## D-346 Figure D-344: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Spatial Plots For December 13, 2002

## D-347 D.115 December 16, 2002

Date Julian Day Type Class I Areas Affected 12/16/02 350 W20% OKEF, CHAS, EVER 12/16/02 350 B20%



## Figure D-345: Modeled Predicted And Observed Daily Average Sulfate (SO4) Component Concentrations (top left), Daily Average Nitrate (NO3) Component Concentrations (top right), Daily Average Ammonium (NH4) Component Concentrations, And Daily Average Organic Carbon (OC) Component Concentrations Spatial Plots For December 16, 2002

## D-348 Figure D-346: Modeled Predicted And Observed Daily Average Elemental Carbon (EC) Component Concentrations (top left), Daily Average Coarse Particle Mass (CM) Component Concentrations (to p right), Daily Average Sea Salt Component Concentrations, And Daily Average Soil Component Concentrations Spatial Plots For December 16, 2002

## D-349 Figure D-347: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Sp atial Plots For December 16, 2002

## D-350 D.116 December 19, 2002

Date Julian Day Type Class I Areas Affected 12/19/02 353 W20% 12/19/02 353 B20% SHRO, CACR, SWAN, HEGL, ROMA, UPBU, MING



## Figure D-348: Modeled Predicted And Observed Daily Average Sulfate (SO4) Component Concentrations (top left), Daily Average Nitrate (NO3) Component Concentrations (top right), Daily Average Ammonium (NH4) Component Concentrations, And Daily Average Organic Carbon (OC) Component Concentrations Spatial Plots For December 19, 2002

## D-351 Figure D-349: Modeled Predicted And Observed Daily Average Elemental Carbon (EC) Component Concentrations (top left), Daily Average Coarse Particle Mass (CM) Component Concentrations (to p right), Daily Average Sea Salt Component Concentrations, And Daily Average Soil Component Concentrations Spatial Plots For December 19, 2002

## D-352 Figure D-350: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Sp atial Plots For December 19, 2002

## D-353 D.117 December 22, 2002

Date Julian Day Type Class I Areas Affected 12/22/02 356 W20%
12/22/02 356 B20% LIGO, GRSM, JARI, SIPS, SAMA, OKEF, CACR, BRET, SHEN, DOSO, COHU, MACA, MING, BRIG



## Figure D-351: Modeled Predicted And Observed Daily Average Sulfate (SO4) Component Concentrations (top left), Daily Average Nitrate (NO3) Component Concentrations (top right), Daily Average Ammonium (NH4) Component

## D-354 Concentrations, And Daily Average Organic Carbon (OC) Component Concentrations Spatial Plots For December 22, 2002

Figure D-352: Modeled Predicted And Observed Daily Average Elemental Carbon (EC) Component Concentrations (top left), Daily Average Coarse Particle Mass (CM) Component Concentrations (to p right), Daily Average Sea Salt Component Concentrations, And Daily Average Soil Component Concentrations Spatial Plots For December 22, 2002

## D-355 Figure D-353: Figure D-354: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Sp atial Plots For December 22, 2002

## D-356 D.118 December 25, 2002

Date Julian Day Type Class I Areas Affected 12/25/02 359 W20% 12/25/02 359 B20% LIGO, SHRO, JARI, SIPS, OKEF, CACR, BRET, SHEN, DOSO, SWAN, BRIG



## Figure D-355: Modeled Predicted And Observed Daily Average Sulfate (SO4) Component Concentrations (top left), Daily Average Nitrate (NO3) Component Concentrations (top right), Daily Average Ammonium (NH4) Component Concentrations, And Daily Average Organic Carbon (OC) Component Concentrations Spatial Plots For December 25, 2002

## D-357 Figure D-356: Modeled Predicted And Observed Daily Average Elemental Carbon (EC) Component Concentrations (top left), Daily Average Coarse Particle Mass (CM) Component Concentrations (to p right), Daily Average Sea Salt Component Concentrations, And Daily Average Soil Component Concentrations Spatial Plots For December 25, 2002

## D-358 Figure D-357: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Sp atial Plots For December 25, 2002

## D-359 D.119 December 28, 2002

Date Julian Day Type Class I Areas Affected 12/28/02 362 W20% EVER, BRIG 12/28/02 362 B20% LIGO, SHRO, SIPS



## Figure D-358: Modeled Predicted And Observed Daily Average Sulfate (SO4) Component Concentrations (top left), Daily Average Nitrate (NO3) Component Concentrations (top right), Daily Average Ammonium (NH4) Component Concentrations, And Daily Average Organic Carbon (OC) Component Concentrations Spatial Plots For December 28, 2002

## D-360 Figure D-359: Modeled Predicted And Observed Daily Average Elemental Carbon (EC) Component Concentrations (top left), Daily Average Coarse Particle Mass (CM) Component Concentrations (to p right), Daily Average Sea Salt Component Concentrations, And Daily Average Soil Component Concentrations Spatial Plots For December 28, 2002

## D-361 Figure D-360: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Sp atial Plots For December 28, 2002

## D-362 D.120 December 31, 2002

Date Julian Day Type Class I Areas Affected 12/31/02 365 W20% 12/31/02 365 B20% SHRO, BRET, DOSO, HEGL, MACA, UPBU



## Figure D-361: Modeled Predicted And Observed Daily Average Sulfate (SO4) Component Concentrations (top left), Daily Average Nitrate (NO3) Component Concentrations (top right), Daily Average Ammonium (NH4) Component Concentrations, And Daily Average Organic Carbon (OC) Component Concentrations Spatial Plots For December 31, 2002

## D-363 Figure D-362: Modeled Predicted And Observed Daily Average Elemental Carbon (EC) Component Concentrations (top left), Daily Average Coarse Particle Mass (CM) Component Concentrations(top right), Daily Average Sea Salt Component Concentrations, And Daily Average Soil Component Concentrations Spatial Plots For December 31, 2002

## D-364 Figure D-363: Modeled Predicted And Observed Daily Average Total Fine Particulate Matter (PM25) Concentration Sp atial Plots For December 31, 2002

## APPENDIX E 2018 Visibility Projects at VISTAS a nd Nearby Class I Areas for the Worst 20 Percent Days using EPA Default Approach and Comparison with 2018 Uniform Rate of Progress

## E-1 2018 VISIBILITY PROJECTS AT VIST AS AND NEARBY CLASS I AREAS FOR THE WORST 20 PERCENT DAYS USING EPA DEFAULT APPROACH AND COMPARISON WITH 2018 UNIFO RM RATE OF PROGRESS

VISTAS Class I Areas

• Figure E-1: Sipsey Wilder ness Area (SIPS), Alabama

• Figure E-2: Chassahowitzka W ildlife Refuge (CHAS), Florida

• Figure E-3: Evergl ades National Park (EVER), Florida

• Figure E-4: St. Marks Wildli fe Refuge (SAMA), Florida

• Figure E-5: Cohutta Wild erness Area (COHU), Georgia

• Figure E-6: Okefenokee Wild life Refuge (OKEF), Georgia

• Figure E-7: Mammoth Cave Na tional Park (MACA), Kentucky

• Figure E-8: Linville Gorge Wilderness Area (LIGO), North Carolina

• Figure E-9: Shining Rock Wilder ness Area (SHRO), North Carolina

• Figure E-10: Swanquarter Wildlife Refuge (SWAN), North Carolina

• Figure E-11: Cape Romain Wildlife Refuge (ROMA), South Carolina

• Figure E-12: Great Smoky M ountains National Park (GRSM) , Tennessee-North Carolina

• Figure E-13: James River Face Wilderness Area (JARI), Virginia

• Figure E-14: Shenandoah National Park (SHEN), Virginia

• Figure E-15: Dolly Sods Wilder ness Area (DOSO), West Virginia Nearby Class I Areas

• Figure E-16: Breton Island Wild life Refuge (BRET), Louisiana

• Figure E-17: Caney Creek Wild erness Area (CACR), Arkansas

• Figure E-18: Upper Buffalo Wilderness Area (UPBU), Arkansas

• Figure E-19: Mingo Wildlife Refuge (MING), Missouri

• Figure E-20: Hercules Glade Wilderness Area (HEGL), Missouri

• Figure E-21: Brigantine Wildlif e Refuge (BRIG), New Jersey

## E-2 

## Uniform Rate of Progress Glide Path Sipsey - Worst 20% Days

29.03 27.52 24.80
21.78
18.76
15.74
12.72 10.90 26.43 23.69

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-1a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Sipsey (SIPS), Alabama and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Pr ogress Glide Path Sipsey - Worst 20% Days (36 km)

29.03 27.82
24.80
21.78
18.76
15.74
12.72 10.90 23.66



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-1b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Sipsey (SIPS), Alabama and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-3 Worst 20% Obs (left) vs 2002gt2a (right) at SIPS1

0 50 100 150 200 250 300 350

80 122 131 143 152 155 161 185 188 191 215 218 221 224 251 254 260 263 284 296 338 341 _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-1c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Sipsey (SIPS), Alabama and Worst 20% (W20%) days in 2002. Worst 20% Obs (left) vs 2002gt2a (right) at SIPS1

0 50 100 150 200 250 300 350

80 122 131 143 152 155 161 185 188 191 215 218 221 224 251 254 260 263 284 296 338 341 _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-1d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Sipsey (SIPS), Alabama and Worst 20% (W20%) days in 2002.

## E-4 Bext Response (2018g2b - 2002gt2a) at SIPS1 on Worst 20% Days

-180 -160 -140 -120 -100 -80 -60 -40 -20

0 20

80 122 131 143 152 155 161 185 188 191 215 218 221 224 251 254 260 263 284 296 338 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Fi 

### gure E-1e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Sipsey (SIPS), Alabama and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SIPS1 on Worst 20% Days

-140 -120 -100 -80 -60 -40 -20

0 20

80 122 131 143 152 155 161 185 188 191 215 218 221 224 251 254 260 263 284 296 338 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-1f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Sipsey (SIPS), Alabama and Worst 20% (W20%) days in 2002.

## E-5 

## Uniform Rate of Pr ogress Glide Path

Chassahowitzka - Worst 20% Days

25.75 24.52 22.31 19.86 17.41 14.96 12.50 11.03 23.22 21.85

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-2a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Chassahowitzka (CHAS), Florida and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Chassahowitzka - Worst 20% Days (36 km)

25.75 24.76
22.31 19.86
17.41 14.96 12.50 11.03 21.78

0 5 10 15 20 25 30

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-2b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Chassahowitzka (CHAS), Florida and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results

## E-6 Worst 20% Obs (left) vs 2002gt2a (rig ht) at CHAS1

0 20 40 60 80 100 120 140 160 180 200

5 17 26 41 44 47 56 89 116 128 155 200 206 236 260 278 281 290 296 329 332 341 350 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-2c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Chassahowitzka Wildlife Refuge (CHAS), Florida and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at CHAS1

0 20 40 60 80 100 120 140 160 180

5 17 26 41 44 47 56 89 116 128 155 200 206 236 260 278 281 290 296 329 332 341 350 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-2d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Chassahowitzka Wildlife Refuge (CHAS), Florida and Worst 20% (W20%) days in 2002.

## E-7 Bext Response (2018g2b - 2002gt 2a) at CHAS1 on Worst 20% Days

-120 -100 -80 -60 -40 -20

0 20

5 17 26 41 44 47 56 89 116 128 155 200 206 236 260 278 281 290 296 329 332 341 350 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-2e. Differences in modeled 2002 and 2018 Base G2 CMAQ 12 km results (2018- 2002) daily extinction for Chassahowitzka Wildlife Refuge (CHAS), Florida and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at CHAS1 on Worst 20% Days

-120 -100 -80 -60 -40 -20

0 20

5 17 26 41 44 47 56 89 116 128 155 200 206 236 260 278 281 290 296 329 332 341 350 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-2f. Differences in modeled 2002 and 2018 Base G2 CMAQ 36 km results (2018- 2002) daily extinction for Chassahowitzka Wildlife Refuge (CHAS), Florida and Worst 20% (W20%) days in 2002

.

## E-8 

## Uniform Rate of Progress Glide Path Everglades - Worst 20% Days

22.30 21.45 19.92 18.22 16.52 14.82 13.11 12.09 20.98 20.65



### 0 5 10 15 20 25 30

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-3a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Everglades (EVER), Florida and Worst 20% (W20%) day s using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Everglades - Worst 20% Days (36 km)

22.30 21.62 19.92 18.22 16.52 14.82 13.11 12.09 20.16



### 0 5 10 15 20 25 30

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-3b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Everglades (EVER), Florida and Worst 20% (W20%) day s using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-9 Worst 20% Obs (left) vs 2002gt2a (right) at EVER1

0 20 40 60 80 100 120 140 160 180 200

5 35 44 56 62 74 95 98 113 125 128 152 158 218 236 257 281 290 305 311 332 341 350 362 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-3c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Everglades (EVER), Florida and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at EVER1

0 20 40 60 80 100 120 140 160 180 200

5 35 44 56 62 74 95 98 113 125 128 152 158 218 236 257 281 290 305 311 332 341 350 362 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-3d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Everglades (EVER), Florida and Worst 20% (W20%) days in 2002.

## E-10 Bext Response (2018g2b - 2002gt2a) at EVER1 on Worst 20% Days

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

5 35 44 56 62 74 95 98 113 125 128 152 158 218 236 257 281 290 305 311 332 341 350 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-3e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018- 2002) daily extinction for Everglades (EVER), Florida and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at EVER1 on Worst 20% Days

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

5 35 44 56 62 74 95 98 113 125 128 152 158 218 236 257 281 290 305 311 332 341 350 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-3f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Everglades (EVER), Florida and Worst 20% (W20%) days in 2002.

## E-11 

## Uniform Rate of Progress Glide Path Saint Marks - Worst 20% Days

26.31 25.09 22.89 20.45 18.01 15.57 13.13 11.67 24.40 22.89

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-4a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for St. Marks (SAMA), Florida and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Saint Marks - Worst 20% Days (36 km)

26.31 25.33 22.89 20.45 18.01 15.57 13.13 11.67 22.69

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-4b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for St. Marks (SAMA), Florida and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-12 Worst 20% Obs (left) vs 2002gt2a (right) at SAMA1

0 50 100 150 200 250

35 44 47 56 89 95 98 107 116 122 125 128 131 155 185 188 197 200 260 290 293 296 341 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-4c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for St. Marks (SAMA), Florida and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at SAMA1

0 50 100 150 200 250

35 44 47 56 89 95 98 107 116 122 125 128 131 155 185 188 197 200 260 290 293 296 341 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-4d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for St. Marks (SAMA), Florida and Worst 20% (W20%) days in 2002.

## E-13 Bext Response (2018g2b - 2002gt2a) at SAMA1 on Worst 20% Days

-100 -80 -60 -40 -20

0 20

35 44 47 56 89 95 98 107 116 122 125 128 131 155 185 188 197 200 260 290 293 296 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-4e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018- 2002) daily extinction for St. Marks (SAMA), Florida and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SAMA1 on Worst 20% Days

-100 -80 -60 -40 -20

0 20

35 44 47 56 89 95 98 107 116 122 125 128 131 155 185 188 197 200 260 290 293 296 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-4f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for St. Marks (SAMA), Florida and Worst 20% (W20%) days in 2002.

