1. Title Progress in the development and results of the UNIFIED EMEP model Presented by Leonor Tarrason EMEP/MSC-W 29 th TFIAM meeting, Amiens, France, 10-12 May 2004

2. Outline Meteorologisk Institutt met.no TFMM workshop REVIEW OF THE UNIFIED EMEP MODEL Progress at MSC-W in modelling PM mass PM emission speciation Water bound PM mass SOA empirical approaches to SOA modelling Meteorological variability and consequences for SR calculations

3. Evaluation of the EMEP model Mandate Meteorologisk Institutt met.no  Examination of the processes and meteorological parameterizations, chemical mechanisms and the sources of model input data; and  Evaluation of the model performance against daily observations of key model species and fluxes from the EMEP, AIRBASE and national monitoring networks for 1980, 1985, 1990, 1995, 1997, 1998, 1999 and 2000; and  A consideration of the source-receptor relationships for sulphur, nitrogen, ozone and suspended particulate matter (PM mass). TFMM workshop to review and evaluate the Unified EMEP model was hold in Oslo 3-5 november 2003, with 72 participants, 2 European model inter-comparisons (TNO-EMEP, EURODELTA), individual country reviews

4. Evaluation of the EMEP model Conclusions O 3 Meteorologisk Institutt met.no For ozone, it was concluded that the model: is suitable for the assessment of vegetation exposure and for the assessment of human health effects on the regional scale with the aim to support European air quality strategies. is suitable for the establishment of source-receptor data for human health exposure and vegetation exposure/uptake of ozone on the regional scale. is able to predict changes in ozone concentrations caused by changes in precursor emissions on a European level. “The model showed an excellent level of performance for daily maximum ozone concentrations. For nitrogen dioxide, the performance was less good, in common with all other models, possibly due to subgrid variations. The model shows a tendency to underestimate the episodic ozone peak concentrations (>60ppb) and uncertainties will be higher for source-receptor compared with extreme value statistics”

5. Evaluation of the EMEP model Conclusions O 3 Meteorologisk Institutt met.no Long-term work plan recommendations: Further consideration should be given to: interactions with local scale air pollution (particularly concerning the outcome of the CITY-DELTA exercise) the continued increase in background ozone concentrations for the assessment of trends the model and measured trends in VOCs and oxidation products and to developing improved partitioning of stomatal and non-stomatal fluxes of ozone to vegetation, validated against field observations.

6. Evaluation of the EMEP model Conclusions PM Meteorologisk Institutt met.no For suspended particulate matter, it was concluded that the model:  in its present form significantly underestimates total PM concentrations due to unknown processes and emissions.  is however able to calculate the regional component of main anthropogenic PM fractions (sulphate, nitrate, ammonium, some primary components) with enough accuracy for the assessment of the outcome of different control measures.  requires urgent attention with the aim of developing the model further for the full assessment of the anthropogenic fraction of PM2.5.

7. Evaluation of the EMEP model Conclusions PM Meteorologisk Institutt met.no Short term recommendations: In the short term, attention should be given to: the evaluation of present emission inventories the analysis of measurements and anthropogenic emissions of specific species of PM and the contribution to particle mass from particle-bound water the exploration of empirical approaches to the development of a model for secondary organic aerosol formation based on available data and knowledge. Long-term recommendations: In the longer term, evaluations are required against speciated monitoring data, the inclusion of improved emission inventories, the inclusion of biogenic primary emissions, the formation of secondary biogenic aerosols in order to achieve full mass closure.

8. Meteorologisk Institutt met.no Progress at MSC-W modelling PM mass  still plenty of uncertainties …..

9. PM Emissions Chemical speciation and size distribution of PM Emissions on-going work at PM Expert Group under TFEIP Meteorologisk Institutt met.no PM 2.5 OC (%)EC (%)Mineral dust (%) Power generation33 Residential and other combustion502030 Industrial combustion33 Production processes02080 Extraction & distribution of fossil fuels405010 Solvent and other product use402040 Road transport402040 Other mobile sources and machinery402040 Waste treatment and disposal106030 Agriculture70030 Size distribution (Aitken/accum)15 / 85 (20 / 80) 0 / 100 Coarse PM = PM 10 - PM 2.5 --100 Density,  (kg/m 3 ) 2000 2600 Diameter0.05/0.3 µm(0.02/ 0.2)µm5 (6.5) µm

10. Meteorologisk Institutt met.no Daily PM2.5 vs. EMEP measurements Hourly PM2.5 Aspvreten, SE. 2000

11. Chemical composition of PM (1): Meteorologisk Institutt met.no Unaccounted PM mass ViennaStreithofen PM2.5 Austria,1-6/2000 PM10PM25 Largest discrepancy: OC, EC, dust

12. Chemical composition of PM (2): Meteorologisk Institutt met.no  Non-C atoms in organic aerosol  Particle-bound water  Measurement artefacts Full chemical mass closure is rarely achieved. Unaccounted PM mass - up to 35-40% Gravimetric method (Reference, EU and EMEP) for determining PM mass requires 48-h conditioning of dust-loaded filters at T=20C and Rh=50% - does not remove all water! At Rh=50% particles can contain 10-30% water Gravimetrically measured PM mass does not represent dry PM mass!!!

