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H. Fagerli , P. Wind, A. Nyiri, D. Simpson ++

Improved resolution in the EMEP model; do the results for acidifying and eutrophying components improve?. H. Fagerli , P. Wind, A. Nyiri, D. Simpson ++. TFMM, Paris, 15-17 th June 2009. EMEP/MSC-W. Outline. Stepwise improvement of scale in meteorology and emissions

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H. Fagerli , P. Wind, A. Nyiri, D. Simpson ++

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  1. Improved resolution in the EMEP model; do the results for acidifying and eutrophying components improve? H. Fagerli, P. Wind, A. Nyiri, D. Simpson ++ TFMM, Paris, 15-17th June 2009

  2. EMEP/MSC-W Outline • Stepwise improvement of scale in meteorology and emissions 5O km->25 km->10 km(2006 & 2007) +EMEP model in ~20 km rotated spherical coordinates (real resolution of meteorology) • Evaluation of results against EMEP measurements • Effect on S-R matrices

  3. Meteorology

  4. Emissions • TNO 0.125×0.0625º (Thanks to H. Denier van der Gon) • Keep national sector totals • Interpolated to 10, 25, 50km PS + 20 RS • EMEP emissions ‘disaggregated’ to all scales Model runs:

  5. Comparison to EMEP measurements 2006, spatial correlation, primary components • Bias changes in the order of 5% • Compare blue cells (effect of scale of meteorology) : stepwise improvement • Compare white cells (effect of meteorology + finer scale emissions) : results better, but because of better TNO gridded 50km emissions?

  6. EMEP/MSC-W • The average temporal correlation almost unchanged • Only a few large differences (mountain sites)

  7. EMEP/MSC-W Comparison to EMEP measurements 2006, spatial correlation, ‘secondary’ components • Bias changes in the order of 0-5% • Less clear conclusions than for the primary • Compare blue cells (effect of scale of meteorology) : no systematic changes, but 10km tend to best • Compare white cells (effect of meteorology + finer scale emissions) : results better, but because of better gridded 50km emissions?

  8. The average temporal correlation almost unchanged • H20 tend to be better than H25 • Larger difference in performance at each site (sometimes better, sometimes worse)

  9. EMEP/MSC-W Comparison to EMEP measurements 2006, spatial correlation, wet depositions • Bias changes in the order of 0-5% • Fine scale tend to be better, but most improvement reached at 25 km. The distribution of emissions less important

  10. EMEP/MSC-W • The average temporal correlation almost unchanged • Even larger difference in performance at each site (sometimes better, sometimes worse)

  11. Overall the frequency is better, but it is harder to hit the right grid cell at the right time

  12. EMEP/MSC-W Effect of resolution on SR matrices • 3 example countries: DE, GB, NL • SOx and PPM (simplest examples) • Year 2007 • H50, H25, H25-TNO

  13. Almost no effect of scale in meteorology • Small effect of re-distribution of emissions

  14. EMEP/MSC-W • Very small effect of scale in meteorology • Larger effect of redistribution of emissions -in this case the lack of oil installations in the north sea in the TNO data

  15. EMEP/MSC-W • Small effect of resolution, but larger than depositions; PM2.5 transported longer and more sensitive to meteorology

  16. EMEP/MSC-W Conclusions • Stepwise improvement of results (spatial correlation), especially for the primary components, with improvement of scale in meteorology (and emissions). Most improvement reached at 25 km. Compare with dense network? • Temporal correlations do not in average improve. A lot more scatter in the finest scale runs because of precipitation. • H20 not better than H25, except for temporal correlation of secondary components. Need finer scale emissions? • Preliminary: For depositions the scale matter little for SR matrices. Redistribution of emissions matters more. Calculations in different scales differ less than using 2 different meteorological drivers.

  17. Exceedances of CL’s and resolution acidification eutrophication CL’s: European background database (produced at CCE)

  18. EMEP/MSC-W Zoebelboden Rigi Schauinsland

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