Regional Air Quality Modeling Results for Elemental and

Organic Carbon

John Vimont,

National Park Service

WRAP Fire, Carbon, and Dust Workshop

Sacramento, CA

May 23, 2006

Outline

• How well does the model perform for EC and OC?

• What changes are predicted in EC and OC concentrations on the worst visibility days between the 2002 and 2018 base cases?

• What is the influence of natural emissions in the 2002 base case and projections?

• Conclusions

CMAQ Model Performance By Month Across All WRAP IMPROVE Sites

CMAQ Model Performance By Month Across All WRAP IMPROVE Sites

CRLA

ROMO

CMAQ Model Performance for Elemental CarbonRocky Mountain – July 2002

CMAQ Model Performance for Organic CarbonRocky Mountain – July 2002

CMAQ Model Performance for Elemental CarbonRocky Mountain – February 2002

CMAQ Model Performance for Organic CarbonRocky Mountain – February 2002

CMAQ Model Performance for Elemental CarbonBadlands – July 2002

CMAQ Model Performance for Organic CarbonBadlands – July 2002

CMAQ Model Performance for Elemental CarbonBadlands – February 2002

CMAQ Model Performance for Organic CarbonBadlands – February 2002

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Primary Secondary Bio

Secondary Anthro Total OC

Primary Organic Carbon Concentrations (2002 Annual Average)Resulting From Natural Sources (Primarily Wildfire)

Primary Organic Carbon Concentrations (2002 Annual Average)Resulting From All Sources

Secondary Organic Carbon Concentrations (2002 Annual Average)

Resulting From Non-Fire Biogenic VOCs and No Anthro Emissions

Secondary Organic Carbon Concentrations (2002 Annual Average)

Resulting From Non-Fire Biogenic VOCs Plus Anthro Emissions

Change in Biogenic Organics

Relative Concentrations and Future ChangesIn Organic Carbon Sources

• At these six sites …

• 2nd Anthro: Contribution is small, but generally decreases

• 2nd Biogen: Contribution is large, varies significantly, but generally decreases

• Primary: Contribution is also large, but changes are more variable

Class I Area 2nd Anth 2nd Bio Primary 2nd Anth 2nd Bio Primary

Badlands 0.03 0.30 0.26 -2.7% 0.5% 10.3%

Sawtooth 0.04 1.03 0.34 -0.3% -4.0% -8.2%

Salt Creek 0.04 0.40 0.36 -7.3% -4.2% -14.7%

Rocky Mountain 0.05 0.85 0.29 -7.7% -4.8% -1.4%

Mount Rainier 0.13 1.61 0.72 6.6% -1.7% 5.6%

Yosemite 0.04 0.68 0.42 -20.7% -5.5% -4.3%

2018 Percent Change2002 Modeled Concentration

Major Caveats of CMAQ-Based Carbon Source Identification

• These results based on annual averages– Results likely different on 20% best and worst

visibility days

• Based solely on 2002 emissions– Not necessarily representative of long-term

(2064) natural conditions– Lead to very site-specific results

• Contributions vary across the region, even for non-fire biogenic sources

Percent Change in Annual AverageAnthropogenic Secondary Organic Carbon Concentrations

Percent Change in Annual AverageBiogenic Secondary Organic Carbon Concentrations

Percent Change in Annual AveragePrimary Organic Carbon Concentrations

Elemental Carbon Percent Reduction on 20% Worst Visibility Days(2002 to 2018 Base Case)

Organic Carbon Percent Reduction on 20% Worst Visibility Days(2002 to 2018 Base Case)

YOSE

• Natural sources dominated total, and the variability in particulate organic mass concentrations summer 2002Carbon isotope analyses of fine aerosol filter samples from Turtleback Dome determined a constant contribution for fossil fuel sources of 0.7 ± 0.1 µg/m3 to POM. Contemporary (biogenically derived) carbon represented 2-9 µg/m3. Sources of contemporary aerosol carbon include emissions from fires and vegetative emissions of reactive gases that subsequently form condensable species, both particulate primary emissions and volatile organic aerosol precursors that are later oxidized to secondary organic aerosols.

Conclusions

• Based on comparisons to ambient monitoring data, CMAQ performs adequately for EC and OC at Class I areas for purposes of assessing the impact of emission changes on the 20% best and worst visibility days.

• EC concentrations are expected to decrease significantly in 2018, commensurate with mobile source and some smoke controls.

Conclusions

• Smaller improvements in OC are expected due to large influence of natural sources.

• A significant portion of the OC originates from non-fire biogenic VOC emissions, but is enhanced by anthropogenic sources.

• Natural source contributions are large, vary substantially by site and year, and limit the progress that can be made, but …– OC is not entirely natural and can benefit directly or

indirectly from emission controls

Conclusions

• Fire emissions dominate extreme organic values• Actual future organic emissions from fire are

unpredictable in terms of where and when they occur -

• The model has constrained wildland fires to be in the same between current and future years

• The model can be used to examine different scenarios – limited utility

Conclusions

• Real trick is to account for the dominance of organic concentrations at sites with fire impacts and still show reasonable progress