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U.S. aerosols: observation from space, effects on climate

U.S. aerosols: observation from space, effects on climate. Daniel J. Jacob. with Easan E. Drury, Tzung-May Fu Loretta J. Mickley, and Eric M. Leibensperger. and funding from NASA, EPRI. ATMOSPHERIC AEROSOLS: ensembles of condensed-phase particles suspended in air. number.

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U.S. aerosols: observation from space, effects on climate

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  1. U.S. aerosols: observation from space, effects on climate Daniel J. Jacob with Easan E. Drury, Tzung-May Fu Loretta J. Mickley, and Eric M. Leibensperger and funding from NASA, EPRI

  2. ATMOSPHERIC AEROSOLS:ensembles of condensed-phase particles suspended in air number Typical aerosol size distribution area volume Aerosols are the visible part of the atmosphere: California fire plumes Dust off West Africa Pollution off U.S. east coast

  3. WHY CARE ABOUT ATMOSPHERIC AEROSOLS? Public health Chemistry Visibility Cloud formation Ocean fertilization Climate forcing

  4. Urban air concentrations of particulate matter <2.5 mm diameter (PM2.5) MAJOR AEROSOL COMPONENTS IN U.S. Sulfate: from atmospheric oxidation of SO2 emitted by combustion (mainly coal) Nitrate: from atmospheric oxidation of NOx emitted by combustion Ammonium: from NH3 emitted by agriculture Carbon: elemental carbon from combustion and organic carbon from combustion and vegetation Crustal: suspended mineral dust Dry mass concentrations

  5. GLOBAL AEROSOL OBSERVATION FROM SPACE Aerosol optical depths (AODs) at 0.55 mm from MODIS and MISR sensors Jan 01 – Oct 02 MODIS return time 2x/day MISR 9-day return time Why are the AODs so different? van Donkelaar et al. [2006]

  6. MODIS RETRIEVAL OF AEROSOL OPTICAL DEPTHS (AODs) OVER LAND MODIS measures backscatter solar reflectance in several wavelength channels • Interpretation of this top-of-atmosphere (TOA) reflectance in terms of AOD requires assumptions on surface reflectance, aerosol optical properties • Use TOA reflectance at 2.13 mm (transparent atmosphere) to derive surface reflectance • Assume 0.47/2.13 and 0.65/2.13 surface reflectance ratios to obtain atmospheric reflectances at 0.47 and 0.65 mm by subtraction • Assume aerosol optical properties to convert atmospheric reflectance to AOD • MISR does along-track multi-angle viewing of same aerosol column – better constraints but sparser data 0.47 mm 0.65 mm 2.13 mm AEROSOL SURFACE

  7. CONSTRAINING AND TESTING AEROSOL OBSERVATIONS FROM SPACE DURING ICARTT CAMPAIGN (Jul-Aug 2004) MODIS satellite instrument: aerosol optical depths NASA, NOAA, DOE aircraft: speciated mass concentrations, microphysical & optical properties NASA DC-8 IMPROVE surface network: speciated mass concentrations at background sites AERONET surface network: aerosol optical depths EASTERN U.S.

  8. IMPROVING THE SURFACE REFLECTANCE CORRECTION FOR MODIS AEROSOL RETRIEVALS 0.65 mm 2.13 mm Measured top-of-atmosphere (TOA) reflectances (ICARTT period) 0.65/2.13 surface reflectance ratio Measured 0.65 vs. 2.13 TOA reflectances: take lower envelope for given location to derive surface reflectance ratio Fresno, CA ICARTT period Derive aerosol reflectance at 0.65 mm (same procedure for 0.47 mm) Drury et al. [JGR 2008]

  9. CONVERTING TOA AEROSOL REFLECTANCES TO AODs Standard MODIS algorithm assumes generic aerosol optical properties Better way is to use local info for given scene from a global 3-D aerosol model • Use GEOS-Chem model driven by NASA/GEOS assimilated meteorological data with 2ox2.5o resolution • Model simulates mass concentrations of different aerosol types • Size distributions and optical properties for different aerosol types are assumed (test with ICARTT data) • Key advantage of approach is to allow quantitative test of model with the satellite aerosol reflectance data