13. Chemical composition of PM (3): Meteorologisk Institutt met.no Unaccounted PM mass in obs Aerosol water in model ViennaStreithofen PM2.5 Austria,1-6/2000 (AUPHEP) PM10PM25 To what extend can particle- bound water explain the model underestimation of measured PM?

14. Meteorologisk Institutt met.no Modelled dry PM 2.5 vs. Identified PM 2.5 mass

15. Meteorologisk Institutt met.no Accounting for particle-bound water in PM2.5 Model calculations vs. gravimetric PM2.5 (EMEP, 2001) Dry PM 2.5 N=13 Bias=- 47% Corr=0.69 N=13 Bias=-28% Corr=0.68 Dry PM 2.5 + water

16. Meteorologisk Institutt met.no Model calculated dry PM2.5 (blue) and PM2.5 including aerosol water (black) vs. measured PM2.5 (red) Accounting for water in modelled PM2.5 gives better agreement with measurements…BUT : verification of model calculated aerosol water is needed

17. An example: Vienna Meteorologisk Institutt met.no Daily PM2.5 (June 1999 - June 2000) : What is needed: “component-wise” verification of modelled PM

18. Daily series of SO 4, NO 3 and NH 4 in PM2.5 Meteorologisk Institutt met.no NO3 NH4 SO4 OC EC Na EC PM emissions validation

19. Sea salt

20. Mace Head Birkenes

21. Adding a “standard” SOA module to EMEP model gives too much OC and produces summer maxima that are not observed! (D. Simpson, on-going research) Organic aerosol in the EMEP model

22. Meteorologisk Institutt met.no Meteorological variability

24. Figure 7.3 Difference in mean daily max. summer (June, July, August) ozone averaged over the years 1995 to 2000 and the individual years. Meteorological variability - Daily summer ozone (JJA) AVG -1995 AVG -2000 AVG -1996 AVG -1998 AVG -1999 AVG -1997

25. Annual mean concentrations of PM2.5 Meteorologisk Institutt met.no 2001 2002 Aerosol model EMEP obs

26. Annual mean concentrations of PM2.5 Meteorologisk Institutt met.no 19992003

27. Percentage variability of PM2.5 due to meteorological conditions Meteorologisk Institutt met.no 2003-19992002-2001 25-35% over European countries10-20% over European countries

28. O 3 mean Differences due to meteorological conditions Meteorologisk Institutt met.no 5-10% variations due to meteorology

29. Meteorologisk Institutt met.no Scenario Analysis

30. Reduction in mean concentrations of PM2.5 due to emission changes in 2010 Meteorologisk Institutt met.no 1999 met2003 met 25-35% changes due to envisaged reduction in emissions (2010) Similar to meteorological variability ranges from 1999 – 2003

31. Reduction in mean O3 concentrations due to emission changes in 2010 Meteorologisk Institutt met.no 1999 met2003 met 5-7% changes due to envisaged reduction in emissions (2010) Similar to meteorological variability ranges from 1999 – 2003

32. Reduction in mean concentrations of PM2.5 due to emission changes in 2020 Meteorologisk Institutt met.no 1999 met2003 met 35-50% changes due to envisaged reduction in emissions (2020) Considerably larger than meteorological variability ranges from 1999 – 2003

33. Reduction in mean O3 concentrations due to emission changes in 2020 Meteorologisk Institutt met.no 1999 met2003 met 5-7% changes due to envisaged reduction in emissions (2020) Similar to meteorological variability ranges from 1999 – 2003

34. Meteorologisk Institutt met.no Closing remarks (I) Model calculations vs. gravimetric PM2.5 over Europe show an with average 28% underestimation and correlations of 0.68 for n=17 stations – similar to other state-of-art models. Conclusions on model performance are at present hampered by the availability of measured PM2.5 chemical components and information on primary PM emissions. SOA theories are too immature for application within the EMEP policy framework. The EMEP model results should not be used in studies dependent of the analysis of absolute values of PM2.5 but …they are reasonable to study the effect of identified emission changes.

35. Meteorologisk Institutt met.no Closing remarks (II) Changes in meteorological conditions introduce variability in the scenario analysis that are comparable to the expected variations in PM concentrations due to emission reductions in 2010. In 2020, expected changes due to emission reductions become more significant than the meteorological variations. For ozone, envisaged emission reductions both in 2010 and 2020 would impose concentration changes similar to those expected from meteorological variations. Calculation of source-receptor calculations for IAM needs to be carried out for as many different meteorological years as plausible : 2003 (on-going), 1999, 2000 …