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

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

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

4. MAJOR AEROSOL COMPONENTS IN U.S. Dry mass concentrations Sulfate: from atmospheric oxidation of SO 2 emitted by combustion (mainly coal) Nitrate: from atmospheric oxidation of NO x emitted by combustion Ammonium: from NH 3 emitted by agriculture Carbon: elemental carbon from combustion and organic carbon from combustion and vegetation Crustal: suspended mineral dust Urban air concentrations of particulate matter <2.5  m diameter (PM 2.5 )

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

6. MODIS RETRIEVAL OF AEROSOL OPTICAL DEPTHS (AODs) OVER LAND SURFACE AEROSOL 0.47  m 0.65  m 2.13  m 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  m (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  m 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 MODIS measures backscatter solar reflectance in several wavelength channels

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

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

9. CONVERTING TOA AEROSOL REFLECTANCES TO AODs Use GEOS-Chem model driven by NASA/GEOS assimilated meteorological data with 2 o x2.5 o 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 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

10. PREVIOUS MODEL EVALUATION: sulfate-nitrate-ammonium Annual mean concentrations at IMPROVE sites (2001) – CASTNET for NH 4 + Sulfate is 100% in aerosol; Ammonia NH 3 (g) neutralizes sulfate to form (NH 4 ) 2 SO 4 ; Excess NH 3 (g) if present can combine with HNO 3 (g) to form NH 4 NO 3 as function of T, RH Park et al. [AE 2006] r = 0.96 bias = +10% r = 0.60 bias = +30% r =0.94 bias = +10%

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

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

13. AEROSOL VERTICAL PROFILES IN ICARTT NASA DC-8 IMPROVE (<2.5  m) bulk filter (Dibb, UNH) 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 Standard reversible SOA (Pankow/Seinfeld): Dicarbonyl SOA (Liggio/Fu): Fu et al. (AE, in press)

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 AERONET standard model Assumption (GADs) improved fit (this work) 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 Easan Drury, in prep. 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

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

19. MAPPING SURFACE PM 2.5 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. GLOBAL RADIATIVE FORCING OF CLIMATE BY AEROSOLS IPCC [2007] Large historical offset of greenhouse warming by anthropogenic aerosols Unlike, CO 2, radiative forcing from aerosols is strongly regional and likely to decrease in future: what are the implications for future climate change? Historical and projected U.S. trend of SO 2 emissions

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.)