Modelling air quality requires the description of a large number of processes interacting each other. In order to properly model concentrations of atmospheric pollutants it is crucial to have a realistic reproduction of meteorological parameters, which can be critical in areas presenting a complex orography like the Italian peninsula. This work shows an analysis of the results obtained with the national model MINNI at two different horizontal resolutions (20 and 4 km), for a whole year over Italy. Comparisons between modelled and observed temperature and pollutants concentrations are carried out. The prediction of temperature is improved with the increase of model spatial resolution, as it is for pollutants like NO2 and CO, while the improvement is not always evident for O3 concentrations. Results are discussed providing an interpretation of the observed features. © Springer Science+Business Media Dordrecht 2014.

Study of the impact of low vs. high resolution meteorology on air quality simulations using the MINNI model over italy

Zanini, G.;Righini, G.;Piersanti, A.;Cremona, G.;Ciancarella, L.;Pace, G.;Cappelletti, A.;Briganti, G.;Cionni, I.;Vitali, L.;Mircea, M.;D'Isidoro, M.
2013-01-01

Abstract

Modelling air quality requires the description of a large number of processes interacting each other. In order to properly model concentrations of atmospheric pollutants it is crucial to have a realistic reproduction of meteorological parameters, which can be critical in areas presenting a complex orography like the Italian peninsula. This work shows an analysis of the results obtained with the national model MINNI at two different horizontal resolutions (20 and 4 km), for a whole year over Italy. Comparisons between modelled and observed temperature and pollutants concentrations are carried out. The prediction of temperature is improved with the increase of model spatial resolution, as it is for pollutants like NO2 and CO, while the improvement is not always evident for O3 concentrations. Results are discussed providing an interpretation of the observed features. © Springer Science+Business Media Dordrecht 2014.
2013
Air quality modelling;High resolution;Italy;MINNI
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/353
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