1. Heidy Plata 1, Ezinne Achinivu 1, Szu-Ting Chou 1, Sheryl Ehrman 1, Dale Allen 2, Kenneth Pickering 2♦, Thomas Pierce 3, James Gleason 3 1 Department of Chemical and Biomolecular Engineering 2 Department of Atmospheric and Oceanic Science University of Maryland, College Park, Maryland ♦ Laboratory for Atmospheres, NASA Goddard Space Flight Center 3 Atmospheric Modeling and Analysis Division, NERL, US EPA, Research Triangle Park, North Carolina Towards improved emissions inventories of soil NOx via model/satellite measurement intercomparisons UNIVERSITY OF MARYLAND

2. Outline Current Problem Objectives Brief introduction to BEIS3 and satellite products Biogenic Emissions Inventory System OMI-standard and OMI-DOMINO tropospheric NO2 products Effect of precipitation on NO emissions Approach Discussion and Future Work

3. Current Problem NOx contributes

4. Sources of NOx Sources of Nitrogen Oxides Biogenic Anthropogenic  Modeling NOx emissions from biogenic sources poses a challenge as the frequency and magnitude of their emissions are uncertain. Point Combustion Sources/Power Plants Motor Vehicles Lightning Soil

5. Objectives Develop a better understanding of soil based sources of nitrogen oxides Evaluate whether satellite observations of NO2 can be used to improve emissions estimates for soil derived NOx Use this understanding and satellite observations to improve model estimates of NO x emissions in BEIS3, which is the biogenic emission module used in CMAQ

6. Details about BEIS3 Soil NO emissions in BEIS3 are a function of: Land use and temperature Precipitation: Emissions can increase by up to a factor of 12 with heavy rain. Fertilizer: It doesn’t vary with region. Emissions are constant for first month of growing season (April) and then decrease Canopy: the canopy adjustment factor is 1 for the first 30 days of the growing season then goes down linearly until it is 0.5 and then remains constant.

7. Details about BEIS3 Land use (crop) and temperature

8. Details about Ozone Monitoring Instrument (OMI) Tropospheric NO2 column OMI NASA Standard Product KNMI DOMINO Product Start with same slant column densities from spectral fit of OMI observed radiances Estimate stratospheric NO 2 column using data from areas without significant tropospheric pollution. Interpolate globally using a wave-2 pattern. Use stratospheric Column NO2 from TM4 global chemical transport model. AMF assumes annual mean vertical profiles from GEOS- Chem global model AMF assumes daily vertical profiles from TM4 model

9. Effect of precipitation on NO emissions If dry soil is wetted, a large burst, or pulse occurs and then decays rapidly over a period of time following the wetting event. WettingDrying Nutrient Accumulation NO

10. Effect of precipitation on NO emissions <0.1 cm/day no pulse 0.1<rain<0.5 sprinkle (3 day pulse) 0.5<rain<1.5 shower (1-week pulse) 1.5<rain heavy rain (2 week pulse )

11. Approach Choose dates with likely NOx soil emissions due to precipitation Choose dates with likely NOx soil emissions due to precipitation Remove days with lightning or days with aerosol index>1 Spring 2005 (April6-May15) Spring 2005 (April6-May15) Select regions in which Biogenic emissions are substantial compared to anthropogenic

12. North and South Dakota

13. Missouri and Arkansas

14. Approach Evaluate response of BEIS3 emissions and CMAQ tropospheric NO2 columns to precipitation events Choose dates with likely NOx soil emissions due to precipitation Choose dates with likely NOx soil emissions due to precipitation Remove days with lightning or days with aerosol index>1 Spring 2005 (April6-May15) Spring 2005 (April6-May15) Select regions in which Biogenic emissions are substantial compared to anthropogenic Evaluate response of CMAQ tropospheric NO2 columns using OMI-retrieved columns

15. Time Episode of April 11

16. Biogenic(mol/s ) Episode of April 11

17. Time cm/day 10 15 molecules /cm 2 Episode of April 11

18. Episode of April 12 Precipitation ( cm/day ) Biogenic(mol/s ) Time

19. Precipitation ( cm/day ) and CMAQ(10^15 molecules /cm^2) Biogenic(mol/s ) Episode of April 12

20. Time cm/day 10 15 molecules /cm 2 Episode of April 12

21. Time Episode of May 9 Biogenic(mol/s )

22. Time Episode of May 9 Biogenic(mol/s ) Precipitation ( cm/day ) and CMAQ(10 15 molecules /cm 2 )

23. Time Episode of May 9 10 15 molecules /cm 2 cm/day

24. Discussion Analysis is hampered by lack of OMI data on days during and sometimes following rainfall events due to clouds. For cases in which CMAQ tropospheric NO2 columns show the clearest response to increases in biogenic emissions: CMAQ high-bias relative to OMI increases after precipitation events implying that the sensitivity of BEIS3 soil emissions to precipitation events is overestimated at least for these cases Firm conclusions must await analysis of additional cases. Can additional cases be found in regions where the magnitudes of anthropogenic and biogenic emissions are comparable?

25. Episode of May 08 Biogenic(mol/s) Precipitation ( cm/day )

26. Biogenic(mol/s) Precipitation ( cm/day ) and CMAQ(10^15 molecules /cm^2) Time Episode of May 08

27. 10 15 molecules /cm 2 cm/day Time Episode of May 08

28. 10 15 molecules /cm 2 cm/day Time

29. Discussion  For regions with a greater fraction of anthropogenic emissions, NO2 pulses reflected in BEIS3 output but response of CMAQ tropospheric NO2 columns is controlled by other factors  Suggests utility of our approach limited to rural regions

30. Future Work  Continue focus on Northern Great Plains and Upper Midwest Region  Expand analysis to include spring 2006 precipitation events  Re-run analysis with reprocessed OMI data  Refine screening algorithms

31. Future Work  Refine method used to determine if tropospheric NO2 column response to changes in biogenic emissions is more than expected from normal day-to-day variations  Use satellite-derived adjustments to improve BEIS-3 emissions  Consider modifying BEIS3 to better resolve the magnitude and duration of soil NOx pulses associated with precipitation

32. Acknowledgments  Financial Support: NASA Applied Sciences Air Quality Decision Support System Program.