1. Retrieval and Interpretation of UV/Vis Satellite Observations of Tropospheric Composition Randall Martin With contributions from: Rongming Hu (Dalhousie University) Chris Sioris, Xiong Liu, Kelly Chance (Smithsonian Astrophysical Observatory) Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington) Yongtao Hu, Armistead Russell (Georgia Tech) Tom Ryerson, Andy Neuman (NOAA/CIRES) Ron Cohen (Berkeley) Aaron Swanson, Frank Flocke (NCAR) Andreas Richter (University of Bremen)

2. Major Challenges in Tropospheric Chemistry More Accurate Emission Inventories Understand Processes Controlling Tropospheric Ozone Constrain Aerosol Properties

3. Top-Down Information from the GOME and SCIAMACHY Satellite Instruments GOME 1995-2002 Spatial resolution 320x40 km 2 Global coverage in 3 days SCIAMACHY 2002-present Spatial resolution 60x30 km 2 Global coverage in 6 days Spectral Fit Remove Stratosphere Total NO 2 Slant Column Tropospheric NO 2 Slant Column Calculate AMF Tropospheric NO 2 Column Martin et al., 2002, 2005 Martin et al., 2002 Palmer et al. 2001 Martin et al., 2002, 2003, 2005 5-10x10 14 molec cm -2 2-10x10 14 molec cm -2 40% Pixel Uncertainty Mean Total ±(5x10 14 + 30%)

4. ICARTT Campaign Over and Downwind of Eastern North America in Summer 2004 Aircraft Flight Tracks and Validation Locations Overlaid on SCIAMACHY Tropospheric NO 2 Columns NASA DC-8NOAA WP-3D May-Oct 2004

5. Air Mass Factor Calculation in SCIAMACHY Retrieval Needs External Info on Shape of Vertical Profile Increased NO x Emissions from Midlatitude Improves GEOS-CHEM Simulation of NO 2 Profiles Remaining Discrepancy In Vertical Profile of NOx Emissions Midlatitude lightningMean Bias in AMF: 0.4 Tg N yr -1 12%9%3% 1.6 Tg N yr -1 1%5%3% In Situ 0.4 Tg N yr -1 1.6 Tg N yr -1 NO 2 Measurements from Cohen (DC-8) and Ryerson (WP-3D)

6. Enhanced Midlatitude Lightning Reduces Discrepancy with SCIAMACHY over North Atlantic Profile of NOx Emissions (lifetime) May Explain Remaining Discrepancy May-Oct 2004 SCIAMACHY NO 2 (10 15 molec cm -2 ) GEOS-Chem NO 2 (10 15 molec cm -2 ) 1.6 Tg N in Midlat GEOS-Chem NO 2 (10 15 molec cm -2 ) 0.4 Tg N in Midlat

7. Significant Agreement Between Coincident Cloud-Filtered SCIAMACHY and In-Situ Measurements r = 0.79 slope = 0.8 1:1 line Ryerson (WP-3D) Cohen (DC-8) Chris Sioris Cloud-radiance fraction < 0.5 In-situ measurements below 1 km & above 3 km Assume constant mixing ratio below lowest measurement Add upper tropospheric profile from mean obs Horizontal bars show 17 th & 83 rd percentiles

8. Cloud-filtered Tropospheric NO 2 Columns Retrieved from SCIAMACHY May-Oct 2004 detection limit

9. A. Richter et al. Nature, 437, 129-132, 2005 1996 - 2002 Annual changes in tropospheric NO 2 observed with GOME

10. Error weighting Conduct a Chemical Inversion & Combine Top-Down and Bottom-up Inventories with Error Weighting A posteriori emissions Top-Down Emissions 10 15 molec cm -2 A Priori NOx Emissions SCIAMACHY NO 2 Columns 10 11 molec N cm -2 s -1 GEOS-CHEM model GEIA

11. May-Oct 2004 Global Optimal Emission Inventory Reveals Major Discrepancy in NOx Emissions from Megacities r 2 =0.82 vs a priori

12. A Posteriori NOx Emissions from East Asia Exceed Those from Either North America or Europe A priori (Tg N yr -1 ) A posteriori (Tg N yr -1 ) East Asia6.89.2 North America8.18.8 Europe6.58.5 Africa7.18.2 SE Asia & India5.05.3 South America4.45.1 Australia1.11.9 Total39.147.0

13. Large Change in NOx Emissions Near New York City 10 11 atoms N cm -2 s -1  10 11 atoms N cm -2 s -1 A prioriA posteriori A posteriori – A priori 7.8 Tg N 0.6 Tg N r 2 = 0.92 Evaluate Each Inventory By Conducting GEOS-CHEM Simulation & Sampling Model Along Aircraft Flight Tracks  NO x (pptv) Simulation with A Posteriori – Simulation with A Priori  HNO 3 (pptv) 7.2 Tg N  PAN (pptv)

