Appendix A

WRAP Regional Summary Report

The “Western Regional Air Partnership Regional Haze Rule Reasonable Progress 

Summary Report” contains analyses for 15 states in the western region of the United 

States and is available at: http://www.wrapair2.org/RHRPR.aspx. The Summary 

Report section for California can be downloaded from the same website, as Section 6.3, 

under the State Summaries (and State Specific Appendices):

California (pdf) (1.1 MB, 39 pages), Appendix C (pdf) (2.6 MB, 154 pages.)
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Appendix B

Emission Inventory

2013 Almanac
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B - 1

NOx Emissions (TPD)

Statewide 2000 2005 2010 2015 2020

Electric Utilities 60.6 26.8 23.1 25.3 26.8

Cogeneration 28.7 18.1 15.9 17.2 20.6

Oil And Gas Production (Combustion) 24.7 14.4 10.2 9 8.4

Petroleum Refining (Combustion) 46.9 25.6 20.2 19.7 19.6

Manufacturing And Industrial 145.2 80.3 63.1 65.3 64.9

Food And Agricultural Processing 42 36.3 28.3 15.3 9.5

Service And Commercial 72.1 49.6 46.5 45.8 47.2

Other (Fuel Combustion) 20.1 17.2 12.3 14.7 13.5

Sewage Treatment 0.4 0.4 0.4 0.5 0.5

Landfills 0.6 1 1 1.1 1.2

Incinerators 1.7 2.1 2.6 2.7 2.9

Soil Remediation 0.1 0.1 0.1 0.1 0.1

Other (Waste Disposal) 0.1 0 0 0 0

Laundering 0 0 0 0 0

Degreasing 0 0 0 0 0

Coatings And Related Process Solvents 0.1 0.1 0 0.1 0.1

Printing 0 0 0 0 0

Adhesives And Sealants 0 0 0 0 0

Other (Cleaning And Surface Coatings) 0.1 0.1 0.1 0.2 0.2

Oil And Gas Production 3.6 2.7 2.2 2 1.8

Petroleum Refining 9.9 5.4 13.8 2.3 2.3

Petroleum Marketing 0.7 0.2 0.2 0.3 0.3

Other (Petroleum Production And Marketing) 0 0 0 0 0

Chemical 1.8 2 1.7 1.9 2

Food And Agriculture 0.7 0.2 0.1 0.2 0.2

Mineral Processes 101.2 103.3 54.4 57 61.9

Metal Processes 1.5 1.1 1 0.7 0.7

Wood And Paper 3.8 2.5 1 1 1.1

Glass And Related Products 13.7 10.1 5.8 4.1 4.4

Electronics 0 0 0 0 0

Other (Industrial Processes) 3.4 2.7 9.1 1.1 1.4

Consumer Products 0 0 0 0 0

Architectural Coatings And Related Process Solvents 0 0 0 0 0

Pesticides/Fertilizers 0 0 0 0 0

Asphalt Paving / Roofing 0 0 0 0 0

Residential Fuel Combustion 80.6 68.1 59.9 59.3 59

Farming Operations 0 0 0 0 0

Construction And Demolition 0 0 0 0 0
B - 2

NOx Emissions (TPD) (continued)

Statewide 2000 2005 2010 2015 2020

Paved Road Dust 0 0 0 0 0

Unpaved Road Dust 0 0 0.1 0 0

Fugitive Windblown Dust 0 0 0 0 0

Structural and Automobile Fires 0.2 0.2 0.2 0.2 0.2

Managed Burning And Disposal 15 16.6 14.7 14.6 14.6

Cooking 0 0 0 0 0

Other (Miscellaneous Processes) 0 0 0 0 0

Light Duty Passenger (Lda) 463.7 249.8 157.4 83.7 50.5

Light Duty Trucks - 1 (Ldt1) 166.8 66.9 39.2 26.6 17.6

Light Duty Trucks - 2 (Ldt2) 265.3 148.1 101 56.9 32.2

Medium Duty Trucks (Mdv) 117 127.2 107.1 75.5 52.2

Light Heavy Duty Gas Trucks - 1 (Lhdv1) 28.1 49.6 47.9 41 34.4

Light Heavy Duty Gas Trucks - 2 (Lhdv2) 9.7 5.6 4.2 3.3 2.6

Medium Heavy Duty Gas Trucks (Mhdv) 18.3 12 10.5 6.5 4.1

Heavy Heavy Duty Gas Trucks (Hhdv) 11.3 4 3.9 3.5 3.2

Light Heavy Duty Diesel Trucks - 1 (Lhdv1) 24.6 98 102.1 74.7 53.6

Light Heavy Duty Diesel Trucks - 2 (Lhdv2) 23.7 27.1 25.8 18.9 13.8

Medium Heavy Duty Diesel Trucks (Mhdv) 161.7 162.7 100.6 64.7 32.2

Heavy Heavy Duty Diesel Trucks (Hhdv) 706.3 728.3 432 286.2 192.6

Motorcycles (Mcy) 4.4 7.5 9.1 9.1 9.5

Heavy Duty Diesel Urban Buses (Ub) 44.2 35.7 34.2 30.2 26.5

Heavy Duty Gas Urban Buses (Ub) 2.8 2.2 2.2 2 1.9

School Buses - Gas (Sbg) 1 0.8 0.7 0.5 0.5

School Buses - Diesel (Sbd) 10.8 10 7.3 6.8 5.9

Other Buses - Gas (Obg) 2.7 4.4 3.5 2.7 1.9

Other Buses - Motor Coach - Diesel (Obc) 12.4 12.3 8.2 5.5 2.8

All Other Buses - Diesel (Obd) 7.5 7.6 5.1 4 2.1

Motor Homes (Mh) 14.6 8.9 8 5.9 4.5

Aircraft 42.6 45.8 53.2 57.7 64.1

Trains 198.8 157.4 95.6 111.3 109.7

Ships And Commercial Boats 0.2 0.1 0.1 0.1 0.1

Ocean Going Vessels 170.5 218.2 196.1 236.2 224.9

Commercial Harbor Craft 83.4 74.3 63.6 44.9 36.5

Recreational Boats 16.6 20.5 19.5 18.6 18.4

Off-Road Recreational Vehicles 0.4 1.5 1.4 2.7 3

Off-Road Equipment 339.5 307.3 188.7 163.9 126.9

Farm Equipment 154 132.5 106.9 81.4 59.7

Fuel Storage And Handling 0 0 0 0 0

Total (TPD) 3782 3214 2323 1887 1553
B - 3

SOx Emissions (TPD)

Statewide 2000 2005 2010 2015 2020

Electric Utilities 5.4 4.1 5 5.1 5.5

Cogeneration 1.8 1.2 1.1 1.2 1.4

Oil And Gas Production (Combustion) 7.4 1.3 2.1 0.6 0.6

Petroleum Refining (Combustion) 12.8 11.9 18.9 8.9 8.1

Manufacturing And Industrial 9.1 6.3 7.6 8.7 8.4

Food And Agricultural Processing 1.1 0.7 0.6 0.4 0.4

Service And Commercial 3 2.5 2.8 3 3.1

Other (Fuel Combustion) 0.4 0.9 0.4 0.4 0.4

Sewage Treatment 0.2 0.2 0.2 0.3 0.3

Landfills 0.2 0.5 0.5 0.5 0.5

Incinerators 0.1 0.3 0.5 0.6 0.6

Soil Remediation 0 0 0 0 0

Other (Waste Disposal) 0 0 0 0 0

Laundering 0 0 0 0 0

Degreasing 0 0 0 0 0

Coatings And Related Process Solvents 0 0 0 0 0

Printing 0 0 0 0 0

Adhesives And Sealants 0 0 0 0 0

Other (Cleaning And Surface Coatings) 0 0 0 0.1 0.1

Oil And Gas Production 0.1 0.1 0.1 0.1 0.1

Petroleum Refining 56.6 40.1 5 4.7 4.2

Petroleum Marketing 0 0 0 0 0

Other (Petroleum Production And Marketing) 0 0 0 0 0

Chemical 2.9 3.4 2.6 2.6 3

Food And Agriculture 1.8 0.3 0.5 0.5 0.6

Mineral Processes 20.7 18.9 12.4 13.3 14.9

Metal Processes 0.2 0 0.1 0.1 0.1

Wood And Paper 0.7 0 0 0 0

Glass And Related Products 6.6 2.9 2.5 1.8 1.9

Electronics 0 0 0 0 0

Other (Industrial Processes) 0.8 1 1.4 0.5 0.7

Consumer Products 0 0 0 0 0

Architectural Coatings And Related Process Solvents 0 0 0 0 0

Pesticides/Fertilizers 0 0 0 0 0

Asphalt Paving / Roofing 0 0 0 0 0

Residential Fuel Combustion 5.4 3.8 3.4 2.7 2.7

Farming Operations 0 0 0 0 0

Construction And Demolition 0 0 0 0 0
B - 4

SOx Emissions (TPD) (continued)

