Diagnostic Evaluation of Carbon Sources in CMAQ

1. Diagnostic Evaluation of Carbon Sources in CMAQ Sergey L. Napelenok1, Heather Simon1, Prakash V. Bhave1, George A. Pouliot1, Michael Lewandowski1, Rebecca Sheesley2 1U.S. Environmental Protection Agency Research Triangle Park, NC 2Baylor University Waco, Texas 10th Annual CMAS Conference Chapel Hill, NC

2. Sites of interest: Bondville, IL; Northbrook, IL; Detroit, MI; Cincinnati, OHModeling episode: March 2004 – February 2005

3. Traditional Model Evaluation for Particulate Carbon • Routine monitoring networks measure only TEC and TOC. • For these 4 sites, such evaluation is consistent with previous studies. • Four cases to explore: Summer bias = -1.7 μg/m3 Northbrook winter bias = -1.4 μg/m3 Detroit spring bias = -0.3 μg/m3 Non-Detroit spring bias = -1.0 μg/m3 • Diagnosing the causes of model bias with only this data is difficult.

4. More Detailed Measurements • Over 80 particle-phase organic compounds measured from March 2004 to February 2005 at the four Midwestern sites. • Filter samples collected every 6th day • Filter extracts were composited on a monthly basis and analyzed by chemical derivitization and gas chromatography - mass spectrometry (GC-MS) for individual organic compounds. • Hentriacontane, 20R-aaa-cholestane, Fluoranthene, levoglucosan, etc. • Composites were also analyzed by EPA scientists for highly polar compounds, which are tracers for SOA species. • Pinonic acid, 2-methylthreitol, caryophyllinic acid, etc. • Lewandowski, et al, Primary and Secondary Contributions to Ambient PM in the Midwestern United States, Environ. Sci. Technol., 2008, 42, 3003-3309.

5. Organic PM2.5 cloud water ∙OH SV_ALK AALK ∙OH/HO2 AORGC ATOL1, ATOL2 ∙OH long alkanes dissolution SV_TOL1 SV_TOL2 ∙OH/NO AXYL1, AXYL2 ∙OH/HO2 high-yield aromatics SV_XYL1 SV_XYL2 ∙OH/NO low-yield aromatics POA1 POA2 POA3 POA4 POA5 POA6 POA7 POA8 POA9 POA10 POA11 POA12 POA13 POA14 POA15 POA16 benzene SV_BNZ1 SV_BNZ2 ∙OH/HO2 ATRP1, ATRP2 ABNZ1, ABNZ2 ∙OH/NO glyoxal methylglyoxal SV_TRP1 SV_TRP2 ∙OH,O3 ASQT O3P, NO3 AISO1, AISO2 monoterpene VOCs sesquiterpenes ANTHROPOGENIC EMISSIONS BIOGENIC EMISSIONS EMISSIONS EMISSIONS isoprene More Detailed Model (CMAQ v4.7.1 – Similar results expected with CMAQv5.0) Tagged 16 different source categories of EC and OC. – Onroad Diesel Exhaust – Coal Combustion – Nonroad Diesel Exhaust – Oil Combustion – Onroad Gasoline Exhaust – Natural Gas Combustion – Nonroad Gasoline Exhaust – Food Cooking – Aircraft Exhaust – Paved Road Dust – Anthrop Biomass Combustion – Crustal Material – Wildfires – Misc. Industrial Processes – Waste Combustion – Other AOLGA ATOL3 POA AXYL3 ABNZ3 AOLGB AISO3 H+ SV_SQT ∙OH,O3, or NO3 SV_ISO1, SV_ISO2 ∙OH EMISSIONS Pathways do not contribute to SOA O3,O3P, or NO3 Non-volatile

6. PM Carbon Eastern U.S. Emissions Summary

7. Example of Source Specific Emissions – January 1, 2005 onroad diesel oil combustion

8. Converting Source Tagged Species to Organic Tracers

9. Mobile Sources

10. Mobile Sources – Hopanes & Steranes • Calculating change in bias from sector correction: • Ratio Conc Δbias • μg/m3μg/m3 • 0.82 0.33 0.07 • 0.72 0.19 0.07 • 0.76 0.29 0.09 • 0.49 0.16 0.17 0.09 0.07 0.07 0.17

11. Biomass Burning - Levoglucosan -0.07 0.38 0.32 0.08

12. Natural Gas Combustion - Ketones -0.19 -0.04 -0.01 -0.01

13. Organic Aerosol • POC compares reasonably well to measurements. • SOA is underestimated for all species. • Comparison in the Midwest is worse than previous evaluation with tracer data in Research Triangle Park.

14. Midwest – 2004/2005 RTP – 2003 Monoterpenes

15. Midwest – 2004/2005 RTP – 2003 Aromatics

16. Potential Gains From Improvements – Organic Aerosol • Isoprenes • 0.680.000.050.22 • Evidence for missing aqueous chemistry pathways • Monoterpenes • 0.310.030.170.13 • Needs further analysis and data is available at other sites • Sesquiterpenes • 0.130.200.240.09 • Evidence for emissions problems • Aromatics • 0.170.040.150.09 • Potentially increase the yields

17. Concluding Remarks • Unique comparison on model performance for an annual tracer dataset • Measured tracer compounds are not inert – some react, degrade, and/or have secondary sources in the atmosphere • Measurement uncertainty is ~ 30% • A valuable dataset for diagnostic evaluation:

18. contact: napelenok.sergey@epa.gov

19. Additional Material…

20. Model Description • CMAQ v4.7.1 • SAPRC99 Chemistry • 12km horizontal Eastern US domain nested within 36km continental domain • 24 vertical layers up to 100 mb. • MM5 meteorology • SMOKE emissions (special treatment for primary TC) • Hourly Geos-Chem boundary conditions • Track source specific primary carbon concentrations using the Carbon Apportionment option

22. Summary/Conclusions • Comparisons of measured and modeled tracers for primary sources are reasonable considering the uncertainty range of the observations (30%). • Hopanes and Steranes show the best comparison. • Levoglucosan is under predicted by the model in the summer indicating a possible missing source (wild fires in Canada?) • Tracers with high model/obs ratios are known to degrade in the atmosphere (decay process not implemented in the model) e.g. hopanes at the rural site Bondville. • Higher model/obs ratios in the summer support the possibility of tracer volatilization and degradation. • Tracers with low model/obs ratios are known to have secondary source in the atmopshere e.g. n-Alkanoic Acids.