14. In Situ Airborne Measurements Support A Posteriori Inventory In Situ GEOS-CHEM (A priori) GEOS-CHEM (A posteriori) New England New England + Gulf P-3 Measurements from Tom Ryerson (NOAA) Aaron Swanson Andy Neuman Frank Flocke (NCAR) (CIRES/NOAA)

15. Error weighting EMIS: Emissions Mapping Integration Science Optimize NO x Emissions A posteriori emissions Top-Down Emissions May-Oct 2004 10 15 molecules cm -2 NOx Emissions (SMOKE/G.Tech) SCIAMACHY NO 2 Columns 10 11 molec N cm -2 s -1 Aug 2004 CMAQ

16. Algorithm for partitioning top-down NO x inventory (2000) Algorithm tested using synthetic retrieval GOME NO x emissions Fuel Combustion 1. Spatial location of FF- dominated regions in a priori (>90%) 1 Biomass Burning 2. Spatiotemporal distribution of fires used to separate BB/soil VIRS/ATSR fire counts Soils No fires + background 2 Jaeglé et al., 2005

17. Biomass Burning (2000) A priori A posteriori  Good agreement with BB seasonality from Duncan et al. [2003] (±200%) r 2 = 0.72 (±80%) SE Asia/India N. Eq. Africa S. Eq. Africa N. Eq. Africa: 50% increase SE Asia/India: 46% decrease Line: A priori (BB) Bars: A posteriori (BB) 10 10 atoms N cm -2 s -1 A posteriori total Jaeglé et al., 2005

18. Speciated Inventory for Soil emissions A posteriori 70% larger than a priori! A priori A posteriori Largest soil emissions: seasonally dry tropical + fertilized cropland ecosystems (±200%) (±90%) r 2 = 0.62 Soils Onset of rainy season: Pulsing of soil NO x ! North Eq. Africa Jaeglé et al., 2005 Soils East Asia

19. Liu, Chance, et al., 2005 Direct Retrieval of Tropospheric Ozone from GOME Using Optimal Estimation in Ultraviolet with TOMS V8 a priori GOMEGEOS-CHEM Tropospheric Ozone Column (Dobson Units)

20. Northern Tropics Remain a Challenge for Satellites and Models Liu, Chance, et al., 2005 GOMEGEOS-CHEM RBiasR Caracas0.570.80.548.7 Dakar-0.37-3.80.815.2 Tel Aviv0.96-1.50.941.4 Bangkok0.83-2.40.947.2 Comparison with MOZAIC Ozone Measurements

21. Backscattered Radiation is Sensitive to Single Scattering Albedo Over Bright Surfaces TOMS Aerosol Index Measures Absorbing Aerosols In Ultraviolet Where Rayleigh Scattering Acts as Bright Surface July 2000

22. Aerosol Absorption Contributes to Differences Between Aerosol Optical Depth and the Absorbing Aerosol Index Aerosol Vertical Profile Also Important July 2000 1.5 1.1 0.8 0.4 0 3.0 2.2 1.6 0.8 0 July 2000 MODIS TOMS

23. Retrieval of Aerosol Single Scattering Albedo Determined with radiative transfer calculation as Retrieval of Aerosol Single Scattering Albedo Determined with radiative transfer calculation as SSA that reproduces TOMS Aerosol Index when constrained by MODIS aerosol optical depth and GEOS-CHEM aerosol vertical profile Rongming Hu July 2000 MODIS AOT GEOS-CHEM profiles LIDORT RTM Min calc – obs aerosol index SSA

24. Significant Agreement With Aerosol Single Scattering Albedo Determined from AERONET Rongming Hu r = 0.8 Slope = 1.01 Intercept = -0.02

25. Conclusions Growing confidence in top-down constraint on NOx emissions Underestimate in NOx emissions from megacities, in soils, and North American lightning Puzzling ozone distribution in northern tropics Promise for global retrieval of aerosol single scattering albedo

26. Acknowledgements Rongming Hu (Dalhousie University) Chris Sioris, Xiong Liu, Kelly Chance (Smithsonian Astrophysical Observatory) Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington) Yongtao Hu, Armistead Russell (Georgia Tech) Tom Ryerson, Andy Neuman (NOAA/CIRES) Ron Cohen (Berkeley) Aaron Swanson, Frank Flocke (NCAR) Andreas Richter (University of Bremen) Funding: National Aeronautics and Space Administration (NASA) Canadian Foundation for Innovation (CFI) Canadian Foundation for Climate and Atmospheric Sciences (CFCAS) Natural Sciences and Engineering Research Council of Canada (NSERC) Nova Scotia Research and Innovation Trust (NSRIT)