Statewide 2000 2005 2010 2015 2020

Paved Road Dust 0 0 0 0 0

Unpaved Road Dust 0 0 0 0 0

Fugitive Windblown Dust 0 0 0 0 0

Structural and Automobile Fires 0 0 0 0 0

Managed Burning And Disposal 3.6 3.6 3.5 3.6 3.6

Cooking 0 0 0 0 0

Other (Miscellaneous Processes) 0 0 0 0 0

Light Duty Passenger (Lda) 2.7 1.8 1.9 2 1.8

Light Duty Trucks - 1 (Ldt1) 0.7 0.3 0.3 0.3 0.3

Light Duty Trucks - 2 (Ldt2) 1.4 0.9 0.9 1 0.9

Medium Duty Trucks (Mdv) 0.6 1 1 1 1

Light Heavy Duty Gas Trucks - 1 (Lhdv1) 0.1 0.2 0.3 0.3 0.3

Light Heavy Duty Gas Trucks - 2 (Lhdv2) 0 0 0 0 0

Medium Heavy Duty Gas Trucks (Mhdv) 0 0 0 0 0

Heavy Heavy Duty Gas Trucks (Hhdv) 0 0 0 0 0

Light Heavy Duty Diesel Trucks - 1 (Lhdv1) 0.2 0.7 0.1 0.1 0.1

Light Heavy Duty Diesel Trucks - 2 (Lhdv2) 0.2 0.2 0 0 0

Medium Heavy Duty Diesel Trucks (Mhdv) 1.2 1.4 0.1 0.1 0.2

Heavy Heavy Duty Diesel Trucks (Hhdv) 4.9 5.8 0.6 0.7 0.8

Motorcycles (Mcy) 0 0 0 0 0

Heavy Duty Diesel Urban Buses (Ub) 0.4 0.4 0 0 0

Heavy Duty Gas Urban Buses (Ub) 0 0 0 0 0

School Buses - Gas (Sbg) 0 0 0 0 0

School Buses - Diesel (Sbd) 0.1 0.1 0 0 0

Other Buses - Gas (Obg) 0 0 0 0 0

Other Buses - Motor Coach - Diesel (Obc) 0.1 0.1 0 0 0

All Other Buses - Diesel (Obd) 0.1 0.1 0 0 0

Motor Homes (Mh) 0.1 0 0 0 0

Aircraft 3 3.2 3.5 3.8 4.2

Trains 8.4 7.5 0.6 0.1 0.1

Ships And Commercial Boats 0 0 0 0 0

Ocean Going Vessels 120.9 155.1 41.6 8.1 10.2

Commercial Harbor Craft 0.9 0.9 0.4 0.4 0.4

Recreational Boats 0 0 0 0 0

Off-Road Recreational Vehicles 0 0.1 0 0.1 0.1

Off-Road Equipment 1.4 1.6 0.2 0.2 0.2

Farm Equipment 1 0.9 0.1 0.1 0.1

Fuel Storage And Handling 0 0 0 0 0

Total (TPD) 289.3 286.3 122.8 78 81.9
B - 5

VOC Emissions (TPD)

Statewide 2000 2005 2010 2015 2020

Electric Utilities 4.8 3.2 2.4 2.4 2.4

Cogeneration 3 1.8 1.7 2.1 2.5

Oil And Gas Production (Combustion) 2.9 2.6 2.6 2.3 2.1

Petroleum Refining (Combustion) 1.8 2.9 2.6 3 3

Manufacturing And Industrial 11.7 6.6 7.5 7.8 8.3

Food And Agricultural Processing 5.1 4.9 3.8 2.8 2.3

Service And Commercial 5.6 4 4.9 5.2 5.4

Other (Fuel Combustion) 2.2 1.4 1.1 1 0.9

Sewage Treatment 0.6 0.7 1.1 0.7 0.8

Landfills 13.7 10.6 11.4 12.3 13.1

Incinerators 0.2 3.2 1.3 1.5 1.5

Soil Remediation 0.3 0.5 0.4 0.4 0.4

Other (Waste Disposal) 22.6 27.6 27.6 24.8 26.3

Laundering 1.6 2.2 2.1 1.8 1.9

Degreasing 64.1 32.5 33.6 38.1 43

Coatings And Related Process Solvents 90.8 67.3 57.4 64.9 71.6

Printing 24 18.8 17.4 18.8 20.1

Adhesives And Sealants 26.4 19.9 19.8 20.5 21.3

Other (Cleaning And Surface Coatings) 6.2 5.2 7.2 8.1 8.9

Oil And Gas Production 58.6 42.1 37.3 34.3 31

Petroleum Refining 38.4 12.3 16.4 11.9 11.9

Petroleum Marketing 109.4 80.6 80.1 81.8 84.5

Other (Petroleum Production And Marketing) 0.4 0.3 15.9 0.3 0.3

Chemical 22.6 18.4 15.8 17.1 20.2

Food And Agriculture 15.2 16.4 17.7 18.8 20.6

Mineral Processes 6.8 6 4.1 4.2 4.7

Metal Processes 1.3 0.5 0.4 0.4 0.4

Wood And Paper 3.6 2.9 2.5 2.5 2.7

Glass And Related Products 0.2 0 0 0 0

Electronics 0.9 0.4 0.3 0.3 0.3

Other (Industrial Processes) 19.2 19.9 20.6 10.5 12.5

Consumer Products 255.2 230.4 213 202.2 210.6

Architectural Coatings And Related Process Solvents 119.7 104.6 87.7 76.4 79.8

Pesticides/Fertilizers 59.1 47.1 36.8 42 41.9

Asphalt Paving / Roofing 27 28.4 29 30.6 31.9

Residential Fuel Combustion 95.4 71.5 57.5 57.8 57.8

Farming Operations 174.8 177 178.9 149.7 155.5

Construction And Demolition 0 0 0 0 0
B - 6

VOC Emissions (TPD) (continued)

Statewide 2000 2005 2010 2015 2020

Paved Road Dust 0 0 0 0 0

Unpaved Road Dust 0 0 0.3 0 0

Fugitive Windblown Dust 0 0 0 0 0

Structural and Automobile Fires 0.6 0.7 0.7 0.7 0.7

Managed Burning And Disposal 43.2 45.1 42.6 42.6 42.5

Cooking 6 6.3 6.7 7.1 7.6

Other (Miscellaneous Processes) 1.9 1.9 1.9 1.9 1.9

Light Duty Passenger (Lda) 500.8 283.9 191.8 90.1 51.9

Light Duty Trucks - 1 (Ldt1) 165.8 74.5 52.2 31 21.5

Light Duty Trucks - 2 (Ldt2) 160.5 93.7 72.8 43.5 29.4

Medium Duty Trucks (Mdv) 59 63.8 62.8 49.2 41.5

Light Heavy Duty Gas Trucks - 1 (Lhdv1) 16.5 30.2 29.2 21 17.3

Light Heavy Duty Gas Trucks - 2 (Lhdv2) 12.5 5.3 2.9 1.6 1.1

Medium Heavy Duty Gas Trucks (Mhdv) 20 10.4 7.6 3.6 2

Heavy Heavy Duty Gas Trucks (Hhdv) 8 2.6 1.9 0.8 0.4

Light Heavy Duty Diesel Trucks - 1 (Lhdv1) 0.7 3.2 4 3.3 2.7

Light Heavy Duty Diesel Trucks - 2 (Lhdv2) 0.7 0.9 0.9 0.8 0.7

Medium Heavy Duty Diesel Trucks (Mhdv) 8 7.9 5.1 2.8 1.8

Heavy Heavy Duty Diesel Trucks (Hhdv) 37.1 38.6 23.7 13.8 14.3

Motorcycles (Mcy) 48.5 48.4 41.5 31.6 31.1

Heavy Duty Diesel Urban Buses (Ub) 1.5 1.4 1.3 1.2 1.1

Heavy Duty Gas Urban Buses (Ub) 1.8 1.3 1.1 0.9 0.9

School Buses - Gas (Sbg) 1.5 1.1 0.7 0.5 0.3

School Buses - Diesel (Sbd) 0.8 0.7 0.5 0.1 0.1

Other Buses - Gas (Obg) 2.2 2.2 1.5 1.1 0.9

Other Buses - Motor Coach - Diesel (Obc) 0.6 0.6 0.4 0.2 0.2

All Other Buses - Diesel (Obd) 0.5 0.5 0.3 0.1 0.1

Motor Homes (Mh) 8.3 3.8 2.5 1.5 0.9

Aircraft 26.5 26.2 27.8 30.3 33.8

Trains 11.5 12.2 8.3 7.6 6.1

Ships And Commercial Boats 0 0 0 0 0

Ocean Going Vessels 6.9 8.8 8.3 11.2 14.5

Commercial Harbor Craft 5.3 5.1 4.8 4.3 4.2

Recreational Boats 143.8 126.5 107.1 87.5 72.4

Off-Road Recreational Vehicles 30.1 39.8 36.6 32.2 31.5

Off-Road Equipment 195.4 177.4 132.3 110.9 100.1

Farm Equipment 30.1 26.2 20.7 14.9 10.7

Fuel Storage And Handling 50.3 35.7 20.5 14.9 12.3

Total (TPD) 2902.3 2261.6 1943.2 1624.1 1560.9
B - 7

PM2.5 Emissions (TPD)

