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, May 2004

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

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

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”

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.

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.

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.

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

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 combustion Industrial combustion33 Production processes02080 Extraction & distribution of fossil fuels Solvent and other product use Road transport Other mobile sources and machinery Waste treatment and disposal Agriculture70030 Size distribution (Aitken/accum)15 / 85 (20 / 80) 0 / 100 Coarse PM = PM 10 - PM Density,  (kg/m 3 ) Diameter0.05/0.3 µm(0.02/ 0.2)µm5 (6.5) µm

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

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

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!!!

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?

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

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 water

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

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

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

Sea salt

Mace Head Birkenes

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

Meteorologisk Institutt met.no Meteorological variability

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 AVG AVG AVG AVG AVG -1997

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

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

Percentage variability of PM2.5 due to meteorological conditions Meteorologisk Institutt met.no % over European countries10-20% over European countries

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

Meteorologisk Institutt met.no Scenario Analysis

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

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

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

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

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.

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 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 …