  10. Annual mean concentrations at IMPROVE sites (2001) – CASTNET for NH4+ PREVIOUS MODEL EVALUATION: sulfate-nitrate-ammonium r = 0.96 bias = +10% r = 0.60 bias = +30% r =0.94 bias = +10% • Sulfate is 100% in aerosol; • Ammonia NH3(g) neutralizes sulfate to form (NH4)2SO4; • Excess NH3(g) if present can combine with HNO3(g) to form NH4NO3 • as function of T, RH Park et al. [AE 2006]

  11. Elemental carbon (EC) Organic carbon (OC) Annual mean concentrations at IMPROVE sites (2001) PREVIOUS MODEL EVALUATION: carbonaceous aerosol r = 0.75 bias = -15% r = 0.70 bias = +20% • Primary sources: fossil fuel, biofuel, wildfires • Also large growing-season biogenic source of secondary organic aerosol (SOA) volatile organic compounds (VOCs) oxidation, multi-step SOA Park et al. [AE 2006]

  12. GEOS-Chem PREVIOUS MODEL EVALUATION: mineral dust Annual mean concentrations at IMPROVE sites (2001) Asian dust Saharan dust Local Fairlie et al. [AE 2007]

  13. AEROSOL VERTICAL PROFILES IN ICARTT bulk filter (Dibb, UNH) NASA DC-8 IMPROVE (<2.5 mm) PILS (Weber, GIT) • Sulfate model overestimate: excessive cloud processing? • Unresolved disagreement in ammonium and dust observations Easan Dury, in prep.

  14. ORGANIC AEROSOL IN ICARTT PILS water-soluble organic carbon (WSOC) on NOAA P-3 IMPROVE measurements of organic carbon Fu et al. (AE, in press) • Standard reversible SOA (Pankow/Seinfeld): • Dicarbonyl SOA (Liggio/Fu):

  15. MEAN AEROSOL VERTICAL PROFILES IN ICARTT • Bulk of mass is in boundary layer below 3 km: sulfate, organic (dust?) • Dust, organic dominate above 3 km Easan Drury, in prep.

  16. AEROSOL OPTICAL PROPERTIES IN ICARTT Single-scattering albedo is fraction of aerosol extinction due to scattering standard model Assumption (GADs) improved fit (this work) AERONET Easan Drury, in prep.

  17. MEAN AEROSOL OPTICAL DEPTHS DURING ICARTT Model results compared to observations from AERONET network (circles) Model w/ GADs size distributions Model w/improved size distributions r = 0.89 bias = -21% r = 0.89 bias = -7% Main improvement was to reduce the geometric standard deviation in the log-normal size distributions for sulfate and OC from 2.0 to 1.6 Easan Drury, in prep.

  18. IMPROVED MODIS RETRIEVALOF AEROSOL OPTICAL DEPTH This work r=0.84 bias =+2% Circles are AERONET data standard MODIS product (c005) c005 is the latest operational MODIS AOD product (2006) r=0.84 bias =-20% standard MODIS product (c004) Easan Drury, in prep.

  19. MAPPING SURFACE PM2.5 FROM IMPROVED MODIS AODs • Shows model organic aerosol underestimate in Southeast (w/out dicarbonyl SOA) • Questions sulfate problem in Northeast Easan Drury, in prep.

  20. Large historical offset of greenhouse warming by anthropogenic aerosols GLOBAL RADIATIVE FORCING OF CLIMATE BY AEROSOLS Historical and projected U.S. trend of SO2 emissions IPCC [2007] Unlike, CO2, radiative forcing from aerosols is strongly regional and likely to decrease in future: what are the implications for future climate change?

  21. CLIMATE RESPONSE TO SHUTTING DOWN U.S. AEROSOL Mickley et al. (in prep.)

  22. CHANGE IN ANNUAL MEAN TEMPERATURE Mickley et al. (in prep.)

  23. THIS REGIONAL CLIMATE RESPONSE FROM U.S. AEROSOL VANISHES AFTER A FEW DECADES • Explains why previous studies (focusing on 2050 or 2100 endpoints) have found no regional climate response to aerosol emissions • May reflect regional feedbacks important in present atmosphere but already realized in future enhanced-greenhouse atmosphere Mickley et al. (in prep.)

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