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This article outlines the implementation of model review recommendations for heavy metal modelling, including the evaluation of meteorological data and the development of parameterization for HM re-suspension. It also discusses the extension of the model for second priority metals, inclusion of a shallow lowest model layer, and improvement of Hg chemical transformations. The article concludes with the evaluation of different emission scenarios and the comparison of model results with observations.
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Heavy metal modelling:implementation of the model review recommendations Oleg Travnikov EMEP/MSC-E
Recommendations of TFMM Workshop on the HM/POP models review • Evaluation of driving meteorological fields • Development of the model parameterization for HM re-suspension from the ground surface • Extension of the model for the second priority metals (As, Cr, Ni, Cu, Se, Zn) • Inclusion of a shallow lowest model layer • Improvement of the descriptionof removal processes (Hg dry depositions to forests) • Further research and improvement of the description of Hg chemical transformations in the atmosphere • Extension of the hemispheric model to the global scale
Recommendations of TFMM Workshop on the HM/POP models review • Evaluation of driving meteorological fields • Development of the model parameterization for HM re-suspension from the ground surface • Extension of the model for the second priority metals (As, Cr, Ni, Cu, Se, Zn) • Inclusion of a shallow lowest model layer • Improvement of the descriptionof removal processes (Hg dry depositions to forests) • Further research and improvement of the description of Hg chemical transformations in the atmosphere • Extension of the hemispheric model to the global scale
Evaluation procedure Evaluation of meteorological data • Analysis of physical processes parameterization in the meteorological pre-processor (MM5) • Evaluation of generated meteorological fields against ECMWF (ERA-40) and GPCP data • Analysis of spatial and temporal variation of meteorological parameters (wind speed, air temperature, precipitation amount etc.)
Monthly precipitation amount in July 2000 cm/mon Spatial correlation of monthly precipitation modelled by MM5 against ECMWF and GPCP data MM5 (set #1) MM5 (set #6) ECMWF Evaluation of meteorological data
Concluding remarks Evaluation of meteorological data • The optimum set of the pre-processor (MM5) parameters was derived from the evaluation procedure • Good agreement was obtained between meteorological fields generated by the pre-processor and ECMWF/GPCP data • It is planed to move to the ECMWF input data for the pre-processing
Wind re-suspension of HM Dust suspension: • Saltation Horizontal movement of soil aggregates (40 mm – 10 mm) • Sandblasting Collisions of soil aggregates resulting in emission of dust particles (0.1 – 20 mm)
Saltation Horizontal saltation flux Threshold wind friction velocity Factors affecting saltation: • Threshold wind stress • Size of soil aggregates • Soil moisture [Marticorena & Bergametti, 1995]
Dust aerosol populations [Alfaro et al., 1997; 1998] mode 2 mode 1 mode 1 mode 3 Sandblasting Vertical dust flux [Alfaro & Gomes, 2001] Soil populations [Chatenet et al., 1996]
Dust suspension from soil Dust suspension flux (2000) Types of ground surface: • Deserts, bare soils • Agricultural soils (during cultivation period) • Urban areas
HM concentration in soil Pb concentration in European soils Default HM concentrations in soil (Eastern Europe, Africa, Asia) FOREGS (www.gtk.fi/publ/foregsatlas/)
Sea salt suspension Vertical sea salt flux [Gong, 2003] HM emission factors Size distribution of mass flux Gong-Monahan
Anthropogenic emissions vs.re-suspension (Pb) Anthropogenic emissions (ESPREME) Re-suspension
Anthropogenic emissions vs.re-suspension (Pb) Pb emissions in European countries Pb mean concentration in soil
Anthropogenic emissions vs.re-suspension (Cd) Anthropogenic emissions (ESPREME) Re-suspension
Anthropogenic emissions vs. re-suspension (Cd) Cd emissions in European countries Cd mean concentration in soil
Model evaluation for different emission scenarios Comparison of official/TNO emissions data and ESPREME estimates Lead Cadmium Official/TNO – 11 kt/y ESPREME – 13 kt/y Official/TNO – 280 t/y ESPREME – 580 t/y
Pb Model results vs. observations Annual mean Pb concentration in precipitation (2000) ESPREME+resuspen. Official/TNO Official/TNO+resuspen. Areg = 0.35 Rcorr = 0.7 Areg = 0.62 Rcorr = 0.66 Areg = 0.79 Rcorr = 0.62 Areg – linear regression coefficient Rcorr – correlation coefficient
Cd Model results vs. observations Annual mean Cd concentration in precipitation (2000) ESPREME+resuspen. Official/TNO Official/TNO+resuspen. Areg = 0.26 Rcorr = 0.76 Areg = 0.33 Rcorr = 0.71 Areg = 0.71 Rcorr = 0.53 Areg – linear regression coefficient Rcorr – correlation coefficient
Second priority metals Annual depositions of As, Cr, Ni in 2000 As Cr Ni
Ni Second priority metals Annual mean Ni concentration in air (2000) Air concentration of Ni at different monitoring sites (ESPREMEemissions)
Conclusions • A tentative parameterisation of wind re-suspension of heavy metals from soil and seawater has been developed • Re-suspension of lead is comparable to anthropogenic emissions, whereas cadmium re-suspension insignificantly contribute to total emission in Europe • Modelling results based on the ESPREME estimates commonly demonstrate better agreement with measurements than those on the official/TNO data • The model parameterisation has been extended for the second prioritymetals. Preliminary modelling results demonstrate satisfactory agreement with measurements