1. SATELLITE OBSERVATIONS OF TROPOSPHERIC COMPOSITION Daniel J. Jacob with in order of appearance: Dylan B. Millet, PauI I. Palmer, Tzung-May Fu, Colette L. Heald, Easan E. Drury, Solene Turquety, Lin Zhang and: Kelly V. Chance, Thomas Kurosu, Robert J.D. Spurr (Harvard/SAO) Alan Fried and Alex Guenther (NCAR) Brian G. Heikes (URI) Hanwant B. Singh (NASA-Ames) Michael Pilling (Leeds) Donald R. Blake (UCI) The MOPITT and TES Science Teams Jay Herman and Joseph D’Avila (NASA/GSFC) Work supported by NASA, EPA, EPRI

2. A POTPOURRI OF ONGOING WORK 1.Top-down constraints on reactive VOC emissions from satellite observations of HCHO columns (Dylan Millet, Paul Palmer, Tzung-May Fu) 2. Quantifying intercontinental tranport and sources of anthropogenic aerosols using MODIS (Colette Heald, Easan Drury) 3. Using MOPITT CO to constrain fire emission characteristics during summer 2004 (Solene Turquety) 4.Tropospheric ozone-CO correlations from TES (Lin Zhang) 5. Future direction: measurement from L1 orbit (with Jay Herman, Joseph D’Avila) with funding by NASA, EPA, EPRI

3. MEASURING HCHO COLUMNS FROM SPACE Scattering by Earth surface and by atmosphere GOME backscattered spectrum in 338-356 nm HCHO band Vertical column: Air mass factor (AMF) depends on the viewing geometry, the scattering properties of the atmosphere, and the vertical distribution of the absorber “slant column”  s = 3.0 ± 0.4 x10 16 cm -2 from least-squares fit Chance et al. [2000]

4. HCHO SLANT COLUMNS MEASURED BY GOME (JULY 1996) High HCHO regions reflect VOC emissions from fires, biosphere, human activity -0.5 0 0.5 1 1.5 2 2.5x10 16 molecules cm -2 South Atlantic Anomaly (disregard) fittimg error K.V. Chance and T. Kurosu (Harvard/SAO)

5. instrument sensitivity w(  ) at 340 nm HCHO mixing ratio profile S(  ) what instrument sees AMF G = 2.08 actual AMF = 0.71 AMF FORMULATION FOR A SCATTERING ATMOSPHERE Palmer et al. [2001]; Martin et al. [2002, 2003] w(  ): sensitivity computed from radiative transfer model S(  ): normalized vertical profile of mixing ratio (“shape factor”) AMF G : geometric air mass factor (non-scaterring atmosphere)

6. RELATING HCHO COLUMNS TO VOC EMISSION VOC i HCHO h (<345 nm), OH oxn. k ~ 0.5 h -1 Emission E i smearing, displacement In absence of horizontal wind, mass balance for HCHO column  HCHO : yield y i … but wind smears this local relationship between  HCHO and E i depending on the lifetime of the parent VOC with respect to HCHO production: Local linear relationship between HCHO and E VOC source Distance downwind  HCHO Isoprene  -pinene propane 100 km Palmer et al. [2003, submitted]

7. INVERTING HCHO COLUMN DATA FOR ISOPRENE EMISSION GOME slant columns (July 96) GOME vertical columns (July 96) Air Mass Factor E ISOPRENE =(1/S)  HCHO GOME isoprene emission inventory GEOS-Chem CTM instrument sensitivity HCHO vmr Sigma coordinate validation With HCHO surface air observations with GEIA isoprene emission inventory with GOME isoprene emission inventory Palmer et al. [2001, 2003] E ISOPRENE HCHO column non- isoprene contribution Southeast U.S. slope S Observed HCHO, ppb Model HCHO, ppb

8. TEST AMF CALCULATION AND HCHO SOURCE ATTRIBUTION Aircraft 0-10 km HCHO profiles over N. America in INTEX-A (summer 2004) Clouds are the principal source of AMF error; screen at 40% cloud cover to limit error to 30% Dylan B. Millet, in prep. A. Fried (NCAR) B.G. Heikes (URI) GEOS-Chem model Mean HCHO profiles Observed HCHO columns (A. Fried) Observed AMF

9. RELATING OBSERVED HCHO COLUMNS TO PARENT VOCs Detectable HCHO columns and variability over N. America are driven by isoprene Calculate P HCHO from concurrent column observations of VOCs during INTEX-A (D. R. Blake and H.B. Singh) Dylan B. Millet, in prep.

10. HCHO YIELDS FROM ISOPRENE OXIDATION Dylan B. Millet, in prep.; Palmer et al., submitted Estimate yield uncertainty of ~20%, greater in low-NO x regime Box model simulations: GEOS-Chem and MCM v3.1 mechanisms HCHO vs. isoprene columns in INTEX-A observed  HCHO, 10 16 cm -2  ISOP, 10 16 cm -2 m = 3.3 m = 3.5 GEOS-Chem Time, hours HCHO yield, per C atom

11. GOME vs. MEGAN ISOPRENE EMISSION INVENTORIES (2001) Good accord for seasonal variation, regional distribution of emissions; GOME 10-30% higher than MEGAN depending on month, differences in hot spot locations Palmer et al., submitted MEGAN is a state-of-science emission inventory for biogenic VOCs (Guenther et al., 2005)