## E-14 

## Uniform Rate of Progress Glide Path Cohutta - Worst 20% Days

30.25 28.63
25.71
22.46
19.22
15.97
12.73 10.78 27.05

22.84



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-5a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cohutta (COHU), Georgia and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Cohutta - Worst 20 % Days (36 km)

30.25 28.96
25.71
22.46
19.22
15.97
12.73 10.78 22.92



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-5b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cohutta (COHU), Georgia and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-15 Worst 20% Obs (left) vs 2002gt2a (right) at COHU1

0 100 200 300 400 500 600

56 122 152 155 185 188 191 197 206 215 218 221 224 227 233 248 251 260 263 266 281 _ _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-5c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Cohutta (COHU), Georgia and Worst 20% (W20%) days in 2002. 

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

0 100 200 300 400 500 600

56 122 152 155 185 188 191 197 206 215 218 221 224 227 233 248 251 260 263 266 281 _ _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-5d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Cohutta (COHU), Georgia and Worst 20% (W20%) days in 2002.

## E-16 Bext Response (2018g2b - 2002gt2a) at COHU1 on Worst 20% Days

-300 -250 -200 -150 -100 -50

0 50

56 122 152 155 185 188 191 197 206 215 218 221 224 227 233 248 251 260 263 266 281 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-5e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018- 2002) daily extinction for Cohutta (COHU), Georgia and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at COHU1 on Worst 20% Days

-300 -250 -200 -150 -100 -50

0 50

56 122 152 155 185 188 191 197 206 215 218 221 224 227 233 248 251 260 263 266 281 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-5f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Cohutta (COHU), Georgia and Worst 20% (W20%) days in 2002.

## E-17 

## Uniform Rate of Progress Glide Path Okefenokee - Worst 20% Days

27.13 25.81 23.42 20.76 18.11 15.45 12.80 11.21 25.38 23.85



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-6a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Okefenokee (OKEF), Georgia and Worst 20% (W20%) days using 2002/2 018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Okefenokee - Worst 20% Days (36 km)

27.13 26.07 23.42 20.76 18.11 15.45 12.80 11.21 23.61



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-6a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Okefenokee (OKEF), Georgia and Worst 20% (W20%) days using 2002/2 018 Base G2 CMAQ 36 km modeling results.

## E-18 Worst 20% Obs (left) vs 2002gt2a (right) at OKEF1

0 50 100 150 200 250 300 350

17 23 44 56 89 95 122 128 155 188 197 200 218 236 254 260 263 281 296 308 338 341 350 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-6c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Okefenokee (OKEF), Georgia and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2 002gt2a (right) at OKEF1

0 50 100 150 200 250 300 350

17 23 44 56 89 95 122 128 155 188 197 200 218 236 254 260 263 281 296 308 338 341 350 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-6d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Okefenokee (OKEF), Georgia and Worst 20% (W20%) days in 2002.

## E-19 Bext Response (2018g2b - 2002gt2a) at OKEF1 on Worst 20% Days

-140 -120 -100 -80 -60 -40 -20

0 20 40

17 23 44 56 89 95 122 128 155 188 197 200 218 236 254 260 263 281 296 308 338 341 350 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-6e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Okefenokee (OKEF), Georgia and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at OKEF1 on Worst 20% Days

-140 -120 -100 -80 -60 -40 -20

0 20 40

17 23 44 56 89 95 122 128 155 188 197 200 218 236 254 260 263 281 296 308 338 341 350 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-6f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Okefenokee (OKEF), Georgia and Worst 20% (W20%) days in 2002.

## E-20 

## Uniform Rate of Progress Glide Path

Mammoth Cave - Worst 20% Days

31.37 29.68
26.64
23.26
19.87
16.49
13.11 11.08 28.04 25.56



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-7a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mammoth Cave (MACA), Kentucky and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Mammoth Cave - Worst 20% Days (36 km)

31.37 30.02
26.64
23.26
19.87
16.49
13.11 11.08 25.63



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-7b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mammoth Cave (MACA), Kentucky and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-21 Worst 20% Obs (left) vs 2002gt2a (rig ht) at MACA1

0 50 100 150 200 250 300 350 400 450 500

86 149 152 155 170 173 185 191 197 203 206 212 215 218 224 233 236 239 245 251 254 260 263 341 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-7c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Mammoth Cave (MACA), K entucky and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2 002gt2a (right) at MACA1

0 100 200 300 400 500 600 700

86 149 152 155 170 173 185 191 197 203 206 212 215 218 224 233 236 239 245 251 254 260 263 341 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-7d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Mammoth Cave (MACA), Kentucky and Worst 20% (W20%) days in 2002.

## E-22 Bext Response (2018g2b - 2002gt2a) at MACA1 on Worst 20% Days

-350 -300 -250 -200 -150 -100 -50

0 50

86 149 152 155 170 173 185 191 197 203 206 212 215 218 224 233 236 239 245 251 254 260 263 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-7d. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Mammoth Cave (MACA), K entucky and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at MACA1 on Worst 20% Days

-450 -400 -350 -300 -250 -200 -150 -100 -50

0 50

86 149 152 155 170 173 185 191 197 203 206 212 215 218 224 233 236 239 245 251 254 260 263 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-7e. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Mammoth Cave (MACA), Kentucky and Worst 20% (W20%) days in 2002.

## E-23 

## Uniform Rate of Progress Glide Path Linville Gorge - Worst 20% Days

28.77 27.31 24.67
21.74
18.81
15.88
12.95 11.19 24.99
21.98



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-8a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Linville Gorge (LIGO), North Carolina and Worst 20% (W20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Linville Gorge - Worst 20% Days (36 km)

28.77 27.60
24.67
21.74
18.81
15.88
12.95 11.19 21.78



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-8b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Linville Gorge (LIGO), North Carolina and Worst 20% (W20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results..

## E-24 Worst 20% Obs (left) vs 2002gt2a (right) at LIGO1

0 50 100 150 200 250 300 350 400

122 128 137 149 152 170 191 203 206 209 212 215 218 221 224 233 236 239 248 251 254 260 _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-8c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Linville Gorge (LIGO), North Carolina and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at LIGO1

0 50 100 150 200 250 300 350 400

122 128 137 149 152 170 191 203 206 209 212 215 218 221 224 233 236 239 248 251 254 260 _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-8d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Linville Gorge (LIGO), Nort h Carolina and Worst 20% (W20%) days in 2002.

## E-25 Bext Response (2018g2b - 2002gt2a) at LIGO1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

122 128 137 149 152 170 191 203 206 209 212 215 218 221 224 233 236 239 248 251 254 260 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-8e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Linville Gorge (LIGO), North Carolina and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at LIGO1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

122 128 137 149 152 170 191 203 206 209 212 215 218 221 224 233 236 239 248 251 254 260 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-8f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Linville Gorge (LIGO), Nort h Carolina and Worst 20% (W20%) days in 2002.

## E-26 

## Uniform Rate of Progress Glide Path Shining Rock - Worst 20% Days

28.66 27.22 24.65
21.78 18.92 16.05 13.19 11.47 25.01
22.11



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-9a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shining Rock (SHRO), North Carolina and Worst 20% (W20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Shining Rock - Worst 20% Days (36 km)

28.66 27.51 24.65
21.78 18.92 16.05
13.19 11.47 21.45



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction Figure E-9b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shining Rock (SHRO), North Carolina and Worst 20% (W20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results.

## E-27 Worst 20% Obs (left) vs 2002gt2a (right) at SHRO1

0 100 200 300 400 500 600

128 137 152 155 161 164 170 182 185 188 191 197 203 206 212 215 218 221 224 233 248 251 254 260 266 Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-9c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Shining Rock (SHRO), North Ca rolina and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 20 02gt2a (right) at SHRO1

0 100 200 300 400 500 600

128 137 152 155 161 164 170 182 185 188 191 197 203 206 212 215 218 221 224 233 248 251 254 260 266 Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-9d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Shining Rock (SHRO), North Ca rolina and Worst 20% (W20%) days in 2002.

## E-28 Bext Response (2018g2b - 2002gt2a) at SHRO1 on Worst 20% Days

-160 -140 -120 -100 -80 -60 -40 -20

0 20

128 137 152 155 161 164 170 182 185 188 191 197 203 206 212 215 218 221 224 233 248 251 254 260 266 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-9e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Shining Rock (SHRO), North Ca rolina and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at SHRO1 on Worst 20% Days

-160 -140 -120 -100 -80 -60 -40 -20

0 20

128 137 152 155 161 164 170 182 185 188 191 197 203 206 212 215 218 221 224 233 248 251 254 260 266 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-9f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Shining Rock (SHRO), North Ca rolina and Worst 20% (W20%) days in 2002.

## E-29 

## Uniform Rate of Progress Glide Path Swanquarter - Worst 20% Days

24.71 23.62 21.64 19.45 17.25 15.06 12.86 11.55 22.12 20.37



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-10a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Swanquarter (SWAN), North Carolina and Worst 20% (W20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Swanquarter - Worst 20% Days (36 km)

24.71 23.84 21.64 19.45 17.25 15.06 12.86 11.55 20.23



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-10b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Swanquarter (SWAN), North Carolina and Worst 20% (W20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results..

## E-30 Worst 20% Obs (left) vs 2002gt2a (right) at SWAN1

0 50 100 150 200 250

5 53 56 110 119 122 128 146 185 188 197 200 209 212 233 236 254 260 278 293 326 329 341 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-10c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Swanquarter (SWAN), North Carolina and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at SWAN1

0 50 100 150 200 250

5 53 56 110 119 122 128 146 185 188 197 200 209 212 233 236 254 260 278 293 326 329 341 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-10d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Swanquarter (SWAN), North Carolina and Worst 20% (W20%) days in 2002.

## E-31 Bext Response (2018g2b - 2002gt2a) at SWAN1 on Worst 20% Days

-100 -80 -60 -40 -20

0 20

5 53 56 110 119 122 128 146 185 188 197 200 209 212 233 236 254 260 278 293 326 329 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-10e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Swanquarter (SWAN), North Carolina and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SWAN1 on Worst 20% Days

-100 -80 -60 -40 -20

0 20

5 53 56 110 119 122 128 146 185 188 197 200 209 212 233 236 254 260 278 293 326 329 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-10f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Swanquarter (SWAN), North Carolina and Worst 20% (W20%) days in 2002.

## E-32 

## Uniform Rate of Progress Glide Path Cape Romain - Worst 20% Days

26.48 25.28 23.12 20.73 18.33 15.94 13.54 12.10 24.46 22.72



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-11a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cape Romain (ROMA), South Carolina and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Cape Romain - Worst 20% Days (36 km)

26.48 25.52 23.12 20.73 18.33 15.94 13.54 12.10 22.72



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-11b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cape Romain (ROMA), South Carolina and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-33 Worst 20% Obs (left) vs 2002gt2a (right) at ROMA1

0 50 100 150 200 250 300

17 29 44 47 53 110 122 155 158 182 185 188 197 200 206 212 236 254 257 260 293 296 299 341 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-11c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Cape Romain (ROMA), South Carolina and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 20 02gt2a (right) at ROMA1

0 50 100 150 200 250 300

17 29 44 47 53 110 122 155 158 182 185 188 197 200 206 212 236 254 257 260 293 296 299 341 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-11d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Cape Romain (ROMA), South Carolina and Worst 20% (W20%) days in 2002.

## E-34 Bext Response (2018g2b - 2002gt2a) at ROMA1 on Worst 20% Days

-120 -100 -80 -60 -40 -20

0 20

17 29 44 47 53 110 122 155 158 182 185 188 197 200 206 212 236 254 257 260 293 296 299 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-11e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Cape Romain (ROMA), South Carolina and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at ROMA1 on Worst 20% Days

-120 -100 -80 -60 -40 -20

0 20

17 29 44 47 53 110 122 155 158 182 185 188 197 200 206 212 236 254 257 260 293 296 299 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-11f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Cape Romain (ROMA), South Carolina and Worst 20% (W20%) days in 2002.

## E-35 

## Uniform Rate of Progress Glide Path Great Smoky Mountains - Worst 20% Days

30.28 28.67 25.79
22.59
19.38
16.18
12.97 11.05 26.72
23.66

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-12a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Great Smoky Mountains (GRSM), Tennessee-North Carolina and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Great Smoky Mountains - Worst 20% Days (36 km)

30.28 28.99
25.79
22.59
19.38
16.18
12.97 11.05 22.87

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-12b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Great Smoky Mountains (GRSM), Tennessee-North Carolina and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## E-36 Worst 20% Obs (left) vs 2002gt2a (right) at GRSM1

0 50 100 150 200 250 300 350 400

56 122 128 137 152 164 170 173 182 188 191 197 203 212 215 218 221 224 227 233 248 251 254 260 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-12c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Great Smoky Mountains (GRSM), Te nnessee-North Carolina and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2 002gt2a (right) at GRSM1

0 50 100 150 200 250 300 350 400

56 122 128 137 152 164 170 173 182 188 191 197 203 212 215 218 221 224 227 233 248 251 254 260 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-12d. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Great Smoky Mountains (GRSM), Te nnessee-North Carolina and Worst 20% (W20%) days in 2002.

## E-37 Bext Response (2018g2b - 2002gt2a) at GRSM1 on Worst 20% Days

-200 -150 -100 -50

0 50

56 122 128 137 152 164 170 173 182 188 191 197 203 212 215 218 221 224 227 233 248 251 254 260 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-12e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Great Smoky Mountains (GRSM), Te nnessee-North Carolina and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at GRSM1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

56 122 128 137 152 164 170 173 182 188 191 197 203 212 215 218 221 224 227 233 248 251 254 260 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-12f. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Great Smoky Mountains (GRSM), Te nnessee-North Carolina and Worst 20% (W20%) days in 2002.

## E-38 

## Uniform Rate of Progress Glide Path James River Face - Worst 20% Days

29.12 27.62 24.91
21.91
18.90
15.90
12.90 11.09 25.28 22.59



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-13a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for James River Face (JARI), Virginia and Worst 20% (W20%) days using 2 002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path James River Face - Worst 20% Days (36 km)

29.12 27.92
24.91
21.91
18.90
15.90
12.90 11.09 22.40



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-13b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for James River Face (JARI), Virginia and Worst 20% (W20%) days using 2 002/2018 Base G2 CMAQ 36 km modeling results.

## E-39 Worst 20% Obs (left) vs 2002gt2a (right) at JARI1

0 50 100 150 200 250 300 350

137 146 152 155 161 182 185 191 197 200 203 212 215 218 224 233 236 239 254 257 263 266 272 275 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-13c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for James River Face (JARI), Virginia and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at JARI1

0 50 100 150 200 250 300 350

137 146 152 155 161 182 185 191 197 200 203 212 215 218 224 233 236 239 254 257 263 266 272 275 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-13d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for James River Face (JARI), Virginia and Worst 20% (W20%) days in 2002.

## E-40 Bext Response (2018g2b - 2002gt2a) at JARI1 on Worst 20% Days

-180 -160 -140 -120 -100 -80 -60 -40 -20

0 20

137 146 152 155 161 182 185 191 197 200 203 212 215 218 224 233 236 239 254 257 263 266 272 275 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-13e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for James River Face (JARI), Virginia and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at JARI1 on Worst 20% Days

-180 -160 -140 -120 -100 -80 -60 -40 -20

0 20

137 146 152 155 161 182 185 191 197 200 203 212 215 218 224 233 236 239 254 257 263 266 272 275 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-13f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for James River Face (JARI), Virginia and Worst 20% (W20%) days in 2002.

