This study investigates the effect of grid resolution on the particulate matter (PM10, PM2.5) mass concentrations and its chemical composition simulated with the AMS-MINNI modelling system. The air pollution was simulated over Italy with grid resolutions of 20 and 4 km, for a whole year. The gridded emissions were produced performing speciation and spacetime disaggregation of aggregated inventory data, using both land use information and anthropogenic activity-based profiles. Often, the fine grid simulations, based on high resolution gridded emissions, improved the agreement between model and measurements. In particular, the use of a fine grid improved predictions of primary species such as elemental carbon (EC), PM10 and PM2.5 mainly at urban stations. An improvement of predicted PM components and mass concentration at high altitudes sites was also observed, especially during winter. However, a general overestimation of nitrate (NO3–) and of secondary inorganic species, more evident at night than during the day, was increased by employing a finer grid. Organic carbon (OC) was more affected by the grid resolution than the other species. At urban and kerbside stations, the use of a finer grid resulted in an overestimation of primary organic carbon aerosol (POC) but had a negligible effect on secondary organic carbon aerosol (SOC). The overestimation of carbonaceous aerosol (defined as the sum of EC, POC and SOC), at an urban station, opposite to general underestimation of this component by air quality (AQ) models, indicates that the anthropogenic emissions can contribute as much as organic model formulation at the success of simulation in reproducing experimental data. The modelling results obtained under stable meteorological conditions characterised by weak winds, which are often encountered in the Po Valley, did not improve substantially by the increase of the modelling system resolution. © Taiwan Association for Aerosol Research.

Impact of grid resolution on aerosol predictions: A case study over Italy

Zanini, G.;Vitali, L.;Piersanti, A.;Pace, G.;Cremona, G.;Cionni, I.;Cappelletti, A.;Ciancarella, L.;Briganti, G.;Adani, M.;Righini, G.;D’Isidoro, M.;Mircea, M.
2016-01-01

Abstract

This study investigates the effect of grid resolution on the particulate matter (PM10, PM2.5) mass concentrations and its chemical composition simulated with the AMS-MINNI modelling system. The air pollution was simulated over Italy with grid resolutions of 20 and 4 km, for a whole year. The gridded emissions were produced performing speciation and spacetime disaggregation of aggregated inventory data, using both land use information and anthropogenic activity-based profiles. Often, the fine grid simulations, based on high resolution gridded emissions, improved the agreement between model and measurements. In particular, the use of a fine grid improved predictions of primary species such as elemental carbon (EC), PM10 and PM2.5 mainly at urban stations. An improvement of predicted PM components and mass concentration at high altitudes sites was also observed, especially during winter. However, a general overestimation of nitrate (NO3–) and of secondary inorganic species, more evident at night than during the day, was increased by employing a finer grid. Organic carbon (OC) was more affected by the grid resolution than the other species. At urban and kerbside stations, the use of a finer grid resulted in an overestimation of primary organic carbon aerosol (POC) but had a negligible effect on secondary organic carbon aerosol (SOC). The overestimation of carbonaceous aerosol (defined as the sum of EC, POC and SOC), at an urban station, opposite to general underestimation of this component by air quality (AQ) models, indicates that the anthropogenic emissions can contribute as much as organic model formulation at the success of simulation in reproducing experimental data. The modelling results obtained under stable meteorological conditions characterised by weak winds, which are often encountered in the Po Valley, did not improve substantially by the increase of the modelling system resolution. © Taiwan Association for Aerosol Research.
2016
Air quality modeling;Aerosol chemical composition;PM2.5;Horizontal grid resolution;PM10
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/3276
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