Statewide 2000 2005 2010 2015 2020

Electric Utilities 6.9 5.6 5.1 4.8 5

Cogeneration 3.7 2.9 3 2.6 3.2

Oil And Gas Production (Combustion) 1.9 1.8 2.1 1.9 1.7

Petroleum Refining (Combustion) 4 3.4 3.4 1.8 1.8

Manufacturing And Industrial 8.9 5.9 5.9 4.8 4.8

Food And Agricultural Processing 2.4 2.2 1.7 1.3 1.1

Service And Commercial 5.1 3.9 4.8 4.5 4.7

Other (Fuel Combustion) 4.6 3.6 0.7 0.6 0.5

Sewage Treatment 0 0 0 0 0

Landfills 0.3 3.1 0.3 0.5 0.5

Incinerators 0.1 0.3 0.2 0.1 0.1

Soil Remediation 0 0 0 0 0

Other (Waste Disposal) 0.1 0.1 0 0 0.1

Laundering 0 0 0 0 0

Degreasing 0 0 0 0.1 0.1

Coatings And Related Process Solvents 1.1 1.8 1.7 1.8 2

Printing 0 0.2 0.2 0.2 0.2

Adhesives And Sealants 0 0 0 0 0

Other (Cleaning And Surface Coatings) 0 0 0.1 0.8 0.8

Oil And Gas Production 0.1 0.1 0 0 0

Petroleum Refining 2 3.3 3 1.5 1.5

Petroleum Marketing 0.1 0 0 0 0

Other (Petroleum Production And Marketing) 0 0 0 0 0

Chemical 3.1 1.9 1.6 1 1.1

Food And Agriculture 4 3.6 3.3 3.5 3.9

Mineral Processes 24.1 26.1 22.7 22.9 24.8

Metal Processes 1 0.8 0.7 0.4 0.4

Wood And Paper 9.5 9.1 6.6 7.3 8.1

Glass And Related Products 1.4 1.8 0.6 0.5 0.5

Electronics 0 0 0 0 0

Other (Industrial Processes) 7.4 9.2 13.9 1.5 1.7

Consumer Products 0 0 0 0 0

Architectural Coatings And Related Process Solvents 0 0 0 0 0

Pesticides/Fertilizers 0 0 0 0 0

Asphalt Paving / Roofing 0 0 0 0 0

Residential Fuel Combustion 96 71.2 56.4 55.5 55.5

Farming Operations 28.5 21.8 21.4 21.1 20.9

Construction And Demolition 15.4 15.3 16.2 17.9 20.3
B - 8

PM2.5 Emissions (TPD) (continued)

Statewide 2000 2005 2010 2015 2020

Paved Road Dust 23.9 24.3 26.1 24.8 25.4

Unpaved Road Dust 27.8 27.9 25.5 27.1 27.1

Fugitive Windblown Dust 175.3 67.2 49 48.8 48.5

Structural and Automobile Fires 1 1.1 1.1 1.1 1.2

Managed Burning And Disposal 51.4 53.7 50.6 50.4 50.3

Cooking 25.8 26.5 28.1 29.8 31.6

Other (Miscellaneous Processes) 0.3 0.3 0.3 0.3 0.3

Light Duty Passenger (Lda) 15.5 12.3 11.4 11 11.2

Light Duty Trucks - 1 (Ldt1) 3.5 1.9 1.7 1.6 1.5

Light Duty Trucks - 2 (Ldt2) 5.3 4.4 4.1 4 4.1

Medium Duty Trucks (Mdv) 2 3.5 3.4 3.3 3.4

Light Heavy Duty Gas Trucks - 1 (Lhdv1) 0.3 0.7 0.7 0.7 0.7

Light Heavy Duty Gas Trucks - 2 (Lhdv2) 0.1 0.1 0.1 0.1 0.1

Medium Heavy Duty Gas Trucks (Mhdv) 0.1 0.1 0.1 0.1 0.1

Heavy Heavy Duty Gas Trucks (Hhdv) 0 0 0 0 0

Light Heavy Duty Diesel Trucks - 1 (Lhdv1) 0.4 1.3 1.5 1.3 1.1

Light Heavy Duty Diesel Trucks - 2 (Lhdv2) 0.4 0.4 0.4 0.4 0.3

Medium Heavy Duty Diesel Trucks (Mhdv) 6.3 6.4 4.2 2.4 1.6

Heavy Heavy Duty Diesel Trucks (Hhdv) 23.7 24.6 17.4 6.2 5.5

Motorcycles (Mcy) 0.1 0.1 0.1 0.1 0.1

Heavy Duty Diesel Urban Buses (Ub) 1.4 1.2 1.2 1.2 1.2

Heavy Duty Gas Urban Buses (Ub) 0 0 0 0 0

School Buses - Gas (Sbg) 0 0 0 0 0

School Buses - Diesel (Sbd) 0.7 0.6 0.5 0.2 0.2

Other Buses - Gas (Obg) 0 0 0 0 0

Other Buses - Motor Coach - Diesel (Obc) 0.4 0.4 0.3 0.1 0.1

All Other Buses - Diesel (Obd) 0.4 0.4 0.2 0.1 0.1

Motor Homes (Mh) 0.2 0.2 0.2 0.1 0.1

Aircraft 7.8 7.5 7.7 8.2 8.9

Trains 4.2 4.4 2.7 2.9 2.5

Ships And Commercial Boats 0 0 0 0 0

Ocean Going Vessels 15.2 19.5 7.1 4.1 5.3

Commercial Harbor Craft 3.4 3.1 2.6 1.7 1.2

Recreational Boats 6.2 5.9 4.9 4 3.3

Off-Road Recreational Vehicles 0.2 0.3 0.3 0.3 0.3

Off-Road Equipment 16.9 16.9 11.7 10 7.8

Farm Equipment 8.5 7.6 6.1 4.5 3.3

Fuel Storage And Handling 0 0 0 0 0

Total (TPD) 660.4 523.8 446.9 409.8 413.7
Appendix C

Deciview Record (2000-2012)
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C - 1

Table C-1

Worst Days Deciview Record*

IMPROVE 

Monitor

Baseline 

Average 

(2000-2004)

2005 2006 2007 2008 2009 2010 2011 2012** 2018 

RPGs

TRIN* 17.4 na 19.7 13.9 23.1 12.7 12.4 13.9 17.1 16.4

LABE 15.1 13.5 14.4 12.2 16.9 13.9 10.4 11.7 15.9 14.4

LAVO 14.1 12.4 14.1 14.1 22.4 17.1 12.8 11.7 14.3 13.3

BLIS 12.6 12.0 12.5 14.8 16.8 12.0 10.0 11.2 11.0 12.3

HOOV 12.9 10.4 10.5 12.6 15.5 12.0 8.8 8.6 9.8 12.5

YOSE 17.6 15.7 15.9 17.7 18.6 16.5 12.8 14.4 13.9 16.7

KAIS* 15.5 15.2 na 16.2 17.4 14.1 13.1 13.7 12.8 14.9

SEQU 25.4 23.1 23.4 24.7 24.7 21.0 20.1 21.2 20.6 22.7

DOME* 19.4 na na 20.9 19.3 17.6 16.7 17.1 17.0 18.1

REDW* 18.5 18.1 20.8 18.2 19.8 18.9 na 17.2 16.5 17.8

PORE 22.8 22.3 22.0 22.4 22.1 21.3 22 20.2 20.1 21.3

PINN 18.5 18.1 17.9 18.3 19.8 17.8 15.1 16.4 15.6 16.7

RAFA 18.8 18.3 20.2 20.6 19.6 17 16.6 16.5 15.7 17.3

SAGA* 19.9 19.5 17.4 17.4 17.9 na na na 14.3 17.4

SAGO 22.2 21.5 19.9 21.5 20.2 19.2 16.7 15.9 16.1 19.9

AGTI* 23.5 21.2 na 22.0 21.0 19.4 18.4 18.1 17.8 21.6

JOSH 19.6 19.4 18.1 18.1 16.7 16.8 14.7 14.2 14.9 17.9

Table C-2

Best Days Deciview Record*

IMPROVE 

Monitor

Baseline 

Average 

(2000-2004)

2005 2006 2007 2008 2009 2010 2011 2012**

TRIN* 3.4 na 2.1 3.9 4.0 2.6 1.9 2.8 2.2

LABE 3.2 2.9 2.4 3.6 2.6 2.5 2.5 3.1 2.3

LAVO 2.7 2.5 2.2 2.9 2.8 2.4 1.6 2.1 1.8

BLIS 2.5 2.1 2.0 2.7 2.2 1.9 1.6 2.1 1.5

HOOV 1.4 1.1 1.3 1.7 1.2 1.1 0.9 1.3 0.9

YOSE 3.4 3.2 3.4 3.9 2.0 2.3 1.8 2.7 2.8

KAIS* 2.3 1.2 na 1.8 1.4 1.8 1.1 1.5 1.0

SEQU 8.8 7.2 7.7 9.2 9.3 6.2 5.7 7.5 6.8

DOME* 5.1 na na 5.7 4.9 4.8 3.9 5.6 3.7

REDW* 6.1 5.7 5.9 6.0 5.4 4.9 na 6.7 4.7

PORE 10.5 9.8 9.6 8.9 9.5 7.8 8.0 8.8 6.9

PINN 8.9 8.0 7.9 8.5 8.4 7.2 7.2 7.6 7.0

RAFA 6.4 5.0 5.2 6.8 5.9 4.6 4.2 4.5 4.3

SAGA* 4.8 4.3 4.4 5.4 3.7 na na na 2.7

SAGO 5.4 4.1 5.0 5.5 4.4 3.6 3.0 3.3 3.5

AGTI* 9.6 6.9 na 9.0 7.5 6.3 6.8 6.0 6.7

JOSH 6.1 5.5 5.7 5.7 5.1 4.4 4.5 4.3 4.2

* Complete data was not available for the years marked “na.”

