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A gas/aerosol air pollutants study over the urban area of Rome using a comprehensive chemical transport model
Institution:1. Department of Meteorology — Climatology, School of Geology, Aristotle University of Thessaloniki, University Campus, Thessaloniki, Greece;2. IEK-8, Forschungszentrum, Jülich, Germany;3. Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki, Greece;4. Institut P.-S. Laplace, Laboratoire de Météorologie Dynamique, Ecole Polytechnique, Palaiseau, France
Abstract:The aim of this study was to identify areas of potential relevant exposure to pollutants within Rome's urban core. To meet this goal, intensive field campaigns were conducted and simulations were performed, using the flexible air quality regional model (FARM), to study winter and summer pollution episodes. The simulations were performed using a complete emission inventory that included traffic flow model results of the Roman street network to better describe, with respect to the available diffuse national emission inventory, the hourly variation of traffic emissions in the city. The meteorological reconstruction was performed by means of both prognostic and diagnostic models by using experimental data collected during the field campaigns. To evaluate the capability of the FARM model to capture the main features of the selected episodes, a comparison of modelled results against observed air quality data for different pollutants was performed at urban and rural sites. FARM performed well in predicting ozone (O3) and nitrogen dioxide (NO2) concentrations, showing a good reproduction of both daily peaks and their diurnal variations. The model also showed a good capability to reproduce the magnitude of volatile alkane, aromatic and carbonyl compound concentrations. PM10 model results revealed the tendency to under-predict the observed values. PM composition model results were compared with observed data, evidencing good results for elemental carbon (EC), nitrate (NO3) and ammonium (NH4+), underestimation for sulphate (SO42−) and poor performance for organic matter (OM). The soil components of PM were found to be significantly under-predicted by the model, especially during Saharan dust episodes. Overall, the study results show large areas of high O3 and PM10 concentrations where levels of pollutants should be carefully monitored and population exposure evaluated.
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