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Randall Martin

Applying Space-Based Measurements of Ultraviolet and Visible Radiation to Understand Tropospheric Composition. Randall Martin. With contributions from: Aaron Van Donkelaar, Rongming Hu (Dalhousie University) Chris Sioris, Kelly Chance (Smithsonian Astrophysical Observatory)

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Randall Martin

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  1. Applying Space-BasedMeasurements ofUltraviolet and Visible Radiation to Understand Tropospheric Composition Randall Martin With contributions from: Aaron Van Donkelaar, Rongming Hu (Dalhousie University) Chris Sioris, Kelly Chance (Smithsonian Astrophysical Observatory) Lyatt Jaeglé, Linda Steinberger (Univerisity of Washington) Yunsoo Choi, Yuhang Wang, Yongtao Hu, Armistead Russell (Georgia Tech) Arlene Fiore (GFDL) Tom Ryerson (NOAA) Ron Cohen (Berkeley) Bill Brune (Penn State)

  2. Major Challenges in Tropospheric Chemistry More Accurate Emission Inventories Understand Aerosol Sources and Properties

  3. Global Surface NOx Emissions Uncertain to Factor of 2Implications for Tropospheric Ozone, Aerosols, and Indirect Effect • Here in Tg N yr-1 (based on) • Fossil Fuel 24 (GEIA) • Biomass Burning 6 (Duncan et al., 2003) • Soils 5 • (Yienger and Levy, 1995) • NOx Emissions (Tg N yr-1) • Fossil Fuel (20-33) • Biomass Burning (3-13) Soils (4-21) Relative Uncertainty

  4. Top-Down Information from the GOME and SCIAMACHY Satellite Instruments • Nadir-viewing solar backscatter instruments including ultraviolet and visible wavelengths • Low-elevation polar sun-synchronous orbit, late morning observation time • GOME 1995-2002 • Spatial resolution 320x40 km2 • Global coverage in 3 days • SCIAMACHY 2002-present • Spatial resolution 60x30 km2 • Global coverage in 6 days

  5. Spectral Fit of NO2 Distinct NO2 Spectrum Solar Io Ozone Backscattered intensity IB NO2 Scattering by Earth surface and by atmosphere Albedo A O2-O2 Nonlinear least-squares fitting Also Weak H2O line Based on Martin et al., 2002

  6. Total NO2 Slant Columns Observed from SCIAMACHY Dominant stratospheric background (where NO2 is produced from N2O oxidation)Also see tropospheric hot spots (fossil fuel and biomass burning) May-October 2004

  7. Perform a Radiative Transfer Calculation to Account for Viewing Geometry and Scattering Cloud Radiance Fraction IB,c / (IB,o + IB,c) IB,c IB,o Io • GOMECAT (Kurosu) & FRESCO Clouds Fields [Koelemeijer et al., 2002] • Surface Reflectivity [Koelemeijer et al., 2003] • LIDORT Radiative Transfer Model [Spurr et al., 2002] • GEOS-CHEM NO2 & aerosol profiles q Rc Ro Pc dt Rs Based on Martin et al., 2002, 2003

  8. Cloud-filtered Tropospheric NO2 Columns Determined from SCIAMACHY (Data  NASA) May-Oct 2004 detection limit


  10. EMIS: Emissions Mapping Integration ScienceOptimize North American NOx Emissions SCIAMACHY NO2 Columns NOx Emissions (SMOKE/G.Tech) Aug 2004 May-Oct 2004 1011 molec N cm-2 s-1 1015 molecules cm-2 Error weighting A posteriori emissions Top-Down Emissions

  11. Interpret Satellite Observations Using GEOS-CHEM Chemical Transport Model • Assimilated Meteorology (GEOS) • 2ox2.5o horizontal resolution, 30 vertical layers • O3-NOx-VOC chemistry • SO42--NO3--NH4+-H2O, dust, sea-salt, organic & elemental carbon aerosols • Interactive aerosol-chemistry • Anthropogenic and natural emissions • Cross-tropopause transport • Deposition Calculated Mean Surface Ozone for August 1997

  12. Global Top-Down Emission Inventory RevealsMajor Discrepancy in NOx Emissions from Megacities 48 Tg N yr-1 May-Oct 2004 48 - 38 Tg N yr-1 GEIA

  13. ICARTT: COORDINATED ATMOSPHERIC CHEMISTRY CAMPAIGN OVER EASTERN NORTH AMERICA AND NORTH ATLANTIC IN SUMMER 2004 ERS ERS-2 Envisat Terra Aqua SCIAMACHY GOME AIRS, MODIS MISR, MODIS, MOPITT NOAA-P3 Canada Convair DLR Falcon NASA DC-8 UK BAE-143 NASA Proteus International, multi-agency collaboration targeted at regional air quality, pollution outflow, transatlantic transport, aerosol radiative forcing

  14. North American NOx Emissions (May – October)Largest Change in Northeastern US Coast SCIAMACHY - NAPAP GEOS-CHEM (NAPAP) SCIAMACHY 1011 atoms N cm-2 s-1 1011 atoms N cm-2 s-1 1011 atoms N cm-2 s-1 r2= 0.85 7.6 Tg N 0.8 Tg N 8.4 Tg N