## E-41 

## Uniform Rate of Progress Glide Path Shenandoah - Worst 20% Days

29.31 27.81 25.12
22.13
19.14
16.15
13.16 11.37 24.89
22.11



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-14a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shenandoah (SHEN), Virginia and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Shenandoah - Worst 20% Days (36 km)

29.31 28.11
25.12
22.13
19.14
16.15
13.16 11.37 21.98



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-14b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shenandoah (SHEN), Virginia and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## E-42 Worst 20% Obs (left) vs 2002gt2a (right) at SHEN1

0 100 200 300 400 500 600

59 146 149 155 161 164 170 176 182 185 197 200 203 212 215 224 233 236 239 254 257 260 272 275 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-14c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Shenandoah (SHEN), Virgin ia and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2 002gt2a (right) at SHEN1

0 50 100 150 200 250 300 350 400 450

59 146 149 155 161 164 170 176 182 185 197 200 203 212 215 224 233 236 239 254 257 260 272 275 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-14d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Shenandoah (SHEN), Virgin ia and Worst 20% (W20%) days in 2002.

## E-43 Bext Response (2018g2b - 2002gt2a) at SHEN1 on Worst 20% Days

-350 -300 -250 -200 -150 -100 -50

0 50

59 146 149 155 161 164 170 176 182 185 197 200 203 212 215 224 233 236 239 254 257 260 272 275 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-14e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Shenandoah (SHEN), Virgin ia and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at SHEN1 on Worst 20% Days

-350 -300 -250 -200 -150 -100 -50

0 50

59 146 149 155 161 164 170 176 182 185 197 200 203 212 215 224 233 236 239 254 257 260 272 275 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-14f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Shenandoah (SHEN), Virgin ia and Worst 20% (W20%) days in 2002.

## E-44 

## Uniform Rate of Progress Glide Path Dolly Sods - Worst 20% Days

29.04 27.49 24.69
21.57
18.46
15.34
12.23 10.36 24.78
21.64



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-15a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Dolly Sods (DOSO), West Virginia and Worst 20% (W20%) days using 2 002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Dolly Sods - Worst 20% Days (36 km)

29.04 27.80
24.69
21.57
18.46
15.34
12.23 10.36 21.71



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-15b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Dolly Sods (DOSO), West Virginia and Worst 20% (W20%) days using 2 002/2018 Base G2 CMAQ 36 km modeling results.

## E-45 Worst 20% Obs (left) vs 2002gt2a (right) at DOSO1

0 50 100 150 200 250 300 350 400 450 500

122 128 137 146 149 152 155 161 164 170 173 176 182 191 206 224 227 254 257 260 263 272 275 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-15c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Dolly Sods (DOSO), West Vi rginia and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at DOSO1

0 50 100 150 200 250 300 350 400 450 500

122 128 137 146 149 152 155 161 164 170 173 176 182 191 206 224 227 254 257 260 263 272 275 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-15d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Dolly Sods (DOSO), West Virginia and Worst 20% (W20%) days in 2002.

## E-46 Bext Response (2018g2b - 2002gt2a) at DOSO1 on Worst 20% Days

-300 -250 -200 -150 -100 -50

0 50

122 128 137 146 149 152 155 161 164 170 173 176 182 191 206 224 227 254 257 260 263 272 275 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-15e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Dolly Sods (DOSO), West Vi rginia and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at DOSO1 on Worst 20% Days

-300 -250 -200 -150 -100 -50

0 50

122 128 137 146 149 152 155 161 164 170 173 176 182 191 206 224 227 254 257 260 263 272 275 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-15f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Dolly Sods (DOSO), West Virginia and Worst 20% (W20%) days in 2002.

## E-47 

## Uniform Rate of Progress Glide Path Breton - Worst 20% Days

26.00 24.82 22.71 20.37 18.02 15.68 13.34 11.93 24.89 23.41



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-16a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Breton Island (BRET), Louisiana and Worst 20% (W20%) days using 2002/2 018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Breton - Worst 20% Days (36 km)

26.00 25.06 22.71 20.37 18.02 15.68 13.34 11.93 23.35



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-16b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Breton Island (BRET), Louisiana and Worst 20% (W20%) days using 2002/2 018 Base G2 CMAQ 36 km modeling results.

## E-48 Worst 20% Obs (left) vs 2002gt2a (right) at BRET1

0 20 40 60 80 100 120 140 160 180

44 47 74 125 143 179 194 197 200 206 215 239 248 251 254 257 260 263 272 281 284 287 305 311 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-16c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Breton Island (BRET), Loui siana and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at BRET1

0 20 40 60 80 100 120 140 160 180

44 47 74 125 143 179 194 197 200 206 215 239 248 251 254 257 260 263 272 281 284 287 305 311 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-16d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Breton Island (BRET), Louisiana and Worst 20% (W20%) days in 2002.

## E-49 Bext Response (2018g2b - 2002gt2a) at BRET1 on Worst 20% Days

-60 -50 -40 -30 -20 -10

0 10

44 47 74 125 143 179 194 197 200 206 215 239 248 251 254 257 260 263 272 281 284 287 305 311 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-16e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Breton Island (BRET), Loui siana and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at BRET1 on Worst 20% Days

-70 -60 -50 -40 -30 -20 -10

0 10

44 47 74 125 143 179 194 197 200 206 215 239 248 251 254 257 260 263 272 281 284 287 305 311 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-16f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Breton Island (BRET), Louisiana and Worst 20% (W20%) days in 2002.

## E-50 

## Uniform Rate of Progress Glide Path Caney Creek - Worst 20% Days

26.36 25.13 22.91 20.45 17.98 15.51 13.05 11.57 24.01 22.38



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-17a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Caney Creek (CACR), Arkansas and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Caney Creek - Worst 20% Days (36 km)

26.36 25.38 22.91 20.45 17.98 15.51 13.05 11.57 22.34



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-17b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Caney Creek (CACR), Arkansas and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-51 Worst 20% Obs (left) vs 2002gt2a (right) at CACR1

0 50 100 150 200 250 300 350 400

80 128 143 155 170 173 188 191 200 203 215 218 221 239 242 248 251 254 257 260 296 320 341 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-17c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Caney Creek (CACR), Arkansas and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 20 02gt2a (right) at CACR1

0 50 100 150 200 250 300 350

80 128 143 155 170 173 188 191 200 203 215 218 221 239 242 248 251 254 257 260 296 320 341 _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-17d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Caney Creek (CACR), Arkansas and Worst 20% (W20%) days in 2002.

## E-52 Bext Response (2018g2b - 2002gt2a) at CACR1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

80 128 143 155 170 173 188 191 200 203 215 218 221 239 242 248 251 254 257 260 296 320 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-17e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Caney Creek (CACR), Arkansas and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at CACR1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

80 128 143 155 170 173 188 191 200 203 215 218 221 239 242 248 251 254 257 260 296 320 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-17f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Caney Creek (CACR), Arkansas and Worst 20% (W20%) days in 2002.

## E-53 

## Uniform Rate of Progress Glide Path Upper Buffalo - Worst 20% Days

26.27 25.03 22.82 20.35 17.89 15.43 12.96 11.49 23.74 22.12



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-18a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Upper Buffalo (UPBU), Arkansas and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Upper Buffalo - Worst 20% Days (36 km)

26.27 25.28 22.82 20.35 17.89 15.43 12.96 11.49 22.19



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-18b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Upper Buffalo (UPBU), Arkansas and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-54 Worst 20% Obs (left) vs 2002gt2a (right) at UPBU1

0 50 100 150 200 250 300 350 400 450 500

128 143 158 170 173 179 191 197 203 206 215 218 221 224 239 242 248 251 254 257 269 296 320 332 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-18c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Upper Buffalo (UPBU), Arkans as and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at UPBU1

0 50 100 150 200 250 300 350

128 143 158 170 173 179 191 197 203 206 215 218 221 224 239 242 248 251 254 257 269 296 320 332 _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-18d. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Upper Buffalo (UPBU), Ark ansas and Worst 20% (W20%) days in 2002

## E-55 Bext Response (2018g2b - 2002gt2a) at UPBU1 on Worst 20% Days

-300 -250 -200 -150 -100 -50

0 50

128 143 158 170 173 179 191 197 203 206 215 218 221 224 239 242 248 251 254 257 269 296 320 332 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-18e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Upper Buffalo (UPBU), Arkans as and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at CACR1 on Worst 20% Days

-300 -250 -200 -150 -100 -50

0 50

80 128 143 155 170 173 188 191 200 203 215 218 221 239 242 248 251 254 257 260 296 320 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-18f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Upper Buffalo (UPBU), Ark ansas and Worst 20% (W20%) days in 2002.

## E-56 

## Uniform Rate of Progress Glide Path Mingo - Worst 20% Days

28.05 26.68 24.22 21.48 18.74 16.00 13.26 11.62 25.37 23.85



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-19a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mingo (MING), Missouri and Worst 20% (W20%) days using 2002/2 018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Mingo - Worst 20% Days (36 km)

28.05 26.95 24.22 21.48 18.74 16.00 13.26 11.62 24.02



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-19b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mingo (MING), Missouri and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## E-57 Worst 20% Obs (left) vs 2002gt2a (right) at MING1

-50

0 50 100 150 200 250 300 350 400 450

20 77 95 158 185 188 191 194 197 206 215 218 221 239 242 245 251 260 272 296 332 341 _ _ _ Avg

Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-19c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Mingo (MING), Missouri and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 20 02gt2a (right) at MING1

-50

0 50 100 150 200 250 300 350 400

20 77 95 158 185 188 191 194 197 206 215 218 221 239 242 245 251 260 272 296 332 341 _ _ _ Avg

Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-19d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Mingo (MING), Missouri and Worst 20% (W20%) days in 2002.

## E-58 Bext Response (2018g2b - 2002gt2a) at MING1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

20 77 95 158 185 188 191 194 197 206 215 218 221 239 242 245 251 260 272 296 332 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-19e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Mingo (MING), Missouri and Worst 20% (W20%) days in 2002. Bext Response (2018g2a - 2002gt2a) at MING1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

20 77 95 158 185 188 191 194 197 206 215 218 221 239 242 245 251 260 272 296 332 341 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-19f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Mingo (MING), Missouri and Worst 20% (W20%) days in 2002.

## E-59 

## Uniform Rate of Progress Glide Path

Hercules - Glade - Worst 20% Days

26.75 25.46 23.13 20.55 17.96 15.38 12.80 11.24 24.58 23.09



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-20a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Hercules Glade (HEGL), Missouri and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Hercules - Glade - Wo rst 20% Days (36 km)

26.75 25.72 23.13 20.55 17.96 15.38 12.80 11.24 23.24



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-20b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Hercules Glade (HEGL), Missouri and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-60 Worst 20% Obs (left) vs 2002gt2a (right) at HEGL1

0 50 100 150 200 250 300 350 400 450

5 149 152 170 173 179 188 191 206 215 218 221 224 239 242 245 248 251 257 260 269 296 320 341 347 Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-20c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Hercules Glade (HEGL), Missouri and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2 002gt2a (right) at HEGL1

0 50 100 150 200 250 300 350 400

5 149 152 170 173 179 188 191 206 215 218 221 224 239 242 245 248 251 257 260 269 296 320 341 347 Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-20d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Hercules Glade (HEGL), Missouri and Worst 20% (W20%) days in 2002.

## E-61 Bext Response (2018g2b - 2002gt2a) at HEGL1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

5 149 152 170 173 179 188 191 206 215 218 221 224 239 242 245 248 251 257 260 269 296 320 341 347 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-20e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Hercules Glade (HEGL), Missouri and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at HEGL1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

5 149 152 170 173 179 188 191 206 215 218 221 224 239 242 245 248 251 257 260 269 296 320 341 347 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-20f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Hercules Glade (HEGL), Missouri and Worst 20% (W20%) days in 2002.

## E-62 

## Uniform Rate of Progress Glide Path Brigantine - Worst 20% Days

29.01 27.59 25.05 22.23 19.40 16.58 13.76 12.06 26.07 24.62

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-21a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Brigantine (BRIG), New Jersey and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. 

## Uniform Rate of Progress Glide Path Brigantine - Worst 20% Days (36 km)

29.01 27.88 25.05 22.23 19.40 16.58 13.76 12.06 24.37

0 5 10 15 20 25 30 35

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

Glide Path Natural Condition (Worst Days) Observation Method 1 Prediction 

### Figure E-21b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Brigantine (BRIG), New Jersey and Worst 20% (W20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## E-63 Worst 20% Obs (left) vs 2002gt2a (right) at BRIG1

0 100 200 300 400 500 600 700 800

20 74 107 122 137 149 152 170 176 179 185 188 191 197 209 224 230 275 278 329 341 362 _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-21c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Brigantine (BRIG), New Jersey and Worst 20% (W20%) days in 2002. 

### Worst 20% Obs (left) vs 2002gt2a (right) at BRIG1

0 100 200 300 400 500 600 700 800

20 74 107 122 137 149 152 170 176 179 185 188 191 197 209 224 230 275 278 329 341 362 _ _ _ Avg Julian Day in Worst 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-21d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Brigantine (BRIG), New Jersey and Worst 20% (W20%) days in 2002.

## E-64 Bext Response (2018g2b - 2002gt2a) at BRIG1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

20 74 107 122 137 149 152 170 176 179 185 188 191 197 209 224 230 275 278 329 341 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-21e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018- 2002) daily extinction for Brigantine (BRIG), New Jersey and Worst 20% (W20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at BRIG1 on Worst 20% Days

-250 -200 -150 -100 -50

0 50

20 74 107 122 137 149 152 170 176 179 185 188 191 197 209 224 230 275 278 329 341 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure E-21f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018- 2002) daily extinction for Brigantine (BRIG), New Jersey and Worst 20% (W20%) days in 2002.

## APPENDIX F 2018 Visibility Projections at VISTAS and Nearby Class I Areas for the Best 20 Percent Days using EPA Default Approach

## F-1 2018 VISIBILITY PROJECTS AT VIST AS AND NEARBY CLASS I AREAS FOR THE BEST 20 PERCEN T DAYS USING EPA DE FAULT APPROACH

VISTAS Class I Areas

• Figure F-1: Sipsey Wilder ness Area (SIPS), Alabama

• Figure F-2: Chassahowitzka W ildlife Refuge (CHAS), Florida

• Figure F-3: Everglades Na tional Park (EVER), Florida

• Figure F-4: St. Marks Wildli fe Refuge (SAMA), Florida

• Figure F-5: Cohutta Wild erness Area (COHU), Georgia

• Figure F-6: Okefenokee Wild life Refuge (OKEF), Georgia

• Figure F-7: Mammoth Cave Na tional Park (MACA), Kentucky

• Figure F-8: Linville Gorge Wilderness Area (LIGO), North Carolina

• Figure F-9: Shining Rock Wilder ness Area (SHRO), North Carolina

• Figure F-10: Swanquarter Wildlif e Refuge (SWAN), North Carolina

• Figure F-11: Cape Romain Wildlife Refuge (ROMA), South Carolina

• Figure F-12: Great Smoky Mountains Nati onal Park (GRSM), Te nnessee-North Carolina

• Figure F-13: James River Face Wilderness Area (JARI), Virginia

• Figure F-14: Shenandoah National Park (SHEN), Virginia

• Figure F-15: Dolly Sods Wilder ness Area (DOSO), West Virginia Nearby Class I Areas

• Figure F-16: Breton Island Wild life Refuge (BRET), Louisiana

• Figure F-17: Caney Creek Wild erness Area (CACR), Arkansas

• Figure F-18: Upper Buffalo Wilderness Area (UPBU), Arkansas

• Figure F-19: Mingo Wildlife Refuge (MING), Missouri

• Figure F-20: Hercules Glade Wilderness Area (HEGL), Missouri

• Figure F-21: Brigantine Wildlif e Refuge (BRIG), New Jersey

## F-2 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Sipsey - Best 20% Days (12 km)

15.57 15.57 15.57

14.37

5.03

0 5 10 15 20 25

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

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

### Figure F-1a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Sipsey (SIPS), Alabama and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results.



