PAGE 1 An adaptation of SMOKE for Europe Johannes Bieser Armin Aulinger, Volker Matthias, Markus Quante GKSS Research Center Geesthacht, Germany.

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Presentation transcript:

PAGE 1 An adaptation of SMOKE for Europe Johannes Bieser Armin Aulinger, Volker Matthias, Markus Quante GKSS Research Center Geesthacht, Germany

PAGE 2 Outline Introduction Data used for European emission modelling Changes to the SMOKE model CMAQ performance using SMOKE emissions Conclusions

PAGE 3 Introduction Consistency Consistent data for all of Europe Consistent emissions for long-term CTM runs Flexibility Other species, chemical mechanisms, etc... Emission scenarios Model domain, year

PAGE 4 SMOKE for Europe Introduction Emission Inventories Surrogates Temporal profiles Stack information Meteorology Speciation profiles Pre-processors SMOKE Additional modules Model ready emissions

The bulk emission inventory EMEP official national annual emissions EPER Major point sources Species included: CO, NOx, NH3, SOx, PM10, PM2.5, NMVOC

Gridded Population of the World v.3 Resolution: 1 x 1 km Data available for:

CORINAIR LAND COVER 100 x 100 m 1990,2000,2006

USGS Global Landcover

Official European statistics: - Spatial resolution: NUTS2 - Employment rates for different industrial sectors - Employment rates in agriculture - Net working times - Animal stocks EUROSTAT

OPENSTREETMAPS.ORG

Digital Chart of the World Road and Rail Network 1992 Germany Western Russia

UBA Forest database Forest cover database 120 different tree types used as input for BEIS 3.14 Resolution: 1 x 1 km

PAGE 13 New SMOKE modules - SMOKE for Europe introduces two new modules (blue) which affect the temporal and spatial disaggregation of the emissions. - NORMAT reads meteorological datafor one whole year and creates a normalization matrix. - MODMAT changes the gridding matrix for each day depending on meteorological data.

Influence of the MODMAT module

SMOKE modelling domain used for evaluation - 54x54km² grid over Europe - 30 vertical layers up to 100 hPa - Scenario year: CTM: CMAQ chemical mechanism: CB IV - meteorology: CCLM - BC: TM4

Emission model used for comparison EMEPIER-GKSS TNO-GEMSSMOKE-EU

Regional comparison of Sulfate concentrations

Regional comparison of Ozone concentrations

Conclutions - The SMOKE model has been adapted to create European emissions for long-term CTM runs ( ). - A new module has been introduced which allows to directly couple meteorological fields with the spatial and temporal disaggregation of area sources. - SMOKE-EU emissions were evaluated by comparison with emission datasets from three widely used European emission models. - CMAQ runs for the year 2000 using the different emission datasets created comparable results.