13 th TFMM annual meeting: 17 th –19 th April 2012 - Grand Hotel – Mgarr – Gozo – MALTA

1. A source apportionment study and model validation for HMs and POPs air concentrations of MINNI project C. Silibello1, G. Calori1, M. Costa1, P. Radice1, M. Mircea2 1 ARIANET Srl, Via Gilino, 9, 20128, Milan, Italy 2 ENEA, National Agency for New Technologies, Energy and Sustainable Economic Development, via Martiri di Monte Sole 4, 40129, Bologna, Italy 13th TFMM annual meeting: 17th–19th April 2012 - Grand Hotel – Mgarr – Gozo – MALTA

2. Outline • Simulation setup • Wind re-suspension from soil and seawater • Comparison with experimental data • Source apportionment: foreign sources contribution and sector contribution • Summary and future plans

3. Simulation setup

4. The MINNI ProjectAtmospheric Modelling System Space,time, species info Local data Reference inventory ECMWF fields Meteorological Subsystem Emission Subsystem RAMS SURFPRO Emission Manager Reference Meteorological year Reference Emission year B.C. MSC-W: Inorganic/Organic MSC-East: POPs/HMs Chemical- transport Subsystem FARM Transfer matrices Concentration Deposition fields RAINS

5. Meteorology Meteorology subsystem ECMWF fields Re-analysis RAMS 1 | 2 grids, 4DDA SYNOPs

6. Emission subsystemNational emission inventory for heavy metals: year 2005 (ISPRA, 2009)

7. Emission subsystemIntegration of inventories National emission inventory by province and sector (NUTS3 and SNAP2/3) + LPS (~140) Emissions of surrounding countries from EMEP

8. Emission subsystemExample: Sea traffic International (EMEP) National Total

9. Boundary conditions: EMEP Meteorological Synthesizing Centre East (MSC-E) • EMEP MSC-E air concentrations • 50 kmx50km, 6 hours • HMs: • Pb, Cd, Hg, As, Ni, Cr, Zn, Cu, Se; • POPs: • 4 indicator PAHs; • γ-HCH; • HCB; • 17 congeners of PCDD/Fs; • 5 congeners PCBs.

10. Yearly average concentrations of As EMEP 50km x 50km MINNI 20km x 20km

11. Wind re-suspension from soil and seawater

12. Metal Emission factor (mg/kg) Reference As 300 Nriagu, 1989 Cd 40 Richardson et al., 2001 Cr 80 Nriagu, 1989 Ni 180 Nriagu, 1989 Pb 4000 Richardson et al., 2001 Wind re-suspension from soil and seawater Wind re-suspension of particles from soil and with sea-salt is estimated using Vautard et al. (2005) and Zhang et al. (2005). The production of dust from soils is not taken into account if precipitation during the last 48 hours exceeds 0.5 mm. Emission factors of heavy metals for suspension with sea-salt aerosol From: MODELLING OF HEAVY METALS ATMOSPHERIC DISPERSION IN EUROPE by Oleg Travnikov and Ilia Ilyin; Meteorological Synthesizing Centre – East of EMEP

13. Metal Soil concentration, mg/kg Reference As 5 Beyer & Cromartie, 1987 Cd 0.2 Nriagu, 1980a Cr 50 Shacklette et al., 1970 Ni 15 Nriagu, 1980b Pb 15 Reimann and Cariat, 1998 As concentration in topsoil Spatial distribution of heavy metal concentration in soil has obtained using data available from FOREGS web site. For Eastern Europe and Africa default concentration values based on the literature data were used (Table below). Default concentrations of heavy metals in soil

14. Yearly averaged concentration of As MINNI All sources Wind re-suspension from soil and seawater The contribution from Aeolian resuspension is about 1%