### Reasonable Progress Assessment Base G2, new IMPROVE Algorithm Sipsey - Best 20% Days (36 km)

15.57 15.57 15.57

14.15

5.03



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



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

### Figure F-1b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Sipsey (SIPS), Alabama and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-3 Best 20% Obs (left) vs 2002gt2a (right) at SIPS (12 km)

0 20 40 60 80 100 120

11 14 26 32 59 77 89 113 116 167 176 179 212 230 257 302 308 347 356 359 362 _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-1c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Sipsey (SIPS), Alabama and Best 20% (B20%) days in 2002. Best 20% Obs (left) vs 2002gt2a (right) at SIPS (36 km)

0 20 40 60 80 100 120

11 14 26 32 59 77 89 113 116 167 176 179 212 230 257 302 308 347 356 359 362 _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-1d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Sipsey (SIPS), Alabama and Best 20% (B20%) days in 2002.

## F-4 Bext Response (2018g2b - 2002gt2a) at SIPS on Best 20% Days (12 km)

-60 -50 -40 -30 -20 -10

0 10 20

11 14 26 32 59 77 89 113 116 167 176 179 212 230 257 302 308 347 356 359 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Fi 

### gure F-1e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Sipsey (SIPS), Alabama and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SIPS on Best 20% Days (36 km)

-70 -60 -50 -40 -30 -20 -10

0 10

11 14 26 32 59 77 89 113 116 167 176 179 212 230 257 302 308 347 356 359 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-1f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Sipsey (SIPS), Alabama and Best 20% (B20%) days in 2002.

## F-5 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Chassahowitzka - Best 20% Days (12 km)

15.51 15.51 15.51

13.50

5.91

0 5 10 15 20 25

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

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

### Figure F-2a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Chassahowitzka (CHAS), Florida and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results.

Reasonable Progress Assessment Base G2, new IMPROVE Algorithm Chassahowitzka - Best 20% Days (36 km)

15.51 15.51 15.51

13.19

5.91



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



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

### Figure F-2b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Chassahowitzka (CHAS), Florida and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results

## F-6 Best 20% Obs (left) vs 2002gt2a (right) at CHAS (12 km)

0 10 20 30 40 50 60 70 80 90

38 68 71 104 146 161 164 170 173 176 182 191 203 224 227 239 242 248 266 320 344 347 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-2c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Chassahowitzka Wildlife Re fuge (CHAS), Florida and Best 20% (B20%) days in 2002. Best 20% Obs (left) vs 2002gt2a (right) at CHAS (36 km)

0 10 20 30 40 50 60 70 80 90

38 68 71 104 146 161 164 170 173 176 182 191 203 224 227 239 242 248 266 320 344 347 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-2d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Chassahowitzka Wildlife Re fuge (CHAS), Florida and Best 20% (B20%) days in 2002.

## F-7 Bext Response (2018g2b - 2002gt2a) at CHAS on Best 20% Days (12 km)

-40 -35 -30 -25 -20 -15 -10 -5 0 5

38 68 71 104 146 161 164 170 173 176 182 191 203 224 227 239 242 248 266 320 344 347 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-2e. Differences in modeled 2002 and 2018 Base G2 CMAQ 12 km results (2018- 2002) daily extinction for Chassahowitzka Wildlife Refuge (CHAS), Florida and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at CHAS on Best 20% Days (36 km)

-40 -35 -30 -25 -20 -15 -10 -5 0 5

38 68 71 104 146 161 164 170 173 176 182 191 203 224 227 239 242 248 266 320 344 347 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-2f. Differences in modeled 2002 and 2018 Base G2 CMAQ 36 km results (2018- 2002) daily extinction for Chassahowitzka Wildlife Refuge (CHAS), Florida and Best 20% (B20%) days in 2002

.

## F-8 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Everglades - Best 20% Days (12 km)

11.69 11.69 11.69 11.44

5.21

0 5 10 15 20

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

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

### Figure F-3a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Everglades (EVER), Florida and Best 20% (B20%) days us ing 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Everglades - Best 20% Days (36 km)

11.69 11.69 11.69 14.44

5.21



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



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

### Figure F-3b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Everglades (EVER), Florida and Best 20% (B20%) days usi ng 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-9 Best 20% Obs (left) vs 2002 gt2a (right) at EVER (12 km)

0 5 10 15 20 25

23 29 32 71 80 104 134 137 140 164 176 191 206 212 242 245 248 251 254 284 287 296 299 302 _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-3c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Everglades (EVER), Florida and Best 20% (B20%) days in 2002. Best 20% Obs (left) vs 2002 gt2a (right) at EVER (36 km)

0 5 10 15 20 25

23 29 32 71 80 104 134 137 140 164 176 191 206 212 242 245 248 251 254 284 287 296 299 302 _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-3d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Everglades (EVER), Florida and Best 20% (B20%) days in 2002.

## F-10 Bext Response (2018g2b - 2002gt2a) at EVER on Best 20% Days (12 km)

-8 -7 -6 -5 -4 -3 -2 -1 0 1

23 29 32 71 80 104 134 137 140 164 176 191 206 212 242 245 248 251 254 284 287 296 299 302 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-3e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Everglades (EVER), Florida and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at EVER1 on Best 20% Days

-8 -7 -6 -5 -4 -3 -2 -1 0 1

23 29 32 71 80 104 134 137 140 164 176 191 206 212 242 245 248 251 254 284 287 296 299 302 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-3f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Everglades (EVER), Florida and Best 20% (B20%) days in 2002.

## F-11 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Saint Marks - Best 20% Days (12 km)

14.37 14.37 14.37

12.67

5.39

0 5 10 15 20

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

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

### Figure F-4a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for St. Marks (SAMA), Florida and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Saint Marks - Best 20% Days (36 km)

14.37 14.37 14.37

12.58

5.39



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



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

### Figure F-4b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for St. Marks (SAMA), Florida and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-12 Best 20% Obs (left) vs 2002gt2a (right) at SAMA (12 km)

0 10 20 30 40 50 60 70 80 90

11 14 20 32 38 68 80 158 161 173 176 179 194 206 209 218 224 239 266 302 344 356 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-4c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for St. Marks (SAMA), Florida and Best 20% (B20%) days in 2002. Best 20% Obs (left) vs 2002gt2a (right) at SAMA (36 km)

0 10 20 30 40 50 60 70 80 90

11 14 20 32 38 68 80 158 161 173 176 179 194 206 209 218 224 239 266 302 344 356 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-4d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for St. Marks (SAMA), Florida and Best 20% (B20%) days in 2002.

## F-13 Bext Response (2018g2b - 2002gt2a) at SAMA on Best 20% Days (12 km)

-35 -30 -25 -20 -15 -10 -5 0 5

11 14 20 32 38 68 80 158 161 173 176 179 194 206 209 218 224 239 266 302 344 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-4e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for St. Marks (SAMA), Florida and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SAMA on Best 20% Days (36 km)

-35 -30 -25 -20 -15 -10 -5 0 5

11 14 20 32 38 68 80 158 161 173 176 179 194 206 209 218 224 239 266 302 344 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-4f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for St. Marks (SAMA), Florida and Best 20% (B20%) days in 2002.

## F-14 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Cohutta - Best 20% Days (12 km)

13.77 13.77 13.77

11.74

4.32

0 5 10 15 20

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

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

### Figure F-5a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cohutta (COHU), Georgia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Cohutta - Best 20% Days (36 km)

13.77 13.77 13.77

11.96

4.32



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



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

### Figure F-5b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cohutta (COHU), Georgia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-15 Best 20% Obs (left) vs 2002g t2a (right) at COHU (12 km)

0 10 20 30 40 50 60 70 80

23 26 32 38 44 62 77 89 113 116 119 173 194 257 269 308 320 341 347 356 _ _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-5c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Cohutta (COHU), Georgia and Best 20% (B20%) days in 2002. Best 20% Obs (left) vs 2002g t2a (right) at COHU (36 km)

0 10 20 30 40 50 60 70 80

23 26 32 38 44 62 77 89 113 116 119 173 194 257 269 308 320 341 347 356 _ _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-5d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Cohutta (COHU), Georgia and Best 20% (B20%) days in 2002.

## F-16 Bext Response (2018g2b - 2002gt2a) at COHU on Best 20% Days (12 km)

-40 -35 -30 -25 -20 -15 -10 -5 0 5 10

23 26 32 38 44 62 77 89 113 116 119 173 194 257 269 308 320 341 347 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-5e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Cohutta (COHU), Georgia and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at COHU on Best 20% Days (36 km)

-40 -35 -30 -25 -20 -15 -10 -5 0 5 10

23 26 32 38 44 62 77 89 113 116 119 173 194 257 269 308 320 341 347 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-5f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Cohutta (COHU), Georgia and Best 20% (B20%) days in 2002.

## F-17 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Okefenokee - Best 20% Days (12 km)

15.23 15.23 15.23

13.83

5.31

0 5 10 15 20

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

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

### Figure F-6a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Okefenokee (OKEF), Georgia and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Okefenokee - Best 20% Days (36 km)

15.23 15.23 15.23

13.69

5.31



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-6a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Okefenokee (OKEF), Georgia and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results.

## F-18 Best 20% Obs (left) vs 2002gt2a (right) at OKEF (12 km)

0 10 20 30 40 50 60 70

11 20 38 59 62 104 170 173 176 179 191 239 242 257 266 275 284 335 344 347 356 359 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-6c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Okefenokee (OKEF), Geor gia and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at OKEF (36 km)

0 10 20 30 40 50 60 70

11 20 38 59 62 104 170 173 176 179 191 239 242 257 266 275 284 335 344 347 356 359 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-6d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Okefenokee (OKEF), Geor gia and Best 20% (B20%) days in 2002.

## F-19 Bext Response (2018g2b - 2002gt2a) at OKEF on Best 20% Days (12 km)

-25 -20 -15 -10 -5 0 5

11 20 38 59 62 104 170 173 176 179 191 239 242 257 266 275 284 335 344 347 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-6e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Okefenokee (OKEF), Geor gia and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at OKEF on Best 20% Days (36 km)

-25 -20 -15 -10 -5 0 5

11 20 38 59 62 104 170 173 176 179 191 239 242 257 266 275 284 335 344 347 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-6f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Okefenokee (OKEF), Geor gia and Best 20% (B20%) days in 2002.

## F-20 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Mammoth Cave - Best 20% Days (12 km)

16.51 16.51 16.51
15.57

4.99

0 5 10 15 20 25

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

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

### Figure F-7a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mammoth Cave (MACA), Kentucky and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Mammoth Cave - Best 20% Days (36 km)

16.51 16.51 16.51

15.33

4.99



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-7b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mammoth Cave (MACA), Kentucky and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-21 Best 20% Obs (left) vs 2002gt2a (right) at MACA (12 km)

0 20 40 60 80 100 120 140

14 23 32 35 44 62 68 83 89 113 116 227 266 269 278 281 287 302 308 323 338 347 356 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-7c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Mammoth Cave (MACA), Kent ucky and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at MACA (36 km)

0 20 40 60 80 100 120 140

14 23 32 35 44 62 68 83 89 113 116 227 266 269 278 281 287 302 308 323 338 347 356 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-7d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Mammoth Cave (MACA), Kent ucky and Best 20% (B20%) days in 2002.

## F-22 Bext Response (2018g2b - 2002gt2a) at MACA on Best 20% Days (12 km)

-40 -30 -20 -10

0 10 20

14 23 32 35 44 62 68 83 89 113 116 227 266 269 278 281 287 302 308 323 338 347 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-7d. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Mammoth Cave (MACA), Kent ucky and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at MACA on Best 20% Days (36 km)

-40 -30 -20 -10

0 10 20

14 23 32 35 44 62 68 83 89 113 116 227 266 269 278 281 287 302 308 323 338 347 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-7e. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Mammoth Cave (MACA), Kent ucky and Best 20% (B20%) days in 2002.

## F-23 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Linville Gorge - Best 20% Days (12 km)

11.11 11.11 11.11

9.64

4.08

0 5 10 15 20

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

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

### Figure F-8a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Linville Gorge (LIGO), North Carolina and Best 20% (B20%) days using 20 02/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Linville Gorge - Best 20% Days (36 km)

11.11 11.11 11.11

9.80

4.08



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-8b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Linville Gorge (LIGO), North Carolina and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## F-24 Best 20% Obs (left) vs 2002gt2a (right) at LIGO (12 km)

0 10 20 30 40 50 60 70

5 8 11 23 26 38 62 77 89 104 116 119 302 308 320 326 341 347 356 359 362 _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-8c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Linville Gorge (LIGO), North Carolina and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at LIGO (36 km)

0 10 20 30 40 50 60 70

5 8 11 23 26 38 62 77 89 104 116 119 302 308 320 326 341 347 356 359 362 _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-8d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Linville Gorge (LIGO), Nort h Carolina and Best 20% (B20%) days in 2002.

## F-25 Bext Response (2018g2b - 2002gt2a) at LIGO on Best 20% Days (12 km)

-20 -15 -10 -5 0 5 10

5 8 11 23 26 38 62 77 89 104 116 119 302 308 320 326 341 347 356 359 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-8e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Linville Gorge (LIGO), North Carolina and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at LIGO on Best 20% Days (36 km)

-20 -15 -10 -5 0 5 10

5 8 11 23 26 38 62 77 89 104 116 119 302 308 320 326 341 347 356 359 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-8f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Linville Gorge (LIGO), Nort h Carolina and Best 20% (B20%) days in 2002.

## F-26 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Shining Rock - Best 20% Days (12 km)

8.21 8.21 8.21

6.91

2.51

0 5 10 15 20

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

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

### Figure F-9a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shining Rock (SHRO), North Carolina and Best 20% (B20%) days using 20 02/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Shining Rock - Best 20% Days (36 km)

8.21 8.21 8.21

6.92

2.51



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-9b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shining Rock (SHRO), North Carolina and Best 20% (B20%) days using 20 02/2018 Base G2 CMAQ 36 km modeling results.

## F-27 Best 20% Obs (left) vs 2002gt2 a (right) at SHRO (12 km)

0 10 20 30 40 50 60 70 80

5 8 11 26 38 50 68 71 86 89 104 257 269 299 302 308 320 326 341 344 347 353 359 362 _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-9c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Shining Rock (SHRO), North Ca rolina and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2 a (right) at SHRO (36 km)

0 10 20 30 40 50 60 70 80

5 8 11 26 38 50 68 71 86 89 104 257 269 299 302 308 320 326 341 344 347 353 359 362 _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-9d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Shining Rock (SHRO), North Carolina and Best 20% (B20%) days in 2002.

## F-28 Bext Response (2018g2b - 2002gt2a) at SHRO on Best 20% Days (12 km)

-35 -30 -25 -20 -15 -10 -5 0 5 10 15

5 8 11 26 38 50 68 71 86 89 104 257 269 299 302 308 320 326 341 344 347 353 359 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-9e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Shining Rock (SHRO), North Ca rolina and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SHRO on Best 20% Days (36 km)

-35 -30 -25 -20 -15 -10 -5 0 5 10 15

5 8 11 26 38 50 68 71 86 89 104 257 269 299 302 308 320 326 341 344 347 353 359 362 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-9f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Shining Rock (SHRO), North Carolina and Best 20% (B20%) days in 2002.

