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Satellite Observations of Tropospheric Composition: Current and Future Research Paul Palmer, University of Leeds www.env.leeds.ac.uk/~pip
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Correlation of high ozone with temperature is driven by: 1) Stagnation, 2) Biogenic hydrocarbon emissions, 3) Chemistry Ozone exceedances of 90 ppbv, summer 2003 (#days) Model values for preindustrial ozone } European mountain- top observations [Marenco et al., 1994] Observed rise in ozone background at northern midlatitudes 0-1; 1-5; 5-10; >10 60 50 40 30 20 10 0 1870189019101930195019701990
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NO HO 2 OH NO 2 O3O3 hv HC+OH HCHO + products NOx, HC, CO Tropospheric O 3 is an important climate forcing agent IPCC, 2001 Level of Scientific Understanding Natural VOC emissions (50% isoprene) ~ CH 4 emissions.
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Bottom-up Isoprene emissions, July 1996 MEGAN 3.6 Tg C GEIA 7.1 Tg C [10 12 atom C cm -2 s -1 ] Guenther et al, JGR, 1995 EPA BEIS2 2.6 Tg C Pierce et al, JGR, 1998 Guenther et al, ACP, 2006 E = A ∏ i γ i Emissions (x,y,t); fixed base emissions(x,y); sensitivity parameters(t)
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Global Ozone Monitoring Experiment (GOME) & the Ozone Monitoring Instrument (OMI) GOME (European), OMI (Finnish/USA) are nadir SBUV instruments Ground pixel (nadir): 320 x 40 km2 (GOME), 13 x 24 km2 (OMI) 10.30 desc (GOME), 13.45 asc (OMI) cross-equator time GOME: 3 viewing angles global coverage within 3 days OMI: 60 across-track pixels daily global coverage O3, NO2, BrO, OClO, SO2, HCHO, H2O, cloud properties Launched in 2004
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GOME HCHO columns July 2001 [10 16 molec cm -2 ] 0 1 2 0.5 1.5 2.5 Biogenic emissions Biomass burning * Columns fitted: 337-356nm * Fitting uncertainty < continental signals Data: c/o Chance et al
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MayJunJulAugSep 1996 1997 1998 1999 2000 2001 GOME HCHO column [10 16 molec cm -2 ] 0 1 2 0.5 1.5 2.5 Palmer et al, JGR, 2006.
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Relating HCHO Columns to VOC Emissions VOC HCHO hours OH hours h, OH Local linear relationship between HCHO and E k HCHO E VOC = (k VOC Y VOC HCHO ) HCHO ___________ VOC source Distance downwind HCHO Isoprene -pinene propane 100 km E VOC : HCHO from GEOS-CHEM and MCM models Palmer et al, JGR, 2003.
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MCM HCHO yield calculations Cumulative HCHO yield [per C] pinene ( pinene similar) DAYS 0.4 Isoprene HOURS 0.5 NO x = 1 ppb NO x = 0.1 ppb Parameterization (1 ST -order decay) of HCHO production from monoterpenes in global 3-D CTM Higher CH 3 COCH 3 yield from monoterpene oxidation delayed (and smeared) HCHO production Palmer et al, JGR, 2006. C 5 H 8 +OH (i) RO 2 +NO HCHO, MVK, MACR (ii) RO 2 +HO 2 ROOH ROOH recycle RO and RO 2
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Monthly mean AVHRR LAI MEGAN (isoprene) Canopy model Leaf age LAI Temperature Fixed Base factors MODEL BIOSPHERE GEIA Monoterpenes MBO Acetone Methanol Modeling Overview GEOS-CHEM Global 3D CTM PAR, T Emissions MCM: parameterized HCHO source from monoterpenes and MBO
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Seasonal Variation of Y2001 Isoprene Emissions Good accord for seasonal variation, regional distribution of emissions (differences in hot spot locations – implications for O 3 prod/loss). Other biogenic VOCs play a small role in GOME interpretation May Jun Aug Sep Jul 0 3.5 7 10 12 atom C cm -2 s -1 GOMEMEGAN GOME Palmer et al, JGR, 2006.
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GOME Isoprene Emissions: 1996-2001 MayJunJulAugSep 1996 1997 1998 1999 2000 2001 [10 12 molecules cm -2 s -1 ] 0 5 10 Relatively inactive Palmer et al, JGR, 2006.
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Surface temperature explains 80% of GOME- observed variation in HCHO NCEP Surface Temperature [K] GOME HCHO Slant Column [10 16 molec cm -2 ] G98 fitted to GOME data G98 Modeled curves Time to revise model parameterizations of isoprene emissions? Palmer et al, JGR, 2006.
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Tropical ecosystems represent 75% of biogenic NMVOC emissions 1996 1997 1998 1999 2000 2001 What controls the variability of NMVOC emissions in tropical ecosystems? Importance of VOC emissions in C budget? Kesselmeier, et al, 2002 GOME HCHO column, July
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Challenges: Cloud cover, biomass burning, and lack of fundamental understanding of NMVOC emissions… OMI, 24/9-19/10, 2004 13x24 km 2 TES data @ 6km, 11/04 O3O3 CO MODIS Firecount O 3 -CO-NO 2 -HCHO- firecount correlations import to utilize when looking at the tropics Improved cloud- clearing algorithms and better spatial resolution data help. TES data c/o Bowman, JPL A more integrated approach to understanding controls of NMVOCs, e.g., surface data, lab data,
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Beta NO 2 column data, OMI, August 2004 NAEI NO X emissions as NO 2, 2002 O(1 km) O(few kms) O(10s km) For example, NO 2 Horizontal spatial scales Resolution of new satellite data allows UK air quality monitoring from space “Expect harmful levels of ozone and PM2.5 over the next couple of days; please keep small children and animals inside. Transatlantic pollution represent 20% of today’s ozone.”
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Many scientific milestones on the way to operational NCWP UKCA: global 3-D coupled chemistry- aerosol-climate model UM mesoscale version of UKCA over UK (JCMM, UKMO) Data assimilation/inverse modelling tools for interpreting satellite data. Eg, estimating inter- species error covariance, Numerical chemical weather prediction (NCWP) Public consumption Air-quality-climate links Improved understanding of surface fluxes, aerosol- chemistry processes, and dynamics… DATA
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“First global space-based measurements of CO 2 with the precision and spatial resolution needed to quantify carbon sources and sinks” The Orbiting Carbon Observatory (OCO) Spectroscopic observations of CO 2 ( 1.61 m and 2.06 m) and O 2 (0.765 m) to estimate the column integrated CO 2 dry air mole fraction, X CO2 = 0.2095 x (column CO 2 ) / (column O 2 ) Precisions of 1 ppm on regional scales Global coverage in 16 days (nadir 1x1.5 km footprint) JPL-based instrument: PI D. Crisp; Deputy PI: C. Miller (Crisp et al, 2004) Launch in 2008 2-year mission
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Continuous mapping of tropospheric columns of O 3, AOD, CO, HCHO, NO 2, SO 2 at km-scale resolution Continental-scale for Geo, full sunlit disk for L1 GeoTROPE and Cameo, Janus Geostationary and L1 mission concepts L1 0.8 0.6 0.4 0.2 0.0 SEVIRI, September 1999 0.55µm AOD. C/o Kerridge @ RAL GEO Midday sun-glint screening L1 worked successfully for SOHO – solar physics satellite sun * L1 x x/ 100
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