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Long term modelling analysis of the contribution of the main emission sources to the particulate matter concentration over Italy

pubblicazioni - Articolo

Long term modelling analysis of the contribution of the main emission sources to the particulate matter concentration over Italy

sources to the particulate matter concentration over Italy Guido Pirovano*, Giuseppe Maurizio Riva* IGAC 10th International Conference Bridging the scales in Atmospheric Chemistry Annecy, France 7-12 Settembre 2008 POSTER SESSION * CESI RICERCA Current researches highlight more and more often the relevant interaction existing between climate change and air quality, the latter still representing a very critical issue in Italy, mainly owing to particulate matter. The presence of particulate matter in atmosphere derives from several transformation processes, involving emissions produced by most of the anthropogenic activities. By means of chemical transport models is possible to describe the main phenomena driving the pollution processes as well as to discriminate the role played by the different sources. To this aim, in particular, the CAMx model implements the PSAT algorithm, an advanced source apportionment tool. The CAMx model ha been applied for the whole 2004 over a simulation domain covering the whole Italy, with a grid step of 25 km. CAMx has been driven by the RAMS meteorological model; emissions have been derived from the Italian official inventory and the EMEP database; finally, the initial and boundary conditions have been obtained by CHIMERE model runs at European scale. The PSAT tool has been applied in order to evaluate the contribution of main emission sectors to PM concentrations over Italy, such as energy production, transport and domestic heating. Transport proved to be the most relevant sector contributing up to 30%, on yearly basis, of the particulate matter concentrations in the most polluted areas, such as the Po valley. Residential heating contribution ranged around 5-10%, while energy production influence was generally lower than 5%.

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