  15. Evaluate Top-Down and Bottom-Up NOx InventoriesConduct GEOS-CHEM Simulation For Each InventorySampled GEOS-CHEM Along Flight Tracks Simulation with SCIAMACHY – Original NOx Emission Inventory HNO3 (ppbv) NOx (ppbv)

  16. In Situ Airborne Measurements Support Top-Down Inventory New England New England + Gulf Remote GEOS-CHEM (Top-Down) In Situ GEOS-CHEM (Bottom-up) P-3 Measurements from Tom Ryerson (NOAA)

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

  18. Biomass Burning (2000) A priori A posteriori 1010atoms N cm-2 s-1 r2= 0.72 (±200%) (±80%) SE Asia/India: 46% decrease N. Eq. Africa: 50% increase Line: A priori (BB) SE Asia/IndiaN. Eq. Africa S. Eq. Africa A posteriori total Bars: A posteriori (BB) • Good agreement with BB seasonality from Duncan et al. [2003] Jaeglé et al., 2005

  19. Largest soil emissions: seasonally dry tropical + fertilized cropland ecosystems Soil emissions A posteriori 70% larger than a priori! A priori A posteriori r2= 0.62 (±90%) (±200%) North Eq. Africa East Asia Soils Soils Onset of rainy season: Pulsing of soil NOx! Jaeglé et al., 2005

  20. Transient Enhancements In GOME NO2 Columns from Lightning Choi et al., GRL, 2005

  21. SCIAMACHY Shows Elevated NOx Export from North America SCIAMACHY NO2 (1015 molec cm-2) May-Oct 2004 GEOS-CHEM NO2 (1015 molec cm-2) May-Oct 2004

  22. Explained by Model Bias in Upper Tropospheric NOx West of -60 degrees lon, “land” East of -60 degrees lon, “ocean” GEOS-CHEM NO2 Cohen NO2 GEOS-CHEM low by factor of 2 in column GEOS-CHEM low by 7.5% in column GEOS-CHEM NO Brune NO Errorbars Show 17th and 83rd percentiles

  23. EMISSION CONTROL STRATEGY FOR OZONE POLLUTION: ARE NOx OR VOCs THE LIMITING PRECURSORS? Use GOME observations of HCHO/NO2 ratio to determine ozone production regime [Sillman, 1995] HCHO/NO2 < 1 (blue) a VOC-limited HCHO/NO2 > 1 (green-red) a NOx-limited Martin et al. [2004]

  24. Aerosol Single Scattering Albedo Major Source of Uncertainty in Global Radiative Forcing Estimates IPCC [2001]

  25. Maximum Sensitivity to Aerosol Optical Thickness Over Dark SurfacesMore Sensitive to Single Scattering Albedo Over Bright Surfaces Staten Island Refinery Fire Saharan Dust Plume King et al., BAMS, 1999

  26. TOMS Aerosol Index Measures Absorbing Aerosols In Ultraviolet Where Rayleigh Scattering Acts as Bright Surface July 2000 TOA spectral albedo measured by GOME

  27. MODIS Aerosol Optical Depth Includes Both Scattering and Absorbing Aerosols 1.5 1.1 0.8 0.4 0 MODIS July 2000 3.0 2.2 1.6 0.8 0 TOMS July 2000

  28. Retrieval of Aerosol Single Scattering AlbedoDetermined with Radiative Transfer Calculation as SSA that reproduces TOMS Aerosol Index July 2000 Rongming Hu

  29. Modeled Organic Carbon Too Low in Southeast in July Ground-Based Measurements from IMPROVE (ug m-3) GEOS-CHEM model calculation (ug m-3) Aaron Van Donkelaar

  30. Summer Organic Carbon BiasGEOS-CHEM already accounts for primary and secondary sources of organic aerosol IMPROVE minus GEOS-CHEM OC [ug/m3], 2001 Aaron Van Donkelaar

  31. Distribution of Isoprene Emissions Similar to OC BiasMounting Field and Laboratory Evidence of OC Yield from Isoprene Oxidation Products 2001Isoprene Emission (1012 moles C cm-2 s-1) Aaron Van Donkelaar

  32. Organic Carbon from Isoprene Oxidation Products Largely Corrects Bias IMPROVE minus GEOS-CHEM OC [ug/m3], 2001 Aaron Van Donkelaar

  33. Conclusions • Growing confidence in top-down constraint on NOx emissions • Gross-underestimate in NOx emissions from megacities • Soil NOx emissions underestimated, especially from Northern Equatorial Africa • North American lightning NOx emissions underestimated • Promise for global retrieval of aerosol single scattering albedo • Low yield of organic carbon from isoprene oxidation products reduces model bias

  34. Acknowledgements Aaron Van Donkelaar, Rongming Hu (Dalhousie U.) Chris Sioris, Kelly Chance (Smithsonian) Lyatt Jaeglé, Linda Steinberger (U. of Washington) Yunsoo Choi, Yuhang Wang, Yongtao Hu, Armistead Russell (Georgia Tech) Arlene Fiore (GFDL) Tom Ryerson (NOAA) Ron Cohen (Berkeley) Bill Brune (Penn State) 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)

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