15. Comparison with experimental data

16. Background monitoring sites

17. As yearly averaged concentration All stations Target value 6 ng m-3

18. Ni yearly averaged concentrations All stations Target value 20 ng m-3

19. Cd yearly averaged concentrations All stations Target value 5 ng m-3

20. Pb yearly averaged concentrations All stations Limit value 500 ng m-3

21. B[a]P yearly averaged concentrations All stations Target value 1 ng m-3

22. Source apportionment

23. Source apportionment • Foreign sources: • A) Zeroing BCs ( “Long-range contribution”); • Zeroing both BCs and emissions in surrounding countries • For both cases: • Two months run of the AMS (winter –January- and summer –July-); • Computation of the variation between reference and ‘case run’ concentrations (). The percentage contribution of the ‘case run’ is computed as: 100* / Creference • Sector contribution: • Emission scenario: decrease of sector emissions (-20%); • Two months run of the AMS (winter –January- and summer –July-); • Computation of the variation between reference and scenario averaged concentrations (). The percentage contribution of a sector i is computed as: i / iN

24. Foreign sources contributions:Ni and B[a]P

25. Ni Long-range contribution (A) Contribution % Variation i

26. 90 80 70 60 50 40 30 20 10 5 2 1 0.1 [%] Ni Long-range contribution (A) Contribution %

27. Ni Surrounding countries emissions (B) Contribution % Variation i

28. B[a]P Long-range contribution (A) Contribution % Variation i

29. B[a]P Surrounding countries emissions (B) Contribution % Variation i

30. Major sectors contribution on concentrations • Sector contribution: • combustion in energy production and transformation (Sector 1); • non-industrial combustion, residential and commercial (Sector 2); • combustion in manufacturing industry (Sector 3); • industrial processes (Sector 4); • road transport (Sector 7); • other mobile sources (Sector 8); • waste treatment and disposal (Sector 9).

31. Pb Combustion in Residential, Combustion in Industry and Production Processes

32. Pb Non-industrial combustion, residential and commercial (Sector 2) Contribution % Variation i

33. Pb Combustion in manufacturing industry (Sector 3) Contribution % Variation i

34. Pb Production processes (Sector 4) Contribution % Variation i

35. B[a]P Non-industrial combustion, residential and commercial (Sector 2) Contribution % Variation i

36. Summary and future plans • the atmospheric modelling system of the MINNI project is able to simulate realistic concentrations of heavy metals and B[a]P; • lower values of modelled concentrations suggest a significant underestimation in the emissions. A better knowledge in emission inventories may improve predictions; • more observations, for longer periods and covering the whole country, are necessary for a comprehensive validation of model results; • the contribution of Aeolian resuspension to heavy metals concentrations is low; B[a]P concentrations are strongly influenced by national sources, over most of the Italian territory; • the effect of foreign emissions is higher near the Alpine border at the north, over the islands (Sardinia and Sicily) and in some rural areas in the central-southern part of the Italian peninsula, far from densely inhabited zone; • civil heating, particularly in the regions where wood burning devices are used, is the main contributor B[a]P concentrations. The contribution of the industrial sector isrelevant around major facilities, with the largest absolute contribution in Taranto, whose steel industries are the largest individual source of PAH in the country according to the national emission inventory. Road traffic contributes for a few percentage points, with highest absolute contributions in the Po Valley and near Rome and Naples metropolitan areas. The remaining sectors play an almost negligible role. • simulations for other years, with higher spatial resolution, coupling of POPs partitioning to full chemical model (SAPRC99 and AERO3)

37. Acknowledgements • This work is part of the MINNI (Integrated National Model in support to the International Negotiation on Air Pollution) project, funded by the Italian Ministry of Environment, Territory and Sea. • We wish to thank Ilia Ilyin, Marina Varygina and Alexey VladimirovichGusev (EMEP MSC-E) and Anna Carlin Benedictow and Michael Gauss (EMEP MSC-W) for providing EMEP models output. • We also wish to thank Beatrice Bondanelli (Autonomous Province of Bolzano), Monica Angelucci (Environmental Agency of Umbria Region), SandroZampilloni (Lazio Region), Carla Contardi (Piemonte Region), FulvioStel (Environmental Agency of Region Friuli-Venezia Giulia), Giuseppe Onorati (Campania Region), Salvatore Patti (Environmental Agency of Veneto Region) for supplying monitoring data.

38. Thank you!