## F-29 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Swanquarter - Best 20% Days (12 km)

12.02 12.02 12.02

10.96

5.46

0 5 10 15 20

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

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

### Figure F-10a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Swanquarter (SWAN), North Carolina and Best 20% (B20%) days using 20 02/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Swanquarter - Best 20% Days (36 km)

12.02 12.02 12.02

10.88

5.46



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-10b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Swanquarter (SWAN), North Carolina and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## F-30 Best 20% Obs (left) vs 2002 gt2a (right) at SWAN (12 km)

0 10 20 30 40 50 60 70 80

14 26 68 104 125 173 176 194 221 227 242 251 263 269 284 290 314 320 332 335 344 353 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-10c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Swanquarter (SWAN), North Carolina and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002 gt2a (right) at SWAN (36 km)

0 10 20 30 40 50 60 70 80

14 26 68 104 125 173 176 194 221 227 242 251 263 269 284 290 314 320 332 335 344 353 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-10d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Swanquarter (SWAN), North Carolina and Best 20% (B20%) days in 2002.

## F-31 Bext Response (2018g2b - 2002gt2a) at SWAN on Best 20% Days (12 km)

-25 -20 -15 -10 -5 0 5

14 26 68 104 125 173 176 194 221 227 242 251 263 269 284 290 314 320 332 335 344 353 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-10e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Swanquarter (SWAN), North Carolina and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SWAN on Best 20% Days (36 km)

-25 -20 -15 -10 -5 0 5

14 26 68 104 125 173 176 194 221 227 242 251 263 269 284 290 314 320 332 335 344 353 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-10f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Swanquarter (SWAN), North Carolina and Best 20% (B20%) days in 2002.

## F-32 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Cape Romain - Best 20% Days (12 km)

14.29 14.29 14.29

12.74

5.92

0 5 10 15 20

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

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

### Figure F-11a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cape Romain (ROMA), South Carolina and Best 20% (B20%) days using 20 02/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Cape Romain - Best 20% Days (36 km)

14.29 14.29 14.29
12.82

5.92



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-11b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Cape Romain (ROMA), South Carolina and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-33 Best 20% Obs (left) vs 2002 gt2a (right) at ROMA (12 km)

0 10 20 30 40 50 60 70 80 90

14 23 62 65 68 92 104 107 125 161 170 173 176 191 227 242 245 248 263 266 269 284 353 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-11c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Cape Romain (ROMA), South Carolina and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002 gt2a (right) at ROMA (36 km)

0 10 20 30 40 50 60 70 80 90

14 23 62 65 68 92 104 107 125 161 170 173 176 191 227 242 245 248 263 266 269 284 353 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-11d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Cape Romain (ROMA), South Carolina and Best 20% (B20%) days in 2002.

## F-34 Bext Response (2018g2b - 2002gt2a) at ROMA on Best 20% Days (12 km)

-30 -25 -20 -15 -10 -5 0 5

14 23 62 65 68 92 104 107 125 161 170 173 176 191 227 242 245 248 263 266 269 284 353 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-11e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Cape Romain (ROMA), South Carolina and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at ROMA on Best 20% Days (36 km)

-30 -25 -20 -15 -10 -5 0 5 10

14 23 62 65 68 92 104 107 125 161 170 173 176 191 227 242 245 248 263 266 269 284 353 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-11f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Cape Romain (ROMA), South Carolina and Best 20% (B20%) days in 2002.

## F-35 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Great Smoky Mountains - Best 20% Days (12 km)

13.58 13.58 13.58

12.15

4.54

0 5 10 15 20 25

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

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

### Figure F-12a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Great Smoky Mountains (GRSM), Tennessee-North Carolina and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Great Smoky Mountains - Best 20% Days (36 km)

13.58 13.58 13.58
12.02

4.54



### 0 5 10 15 20 25 30 35

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-12b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Great Smoky Mountains (GRSM), Tennessee-North Carolina and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## F-36 Best 20% Obs (left) vs 2002gt 2a (right) at GRSM (12 km)

0 20 40 60 80 100 120

8 11 14 23 32 38 50 59 62 68 89 116 194 257 269 299 302 308 320 326 341 347 356 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-12c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Great Smoky Mountains (GRSM), Tenn essee-North Carolina and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt 2a (right) at GRSM (36 km)

0 20 40 60 80 100 120

8 11 14 23 32 38 50 59 62 68 89 116 194 257 269 299 302 308 320 326 341 347 356 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-12d. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Great Smoky Mountains (GRSM), Tenn essee-North Carolina and Best 20% (B20%) days in 2002.

## F-37 Bext Response (2018g2b - 2002gt2a) at GRSM on Best 20% Days (12 km)

-45 -40 -35 -30 -25 -20 -15 -10 -5 0 5 10 15

8 11 14 23 32 38 50 59 62 68 89 116 194 257 269 299 302 308 320 326 341 347 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-12e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Great Smoky Mountains (GRSM), Tenn essee-North Carolina and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at GRSM on Best 20% Days (36 km)

-45 -40 -35 -30 -25 -20 -15 -10 -5 0 5 10 15

8 11 14 23 32 38 50 59 62 68 89 116 194 257 269 299 302 308 320 326 341 347 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-12f. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Great Smoky Mountains (GRSM), Tenn essee-North Carolina and Best 20% (B20%) days in 2002.

## F-38 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm James River Face - Best 20% Days (12 km)

14.21 14.21 14.21

12.48

4.38

0 5 10 15 20 25

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

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

### Figure F-13a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for James River Face (JARI), Virginia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm James River Face - Best 20% Days (36 km)

14.21 14.21 14.21

12.43

4.38



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-13b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for James River Face (JARI), Virginia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-39 Best 20% Obs (left) vs 2002gt2a (right) at JARI (12 km)

0 10 20 30 40 50 60 70 80 90

8 11 23 26 35 44 59 68 77 101 104 113 116 134 158 245 299 302 326 332 335 356 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-13c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for James River Face (JARI), Virginia and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at JARI (36 km)

0 10 20 30 40 50 60 70 80 90

8 11 23 26 35 44 59 68 77 101 104 113 116 134 158 245 299 302 326 332 335 356 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-13d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for James River Face (JARI), Virginia and Best 20% (B20%) days in 2002.

## F-40 Bext Response (2018g2b - 2002gt2a) at JARI on Best 20% Days (12 km)

-40 -35 -30 -25 -20 -15 -10 -5 0 5 10

8 11 23 26 35 44 59 68 77 101 104 113 116 134 158 245 299 302 326 332 335 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-13e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for James River Face (JARI), Virginia and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at JARI on Best 20% Days (36 km)

-40 -35 -30 -25 -20 -15 -10 -5 0 5 10

8 11 23 26 35 44 59 68 77 101 104 113 116 134 158 245 299 302 326 332 335 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-13f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for James River Face (JARI), Virginia and Best 20% (B20%) days in 2002.

## F-41 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Shenandoah - Best 20% Days (12 km)

10.93 10.93 10.93

8.79

3.14

0 5 10 15 20

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

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

### Figure F-14a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shenandoah (SHEN), Virginia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Shenandoah - Best 20% Days (36 km)

10.93 10.93 10.93

8.85

3.14



### 0 5 10 15 20

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-14b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Shenandoah (SHEN), Virginia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results..

## F-42 Best 20% Obs (left) vs 2002gt2a (right) at SHEN (12 km)

0 20 40 60 80 100 120 140 160 180

5 14 23 26 38 50 62 68 77 158 206 221 245 269 284 320 335 338 341 344 347 356 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-14c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Shenandoah (SHEN), Virginia and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at SHEN (36 km)

0 20 40 60 80 100 120 140 160 180

5 14 23 26 38 50 62 68 77 158 206 221 245 269 284 320 335 338 341 344 347 356 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-14d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Shenandoah (SHEN), Virginia and Best 20% (B20%) days in 2002.

## F-43 Bext Response (2018g2b - 2002gt2a) at SHEN on Best 20% Days (12 km)

-120 -100 -80 -60 -40 -20

0 20

5 14 23 26 38 50 62 68 77 158 206 221 245 269 284 320 335 338 341 344 347 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-14e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Shenandoah (SHEN), Virginia and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at SHEN on Best 20% Days (36 km)

-120 -100 -80 -60 -40 -20

0 20

5 14 23 26 38 50 62 68 77 158 206 221 245 269 284 320 335 338 341 344 347 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-14f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Shenandoah (SHEN), Virginia and Best 20% (B20%) days in 2002.

## F-44 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Dolly Sods - Best 20% Days (12 km)

12.28 12.28 12.28

10.79

3.64

0 5 10 15 20 25

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

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

### Figure F-15a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Dolly Sods (DOSO), West Virginia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Dolly Sods - Best 20% Days (36 km)

12.28 12.28 12.28

10.78

3.64



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-15b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Dolly Sods (DOSO), West Virginia and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-45 Best 20% Obs (left) vs 2002gt2a (right) at DOSO (12 km)

0 10 20 30 40 50 60 70 80

5 14 23 26 50 68 89 104 119 158 284 293 299 302 320 326 338 341 347 356 359 _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-15c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Dolly Sods (DOSO), West Virg inia and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at DOSO (36 km)

0 10 20 30 40 50 60 70 80

5 14 23 26 50 68 89 104 119 158 284 293 299 302 320 326 338 341 347 356 359 _ _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-15d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Dolly Sods (DOSO), West Virginia and Best 20% (B20%) days in 2002.

## F-46 Bext Response (2018g2b - 2002gt2a) at DOSO on Best 20% Days (12 km)

-25 -20 -15 -10 -5 0 5 10

5 14 23 26 50 68 89 104 119 158 284 293 299 302 320 326 338 341 347 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-15e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Dolly Sods (DOSO), West Virg inia and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at DOSO on Best 20% Days (36 km)

-25 -20 -15 -10 -5 0 5 10

5 14 23 26 50 68 89 104 119 158 284 293 299 302 320 326 338 341 347 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-15f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Dolly Sods (DOSO), West Virginia and Best 20% (B20%) days in 2002.

## F-47 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Breton - Best 20% Days (12 km)

14.04 14.04 14.04 13.54

5.33

0 5 10 15 20 25

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

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

### Figure F-16a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Breton Island (BRET), Louisiana and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Breton - Best 20% Days (36 km)

14.04 14.04 14.04 13.50

5.33



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-16b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Breton Island (BRET), Louisiana and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-48 Best 20% Obs (left) vs 2002gt2a (right) at BRET (12 km)

0 5 10 15 20 25 30 35 40

8 14 20 32 38 68 80 101 149 158 170 176 191 209 227 233 236 245 299 302 335 356 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-16c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Breton Island (BRET), Louisiana and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at BRET (36 km)

0 5 10 15 20 25 30 35 40

8 14 20 32 38 68 80 101 149 158 170 176 191 209 227 233 236 245 299 302 335 356 359 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-16d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Breton Island (BRET), Louisiana and Best 20% (B20%) days in 2002.

## F-49 Bext Response (2018g2b - 2002gt2a) at BRET on Best 20% Days (12 km)

-10 -8 -6 -4 -2 0 2 4 6

8 14 20 32 38 68 80 101 149 158 170 176 191 209 227 233 236 245 299 302 335 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-16e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Breton Island (BRET), Louisiana and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at BRET on Best 20% Days (36 km)

-10 -8 -6 -4 -2 0 2 4 6

8 14 20 32 38 68 80 101 149 158 170 176 191 209 227 233 236 245 299 302 335 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-16f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Breton Island (BRET), Louisiana and Best 20% (B20%) days in 2002.

## F-50 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Caney Creek - Best 20% Days (12 km)

11.24 11.24 11.24
10.15

4.23

0 5 10 15 20 25

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

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

### Figure F-17a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Caney Creek (CACR), Arkansas and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Caney Creek - Best 20% Days (36 km)

11.24 11.24 11.24
10.27

4.23



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-17b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Caney Creek (CACR), Arkansas and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results.

## F-51 Best 20% Obs (left) vs 2002g t2a (right) at CACR (12 km)

0 20 40 60 80 100 120

11 14 26 89 98 116 197 266 278 284 287 293 299 302 311 323 329 335 338 353 356 359 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-17c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Caney Creek (CACR), Arkansas and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002g t2a (right) at CACR (36 km)

0 20 40 60 80 100 120

11 14 26 89 98 116 197 266 278 284 287 293 299 302 311 323 329 335 338 353 356 359 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-17d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Caney Creek (CACR), Arkansas and Best 20% (B20%) days in 2002.

## F-52 Bext Response (20 18g2b - 2002gt2a) at CACR on Best 20% Days (12 km)

-30 -25 -20 -15 -10 -5 0 5

11 14 26 89 98 116 197 266 278 284 287 293 299 302 311 323 329 335 338 353 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-17e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Caney Creek (CACR), Arkansas and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at CACR on Best 20% Days (36 km)

-30 -25 -20 -15 -10 -5 0 5

11 14 26 89 98 116 197 266 278 284 287 293 299 302 311 323 329 335 338 353 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-17f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Caney Creek (CACR), Arkansas and Best 20% (B20%) days in 2002.

## F-53 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Upper Buffalo - Best 20% Days (12 km)

11.71 11.71 11.71
10.61

4.13

0 5 10 15 20 25

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

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

### Figure F-18a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Upper Buffalo (UPBU), Arkansas and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Upper Buffalo - Best 20% Days (36 km)

11.71 11.71 11.71
10.66

4.13



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-18b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Upper Buffalo (UPBU), Arkansas and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results.

## F-54 Best 20% Obs (left) vs 2002gt2a (right) at UPBU (12 km)

0 10 20 30 40 50 60 70 80

14 26 47 68 89 98 116 119 164 167 176 227 266 278 281 287 290 302 311 323 335 353 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-18c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Upper Buffalo (UPBU), Arkans as and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at UPBU (36 km)

0 10 20 30 40 50 60 70 80

14 26 47 68 89 98 116 119 164 167 176 227 266 278 281 287 290 302 311 323 335 353 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-18d. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Upper Buffalo (UPBU), Ark ansas and Best 20% (B20%) days in 2002

## F-55 Bext Response (2018g2b - 2002gt2a) at UPBU on Best 20% Days (12 km)

-14 -12 -10 -8 -6 -4 -2 0 2 4

14 26 47 68 89 98 116 119 164 167 176 227 266 278 281 287 290 302 311 323 335 353 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-18e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Upper Buffalo (UPBU), Arkans as and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at UPBU on Best 20% Days (36 km)

-14 -12 -10 -8 -6 -4 -2 0 2 4

14 26 47 68 89 98 116 119 164 167 176 227 266 278 281 287 290 302 311 323 335 353 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-18f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Upper Buffalo (UPBU), Ark ansas and Best 20% (B20%) days in 2002.

## F-56 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Mingo - Best 20% Days (12 km)

14.41 14.41 14.41
13.50

5.35

0 5 10 15 20 25

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

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

### Figure F-19a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mingo (MING), Missouri and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Mingo - Best 20% Days (36 km)

14.41 14.41 14.41
13.49

5.35



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-19b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Mingo (MING), Missouri and Best 20% (B20%) days using 2002/ 2018 Base G2 CMAQ 36 km modeling results..