** Data made available February 28, 2014 is outside the Mid-Course Review time frame but is shown 

here for continuity, and to illustrate further progress.
C - 2

Table C-3

Statewide 2018 Reasonable Progress Goal Summary using 2012 Data

IMPROVE 

Monitor California Class I Area(s)

Best Days 

Baseline 

(dv)

Best Days 

(2008-2012) 

(dv)

Visibility 

Change 

(dv)

Worst Days 

Baseline (dv)

Worst Days 

(2008-2012) 

(dv)

Visibility 

Change 

(dv)

2018 

RPG

(dv)

Progress to 

2018 RPG

by 2012

NORTHERN CALIFORNIA

TRIN Marble Mountain W.

Yolla Bolly-Middle Eel W. 3.4 2.7 0.7 17.4 15.8 1.6 16.4 160%

LABE Lava Beds N.M.

South Warner W. 3.2 2.6 0.6 15.1 13.7 1.4 14.4 200%

LAVO

Lassen Volcanic N.P.

Caribou W.

Thousand Lakes W.

2.7 2.1 0.6 14.1 15.6 -1.5 13.3 -188%

SIERRA CALIFORNIA

BLIS Desolation W.

Mokelumne W. 2.5 1.9 0.6 12.6 12.2 0.4 12.3 133%

HOOV Hoover W. 1.4 1.1 0.3 12.9 10.9 2 12.5 500%

YOSE Yosemite N.P.

Emigrant W. 3.4 2.3 1.1 17.6 15.2 2.4 16.7 267%

KAIS

Ansel Adams W.

Kaiser W.

John Muir W.

2.3 1.4 0.9 15.5 14.2 1.3 14.9 217%

SEQU Sequoia N.P.

Kings Canyon N.P. 8.8 7.1 1.7 25.4 21.5 3.9 22.7 144%

DOME Dome Lands W. 5.1 4.6 0.5 19.4 17.5 1.9 18.1 146%

COASTAL CALIFORNIA

REDW Redwood N.P. 6.1 5.4 0.7 18.5 18.1

(missing 2010) 0.4 17.8 57%

PORE Point Reyes N.S. 10.5 8.2 2.3 22.8 21.2 1.6 21.3 107%

PINN Pinnacles W.

Ventana W. 8.9 7.5 1.4 18.5 16.9 1.6 16.7 89%

RAFA San Rafael W. 6.4 4.7 1.7 18.8 17.1 1.7 17.3 113%

SOUTHERN CALIFORNIA

SAGA San Gabriel W.

Cucamonga W. 4.8 3.2 1.6 19.9 16.1

(2008,2012 only) 3.8 17.4 152%

SAGO San Gorgonio W.

San Jacinto W. 5.4 3.6 1.8 22.2 17.6 4.6 19.9 200%

AGTI Agua Tibia W. 9.6 6.7 2.9 23.5 18.9 4.6 21.6 242%

JOSH Joshua Tree N.P. 6.1 4.5 1.6 19.6 15.4 4.2 17.9 247%

W = Wilderness N.M. = National Monument N.P. = National Park N.S. = National Seashore
Appendix D

Technical Analyses of Factors Impeding Progress
This page intentionally left blank.
D - 1

Purpose of Focused Technical Analysis

The annual deciview levels in California are trending downward over the long-term, as 

measured by the IMPROVE monitors, indicating diminishing light extinction from hazecausing pollutants in ambient air. Episodic events, such as wildfires and dust storms, 

cause short-term increases in the concentrations of these pollutants. These events are 

predominately natural in origin, but can be significant. Some of the episodic wildfire 

emissions are substantial enough to skew an annual average, and influence the fiveyear average trend. There are other activities, beyond the regulatory jurisdiction of the 

State of California, which also influence the deciview levels at some sites. The following 

Case Studies analyze the data from three monitoring sites to explain how these events 

and activities impede short-term progress in otherwise long-term visibility 

improvements.

ARB examined five-year deciview average trends at the IMPROVE monitors 

representing California’s Class 1 Areas and selected the three IMPROVE monitors that 

did not show short-term progress in the reporting period ending with 2011 IMPROVE 

monitoring data. Individually, the BLIS, LAVO, and REDW monitors have collected data 

for over twenty years and show long-term visibility improvements. The ARB emissions 

inventory shows continuous reductions in emissions from the RH Plan control strategy, 

which should assure improved visibility. Closer examination of the monitoring data 

comprising the five-year averages through 2011, shows how reasonable progress from 

the reductions in anthropogenic emissions within California’s jurisdiction is sometimes 

masked by uncontrollable factors. These uncontrollable factors are pollution from 

natural events and man-made emissions beyond the regulatory jurisdiction of individual 

states.

IMPROVE monitoring data for 2012 was posted to the WRAP-TSS website, on 

February 28, 2014. See http://vista.cira.colostate.edu/tss/Results/HazePlanning.aspx to 

use the interactive Haze Planning tool and view the monitoring data and recent five-year 

deciview averages. 
D - 2

Case Study: BLIS

Wildfire Impacts

Organic carbon (OMC) is the primary driver of haze on Worst Days at BLIS. Figure D-1 

shows that in every year in the past decade, except 2010, OMC has contributed more 

than any other species to light extinction on Worst Days. The years with higher OMC 

extinction correlate with wildfire smoke impacts. Notably, in 2010, when no significant 

wildfires affected BLIS, the OMC contribution to extinction was less than natural 

Rayleigh gas scattering. Rayleigh scattering consists mainly of light scattering from 

atmospheric gases that are smaller in diameter than the wavelength of incoming light. 

Additional light scattering and light absorption by larger particulate matter are what adds 

to haze. Gaps in data in 2004 meant that neither Best nor Worst Days averages could 

be calculated that year.

Figure D-1

Species Driving Light Extinction at BLIS on Worst Days

Figure D-2 shows the relationship between OMC light extinction and deciview for each 

sampling day at BLIS since 1990. Although there are wildfire impact days in almost 

every year in the past decade, the magnitude of natural wildfire smoke impacts at BLIS 

is most obvious in 2008. Fifty-seven named wildfires were burning at the same time in 

California, consuming more than one million acres of primarily forested natural areas. 

The American River Complex wildfire (20,500 acres) was the largest of the six named 

fires within 50 miles of the BLIS monitor during June through August. Figure D-2 shows 

that in 2008, daily OMC extinction and deciview levels reached the highest levels in 21 

0

10

20

30

40

50

60

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Inverse Megameters

BLIS: WORST Days - Annual Average Species Extinction

Rayleigh

OMC Extinction

SO4 Extinction

NO3 Extinction

EC Extinction

CM Extinction

Soil Extinction

SeaSalt Extinction

Note: There was insufficient data to calculate the Worst Days average in 2004.
D - 3

years of recordkeeping at BLIS. The five worst deciview days in 2008 had OMC 

extinction values 5-33 times the average levels for that time of year. Those five days 

alone caused a 3.0 deciview increase in the Worst Days annual average for 2008.

Figure D-2

Historical Record of OMC Extinction and Deciview Levels at BLIS

Table D-1 shows how the Worst Days annual averages pattern for OMC light extinction 

(green column) corresponds with that for deciviews (last column) in the past decade. 

The slopes of the trend lines from 2000-2011, for each species contribution, are shown

on the bottom line. The slopes indicate that almost all species are trending downward 

in their contribution to light extinction (haze) since 2000. The increasing trend in light 

extinction due to sea salt was not analyzed further because its contribution to light 

extinction is negligible, and the source is natural. Elemental carbon (EC) is occasionally 

elevated from wildfire smoke, but the annual average Worst Days EC extinction level is 

decreasing over the long term due to the strict regulation of diesel-fuel combustion 

emissions, which also generate EC. The dramatic decrease in nitrate extinction is 
D - 4

attributed to NOx source controls. The high OMC light extinction in 2008 correlates with 

the Lightning Strike Complex Fires.

