|Title||Assessment of the AMS-MINNI system capabilities to simulate air quality over Italy for the calendar year 2005|
|Publication Type||Articolo su Rivista peer-reviewed|
|Year of Publication||2014|
|Authors||Mircea, Mihaela, Ciancarella Luisella, Briganti G., Calori G., Cappelletti Andrea, Cionni Irene, Costa M., Cremona G., D'Isidoro Massimo, Finardi S., Pace G., Piersanti A., Righini Gaia, Silibello C., Vitali L., and Zanini Gabriele|
|Keywords||air monitoring, air pollutant, Air pollution, Air pollution assessments, Air quality, air quality control, Air quality monitoring stations, Annual average concentration, Anthropogenic pollution, anthropogenic source, article, atmospheric pollution, city, Comprehensive evaluation, controlled study, environmental impact assessment, Italian Peninsula, Italy, Laws and legislation, Model validation, Nitrogen dioxide, Nitrogen dioxides, Nitrogen oxides, Ozone, particulate matter, PM10, Pollution, priority journal, rural area, Sardinia, seashore, secondary organic aerosol, Sicily, spatiotemporal analysis, summer, Surface measurement, surface property, Time series analysis, winter|
This paper presents a comprehensive evaluation of AMS-MINNI modelling system for the year 2005, over Italian peninsula and major islands Sicily and Sardinia, for gas-phase species ozone (O3) and nitrogen dioxide (NO2), and particulate matter with an aerodynamic diameter less than or equal to 10μm (PM10), against surface measurements from the Italian air quality database. Statistical indicators currently used in air quality models performance assessment and recommended by European Union (EU) guidelines were calculated at rural, urban and suburban background air quality monitoring stations, on purpose of understanding the model behaviour in areas not directly affected by anthropogenic pollution sources. Results show that measured O3 concentrations are generally well reproduced by the model, with the best agreement between model and observations at rural stations. Simulated PM10 annual average concentrations are generally lower than those observed but simulated and observed variabilities are comparable at urban and suburban stations. As for NO2, the model underestimates concentrations at all stations but gives similar variability to the observed one. Overall, the values of the statistical indicators comply with the acceptance criteria requested by EU legislation and are similar with those published by previous studies for the three pollutants investigated in this study. Further work will be carried out to evaluate the impact of uncertainties in input data (meteorology, emissions and boundary conditions) and in description of gaseous and aerosol chemical and physical processes on the simulated concentrations. © 2013 Elsevier Ltd.
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