities, and the role of NH3 and

potential benefits if emissions from agricultural sources were mitigated.

On July 2008, Georgia EPD entered into a memorandum of understanding with the

Georgia Forestry Commission and Georgia Department of Natural Resources Wildlife

Resources Division adopting a smoke management plan that addresses the issues laid out

in EPA’s 1998 draft guidance for smoke management plans. The Memorandum, along

with the Basic Smoke Management Plan, is given in Appendix H.10. 

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
 Appendix H

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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.

Table 10-1 lists Georgia’s Reasonable Progress Goals.

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

Class I Area Baseline

Visibility

(dv, 20

percent

Worst Days)

Reasonable

Progress Goal

(Deciview

Improvement

Expected by 2018,

20 percent Worst

Days)

Deciview

Improvement

Needed 2018-

2064 (20 percent

Worst Days)

Cohutta Wilderness Area 30.25 7.47 12.00

Okefenokee Wilderness Area 27.13 3.36 12.56

Wolf Island 27.13 3.36 12.56

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

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

REFERENCES:

1. Boylan, J., 2006, VISTAS Joint Tech Analysis-Planning Call. Power Point

Presentation: Summary BART_VOC_NH3_PM.ppt.
 Appendix H

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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 Alogrithm 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.