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Frascati 26-27 nov 2009

Frascati 26-27 nov 2009

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Frascati 26-27 nov 2009

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  1. NorwegianInstitue for Air Research NILU Dept. Atmospheric and Climate Research (ATMOS) • www.nilu.no Frascati 26-27 nov 2009 A.-C. Engvall, A. Stohl, N. I. Kristiansen, A. Fahre Vik, K. Tørseth, and others

  2. FLEXPART group at NILU • Research projects within our group focus on various aspects of atmospheric transport - a few examples: • Arctic pollutants – transport linked to ground-basedmeasurements as well as aircraftmeasurements (Zeppelin station, POLARCAT). • Antarctic: Transport linked to Ground-basedmeasurements at Troll station. • Determine the mean and variation of the combined oceanic and atmospheric heat transports toward Svalbard and the European Arctic (POCAHONTAS). • …and more informationcan be find at http://transport.nilu.no

  3. Seasonalvariationof Arctic Haze Joranger and Ottar, Geophys. Res. Lett., 1984

  4. Climateeffectsof Arctic pollution Quinn et al., ACPD, 2008

  5. AMAP Expert Group on SLCF • Arctic Council Task Force on SLCF • IPCC activitieson Black Carbon • However: very large uncertainties; weneed to understand sources and relevant processesbetter

  6. Picture courtesy: Ann-Christine Engvall

  7. Transport ofagriculture fire emissionplumes Stohl et al., ACPD, 2007

  8. Dramaticeffectsonpollutionlevels At Zeppelin, newrecordssetfor practically all measured compounds Even for ozone and aerosol opticaldepth, whicharebothmeasuredsince 18 years Stohl et al., ACPD, 2007

  9. Long-term monitoringofvarious persistent organicpollutants (POPs) at Zeppelin Highestconcentrations observed during biomass burning episodes: Green: Alaskan fires Orange: Agricultural fires in EasternEurope Eckhardt et al., ACPD, 2007

  10. Volcanic eruptions Emissionsof SO2canaffecttheclimate and volcanicash is a major hazard to aviation. Goal: Simulatethe transport oftheemittedspecies and predicttheaffected areas. Problem: The modelsimulationrequire a verticalemissionheightprofile, which is unknown. Satellite data normally only provide total columns or very poorly resolved vertical profiles. Solution: Use a dispersionmodel, satellite observations of SO2 during the first few hours/days after the eruption, and an inversion algorithm to determine an optimal emission height profile of the eruption.

  11. Case study: Kasatochi Volcano, Alaska Eruption: 7-8 August 2008 Significant amount of SO2 emitted (1.5 – 2.5 Tg) Satellite observations from GOME-2 OMI AIRS Challenges: Temporal resolution: Only 1-2 overpasses each day observing the SO2 cloud. Retrievals: The satellite retrievals provide different total columns of SO2.

  12. Case study: Kasatochi Volcano, Alaska Inversion result: FLEXPART transport simulation: • Future/ongoing work: Inversion results for volcanic ash. • Requirements: • Satellite measurements cover the region of the volcano. • Good temporal resolution of the satellite data for the hours/days after the eruption • Good retrievals of both SO2 and volcanic ash.

  13. Motivation for investigation satellite based measurements • Data coverage of regular monitoring network not sufficient to answer questions like: • How large is the contribution of intercontinental transport of Air Pollution of regional-scale Air Quality ? • In particular in the eastern part of the EMEP region, central Asia and the eastern Mediterranean. Sites in North Africa would be valuable. …. no data over oceans … • Satellite data are available and should be used? • Request for additional data sources such as airborne measurements and remote sensing data • Evaluation of the SYNAER data product for regional air quality monitoring over Europe

  14. The SYNAER (SYNergetic Aerosol Retrieval) data product • The SYNAER product • Provided by DLR through ESA-GSE project PROMOTE “European multi-annual PM record” • see Holzer-Popp et al., ACPD, 2008 • Synergistic retrieval of aerosol properties based AATSR and SCIAMACHY (and ATSR/GOME) • Radiometer used to estimate AOD • Spectrometer used to estimate aerosol composition • Surface levels of PM10, PM2.5 and PM0.5 given for cloud-free pixels on SCIAMACHY-grid

  15. Requirements Useofsatellite data at NILU • Examples have beenshownhowsatellite data is used for analysing air mass transport ofpollutantswiththe FLEXPART model. • The inversion algorithm in FLEXPART (Stohl et al. 2009) is suitable also for incorporating satellite data and that we will do exactly that in the framework of SOGG-EA (Sources of Greenhouse Gases in East Asia). • EMEP programme: Validation and usage of satellite based AOD and PM measurements – SYNAER • Evaluation of different SYNAER versions • Validation against EMEP surface measurements and EMEP model • Close interaction between data provider and data user is beneficial – such cooperation should be encouraged by space agencies for current and future missions.

  16. Thankyou for yourattention!