Table D-1

Annual Averages for Worst Days

Light Extinction (in lnverse Megameters) and Deciviews at BLIS

Year* Sulfate 

Extinction

Nitrate 

Extinction

Organic 

Carbon 

Extinction

Elemental 

Carbon 

Extinction

Fine Soil 

Extinction

Coarse 

Mass 

Extinction

Sea Salt 

Extinction

Rayleigh 

Gas 

Extinction

Deciview

2000 5.29 3.55 9.5 2.8 0.47 1.51 0 9 11.6

2001 4.91 2.74 15.78 3.48 1.91 3.21 0.01 9 13.4

2002 4.56 2.15 17.36 3.26 1.04 1.91 0 9 13.4

2003 5.54 1.06 13.57 2.42 0.62 1.78 0.06 9 12.2

2005 6.79 1.77 11.4 3.12 0.51 1.86 0.03 9 12

2006 6.34 1.38 14.42 2.81 0.86 2.42 0.05 9 12.5

2007 5.79 3.67 22.75 3.88 0.77 2.17 0.11 9 14.8

2008 6.3 2.08 49.24 6.29 0.94 2.25 0.08 9 16.8

2009 4.86 1.69 13.54 2.42 0.69 1.97 0.07 9 12

2010 4.52 2.31 7 1.58 1.09 2.13 0.09 9 10

2011 4.89 1.19 12.51 2.49 0.4 1.99 0.18 9 11.2

SLOPE -0.01 -0.09 0.45 -0.02 -0.03 -0.003 0.01 constant -0.05

*Insufficient sampling points for calculating Worst Days averages for 2004.

Although the annual Worst Days deciview average trends downwards, further analysis 

shows that elevated OMC extinction on Worst Days in 2008 subsequently impeded the 

rate of progress measured by the 5-year rolling average. If the top five Worst Days 

occurring during the Lightning Strike Complex Fires are excluded, recalculation of the 

2008 OMC light extinction average becomes 17.0 inverse megameters, and the slope of 

the trendline for OMC becomes -0.01 (decreasing trend.) If those same top five Worst 

Days are not included in the Worst Days annual average by deciviews, the 2008 

deciview level would be 13.8 dv. As shown in Table D-2, the 5-year rolling average 

changes to a decreasing trendline.

Table D-2

BLIS without Wildfire Days

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 Slope

Deciview 11.6 13.4 13.4 12.2 12 12.5 14.8 16.8 12 10 11.2 -0.05

5-year Rolling 

Average

12.7 12.8 12.5 12.9 14.0 13.6 13.2 13.0 0.11

Recalculated 

2008 Deciview

11.6 13.4 13.4 12.2 12 12.5 14.8 13.8 12 10 11.2 -0.10

Recalculated 

5-year Rolling 

Average

12.7 12.8 12.5 12.9 13.3 13.0 12.6 12.4 -0.01
D - 5

Annual deciview values and the forecast trendlines to 2018 (dashed line) are plotted in 

Figure D-3 to show progress to the 2018 RPG. The trendlines are regression lines that 

display a straight-line trend based on available data. While they cannot forecast a longterm glide path, they illustrate the sensitivity of trends to single point changes. The top 

graph shows how the 5-year rolling average for Worst Days would change with the 

substitutions made for 2008. In the absence of large wildfire impacts, visibility at BLIS is 

improving, even though the 2008 data dampens progress for the 5-year rolling average 

from 2008 through 2011. Wildfire smoke also led to several Worst Days in 2007 at 

BLIS. If those days are also removed from annual average calculations, the rolling 

averages for 2007 through 2011 improve even more, as shown in the lower graph.

Figure D-3

BLIS: Worst Days Averages with Wildfire Adjustments

0

2

4

6

8

10

12

14

16

18

2000200120022003200420052006200720082009201020112012201320142015201620172018

Deciviews

2018 RPG

Annual Worst Days

Average (no

substitution)

5-Year Rolling

Average

5-Year rolling

average with 2008

substitution

Linear (Annual

Worst Days Average

(no substitution))

0

2

4

6

8

10

12

14

16

18

2000200120022003200420052006200720082009201020112012201320142015201620172018

Deciviews

2018 RPG

Annual Worst Days

Average without

Wildfire Days

5-Year Rolling

Average without

Wildfire Days

Linear (Annual Worst

Days Average

without Wildfire

Days)

Linear (5-Year

Rolling Average

without Wildfire

Days)
D - 6

The BLIS monitor is located in El Dorado County. It represents the Desolation 

Wilderness in Placer and El Dorado Counties and the Mokelumne Wilderness in Alpine, 

Amador and Calaveras counties. A quick examination of the emissions inventories for 

these surrounding counties further illustrates the impact of wildfires. Total organic gas 

(TOG) emissions are used as a surrogate for OMC because they include the building 

blocks for organic aerosol molecules, in the absence of a precise inventory of directly 

emitted organic aerosols.

The local emissions inventory of Reactive Organic Gases (ROG) from anthropogenic 

sources in these counties is decreasing. The 10-year average of natural ROG sources 

(predominately from biogenic emissions) is included for comparison. Emissions from 

natural sources make up more than 50 percent of the ROG inventory. Figure D-4

shows that despite natural source emissions, anthropogenic source control strategies 

are effectively reducing precursor emissions. The summary result is that the annual 

Worst Days deciview average at BLIS is trending downward, despite the progress 

impeded by the impacts of uncontrollable sources on visibility.

Figure D-4

Local Inventory Changes Over Time

0

20

40

60

80

100

120

140

160

2000 2005 2008 2010 2015 2020

Tons Per Day

Year

ROG Emissions Inventory for 5 Counties Surrounding BLIS

Placer

El Dorado

Calaveras

Amador

Alpine

5-County Natural ROG

(10-Year Average)

5-County Total

Anthropogenic ROG
D - 7

Impact of 2012 data for BLIS

The 2012 Worst Days deciview average for BLIS is 11.0 dv. The five-year Worst Days 

Rolling Average for the years 2008-2012 at BLIS is 12.2 dv. Both of these deciview 

values are below 12.3 dv, the 2018 RPG for BLIS. The years after 2008 were low 

wildfire impact years at BLIS, as indicated by the OC extinction levels on the Worst 

Days from 2008 through 2012, shown below in Figure D-5. The single high OMC 

extinction days in 2011 and 2012 contribute to high deciview days, but the remaining 

days have deciview levels slightly lower than those prior to 2008, shown in Figure D-2.

Figure D-5

Recent OMC Extinction and Deciview Levels at BLIS on Worst Days (2008-2012)
D - 8

Case Study: LAVO

Wildfire Impacts

Data has been collected at the LAVO monitoring site since 1988. Comparing pre-2000 

data for all sampling days with that from 2000-2011 shows that OMC contributions to

total light extinction increased 60 percent while other contributions decreased slightly on 

average. The net effect is a very slight decrease in the decadal deciview average, for 

all monitored days. Figure D-6 shows light extinction for all sampling days over two 

decades. The Best Days annual average is improving, as is the average for all 

Sampling Days. The following analysis shows that wildfire smoke, rather than 

anthropogenic sources, are skewing long-term progress on Worst Days.

Figure D-6

Changes in Light Extinction at LAVO – All Sampling Days

Wildfire Smoke and OMC Extinction

Worst Days occur most frequently June through September at LAVO. Elevated organic 

mass extinction tracks with the occurrence of Worst Days. OMC extinction at LAVO can 

be about 40 percent of total extinction on Worst Days. No Best Days occurred in July or 

August from 2000 through 2011, when organic mass extinction contributions are 

normally at their highest. The fire season begins in May or June and can run through 

November, depending on moisture conditions. There are almost no residences having 

the potential to generate woodsmoke near LAVO, which is why there is very low organic 

matter extinction in winter months. This pattern is the basis for suggesting that wildfire 

smoke alone can skew the annual deciview levels and mask progress in reducing 

anthropogenic emissions.

38%

26%

13%

8%

8%

5% 2%

<0.5%

LAVO - LIGHT EXTINCTION 1988-1999

Rayleigh

OMC Extinction

SO4 Extinction

CM Extinction

EC Extinction

NO3 Extinction

Soil Extinction

SeaSalt Extinction

Total Extinction Average: 25.96 Inverse Megameters

31%

42%

12%

4%

6% 4% 1% <0.5%

LAVO - LIGHT EXTINCTION 2000-2011

Rayleigh

OMC Extinction

SO4 Extinction

CM Extinction

EC Extinction

NO3 Extinction

Soil Extinction

SeaSalt Extinction

Total Extinction Average: 25.35 Inverse Megameters
D - 9

The long-term Worst Days deciview average for 1989 through 2011 is 14.3 dv, higher 

than the 2000-2004 baseline average of 14.1 dv. In the recent years of 2002, 2008, and 

2009, both averages were exceeded. In those specific years, large wildfires occurred in 

southern Oregon or northern California with wildfire smoke impacting the monitor. 

Every other year since 2000 was equal to or below the baseline Worst Day average 

(14.1dv.) Figure D-7 shows the particle species and Rayleigh contribution to light 

extinction on Worst Days since 2000, demonstrating the influence of OMC contributions 

to haze.

Figure D-7

Relative Contributions to Total Light Extinction at LAVO

The charts in Figure D-8 compare the Worst Days deciview levels for 2008 with the 

contributions to light extinction on those days. The highest deciview values correlate 

with the highest OMC contributions to light extinction, and coincide with the timing of the 

2008 Lightning Strike Complex fires. There is a 23-deciview spread between the 

minimum and maximum values for Worst Days in 2008, with the two highest values 

almost two standard deviations from the average. OMC has the highest contribution to 

light extinction in every Worst Day above the Worst Day annual average, evidence of its 

strength in controlling the twenty percent Worst Days average.