## F-57 Best 20% Obs (left) vs 2002gt2a (right) at MING (12 km)

0 20 40 60 80 100 120 140 160 180 200

14 32 44 62 116 134 137 140 164 167 176 200 227 263 266 278 281 290 302 308 353 356 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-19c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Mingo (MING), Missouri and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt2a (right) at MING (36 km)

0 20 40 60 80 100 120 140 160 180 200

14 32 44 62 116 134 137 140 164 167 176 200 227 263 266 278 281 290 302 308 353 356 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-19d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Mingo (MING), Missouri and Best 20% (B20%) days in 2002.

## F-58 Bext Response (2018g2b - 2002gt2a) at MING on Best 20% Days (12 km)

-25 -20 -15 -10 -5 0 5 10

14 32 44 62 116 134 137 140 164 167 176 200 227 263 266 278 281 290 302 308 353 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-19e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Mingo (MING), Missouri and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at MING on Best 20% Days (36 km)

-25 -20 -15 -10 -5 0 5 10

14 32 44 62 116 134 137 140 164 167 176 200 227 263 266 278 281 290 302 308 353 356 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-19f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Mingo (MING), Missouri and Best 20% (B20%) days in 2002.

## F-59 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Hercules - Glade - Best 20% Days (12 km)

12.84 12.84 12.84
11.97

4.67

0 5 10 15 20 25

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

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


### Figure F-20a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Hercules Glade (HEGL), Missouri and Best 20% (B20%) days using 2 002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Hercules - Glade - Best 20% Days (36 km)

12.84 12.84 12.84
11.96

4.67



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



### Baseline Natural Condition (20% Best Days) Observation Method 1 Prediction Figure F-20b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Hercules Glade (HEGL), Missouri and Best 20% (B20%) days using 2 002/2018 Base G2 CMAQ 36 km modeling results.

## F-60 Best 20% Obs (left) vs 2002gt 2a (right) at HEGL (12 km)

0 20 40 60 80 100 120 140 160

14 26 44 68 71 89 113 116 119 134 137 227 266 278 281 287 290 302 308 311 317 335 353 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-20c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Hercules Glade (HEGL), Miss ouri and Best 20% (B20%) days in 2002. 

### Best 20% Obs (left) vs 2002gt 2a (right) at HEGL (36 km)

0 20 40 60 80 100 120 140 160

14 26 44 68 71 89 113 116 119 134 137 227 266 278 281 287 290 302 308 311 317 335 353 _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-20d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Hercules Glade (HEGL), Missouri and Best 20% (B20%) days in 2002.

## F-61 Bext Response (2018g2b - 2002gt2a) at HEGL on Best 20% Days (12 km)

-20 -15 -10 -5 0 5

14 26 44 68 71 89 113 116 119 134 137 227 266 278 281 287 290 302 308 311 317 335 353 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-20e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018-2002) daily extinction for Hercules Glade (HEGL), Miss ouri and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at HEGL on Best 20% Days (36 km)

-20 -15 -10 -5 0 5

14 26 44 68 71 89 113 116 119 134 137 227 266 278 281 287 290 302 308 311 317 335 353 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-20f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018-2002) daily extinction for Hercules Glade (HEGL), Missouri and Best 20% (B20%) days in 2002.

## F-62 Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Brigantine - Best 20% Days (12 km)

14.33 14.33 14.33
13.24

5.45

0 5 10 15 20 25

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

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

### Figure F-21a. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Brigantine (BRIG), New Jersey and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 12 km modeling results. Reasonable Progress Assessment B ase G2, new IMPROVE Algorithm Brigantine - Best 20% Days (36 km)

14.33 14.33 14.33

13.09

5.45



### 0 5 10 15 20 25

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

### YearHaziness Index (Deciviews)



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

### Figure F-21b. 2018 Visibility Projections and 2018 URP Glidepath in deciview for Brigantine (BRIG), New Jersey and Best 20% (B20%) days using 2002/2018 Base G2 CMAQ 36 km modeling results.

## F-63 Best 20% Obs (left) vs 2002gt2a (right) at BRIG (12 km)

0 20 40 60 80 100 120 140

32 68 77 113 119 125 158 194 206 221 251 263 269 281 284 287 302 317 332 335 356 359 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-21c. Comparison of observed (left) and 2002 Base G2 CMAQ 12 km modeled (right) daily extinction for Brigantine (BRIG), New Jersey and Best 20% (B20%) days in 2002. Best 20% Obs (left) vs 2002gt2a (right) at BRIG (36 km)

0 20 40 60 80 100 120 140

32 68 77 113 119 125 158 194 206 221 251 263 269 281 284 287 302 317 332 335 356 359 _ _ _ Avg Julian Day in Best 20% groupbEXT (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-21d. Comparison of observed (left) and 2002 Base G2 CMAQ 36 km modeled (right) daily extinction for Brigantine (BRIG), New Jersey and Best 20% (B20%) days in 2002.

## F-64 Bext Response (2018g2b - 2002gt2a) at BRIG on Best 20% Days (12 km)

-30 -25 -20 -15 -10 -5 0 5 10

32 68 77 113 119 125 158 194 206 221 251 263 269 281 284 287 302 317 332 335 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-21e. Differences in modeled 2002 and 2018 Base G CMAQ 12 km results (2018- 2002) daily extinction for Brigantine (BRIG), New Jersey and Best 20% (B20%) days in 2002.
Bext Response (2018g2a - 2002gt2a) at BRIG on Best 20% Days (36 km)

-30 -25 -20 -15 -10 -5 0 5 10

32 68 77 113 119 125 158 194 206 221 251 263 269 281 284 287 302 317 332 335 356 359 Avg Julian DayDelta Bext (1/Mm) bCM bSOIL bEC bOC bNO3 bSO4



### Figure F-21f. Differences in modeled 2002 and 2018 Base G CMAQ 36 km results (2018- 2002) daily extinction for Brigantine (BRIG), New Jersey and Best 20% (B20%) days in 2002.

## APPENDIX G
Evaluation of the 2002 GEOS-C HEM Global Chemistry Model Used for Boundary Conditions in the VISTAS Regional Haze Modeling

## G-2 

# Application of GEOS CHEM for 2002 Boundary Conditions for CMAQ Modeling of the VISTAS Region
Ivar Tombach

5 October 2007

CMAQ modeling of regional haze in the VISTAS region for 2002 and 2018 was carried out on a grid of 12x12 km cells that covers the VISTAS states (AL, GA, FL, MS, SC, NC, TN, KY, VA, WV) and states adjacent to them. This grid is nested within a larger national CMAQ modeling grid of 36x36 km grid cells that covers the con tinental United States, portions of Canada and Mexico, and portions of the Atlantic and Pacific Oceans along the east and west coasts. Transport of pollution from the national domain in to the VISTAS modeli ng domain is reflected in hourly-varying boundary conditions around the VI STAS domain, which are derived from the CMAQ simulations in the 36 km national domain. The national domain incorporates emissions from northern Mexico and southern Canada, and th erefore explicitly calc ulates the effects of these international emissions on concentrations at the boundaries of the VISTAS modeling domain.
Effects of emissions from more distant source s that are outside of the 36 km national domain were estimated using outputs from a global air pollution model. The Big Bend Regional Aerosol and Visibility Observational (BRAVO) study had found that the performa nce of national-scale modeling was enhanced by using monthly averages of outputs from a global air pollution model, GOCART, to generate SO 2 

## and sulfate boundary conditions for its 36 km national modeling grid (Schichtel, et al., 2005), instead of using the EPA default concentrations that are normally used. VISTAS elected to use a similar approach, us ing the outputs of the GEOS-CHEM global air pollution model, which also contains a detailed representation of ozone-NO x 

## -VOC-PM chemistry. Under EPRI sponsorship, Harvard University ha d already used the GEOS-CHEM model, with 2 ° x2.5 ° horizontal resolution, to estimate natura l conditions and transboundary influences on elemental and organic carbon aeroso ls in the United States in 1998 (Park et al., 2003). After some emission inventory and model improvements, similar information was developed for sulfate and nitrate aerosols in 2001 (Park et al., 2004). Under contract to VISTAS (which was acting on behalf of all the RPOs), Harvard then simulated global air pollution for the year 2002 (the VISTAS modeling year) with 4 ° x5 ° horizontal resolution and 3-hour temporal resolution (Jacob, 2005). The coarser grid scale was considered sufficient to provide boundary conditions outside of North America, largely over the oceans. Although the VISTAS simulation was generally si milar to the 2001 EPRI simulation mentioned above, the VISTAS modeling incorporated the fo llowing substantive changes in addition to the change in grid scale: (1) use of U.S. anthropogenic emissions from the EPA NEI 1999 inventory, except for ammonia; (2) use of forest fire info rmation specific to 2002; (3) inclusion of the secondary organic aerosol (SOA) formation m echanism from Chung and Seinfeld (2002); and (4) inclusion of prototype soil dust and sea sa lt simulations. An additional model improvement, which has since been implemented in the standa rd version of GEOS-CHEM, was the application of surface emissions and dry deposition to the en tire mixed layer column diagnosed by GEOS

## G-3 (the Global Earth Observation System of NASA) rather than to just the surface layer of the model. Details of the emissions, meteorology, model configuration, an d model performance evaluation for the VISTAS simulations are de scribed in the report to VISTAS (Jacob, 2005). For North America, the VISTAS GEOS-CHEM m odeling used monthly-av erage emissions, so the model results do not reflect diurnal or weekda y-weekend variability in emissions, and also diminish the impacts of episodic emissions, such as the July 2002 wildfire in Ontario, Canada. The Mexican emissions were from the inve ntory of the BRAVO Study, while Canadian emissions for the year 2000 were used. Emissions from Caribbean islands were not included, which could impact model estimates at the Everglades. The surface meteorological data inputs to GEOS-CHEM had 3-hr temporal resolution and the upper air meteorological inputs had 6-hr resolution, with a horizontal resolution of 1 ° x1 ° or better and 48 layers vertically. The output of the GEOS-CHEM mode ling, as delivered to VISTAS, contained concentrations of all visibility-related components of particulate matte r with 3-hr tempor al resolution and 4 ° x5 ° horizontal resolution over multiple layers of the atmosphere. Even though the coarse spatial resolution degr aded the performance of the model over North America, relative to results from prior m odeling for other years using finer grids, the concentrations simulated by GEOS-CHEM maintain ed the synoptic-scale structure and did not have a continental-scale bias. At a finer scale, the concentrations simulated by GEOS-CHEM for the surface layer in 2002 were generally within a factor of two of regional-averages (~500 km scale) of measurements of the various chemical components of particulat e matter in the United States and, except for organic carbon, satisfactorily simulated the seasonal variability in the observations. In the meantime, Harvard University had also carried out new finer-grid simulations for 2001 for EPRI, using a 1 ° x1 ° grid over North America, nested in a coarser grid that covered the globe. The final version of these simulations included modifications to the modeling grid to improve delineation between domestic US emissions a nd those of foreign sources at the national boundaries, and revision (reduction) of the Cana dian and Mexican sulfur emissions. These GEOS-CHEM 1 ° x1 ° grid scale simulations for 2001 and th eir results are desc ribed in the paper by Park et al. (2006). Over a ppropriate geographic and temporal scales, the results of these simulations for 2001were similar to those of the 2002 VISTAS simulations, which gave confidence in the VISTAS GEOS-CHEM results.
The concentration fields that resulted from the GEOS-CHEM simulations were not directly usable as boundary conditions for the 36 km grid scale CMAQ simulations. GEOS-CHEM and CMAQ use different horizontal and vertical grid scales and diffe rent map projections, and have different labels for chemical constituents . The GEOS-CHEM outputs were processed by Dr. Daewon Byun at the University of Houston to adjust for these discrepancies and to develop boundary conditions for the 36 km CMAQ modeli ng. Since the CMAQ modeling has temporal resolution of one hour, the boundary conditions were given for every hour. However, since the GEOS-CHEM outputs had 3-hr resolution, the hour ly boundary conditions were the same for three consecutive hours. An example of the re sulting boundary conditions for sulfate at the surface is shown in Figure G-1. As indicated by the colo rs along the boundary of the modeling

## G-4 domain, GEOS-CHEM projects hi gher sulfate values for th e southern boundary, indicating emissions from Mexico, and the eastern boundary, i ndicating recirculation of emissions from the eastern US. 

# Average Sulfate Boundary Conditions GEOS-CHEM for July 1, 2001

Figure G-1. GEOS-CHEM projections of sulfate boundary conditions for the national CMAQ modeling grid on July 1, 2001.

## G-5 Model performance for the 2002 4x4 degree annual GEOS-CHEM run was compared to observations at 145 IMPROVE sites and CASTNET sites across the continental US. Example plots from the model performance evaluation are illustrated in Fi gures G-2 through G-9. Additional information is provided in th e final GEOS-CHEM report (Jacobs, 2005). Performance at the boundaries is driven by accu racy of international emission estimates; performance at US continental monitors is driv en by US emissions. Given the large grid size, projections are approximations th at show the correct order magnitude. Performance for 2002 boundary conditions is acceptable compared to observations and an improvement over the CMAQ default single annual value for all boundaries. Sulfate pr ojections reproduce observed values fairly well, particularly for boundary cond itions. Sulfate is slightly over predicted for winter months. Summer sulfate levels are under pr edicted, particularly on high sulfate days, but mean fraction bias for monthly average sulfate is within performance criteria set for CMAQ (+/- 30%).

## G-6 Figure G-2. GEOS-CHEM 2002 SO4 annual performance compared to IMPROVE (145 sites) and CASTNET monitoring networks.

## G-7 Figure G-3. GEOS-CHEM 2002 Monthly SO4 Performance compared to 145 IMPROVE sites in the continental US.

Figure G-4. GEOS-CHEM 2002 Monthly SO4 Performance compared to 145 IMPROVE sites in the continental US. 

## GEOS-CHEM nitrate performance is acceptable for boundary conditions. Nitrate is over predicted at some sites on some winter days; over all nitrate is under predic ted in all months, and particularly in summer months. Since summer nitrate values are gene rally low, this under prediction does not affect overall model performance for CMAQ. 

# Monthly Average Sulfate

0 2 4 6 8 10 12 14

0 2 4 6 8 10 12 14 

# IMPROVE ( μ g/m 3 

# )GEOS-CHEM (μg/m3) 

### January February March April May June July August September October November Decembe r



# Sulfate Model Performance (IMPROVE)

-40 -30 -20 -10 0 10 20 30

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMean Fractional Bias (%)

## G-8 Figure G-5. GEOS-CHEM 2002 NO3 annual average performance compared to IMPROVE (145 sites) and CASTNET monitoring networks.

## G-9 Figure G-6. GEOS-CHEM 2002 Monthly NO3 Performance compared to 145 IMPROVE sites in the continental US.

Figure G-7. GEOS-CHEM 2002 Monthly NO3 Performance compared to 145 IMPROVE sites in the continental US. 

# Monthly Average Nitrate

0 1 2 3 4 5 6 7 8

012345678 

## IMPROVE ( μ g/m 3 

## )GEOS-CHEM (μg/m3) 

### January February March April May June July August September October November Decembe r



# Nitrate Model Performance (IMPROVE)

-180 -160 -140 -120 -100

-80 -60 -40 -20 0

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov DecMean Fractional Bias (%)

## G-10 Figure G-8. GEOS-CHEM 2002 Organic Matter Carbon (OMC) annual average performance compared to IMPROVE (145 sites) and CASTNET monitoring networks.