12. YEAR-TO-YEAR VARIABILITY OF GOME ISOPRENE EMISSIONS OVER SOUTHEAST U.S. Amplitude and phase are highly reproducible Palmer et al., submitted

13. WHAT DRIVES THE TEMPORAL VARIANCE OF ISOPRENE OVER SOUTHEAST U.S. DURING THE GROWING SEASON? Monthly mean GOME HCHO vs. surface air temperature; MEGAN parameterization shown as fitted curve Temperature accounts for ~80% of the variance Palmer et al., submitted

14. Detectable winter signal implies short-lived anthropogenic VOC emissions 2x values in Streets et al. [2003] inventory Large, previously recognized agricultural burning source in E. China in Jun-Jul Biogenic emissions ~3x higher than in MEGAN inventory Tzung-May Fu, in prep. GOME HCHO COLUMNS OVER EAST ASIA (1996-2001) 10 16 molecules cm -2

15. AGRICULTURAL BURNING IN E. CHINA PLAIN IN JUNE r 2 = 0.98 bioburnx27 biox4 Tzung-May Fu, in prep. Large, previously unrecognized VOC source from winter wheat harvest

16. PRELIMINARY OBSERVATIONS FROM OMI (Kelly Chance’s poster) Jakarta Chongqing (Red Basin) OMI HCHO MODIS fire data 24 Sep – 19 Oct 2004

17. DJF MAM JJA SON MODIS AOD GEOS-Chem AOD: sulfate dust MODIS AOD OBSERVATIONS OVER PACIFIC Colette L. Heald, in prep. Evidence for transpacific Asian polllution in all seasons, but positive and variable bias relative to AERONET observations

18. DIFFERENTIAL TRANSPORT OF AEROSOLS AND CO Colette L. Heald, in prep. March 2001 Anthropogenic plume, similar for CO and aerosols (allowing for aerosol scavenging) Biomass burning plume for CO – why can’t we see it for aerosols?

19. USING MODIS TO TRACK TRANSPACIFIC AEROSOL POLLUTION EVENTS AFFECTING THE U.S. Event #2 works nicely, but #3 and #4 don’t (clouds…) Colette L. Heald (Harvard) Northwest U.S. sites, IMPROVE network (spring 2001) Obs as symbols: sulfate, dust Model as lines (Asian sulfate as thin line)

20. USING MODIS BACKSCATTERED REFLECTANCES FOR INVERSE MODELING OF AEROSOL SOURCES Backscattered reflectances 0.47  m0.66  m2.13  m0.47  m0.66  m MODIS0.17 ± 0.0080.11 ± 0.0050.14 ± 0.010.11 ± 0.010.047 ± 0.01 GEOS-Chem0.140.10same0.12 0.038 Land: 3 backscatter channels (2.13  m constrains surface albedo) Ocean: 7 backscatter channels Sample 1 o x1 o scenes for April 16, 2005 LAND SCENEOCEAN SCENE Easan E. Drury, in progress

21. USING MOPITT CO COLUMNS AS CONSTRAINTS FOR BOREAL FIRE EMISSIONS IN SUMMER 2004 MOPITT CO Summer 2004 GEOS-Chem CO x MOPITT AK Bottom-up fire emission inventory (Tg CO) constructed w/daily resolution without peat burning with peat burning MOPITT data confirm large peat burning source Solene Turquety, in prep. 17 Tg CO 11 Tg CO From above-ground vegetation From peat

22. MOPITT CONSTRAINTS ON FIRE INJECTION HEIGHTS Strong day-to-day variability in injection heights MOPITT CO column (Jul 17-19)GEOS-Chem w/AK – BB 100% BL GEOS-Chem w/AK – BB 40% BL + 55% MT + 5% UT GEOS-Chem w/AK – BB 30% BL + 40% MT + 30% UT Solene Turquety, in prep.

23. FIRST TES OBSERVATIONS FOR TROPOSPHERIC OZONE 1-3 pieces of info in vertical Sep 20, 2004 800 hPa 500 hPa 300 hPa R 2 = 0.8, m = 0.96 R 2 = 0.7, m = 1.01 TES GEOS-Chem w/TES AK Lin Zhang, in progress Averaging kernels (tropical scene)

24. TES “STEP AND STARE” OVER S. ATLANTIC Latitude, degrees Pressure, hPa Five transects in Sep-Oct 2004 TES (1.2-2.2 dofs) GEOS-Chem Line Jourdain and Qinbin Li (JPL), in progress

25. OZONE-CO CORRELATIONS FROM TES Nov 2004, 500 hPa TES (n > 15) GEOS-Chem w/TES AK GEOS-Chem Lin Zhang, in progress  O 3 /  CO, mol mol -1 R 2

26. JANUS MISSION JANUS MISSION Unified Earth-Sun observation from L-1; white paper submitted to NRC Decadal Survey Sun : coronal heating, solar wind acceleration, flares and transients. CMEs, UV irradiance variability Solar wind and middle/upper atmosphere: space weather, Sun-Earth connections, upper atmosphere and stratosphere chemistry and dynamics Troposphere: sources and sinks of gases and aerosols, long- range transport of pollution Continuous observation of Earth’s sunlit disk with 5 km nadir horizontal resolution EUV/MUV spectrometers (50-340 nm) Magnetometer Faraday Cup near-UV/near-IR spectrometers, 300- 2400 nm White light coronagraph soft X-ray/EUV spectrometers (0.1-63 nm)