0.0

10.0

20.0

30.0

40.0

50.0

60.0

70.0

80.0

90.0

100.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011

Inverse Megameters

LAVO: Contributions to Light Extinction on Worst Days

Rayleigh

Organic Carbon

Sulfate

Elemental Carbon

Nitrate

Coarse Mass

Fine Soil

Sea Salt
D - 10

Figure D-8

Comparison of Deciview Value and Causes of Light Extinction (2008)

Several very high deciview days also occur in 2009. Two in July are more than two 

standard deviations from the average. They correspond with high OMC extinction days, 

as shown in Figure D-9. At that time, there were several wildfires close to the 

southeastern corner of Shasta County, where the LAVO monitor is located, as shown in 

Figure D-10. As with 2008, all of the days above the annual average for Worst Days 

were driven by elevated OMC.

0

5

10

15

20

25

30

35

40

5/3/2008

5/10/20085/17/20085/24/20085/31/2008

6/7/2008

6/14/20086/21/20086/28/2008

7/5/2008

7/12/20087/19/20087/26/2008

8/2/20088/9/2008

8/16/20088/23/20088/30/2008

9/6/2008

9/13/20089/20/20089/27/200810/4/2008

10/11/200810/18/2008

Deciviews

LAVO 2008 Worst Days (Deciviews)

Annual Deciview Worst Day Average (22.4 dv)

Daily Worst Day deciview

one standard deviation

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

5/3/2008 6/3/2008 7/3/2008 8/3/2008 9/3/2008 10/3/2008

Percent Contribution to Light Extinction

LAVO 2008 Worst Days (Light Extinction)

Rayleigh Organic Carbon Sulfate Elemental Carbon Nitrate Coarse Mass Fine Soil Sea Salt
D - 11

Figure D-9

Comparison of Deciview Value and Causes of Light Extinction (2009)

The Table D-3 lists the dates of wildfires in counties close to LAVO, to compare with 

deciview levels at the same time. There is fluctuation in the monitor values over the 

0

5

10

15

20

25

30

35

4/28/2009

5/5/2009

5/12/20095/19/20095/26/2009

6/2/20096/9/2009

6/16/20096/23/20096/30/2009

7/7/2009

7/14/20097/21/20097/28/2009

8/4/2009

8/11/20098/18/20098/25/2009

9/1/20099/8/2009

9/15/20099/22/20099/29/200910/6/2009

10/13/200910/20/200910/27/2009

11/3/2009

11/10/2009

Deciviews

LAVO 2009 Worst Days (Deciviews)

Annual Deciview Worst Day Average (17.1 dv) Daily Worst Day deciview

one standard deviation

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

4/28/2009 5/28/2009 6/28/2009 7/28/2009 8/28/2009 9/28/2009 10/28/2009

Percent Contribution to Light Extinction

LAVO 2009 Worst Days (Light Extinction)

Rayleigh Organic Carbon Sulfate Elemental Carbon Nitrate Coarse Mass Fine Soil Sea Salt
D - 12

several weeks of active and smoldering fires, as the wind shifts and alters the tracks of 

smoke plumes.11

Table D-3

Large Wildfires (>500 acres)

Year Fire Name Location & Acreage Dates

2008 Lightning Strike 

Complex

See Figure 8 6/22 through 8/11/2008

2009 Backbone Trinity Alps/Trinity County 7/7/09

2009 Tennant Macdoel/Siskiyou County 7/19/09

2009 Dodge Complex

SHU Lightning

Lassen County, 1,601 acres

Shasta County, 17,623 acres

8/1 through 8/18, 2009

2009 Hat Creek Complex Lassen/Shasta Counties, 11,269 

acres

8/1 through 8/26, 2009

2009 Day Lassen County 8/27/09

2009 Silver Meadow Valley/Plumas County 9/19/09

Figure D-10

Location of 2008 Wildfires near LAVO

 

11 http://www.arb.ca.gov/smp/wildfire/wildfire.htm

LAVO
D - 13

There is a ten-deciview spread between the highest (22.4 dv in 2008) and lowest 

(11.7dv in 2011) Worst Days annual averages in the past ten years at LAVO. The large

variation is shown in Figure D-11. The two most recent years, 2010 and 2011, are 

actually below the 2018 RPG of 13.3 dv, in contrast with the two highest values in the 

two prior years. Both 2008 and 2009 are in five-year averaging periods for several 

consecutive years, flattening the linear forecast trendline for the five-year rolling 

average shown as the dashed blue line in Figure D-11. They also flatten the linear 

forecast trendline for the annual Worst Days deciview average, shown as the solid 

brown line. As previously noted, these trendlines do not forecast a long-term glide path, 

but they do illustrate the sensitivity of the short-term slope to single year point values.

Figure D-11

Forecast Trend Lines for LAVO

If the two wildfire-impacted years of 2008 and 2009 are excluded from the Worst Days 

annual averages, the linear forecast trendline (dashed red line) approaches the 2018 

RPG. Otherwise, the annual average trendline (solid red line) is level. The solid blue 

line shows the forecast trendline for the five-year rolling average. If only the highest 

smoke-impacted days are removed from the calculation of the 2008 and 2009 Worst 

Days averages (the new values for 2008 and 2009 are the orange triangles), the five13.3

0

5

10

15

20

25

Baseline 2006 2008 2010 2012 2014 2016 2018

Deciviews

2018 RPG (13.3 dv)

Annual Average

Annual Average Without 2008-2009 Wildfire Days

5-year Rolling Average

5-year Rolling Average without 2008-9 Wildfire Days

Linear (Annual Average)

Linear (Annual Average Without 2008-2009 Wildfire Days)

Linear (5-year Rolling Average)

Linear (5-year Rolling Average without 2008-9 Wildfire Days )
D - 14

year average begins to level out (dashed blue line). This demonstrates the impact of 

outlier days from wildfire smoke on the rolling averages and forecasts. In 2010 and 

2011, the annual averages for Worst Days were actually lower (better) than the 2018 

RPG.

Reductions in the anthropogenic emissions inventory support a forecast of improved 

visibility, as shown in Figure D-12. Emissions of NOx, ROG, and SOx are all declining 

in the four counties surrounding LAVO. PM is the only increasing category due 

primarily to the formula predicting growth in road dust as vehicle miles traveled 

increases with population growth. Coarse Mass and Fine Soil are major components of 

road dust, but neither of these haze pollutants is a strong light extinguisher and both 

have limited impact on the Worst Days averages.

Figure D-12

Local Inventory Changes over Time

0

50

100

150

200

250

300

350

400

450

2000 2005 2008 2010 2015 2020

Tons Per Day

Year

TOTAL 4-County

Natural ROG*

TOTAL 4-County

Anthropogenic ROG

Shasta Total

Anthropogenic ROG

Tehama Total

Anthropogenic ROG

Plumas Total

Anthropogenic ROG

Lassen Total

Anthropogenic ROG

*Natural Inventory is 

multi-year average.
D - 15

Impact of 2012 data for LAVO

The 2012 Worst Days deciview average for LAVO is 14.3 dv. The five-year Worst Days 

Rolling Average for the years 2008-2012 at LAVO is 15.6 dv. Both of these deciview 

values are above 13.3 dv, the 2018 RPG for LAVO. While the Worst Days deciview 

annual averages were decreasing each year since the high year of the 2008-2012 

period, wildfire smoke in 2012 reversed the trend. In that year, a lightning strike wildfire 

started June 23 and burned more than 28,000 acres of predominately forested land 

through the containment date of August 22. As Figure D-13 below illustrates, the fire 

was located within 15 miles of the monitor.

Figure D-13

Reading Fire of 2012

Despite prevailing winds from the southwest, occasional easterly winds brought smoke 

to the LAVO monitor location. As a result, seven of the 23 Worst Days in 2012 occurred 

during that period. One of the days, August 19, 2012, recorded 41.9 dv, the highest 

deciview level measured since recordkeeping began in 1989. That value was nearly 

twice the next highest deciview level measured in 2012 (21.6 dv) and the OMC mass 

LAVO

Reading Fire Perimeter

Lassen Volcanic Park
D - 16

concentration that day was 12.3 times the average OMC mass on Worst Days that year. 

If that single high deciview day value is removed, and the Worst Days average 

recalculated for 2012, it would be 13.0 dv, lower than the 2018 RPG of 13.3 dv.
D - 17

Case Study: REDW

Impacts from Pacific Offshore Shipping and Wildfire Smoke

Since 1988, when data was first collected at REDW, all the long-term trends indicate 

that visibility is improving. Figure D-14 plots the Worst Days annual averages (brown), 

the All Sampling Days annual averages (green), the Best Days annual averages (blue), 

and the required rolling Worst Days 5-year averages (black). Examining this data 

further explains why visibility improvement appears to level off using the 2005-2009 and 

2007-2011 five-year averages. Figure D-12 shows the years 2006, 2008, and 2009

were the only years since 2000 above the long-term Worst Days annual average 

trendline (dashed brown line.) All three years skew the reported five-year average in 

Table 3 of the Progress Report and warrant further analysis.