## Model performance for organic matter carbon (OMC ) and elemental carbon (EC) are acceptable. Performance at the boundaries is driven by quality of the fi re inventory for international emissions. While a new biomass burning inventory was de veloped as part of this study, monthly average fire emissions do not accurately ca pture the impacts from episodic fires.

## G-11 Figure G-9. GEOS-CHEM 2002 Elemental Carbon annual average performance compared to IMPROVE (145 sites) and CASTNET monitoring networks.


## GEOS-CHEM 3-hr average outputs were used as inputs to CMAQ modeling for 2002 and 2018. Since VISTAS did not have information to proj ect future changes in international emissions, VISTAS used the same boundary conditions in 2018 as developed for 2002.
References Chung, S. H. and Seinfeld, J.H. (2002), Global di stribution and climate fo rcing of carbonaceous aerosols, Journal of Geophysical Research, Vol. 107 (D19), 4407, doi:10.1029/2001JD001397. Jacob, D.J. (2005), Documenta tion and Evaluation of the GEOS-CHEM Simulation for 2002 Provided to the VISTAS Group. Final re port, Harvard University. June 24. Park. R.J., Jacob, D.J., Chin, M., and Marti n, R.V. (2003). Sources of carbonaceous aerosols over the United States and implications for natural visibility. Journal of Geophysical Research, Vol. 108 (D12), 4355, doi:10.1029/2002JD003190.

## G-12 Park. R.J., Jacob, D.J., Field, B.D., Yantos ca, R.M., and Chin, M. (2004). Natural and transboundary pollution influences on sulfate-nitrate-ammonium aerosols in the United States: Implications for policy. Journal of Geophysical Research, Vol. 109, D15204, doi:10.1029/2003JD004473. Park. R.J., Jacob, D.J., Kumar, N ., and Yantosca, R.M. (2006). Regi onal visibility statistics in the United States: Natural a nd transboundary pollution influen ces, and implications for the Regional Haze Rule. Atmospheric Environment, Vol. 40, pp. 5405-5423. Schichtel, B.A., Gebhart, K.A., Malm, W.C., Barn a, M.G., Pitchford, M.L., Knipping, E.M., and Tombach, I.H. (2005). Reconciliation and Interp retation of Big Bend National Park Sulfur Source Apportionment: Results from the Big Bend Regional Aerosol and Visibility Observational Study – Part I. Journal of the Air & Waste Management Assoc. Vol. 55, pp. 1709- 1725.

## APPENDIX H VISTAS Area of Influence Analyses Based on “VISTAS Area of Influence Analyses for Sulfur Dioxide” by Archuleta, Adhloch, Mansell, Stella and Brewer (February 28, 2007) and “Procedures for Developing and Displaying AoI Back-trajectories Residence Time GIS Data by Mansell (August 29, 2007)

## H-1 H.1 Introduction The objective of the VISTAS Area of Influence analysis is to identif y the geographic source regions that are contributing to vi sibility impairment at the Class I areas on the worst 20 percent visibility days. This information is being used by the VISTAS states as part of the evaluation and demonstration of reasonable progress toward visibility improvement in Class I areas.
VISTAS’ contribution assessment based on IMPR OVE monitoring data (Brewer and Adhloch, 2005) that demonstrated ammonium sulf ate is the major contributor to PM 2.5 

## mass and visibility impairment at Class I areas in the VISTAS and neighboring states. As il lustrated in Figure H-1, on the worst 20 percent visibility days during the 2000-2004 5-year Baseline, 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 coastal sites in the VISTAS states (excepting Everglades). In cont rast, ammonium nitrate contributed less than 5% of the calculated light extinction at VISTAS Class I areas on the worst 20 percent visibility days. (Nitrate has a somewhat larger contribution on the worst 20 percent days at Class I areas in neighboring states.) Particulat e organic matter carbon (OMC) ac counted for 10-20% of light extinction on the worst 20 percent visibility days (except Everglades where organic carbon accounted for 40%).

Figure H-1. Average extinction for the worst 20 percent visibility days in 2000-2004 using the new IMPROVE equation (data from VIEWS September 2006).



## VISTAS emissions sensitivity analyses using th e CMAQ regional air quality model project that reductions in SO2 emissions from Electric Ge nerating Utilities (EGU) and non-EGU industrial point sources will result in the greatest improveme nts 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 emissi ons from ground- level sources or point sources would be small. Based on these analyses, VI STAS states chose to focus their reasonable 0 50 100 150 200 250 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1CADI1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (Mm-1) Sea Salt CM Soil EC POM Amm NO3 Amm SO4 Rayleigh

0 50 100 150 200 250 300SWAN1ROMA1OKEF1EVER1CHAS1SAMA1DOSO1SHEN1JARI1LIGO1SHRO1GRSM1COHU1SIPS1MACA1CADI1BRIG1BRET1MING1HEGL1UPBU1CACR1

VISTAS coastal VISTAS inland non-VISTASExtinction (Mm-1) Sea Salt CM Soil EC POM Amm NO3 Amm SO4 Rayleigh

## H-2 progress evaluation on potential controls of SO2 emissions from E GU and non-EGU point sources. To select the specific point sources that would be considered for each Class I area, VISTAS first identified the geographic area that wa s most likely to influence visibility in each Class I area and then identified the major SO 2 point sources in that geographic area.

H.2 Back Trajectory Analyses In support of VISTAS’s Area of Influence (AoI) analysis, Air Resource Specialists (ARS) generated meteorological back trajectories for IMPROVE site s in VISTAS and neighboring states. Back trajectory analyses use interpolat ed 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 fo r chemical transformation and dispersion of emissions. Trajectories were generated using the Hybrid-Si ngle Particle Lagrangian Integrated Trajectory (HYSPLIT) model developed by the National Oceanic and Atmospheric Administration’s (NOAA) Air Resources Laborat ory (ARL). HYSPLIT uses archived 3-dimensional meteorological fields generated from observations and short-term forecasts. HYSPLIT can be run to generate forward or backward trajectorie s using several availabl e meteorological data archives. The data archives used in this analysis were the National Weather Service's National Centers for Environmental Prediction Eta Data Assimilation Sy stem (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 horizont al 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 thos e listed in Table H-1.
Table H-1. 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

The choice of these parameters affects the tr ajectories generated a nd the final attribution analyses. In particular, trajectories tend to be come increasingly uncertain the further back in time they are used. Vertical motion in the model is sometimes best represented by following actual vertical motion measuremen ts (represented by model data), surfaces of constant entropy, or surfaces of constant pressure, depending on th e meteorological conditions at a given location and time. The impact of receptor height (or e nd height) on an individual trajectory is also

## H-3 important. Low-ending trajectories represent air parcels nearer to ground level and high-ending trajectories may represent more accurate bound ary layer flow above the local terrain. For the years 2000 through 2004, back trajectori es were computed for the following 22 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 NWR, SC (ROMA1) 6. Chassahowitzka NWR, FL (CHAS1) 7. Cohutta, 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 NWR, 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) Based on the five years of individual back tr ajectories, ARS generate d extinction-weighted residence time data for each IMPROVE site. Each hourly trajectory point was tagged with its associated sample (or end) date. Back trajec tories with end dates corresponding to the worst 20 percent visibility days were weighted with ca lculated extinction values and summed into 1 degree horizontal grid cells of latitude and longitude. Extinction data is based on the IMPROVE Regiona l 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 or iginal 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. Othe r components were filled based on data from nearby sites. Trajectory data were weighted by total extinction, and by ex tinction components including ammonium sulfate (AmmSO4), ammonium nitrate (AmmNO3), organic matter carbon (OMC), Light Absorbing Carbon (LAC or EC), Soil, and Coarse Mass (CM). Wei ghting trajectories for the worst 20 percent 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 id entified based on sulfate contributions and not skewed by contributions from fire.

## H-4 Figure H-2. Example Back trajectories for 20% worst visibility days in 2002 for Sipsey Wilderness Area.



## These data files were provided to ENVIRON. ENVIRON was charge d with developing residence time plots to define the geographic area w ith highest probability of influencing the receptor on the worst 20 percent days dominated by sulfate. Residence time over an area is indicative of general flow patterns, but sin ce it does not account for emissions and removal processes, it does not necessa rily imply specific areas contributed significantly to haze compounds at a receptor site.

H.3 Area of Influence Data and Displays The primary objective of the Area of Influence ( AOI) displays and data sets are to assist the States in focusing their reasonable progress an alysis on those geographic regions and source categories which most impact a particular Cla ss I Area. The sources of data used in these analyses include back-trajector y residence time data, provided by ARS and described above, and the VISTAS 2002 and 2018 36-km gridded emissi ons data (Base G, August 2006 inventory version).

## H-5 Extinction weighted back-trajectory residence ti me 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., geod etic lat/lon 1 degree by 1 degree) grid and transferred to ENVIRON for furthe r GIS processing and analysis. Back-trajectories were run for 100-meter and 500-meter start heights. Because the back-trajectories were to be combined with gridded emissions data, the first step in the an alysis and GIS processing involved re-projecting these data to the 36 km Inter-RPO Unified Lambert Conformal Projection domain. Once the data were re-projected, the data were mapped to the 36 km grid cells in the RPO projection using an area-weighted mapping routine. The re-p rojected extinction weighted back-trajectory residence times were then plotted on the VIST AS 12 km modeling domain. As sulfate is the primary visibility impairing component of th e total extinction in the Southeast, the SO4- weighted residence time trajectories were chosen as the basic data set fo r display. For clarity, these data are scaled by the maximum value of the total extinction-weighted residence time within the modeling domain. Fi gure H-3 displays an example of the back-trajectory residence time plot for Sipsey, Alabama.

Figure H-3. Sulfate-weighted back-trajectory residence time (RT) displays for Sipsey, AL. (Red outline delineates the region with RT > 10%; orange outline (grey cells) delineates regions with RT > 5% ).



## As an aid to the analysis, all regions with s caled residence time values greater than 5% and greater than 10% were noted on the displays as shown in Figure H-3. Finally, county boundaries were overlaid to identify those counties and 36 km modeling grid cells for which the extinctionweighted residence time back-tra jectories exceeded 5% and 10%. These data were then exported as comma-delimited ASCII data files for further analyses. These residence time displays are used primarily to determine the regions (counties a nd/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 extinction-weight ed back-trajectory residence time displays and analyses.

## H-6 Previous VISTAS contribution assessment, emissions sensitivity modeling, and inventory analyses have indicated that SO4 is the largest contributor to haze on the worst 20 percent visibility days and that Electric Generating Uti lities and industrial point sources are the largest contributors to SO4 levels at th e Class I areas. These two source categories make up 95% of the VISTAS SO2 inventory. Therefore these two sour ce categories were identified as the highest priority for evaluation of reasonable progr ess in 2018 at the Class I areas. The potential impacts of SO2 point source emissi ons 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 w ith both the 2002 and 2018 base year emission inventories. Figures H-4 and H-5 display the gridded point source SO2 emissions from the VISTAS modeling databases, for 2002 and 2018, resp ectively. These data were processed by summing all vertical layers for each grid column and then summing across all days to obtain annual emission totals for each grid cell.

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

## H-7 Figure H-5. Annual point source SO2 emissions for the VISTAS region for 2018 in tons/year. (2018 BaseG).



## As a way of incorporating the effects of transport, dispersion, deposition, and chemical transformation of point source em issions along the path of the trajectories, these data were weighted by 1/d, where d was calculated as the distance between the 36 km grid cell centers for the source and the Class I area monitor, in kilometers. For the grid cell containing the Class I Area monitor, a weighting of 1/9 was applie d. The distance-weighted point source SO2 emissions are then combined with the gridded extinction-weighted back -trajectory residence times at a spatial reso lution of 36 km. The final step in the development of the displa ys 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 ba sis. These results are then normalized by the domain-wide total and displayed as a percentage. The analysis is carried out for both the 2002 and 2018 base year inventories. Figures H-6 and H-7 display the result of this final analysis step. Note that th e outlined regions (in red and light orange) represent the extent of the >10% and >5% sulfate extinction-weighted resi dence times, determined from the first step in the analysis (see Figure H-3). As with the resi dence time analysis, the results of the combined distance-weighted SO2 emissions and extinction-weighted reside nce times are overlaid with county boundaries and exported to comma-delimited ASCII data files for further analyses of emissions and control options for specific sources.

## H-8 Figure H-6. Normalized 2002 SO2 point source emissions times distance-weighted residence time display for Sipsey, AL. (Red outline delineates the region with RT > 10%; orange outline delineates regions with RT > 5% ).

Figure H-7. Normalized 2018 SO2 point source emissions times distance-weighted residence time display for Sipsey, AL. (Red outline delineates the region with RT > 10%; orange outline delineates regions with RT > 5% ).



## VISTAS states evaluated these plots of reside nce time weighted by sulfate extinction plots of gridded SO2 emissions and define d 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.

## H-9 H.4 Summary of Emission Inventories Used in Cost Curve Analysis A necessary component of control strategy de sign is a thorough review of the emission inventories that are used in the modeling of the fu ture year base case. These inventories can shed light on the residual emissions from sources or source categories de fined to be within areas of transport or impact of a Class I area. We us ed the Base G (fall 2006) version of the VISTAS 2018 base case and 2002 base year emissions to conduct this cost curve analysis. The NIF formatted and SMOKE-ready modeling f iles 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 fo r the geography and domain of interest. Tables H-2 and H-3 present the State breakdown of these emissions for the entire VISTAS domain. Because the SMOKE-ready files were used in this analysis, the fugitive dust transport factor (FDTF) is included in the PM emission su mmaries. This factor is applied to account for the removal of a substantial portion of f ugitive dust emissions near a source by surrounding vegetation and structures when such emissions are used in regional s cale modeling analyses.
Table H-2. VISTAS 2002 Base Year Annual Emissions Summary.

Table H-3. 2018 Base Case Annual Emissions Summary.
State V OC NOx CO SO2 PM-10 PM-2.5 NH3 AL 327,850 268,067 1,994,607 305,938 258,179 114,681 84,513 FL 990,629 448,443 6,099,425 260,963 483,328 226,529 73,455 GA 585,528 357,169 3,820,095 358,570 472,376 211,406 124,237 KY 236,983 277,271 1,356,496 320,525 166,918 58,559 63,959 MS 247,932 173,893 850,056 62,627 205,761 54,912 76,040 NC 421,965 275,907 2,702,315 164,067 208,015 100,253 196,577 SC 300,291 193,247 1,527,341 163,491 189,358 88,891 42,883 TN 374,093 247,827 1,692,551 228,035 187,066 84,117 46,984 VA 311,835 276,525 2,001,939 294,209 131,708 57,993 64,276 WV 107,675 150,777 576,198 190,683 54,736 31,678 14,400
V ISTA S 3,904,780 2,669,125 22,621,023 2,349,107 2,357,445 1,029,017 787,325 BaseG Annual Emissions - 2018 Base Case (Tons) State V OC NOx CO SO2 PM-10 PM-2.5 NH3 AL 445,497 459,880 2,534,778 584,665 232,229 105,341 67,970 FL 1,291,562 930,086 7,710,376 589,069 408,902 205,450 61,643 GA 765,063 623,645 5,013,024 653,362 408,736 195,654 100,134 KY 286,752 466,403 1,730,622 580,341 148,290 50,981 57,220 MS 302,374 239,547 1,203,899 103,679 180,816 43,533 63,765 NC 655,950 616,583 4,097,444 546,429 179,242 84,513 172,976 SC 382,836 323,976 2,064,423 286,781 165,699 78,356 35,400 TN 473,244 511,151 2,601,059 442,589 165,095 75,458 42,738 VA 448,205 461,628 3,034,414 416,190 109,848 47,004 55,057 WV 135,819 348,576 802,262 569,373 48,423 27,807 12,341
V ISTA S 5,187,303 4,981,474 30,792,301 4,772,477 2,047,281 914,096 669,243 BaseG Annual Emissions - 2002 Typical (Tons)

## H-10 Our review was conducted in a top down fashion st arting 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 high est 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. These analyses are illustrated for sources in th e SO2 Area of Influence for Sipsey in Tables H-4 through H-8. 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. RTmax greater than 10 was used to define emissions included in Tables H-4 through H-8.

