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State-of-the-art synthesis of available information and modelling efforts on heavy metals in Italy

This paper presents the state-of-the-art synthesis and modelling efforts on heavy metals in Italy, including emissions, measurement data, national modeling system MINNI, Hg chemistry, land-cover, and dust production.

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State-of-the-art synthesis of available information and modelling efforts on heavy metals in Italy

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  1. State-of-the-art synthesis of available information and modelling efforts on heavy metals in Italy Mihaela Mircea1, Camillo Silibello2, Paola Radice2 Gabriele Zanini1 1National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), via Martiri di Monte Sole 4, 40129, Bologna, Italy 2ARIANET, Srl, Via Gilino, 9, 20128, Milan, Italy EMEP/TFMM meeting Larnaca, Cyprus, 12-14 May 2010

  2. Working groups ENEA Massimo Berico Gino Briganti Andrea Cappelletti Luisella Ciancarella Antonella Malaguti Pietro Marri Mihaela Mircea Giandomenico Pace Antonio Piersanti Lina Vitali Gabriele Zanini ARIANET Giuseppe Brusasca Giuseppe Calori Sandro Finardi Paola Radice Camillo Silibello

  3. Outline • Emissions • Measurements data • National model MINNI • Heavy metal processes • Hg chemistry • Land-cover • Dust production and re-suspension • Preliminary test case

  4. Emissions by macro-sectors Sector split of emissions of selected heavy metals (EEA member countries) (Ver. 1.00)- Data source: EEA aggregated and gap-filled air emission dataset, based on 2009 officially reported national total and sectoral emissions to UNECE LRTAP Convention. ISPRAinventory2005 In 2007 the largest emitters of lead were Poland (responsible for 20% of total EEA-32 emissions), Spain (10%), Italy (10%) and Bulgaria (9%) (APE005 - EEA32 Heavy metal (HM) emissions - Assessment published Feb 2010)

  5. Emissions by region

  6. Regional emissions of Pb, Hg, Cd

  7. Temporal variability of HM emissions yearly weekly daily

  8. HM measurements 2007-2008: air concentrations Cd,As,Ni -19 stations Pb -33 stations

  9. PM10 crustal metals measurements at Montelibretti: 2006-2007 air concentrations

  10. PM2.5 crustal metals measurements at Montelibretti: 2006-2007 air concentrations

  11. HM measurements at Montelibretti: 2006-2007 precipitation concentrations

  12. Field campaign Trisaia: 1 May – 1 July 2010 Measurements: -meteorology: pressure, temperature, relative humidity, wind speed and direction, radiation -air quality: gases and aerosol gases: NOx, O3, SO2, CO, CH4, NMHC aerosol: mass concentration PM10, PM2.5, chemical composition of PM2.5 and PM10, metals, including HM, in PM10 and PM2.5 each 24 hours Trisaia

  13. Meteo sub-system Emission sub-system ECMWF fields Local data Ref. inventory Space, time, species info RAMS Emission Manager Reference meteo year Emission scenario EMEP B.C. FARM Transfer matrices GAINS Italy Concentration & dep. fields Chemical-transport sub-system National modeling system MINNI: atmospheric module Long Range Transboundary Air Pollution Convention

  14. FARM-Flexible Air Quality Regional Model • Emission of pollutants from area and point sources, with plume rise calculation and mass assignment to vertical grid cells • 3D dispersion by advection and turbulent diffusion • SAPRC99 and POPs-Hg Gas-phase chemical mechanisms generated via KPP Software (LSODE/Rosenbrock solvers) • Treatment of PM10 and PM2.5 (aero0 inorganic equilibrium module, aero3 modal aerosol module) • Dry removal of pollutants dependent on local meteorology and land-use • Removal through precipitation scavenging processes • One- and two-way nesting on arbitrary number of grids • Treatment of additional inert tracers such as heavy metals • Parallel processing using OpenMP paradigm • Inclusion of data assimilation techniques • Online calculation of photolysis rates using TUV model (Tropospheric Ultraviolet and Visible radiation model; Madronich et al, 1989); RADM method to correct for cloud cover (Chang et al., 1987) • Inclusion of map scale factors and different coordinate systems

  15. HM processes • Emission of pollutants from area and point sources • 3D dispersion by advection and turbulent diffusion • HM-Aero0: fine and coarse aerosol particles • Hg gas-phase chemical transformations • Hg aqueous-phase removal in clouds • Dry removal of pollutants dependent on local meteorology and land-use • Removal through precipitation scavenging processes