Figure D-14

Long-Term Trends at REDW

If the long-term 5-year rolling average linear trend line (black dotted line) is extended to 

2018, the 5-year deciview average is predicted to be 17.3 dv. That is actually lower 

than the RPG of 17.8 dv. The annual Worst Days averages are also trending downward 

(brown dashed line) and could reach 17.1 dv by 2018. The Best and Worst Days 

annual averages are not available for 2010 due to incomplete data, however, the 

0

5

10

15

20

25

198819901992199419961998200020022004200620082010201320152017

Deciviews

WORST Days Annual

Average

Reasonable Progress

Goal (17.8 dv)

WORST Days 5-year

Rolling Average

Forecast for 5-year

Rolling Average

ALL Sampling Days

Annual Average

BEST Days Annual

Average

Linear (WORST Days

Annual Average)

Linear (WORST Days 5-

year Rolling Average)

Linear (ALL Sampling

Days Annual Average)

Linear (BEST Days

Annual Average)
D - 18

average of all avaliable data indicates that visibility was improving in 2010 also. The 

following discussion examines what caused the averages for 2006, 2008, and 2009 to 

be above the trendline.

Figure D-15 shows that sea salt, organic carbon, and sulfates contributed the most to 

light extinction on the Worst Days in 2006, 2008, and 2009. The year 2007 is included 

for comparison because the Worst Day deciview average is just under the long-term 

trendline for Worst Days. It is also one of the years in both the 2005-2009 and 2007-

2011 five-year averages. Seasonal contributions to light extinction by particles on the 

Worst Days for all the years show that the summer months have the most Worst Days 

at REDW. This is the time of year when organic mass and sulfate mass concentrations 

are usually at their highest at all California IMPROVE monitors. Sea salt is not analyzed 

further because it is a natural contributor to light extinction.

Figure D-15

Particle Contributions to Light Extinction on Worst Days 
D - 19

Figure D-16 shows the particle and natural Rayleigh gas scattering contributions to total 

light extinction for the Worst Days annual averages at REDW. Rayleigh is a natural and 

constant component of light extinction. Sea salt is a major natural component of haze 

found in coastal areas; the concentrations vary daily with ocean breezes. Disregarding 

sea salt and Rayleigh, sulfates are the strongest contributor to light extinction on Worst 

Days at REDW in the most recent years. Elevated deciview levels also occur when 

OMC light extinction is elevated, as it was in 2006, 2008, and 2009. Nitrate 

contributions are steadily declining, showing the effectivenes of California’s NOx control 

measures over time. The three remaining constitutuents – Coarse Mass, Elemental 

Carbon, and Fine Soil – have fluctuating contributions that are not significant enough in 

light extinction to impair visibility improvement at this time.

Figure D-16

Comparison of Light Extinction and Recent Deciview Levels

Whether the annual Worst Days average is below or above the long-term trend line 

appears to depend on the relative contributions of sulfates and OMC to light extinction 

in any given year. Trends in the emissions inventory for sources of SOx and reactive 

organic gases (ROG) gases, as precursors of sulfates and OMC, can be examined 

further to explain the high years.

The REDW monitor is located at 244 meters above sea level, within one mile of the 

Pacific Ocean, at the mouth of the Klamath River. The delta of the Klamath River is 

undeveloped, limiting the anthropogenic sources nearest REDW to local two-lane roads 

to a scenic overlook and a few homes and buildings. The REDW monitor is exposed to 

ocean fogs year-round, offshore emissions from ocean-going vessels, and smoke 

drainage down the Klamath River from inland wildfires during the dry season in the 

mountains. Elevated humidity also supports the formation of nitrates at lower 

0

5

10

15

20

25

30

2006 2007 2008 2009 2011

Light Extinction in Inverse Megameters

REDW: Contributions to Worst Days Extinction and Deciview Averages

SeaSalt Extinction

SO4 Extinction

Rayleigh

OMC Extinction

NO3 Extinction

CM Extinction

EC Extinction

Soil Extinction

20.8 dv 18.2 dv 19.8 dv 18.9 dv 17.2 dv

Note: The 2010 Worst Days Average is not available. The RPG at REDW is 17.3 dv.
D - 20

temperatures in the winter, although relatively few Worst Days occur then at REDW. 

Light extinction by sulfates, nitrates, and organic aerosols is heightened by elevated 

relative humidity, another factor causing higher haze levels at coastal locations 

nationwide.

The WRAP Summary Report shows an increase in sulfate extinction on Worst Days at 

four monitors near the Pacific coast at the Oregon-California border (REDW, TRIN, 

KALM, and CRLA). This area has very few SOx-emitting sources other than the 

influence from offshore shipping emissions, compared to more populated areas along 

the coast. The relative magnitude of offshore shipping emissions has a greater impact 

on this sparsely populated area. The location of shipping lanes is shown in Figure D-17

for comparison.

Figure D-17

Sulfate Extinction Trends Near Shipping Lanes

In the past decade traffic in these shipping lanes has increased dramatically in response 

to changes in global production and shipment of goods from Asia to North American 

markets. California has developed an inventory of emissions from ocean-going vessels 

(OGV) in shipping lanes within 100 nautical miles of the California coast. Since 2005, 

California has also implemented several control measures aimed at reducing in-port 

emissions and in-transit emissions for ships within 24 nautical miles of the California 

coastline. Vessels travelling outside the State’s jurisdictional control boundary may still 

burn higher sulfur fuel until after 2012, when international agreements to reduce the 

emissions from sulfur fuels begin scheduled implementation.
D - 21

Figure D-18 shows the increase in the relative magnitude of OGV SOx emissions within 

one hundred miles offshore of Del Norte and Humboldt Counties, north and south of 

REDW. The emissions are backcast and forecast, with growth and control factors 

applied, using 2008 as the base year. The emissions do not include the shipping 

emissions offshore the Oregon coast, a little more than 30 miles north of the REDW 

monitor, nor do they include emissions from Curry County in Oregon, the sparsely 

populated county north of the interstate border. The ocean-going vessel emissions of 

SOx along the California coast alone overwhelm the local anthropogenic sources of 

SOx from the two coastal California counties surrounding REDW and containing 

Redwood National Park.

Figure D-18

Anthropogenic Emissions near REDW

Forecasted growth in Pacific shipping will continue to impact REDW. Continued 

reductions of other anthropogenic sources of NOx and ROG will offset potential 

increases in sulfate formation by lessening nitrate and OMC formation. As evidence, 

the Worst Days annual average for 2011 already achieves the 2018 RPG. The relative 

reduction in OMC light extinction in 2011 occurred because there were fewer wildfire 

smoke incidents impacting REDW.

As shown in Figure D-19, wildfire smoke in the summer of 2008 also impacted REDW. 

Beginning in late June and lasting into September, nighttime drainage of wildfire smoke 

down the Klamath River was trapped in the marine layer near REDW. Figure D-19

illustrates how wildfire smoke results in high OMC contributions to light extinction. If just 

the highest of the smoke-related OMC-driven Worst Days is removed from the 

calculation of the annual average for 2008, the deciview level would be 19.3 dv. If the 

three highest smoke days during that time are removed, the Worst Days average would 

be 18.6 dv. When the Worst Days average in a single year is skewed due to very high 

wildfire smoke influence on a few days, both the annual average and the rolling 

averages are also elevated by this natural source. These statistics mask progress 

0

2

4

6

8

10

12

14

16

2000 2005 2010 2015 2020

Tons Per Day

SOx Emissions Inventory for Del Norte and Humboldt Counties

Anthropogenic, non-OGV

Ocean-Going Vessels (OGV)
D - 22

made by reductions in anthropogenic emissions. The 2018 RPG at REDW is 17.8dv. 

In 2011, the Worst Days average was 17.2 dv.

Figure D-19

Wildfire Smoke affects Deciview Calculation

0

5

10

15

20

25

30

2/6/08

2/20/08

3/5/08

3/19/08

4/2/08

4/16/084/30/085/14/085/28/086/11/086/25/08

7/9/08

7/23/08

8/6/08

8/20/08

9/3/08

9/17/0810/1/08

10/15/0810/29/0811/12/0811/26/0812/10/08

DECIVIEWS

REDW: 2008 Worst Days

Worst Days 2008 Worst Days Annual Average (19.8 dv) one standard deviation

0

20

40

60

80

100

120

140

160

2/3/08

2/17/08

3/2/08

3/16/083/30/084/13/084/27/085/11/085/25/08

6/8/08

6/22/08

7/6/08

7/20/08

8/3/08

8/17/088/31/089/14/089/28/08

10/12/0810/26/08

11/9/08

11/23/08

12/7/08

Light Extinction in Inverse Megameters

Sea Salt Sulfates OMC Rayleigh Nitrates Coarse Mass EC Fine Soil
D - 23

Impact of 2012 data for REDW

In 2011, and again in 2012, wildfire smoke impacts were not significant at REDW. The 

Worst Days annual average was 17.2 dv in 2011, and even lower in 2012, at 16.5 dv. 

Both of these values are below the 2018 RPG for REDW, 17.8 dv. The Worst Days 

annual average could not be calculated for 2010, giving additional weight to the 2008 

value in the most recent five-year averaging period. The 2008 Worst Days annual 

average skews the rolling 5-year average through 2012, masking progress made by 

reductions in anthropogenic emissions. Comparing the baseline period average of 

18.5 dv with the most recent five-year average of 18.1 dv for 2008-2012, indicates that 

visibility is improving at REDW, even if the rate of progress is slowed by high wildfire 

smoke days in the calculations for 2008. This improving visibility trend is shown by the 

linear trendlines in Figure D-20.