Table H-4. 2018 Base G2 Annual Emissions (Tons) by Source Category in SO2 Area of Influence for Sipsey Wilderness Area.

Table H-5. 2018 Base G2 Annual Emissions (Percentage) by Source Category in SO2 Area of Influence for Sipsey Wilderness Area. Tie r V OC NOX CO SO2 PM-10 PM-2. 5 NH3 Fuel Comb. Elec. Util. 7,23 7 236,192 82,293 542,524 74,612 56,145 3,91 6 Fuel Comb. Industrial 14,210 181,413 168,051 198,03 3 29,686 19,351 59 2 Fuel Comb. Other 61,63 5 55,145 178,412 57,140 27,763 25,516 87 3 Chemical & Allied Pr oduct Mf g 19,70 7 6,225 61,613 16,31 5 6,046 4,038 1,64 3 Metals Processin g 12,06 9 8,866 235,955 48,88 9 23,309 19,855 778.7 8 Petroleum & Related Industries 2,37 2 1,689 3,353 5,70 9 998 643 0.0 2 Other Industrial Processes 112,62 9 59,626 94,469 42,121 77,815 36,776 3,13 3 Solvent Utilization 583,810 969 574.93 12.8 7 2,387 1,935 105.74 Storage & Transport 84,17 7 462 422.07 122.1 4,637 2,668 3.5 9 Waste Disposal & Recyclin g 46,900 14,606 310,604 2,43 8 53,825 50,254 16 9 Highway Vehicles 231,42 6 220,157 3,159,96 8 3,31 5 10,934 5,399 33,044 Off-highwa y 151,510 186,975 2,304,37 2 7,78 9 13,846 13,083 204.24 Miscellaneous 39,73 3 13,403 642,523 3,640 580,930 117,56 6 308,84 8
V ISTAS Total 1,367,414 985,728 7,242,611 928,04 6 906,789 353,22 9 353,311 A

nnual 2018 BaseG2 Emissions (Tons)

Tie r V OC NO X CO SO2 PM-10 PM-2. 5 NH3 Fuel Comb. Elec. Util. 1% 24 % 1% 58% 8% 16% 1% Fuel Comb. Industrial 1% 18 % 2% 21% 3% 5% 0% Fuel Comb. Other 5% 6% 2% 6% 3% 7% 0% Chemical & Allied Pr oduct Mf g 1% 1% 1% 2% 1% 1% 0% Metals Processin g 1% 1% 3% 5% 3% 6% 0% Petroleum & Related Industries 0% 0% 0% 1% 0% 0% 0% Other Industrial Processes 8% 6% 1% 5% 9% 10% 1% Solvent Utilizatio n 43% 0% 0% 0% 0% 1% 0% Storage & Transpor t 6% 0% 0% 0% 1% 1% 0% Waste Disposal & Recyclin g 3% 1% 4% 0% 6% 14% 0% Highway Vehicles 17% 22 % 44% 0% 1% 2% 9% Off-highwa y 11% 19 % 32% 1% 2% 4% 0% Miscellaneous 3% 1% 9% 0% 64% 33% 87%
V

ISTAS Total 100 % 100 % 100 % 100 % 100 % 100 % 100 % A

nnual 2018 BaseG2 Emissions (%)

## H-11 Table H-6. 2018 Base G2 Annual Emissions (Tons) for Top Three Source Categories in SO2 Area of Influence for Sipsey Wilderness Area.

Table H-7. 2018 Base G2 Annual Emissions (Percentage) for Top Three Source Category in SO2 Area of Influence for Sipsey Wilderness Area.



## In addition to reviewing the resi dual emission categories in the futu re 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 s ource 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-effectiv e emission reduction 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 un its using the best control for the scenario. These tables presented comp arisons of 2002 and 2018 emission levels, for SO2, Tier V OC NOX CO SO2 PM-10 PM-2. 5 NH3 Fuel Comb. Elec. Util.-Coal 5,83 8 222,105 43,332 538,424 70,940 52,634 988 Fuel Comb. Elec. Util.-Oil 6 5 548 9 52 2 1 0 Fuel Comb. Elec. Util.-Gas 66 1,598 609 3,782 323 216 113 Fuel Comb. Elec. Util.-Other 16 235 101 6 76 46 0 Fuel Comb. Elec. Util.-Internal 1,252 11,706 38,242 260 3,272 3,24 8 2,815 Fuel Comb. Industrial-Coal 1,884 41,177 29,545 135,360 13,952 6,177 13 Fuel Comb. Industrial-Oil 231 12,471 4,455 36,115 2,13 8 1,30 5 97 Fuel Comb. Industrial-Gas 6,001 56,185 74,037 17,184 7,836 7,381 482 Fuel Comb. Industrial-Other 3,377 18,346 48,181 9,188 5,14 9 3,902 0 Fuel Comb. Industrial-Internal 2,717 53,233 11,833 185 611 587 0 Fuel Comb. Other- 302 5,437 1,005 18,786 440 29 5 0 Fuel Comb. Other- 131 3,076 1,193 32,056 1,602 96 8 149 Fuel Comb. Other- 65 8 11,045 7,131 946 962 89 8 23 Fuel Comb. Other-Misc. Fuel Comb. 1,14 5 3,811 21,618 1,649 95 8 68 9 3 Fuel Comb. Other-Residential Wood 57,645 3,034 129,21 5 431 21,242 20,34 5 304 Fuel Comb. Other-Residential Other 1,753 28,742 18,249 3,272 2,560 2,323 395 Top Tier Total 83,082 472,750 428,75 6 797,69 7 132,061 101,01 3 5,381 A

nnual 2018 BaseG2 Emissions (Tons)

Tier V OC NO X CO SO2 PM-10 PM-2. 5 NH3 Fuel Comb. Elec. Util.-Coal 0 % 23% 1 % 58% 8 % 15 % 0% Fuel Comb. Elec. Util.-Oil 0 % 0% 0 % 0 % 0 % 0 % 0% Fuel Comb. Elec. Util.-Gas 0 % 0% 0 % 0 % 0 % 0 % 0% Fuel Comb. Elec. Util.-Other 0 % 0% 0 % 0 % 0 % 0 % 0% Fuel Comb. Elec. Util.-Internal 0 % 1% 1 % 0 % 0 % 1 % 1% Fuel Comb. Industrial-Coal 0 % 4% 0 % 15% 2 % 2 % 0% Fuel Comb. Industrial-Oil 0 % 1% 0 % 4 % 0 % 0 % 0% Fuel Comb. Industrial-Gas 0 % 6% 1 % 2 % 1 % 2 % 0% Fuel Comb. Industrial-Other 0 % 2% 1 % 1 % 1 % 1 % 0% Fuel Comb. Industrial-Internal 0 % 5% 0 % 0 % 0 % 0 % 0% Fuel Comb. Other- 0 % 1% 0 % 2 % 0 % 0 % 0% Fuel Comb. Other- 0 % 0% 0 % 3 % 0 % 0 % 0% Fuel Comb. Other- 0 % 1% 0 % 0 % 0 % 0 % 0% Fuel Comb. Other-Misc. Fuel Comb. 0 % 0% 0 % 0 % 0 % 0 % 0% Fuel Comb. Other-Residential Wood 4 % 0% 2 % 0 % 2 % 6 % 0% Fuel Comb. Other-Residential Other 0% 3% 0% 0% 0% 1% 0% Top Tier Total 4 % 47 % 6 % 85 % 14 % 28 % 1 % A

nnual 2018 BaseG2 Emissions (%)

## H-12 and future year control technology assignment ( by IPM forecasting and State modification) for point sources. Non-EGU unit-spec ific technology assignments were identified using the control efficiency tables provided by the VISTAS emissions inventory contractor, MACTEC. Using these emission reviews and summaries like those presented in Figure H-8, VISTAS states made a decision to further evaluate reasonable measures for SO2 emissi ons controls beyond the On-The-Books scenario in 2018 for EGU and non- EGU point sources only. Ultimately, the long-term strategy will include emissions contro ls on the BART applicable sources. However, determinations of BART controls were not available for this analysis.

Figure H-8. VISTAS Base G2 SO2 Emissions Contributions by Major Source Sector.



## H.5 Process in Preparing Files for Cost Effectiveness Curve Development The 2018 IPM file used by VISTAS for EGU sour ces (RPO IPM version 2.1.9) 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. Because IPM does not assign a contro l efficiency with each control device applied to SO 2 

## and NO X 

## , we made some assumptions, based on IP M documentation, as to what pollutant specific level of reduction was applied in the futu re year base case runs. These assumptions, by primary and secondary control device code combinations for SO 2, 

## are presented in Table H-8. Since many of the control technology control cost equations within AirControlNET require additional unit-level characteristic data, we al so 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 and operating and maintenance cost calc ulations for many of the SO2 applied technologies. In cases where these nameplate capacity values could not be identified, emission weighted (based on the Al

a b

a m

a F l o r i d

a K e n t u c k

y G

e o r g i a M i s s i s s i p p i
S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a
T e n n e s s e e V i r g i n i a W e s t V

i r g i n i a 

### 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2002

2009

2018

Al

a b

a m

a F l o r i d

a K e n t u c k

y G

e o r g i a M i s s i s s i p p i
S o u t h

C

a r o l i n a

N

o r t h

C

a r o l i n a
T e n n e s s e e V i r g i n i a W e s t V

i r g i n i a 

### 100 200 300 400 500 600 700Annual SO2 (Thousand Tons) Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2002

2009

2018 Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU Miscellaneous Nonroad Onroad Industrial Other Fuel Combustion EGU 2002

2009

2018

## H-13 final EPA 2002 NEI) were assigned to boilers usi ng a primary (highest emitting) SCC. Table H9 presents these weighted capacities. Additionall y, 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 va riables were obtained where matches could be found, in priority order of VISTAS, CAMD , and other EPA datasets, respectively.
Table H-8. IPM Post Processing Assigned Device Codes and Applied SO 2 

### 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



## H.6 Application of AirControlNET Technologies AirControlNET is a control technology analysis tool developed to support the U.S. EPA in its analyses of air pollution policies and regulations (Pechan, 2005). The tool provides data on emission sources, potential pollutio n control measures and emissi on reductions, and the costs of implementing those controls.
The core of AirControlNET is a relational databa se system in which control technologies are linked to sources within EPA emi ssions inventories. The system contains a database of control measure applicability, efficiency, and cost inform ation for reducing the em issions contributing to ambient concentrations of ozone, PM 10 

## , PM 2.5 

## , SO 2 

## , NO X 

## , as well as visibility impairment (regional haze) from point, ar ea, and mobile sources. PM 10 

## and PM 2.5 

## 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 prepro cessed application of control technologies to a predetermined se t of EPA emission inventories, di rect use of the model in this analysis was not possible. However, VI STAS received approval from EPA’s Innovative Strategies and Economics Group (ISEG) to modify the AirControlNET vers ion 4.1 source code and data tables in order to make it useful to this study (Sorrels, 2006) . 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 cost-effectivene ss based control strategies by source or domain.F:\VISTAS Phase II\TSD\draft#3\Appendix_H_AOI3.docH-14Table H-9.Emissions Weighted NETDC (MW) Association.SCCDescriptionNETDC (MW)10100201 External Combustion Boilers; ElectricGeneration; Bituminous/Subbituminous Coal; Pulverized Coal: Wet Bottom (Bituminous Coal) 20010100202 External Combustion Boilers; ElectricGeneration; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Bituminous Coal) 50010100203 External Combustion Boilers; ElectricGeneration; Bituminous/Subbituminous Coal; Cyclone Furnace (Bituminous Coal) 20010100212External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Tangential) (BituminousCoal)50010100215 External Combustion Boilers; ElectricGeneration; Bituminous/Subbituminous Coal; Cell Burner (Bituminous Coal) 130010100218External Combustion Boilers; Electric Generation; Bituminous/Subbituminous Coal; Atmospheric Fluidized Bed Combustion: Circulating Bed(Bitum. Coal)20010100222 External Combustion Boilers; ElectricGeneration; Bituminous/Subbituminous Coal; Pulverized Coal: Dry Bottom (Subbituminous Coal) 40010100223 External Combustion Boilers; ElectricGeneration; Bituminous/Subbituminous Coal; Cyclone Furnace (Subbituminous Coal)40010100226External Combustion Boilers; Electric Generation; Bituminous/SubbituminousCoal; Pulverized Coal: Dry Bottom Tangential (SubbituminousCoal)50010100401 External Combustion Boilers; Electric Generation; Residual Oil;Grade 6 Oil: Normal Firing40010100404 External Combustion Boilers; Electric Generation; Residual Oil;Grade 6 Oil: Tangential Firing50010100501 External Combustion Boilers;Electric Generation;Distillate Oil; Grades 1 and 2 Oil 40010100601 External Combustion Boilers; Electric Generation; Natural Gas; Boilers > 100 Million Btu/hr except Tangential 40010100701 External Combustion Boilers; Electric Generation; Process Gas; Boilers > 100 Million Btu/hr20010100801 External Combustion Boilers; Electric Generation; Petroleum Coke; All Boiler Sizes 60010101204 External Combustion Boilers; Electric Generation; Solid Waste;Tire Derived Fuel : Shredded 20010300811 External Combustion Boilers; Commercial/Institutional; Landfill Gas; Landfill Gas20020100101 Internal Combustion Engines;Electric Generation; Distillate Oil (Diesel); Turbine20020100109 Internal Combustion Engines; Electric Generation; DistillateOil (Diesel); Turbine: Exhaust 20020100201 Internal Combustion Engines; ElectricGeneration; Natural Gas; Turbine200All other boilers100F:\VISTAS Phase II\TSD\draft#3\Appendix_H_AOI3.doc 

## H-15 H.7 Development of AOI-Based Cost Curves Each Class I area in the VISTAS modeling domain had an associated AOIs. In order to best determine where emission reduction has the great est 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 applica tion of all available control measures to all applicable point sources within the AOI. The curves allow VISTAS States to determine if emission controls, based on the generic appli cation of SO2 control technologies from the associations originally deve loped in AirControlNET and impr oved upon with stakeholder input, will help attain reasonable further progress 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 th e boundaries of the AOIs. This parsed list was then sorted on in incremental cost-effectiveness (marginal cost) basis to determine the most cost effective control suite available to attain emi ssion reduction targets for SO2 within each AOI. Each individual source had its own co st effectiveness curve generated. In aggregate, the results of these applications are SO2 emission cost curves for all EGU and nonEGU point source within the geographic domain of the AOI. Incremental controls on area and mobile sources were not consid ered in this analysis. 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 in cremental review and c onsideration. States can use these values to further determine control st rategy development for individual Class I areas.