Frascati nov 2009 A.-C. Engvall, A. Stohl, N. I. Kristiansen, A. Fahre Vik, K. Tørseth, and others Norwegian Institue for Air Research NILU Dept. Atmospheric and Climate Research (ATMOS)

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-based measurements as well as aircraft measurements (Zeppelin station, POLARCAT). Antarctic: Transport linked to Ground-based measurements 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 information can be find at

Seasonal variation of Arctic Haze Joranger and Ottar, Geophys. Res. Lett., 1984

Climate effects of Arctic pollution Quinn et al., ACPD, 2008

AMAP Expert Group on SLCF Arctic Council Task Force on SLCF IPCC activities on Black Carbon However: very large uncertainties; we need to understand sources and relevant processes better

Picture courtesy: Ann-Christine Engvall

Transport of agriculture fire emission plumes Stohl et al., ACPD, 2007

At Zeppelin, new records set for practically all measured compounds Even for ozone and aerosol optical depth, which are both measured since 18 years Dramatic effects on pollution levels Stohl et al., ACPD, 2007

Eckhardt et al., ACPD, 2007 Long-term monitoring of various persistent organic pollutants (POPs) at Zeppelin Highest concentrations observed during biomass burning episodes: Green: Alaskan fires Orange: Agricultural fires in Eastern Europe

Volcanic eruptions Emissions of SO 2 can affect the climate and volcanic ash is a major hazard to aviation. Goal: Simulate the transport of the emitted species and predict the affected areas. Problem: The model simulation require a vertical emission height profile, which is unknown. Satellite data normally only provide total columns or very poorly resolved vertical profiles. Solution: Use a dispersion model, satellite observations of SO 2 during the first few hours/days after the eruption, and an inversion algorithm to determine an optimal emission height profile of the eruption.

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

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 SO 2 and volcanic ash.

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

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

Requirements Close interaction between data provider and data user is beneficial – such cooperation should be encouraged by space agencies for current and future missions. Use of satellite data at NILU Examples have been shown how satellite data is used for analysing air mass transport of pollutants with the 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

Thank you for your attention!