  16. Hg chemistry Gas-phase Hg + O3 = 0.5HgO + 0.5HgAER: (3.00e-20); Hg + OH = 0.5HgO + 0.5HgAER: (8.70e-14); Hg + H2O2 = HgO : (8.50e-19); Hg + NO3 = HgO + NO2: (4.00e-15); Aqueous-phase Henry’s equilibria HgCl2(aq) Hg2+ + 2Cl- Hg(OH)2(aq)Hg2+ +2OH- Hg2+ + SO32-HgSO3 HgSO3 + SO32-Hg(SO3)22- Aqueous Kinetic Reactions Hg0(aq) + O3 (aq) Hg2+(aq) Hg0(aq) + OH(aq) Hg2+(aq) HgSO3(aq) Hg0(aq) Hg2+(aq) + HO2(aq) Hg0(aq) Hg0(aq) + HOCl(aq) Hg2+(aq) Hg0(aq) + OCl-(aq) Hg2+(aq) Adsorption of Hg(II) on PM (Seigneur et al., 1998) H g(II)(aq)  H(II)(p) Gas-phase chemistry: NO,NO2,NO3,HNO3,N2O5,PAN,SO2,H2SO4 The formation of condensable species from the gas-phase (HgAER) and the adsorption of Hg(II) on the particles within clouds is considered (Seigneur et al., 1998). Hg(II)(aq) represent the ensemble of Hg species in solution: Hg2++HgCl2(aq)+Hg(OH)2(aq)+HgSO3(aq)+Hg(SO3)22- HOCl e OCl- species are formed from Cl2 dissociation. As for HCl and chlorine (Cl2) typical vertical profiles are considered. (Yarwood et al., 2003; Xie et al., 2008; Jung et al., 2009)

  17. Questions for the HM case study organization Hg chemistry: What data to be used for HCl and chlorine (Cl2) vertical profiles? MSC-E and national models intercomparison: - How will be quantified “better model performance”? - Which model variables to be compared? Es. vertical profiles of NO2, etc., concentrations removed in-cloud and below-cloud, etc.

  18. Dry and wet removal Dry deposition Deposition velocities are calculated separately for each class (according to the specific PBL scaling parameters calculated for that class) and then averaged according to the land-use classes percentages, to give the mean value for the grid cell. Dry deposition of gases -resistances approach -Hg (0) and Hg(II) with parameters from Lin et al. (2006, Atm. Env.) Dry deposition of aerosol -the particle deposition velocity of fine and coarse particles is calculated as: Vd =1/ Rpartic where Rparticle is the resistance calculated from the canopy height (m), the friction velocity and the Monin-Obukhov length, and aerosol particle size. . Wet removal Wet removal of gases (EMEP (2003) In-cloud and below-cloud scavenging of soluble gases is a function of scavenging ratio and precipitation rate. Wet removal of aerosol In-cloud scavenging of aerosol particles is a function of scavenging ratio and precipitation rate. Below-scavenging of aerosol particles is a function of precipitation rate, size-dependent collection efficiency of aerosols by raindrops and and raindrop fall velocity (EMEP, 2003; Scott, 1979,J. Appl. Meteo.)

  19. Land-cover Aggregated CORINE classification scheme. # Code Description 1 URFA Urban fabric 2 INCO Industrial, commercial and transport units 3 AIRP Airports 4 OART Other artificial surfaces 5 ARAB Arable land (non-irrigated and permanently irrigated) 6 RICE Rice fields 7 CROP Permanent crops 8 PAST Pastures 9 HAGR Heterogeneous agricultural areas 10 BROA Broad-leaved forest 11 CONI Coniferous forest 12 MIXF Mixed forest 13 GRAS Natural grassland 14 SHRU Shrubs and heathland 15 SAND Beaches, dunes, and sand plains 16 BARE Bare rock 17 SPAR Sparsely vegetated areas 18 ICEF Glaciers and perpetual snow 19 INWE Inland wetlands 20 COWE Coastal wetlands 21 WATE Water bodies Water bodies is divided in sea and land-water in order to allow sea-salt aerosol production. Spatial resolution 250m Extended USGS/BATS classification scheme. # Code Description 1 CRMF crops/mixed farming 2 SHGR short grass 3 EVNE evergreen needleleaf trees 4 DENE deciduous needleleaf trees 5 DEBR deciduous broadleaf trees 6 EVBR evergreen broadleaf trees 7 TAGR tall grass 8 DESE desert 9 TUND tundra 10 IRCR irrigated crops 11 SEMI semi-desert 12 ICEC ice caps/glaciers 13 BOMA bogs and marshs 14 INWA inland water 15 OCEA oceans 16 EVSH evergreen shrub 17 DESH deciduous shrub 18 MIFO mixed woodland 19 FOFI interrupted forest (class added to USGS database) 20 WALA Land and water mixtures (class added to USGS database) 21 URBA urban (class added to USGS database) Land-use fields: Aggregate CORINE BATS Each grid point can be described by the prevailing class or the percentages of all classes. An additional parameter is the minimum urban land-use threshold (%) to be used to force a grid cell to be considered completely urban.

  20. Dust production and re-suspension [t/y] Fine fraction Vautard et al.(2005, Atm. Env.)

  21. Dust production and re-suspension [t/y] Coarse fraction Vautard et al.(2005, Atm. Env.)

  22. Hg preliminary test over Venice lagoon Hg(0) Hg(II) HgAER 1kmx1km resolution mean daily concentrations

  23. Thank you for your attention!

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