Figure D-20

Wildfire Smoke affects Deciview Calculation

0

5

10

15

20

25

2000200120022003200420052006200720082009201020112012201320142015201620172018

DECIVIEWS

REDW: 2000 - 2012

2018 RPG

Annual Worst Day

Average

5-Year Rolling Average

Linear (Annual Worst

Day Average)

Linear (5-Year Rolling

Average)
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Appendix E

Comments of Federal Land Management Agencies

with CARB Responses
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E – 1

Comments and Responses to the Letter from the U.S. Department of 

the Interior, National Park Service, dated March 27, 2014

1. Comment: “Please briefly discuss the major federal and state regulations 

beyond those implemented specifically under CA’s Regional Haze Plan that 

were included in CA’s reasonable progress goals, as these earlier 

requirements, plus those listed in Table 1, appear to account for most of the 

emissions reductions observed since 2000 in CA.”

Response: The RH plan includes a discussion of the regulations used to establish the 

2018 RPGs. The 2018 RPGs were based on rules adopted by the end of the baseline 

period, including those with quantifiable reductions scheduled for implementation after 

2004 and before 2018. The RH Plan also described the State strategy for continual 

adoption and implementation of measures to reduce emissions, for which reductions 

had not been quantified for the RH Plan modeling of the 2018 RPGs. The Progress 

Report lists new and modified rules adopted 2005 through 2011, which clearly have 

provided additional emission reduction benefits through 2020 that go beyond the 

emission reductions included in the RH Plan.

2. Comment: “Please clarify if CA’s Smoke Management Program meets the 

enhanced smoke management goals for states submitting plans under 40 CFR 

51.309. Are Class I Areas identified as sensitive receptors in CA’s Smoke 

Management Plan?”

Response: California elected to prepare its RH Plan pursuant to 40 CFR 51.308. 

California’s Smoke Management Program was established in State regulation at Title 17 

California Code of Regulations sections 80100- 80330. Class 1 Areas are listed and 

defined in the regulation and must be listed as sensitive smoke receptors in smoke 

management plans prepared by those conducting prescribed burns, with provisions 

made to minimize smoke impacts. The Progress Report has been updated to clarify 

that California’s Smoke Management Program identifies Class 1 areas as sensitive 

receptors.

3. Comment: “Please also provide a summary in tons/per year [for the 

emissions inventory], since the conversion from tons per day to tons per year 

likely differs for different emissions categories.”

Response: The California emissions inventory shown in the RH Progress Report is in 

tons per day, using the annual average. To obtain the emissions in tons per year, each 

daily value can be multiplied by 365. The Progress Report has been updated to include 

a statement to calculate tons per year.
E – 2

4. Comment: “Please cite or include in Appendix A the Western Regional [Air] 

Partnership Reasonable Progress Summary Report for California.”

Response: A citation and link has been added to Appendix A of the Progress Report 

for the California Section of the WRAP Reasonable Progress Summary Report, in 

addition to the link for the entire report.

5. Comment: “Please add to the discussion of impacts from off shore shipping 

that the North American Emissions Control Area international treaty limits 

sulfur dioxide content in fuels for marine vessels operating within 200 nautical 

miles of the US and Canadian coastlines, beginning in 2012.”

Response: Appendix D Case Study REDW includes a discussion of the impacts from 

off shore shipping. The benefits of the North American Emissions Control Area will 

begin to be reflected in the data beginning in 2012. Since the 2012 data became 

available after the Progress Report was prepared, California did not include an 

extensive analysis of this data. The summary graph below shows that sulfate is being 

reduced at all coastal sites with a sharp decline in 2012.

0

0.5

1

1.5

2

2.5

3

BASELINE 2005 2006 2007 2008 2009 2010 2011 2012

Mass (ug/m3)

YEAR

Sulfate Mass: Annual Average for All IMPROVE Sampling Days

REDW

PORE

PINN

RAFA

AQTI
E – 3

6. Comment: “CARB concludes that CA emissions reductions are sufficient to 

meet 2018 Reasonable Progress Goals. Please add a table comparing current 

emissions and current projections through 2020 to the 2018 emission 

projections that were used to set the Reasonable Progress Goals.”

Response: California is constantly making improvements to its emissions inventory 

both in methodology and data used to forecast. These updates and refinements are 

based on the best available information about changes in regulations, population, 

business, vehicle and travel data, and control technology implementation for the base 

year of an inventory update. These updates can cause emissions to increase or 

decrease relative to a previous inventory. Since the modeling that the RPGs were 

based on looked at changes on a relative basis, comparing inventories on a relative

basis is most appropriate. When comparing the RH Plan inventories with the Progress 

Plan inventories, Progress Plan emissions are being reduced at a greater rate for all 

pollutants compared to the RH Plan. Based on this comparison, California concluded 

that the emission reductions are sufficient to meet the 2018 RPGs.

7. Comment: “CARB asserts [that] CA emissions reductions are sufficient to 

lessen CA’s impact, and specifically CA’s contributions to ammonium nitrate, 

at neighboring Class 1 Areas. WRAP provided the western states with 

particulate source apportionment analyses using the CAMx regional air quality 

model for 2002 and 2018 inventories [including Crater Lake National Park in 

Oregon and Grand Canyon National Park in Arizona.] We suggest that 

[California] include such example plots to support CARB’s demonstration.”

Response: The plots referenced in your comment have not been updated by the 

WRAP since the RH Plan. As explained in Table 8.1 of the RH Plan, nitrates cause less 

than 10 percent of light extinction (haze) on Worst Days, on average, at Crater Lake in 

Oregon and at the Grand Canyon in Arizona. Nitrates are the second strongest 

extinguishers of light when compared to the other haze pollutants; therefore reducing 

their formation from NOx emissions is still an important visibility strategy. Due to new 

control measures, California NOx emissions will continue to decline beyond the levels 

included in the RH Plan.
E – 4

Comments and Responses to the Letter from the U.S. Department of 

Agriculture, Forest Service, dated April 8, 2014

1. Comment: A review of the US EPA’s “Interim Air Quality Policy” and ARB’s 

“Title 17” indicate that natural fires managed-for-resource-benefits (those 

meeting the objectives defined in Land/Resource Management Plans) to be 

considered as prescribed burns whereas the “Exceptional Event Rule” 

consider these as naturally ignited fires. We look forward to addressing this 

discrepancy with CARB. The FLMs and the California Air Resources Board 

(CARB) need to continue a dialogue in developing strategies, before the 

revision of the SIP in 2019, that can lead to less severe wildfires and thus 

attain the reduction required on targeted “worst days”.

Response: ARB will continue this discussion at a policy level through the regular Air 

and Land Managers meetings of policy makers from the public land management and 

air quality agencies in California. The technical issues relating to planned and 

unplanned burns and air quality will continue to be discussed by the technical staff 

participating in the regular meetings of California’s Interagency Air and Smoke Council. 

Both of these forums have operated for more than a decade to explore these issues, 

develop protocols, and advance practicable policies.
TRANSMITTED VIA ELECTRONIC MAIL - NO HARDCOPY TO FOLLOW

N3615 (2350)

March 27, 2014

Christine Suarez-Murias

California Air Resources Board

1001 I Street

Sacramento, CA 95812

Dear Ms. Suarez-Murias:

Thank you for the opportunity to review and comment on California’s Regional Haze Plan 2014 

Progress Report. We agree with California Air Resources Board (CARB)’s conclusion, 

consistent with the periodic reporting requirements of 40 CFR 51.308(g), that the emissions 

reductions under California’s Regional Haze Plan and other CARB requirements are sufficient 

for California and neighboring states to meet the 2018 Reasonable Progress Goals set in the 

State’s Regional Haze plan. We also agree that no further revision of the Regional Haze Plan is

needed at this time to meet the 2018 goals.

We suggest some additions to the draft Progress Report to better support California’s 

demonstration: 

 Section 2.1: Status of Emissions Control Strategies: Please briefly discuss the major 

federal and state regulations beyond those implemented specifically under CA’s Regional 

Haze Plan that were included in CA’s reasonable progress goals, as these earlier 

requirements, plus those listed in Table 1, appear to account for most of the emissions 

reductions observed since 2000 in CA. 

 Section 2.1: Please clarify if CA’s Smoke Management Program meets the enhanced 

smoke management goals for states submitting plans under 40 CFR 51.309. Are Class I 

areas identified as sensitive receptors in CA’s Smoke Management Plan? Section 1.3 is 

clear that wildfire is a major uncontrollable source impacting visibility in Class I areas in 

CA. A discussion of the possible role of prescribed fire in reducing wildfire smoke 

impacts to visibility is beyond the scope of this progress review, but is a topic for further 

discussion in developing the regional haze plan due in 2018. 

 Section 2.4 Emissions Inventory: CARB presents emissions in tons/day in Table 2 and 

Figure 3 that indicate decreasing emissions from 2000 to 2020. Please also provide a 

United States Department of the Interior

NATIONAL PARK SERVICE

Air Resources Division

P.O. Box 25287

Denver, CO 80225-0287

3


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