Title | The on-line integrated mesoscale chemistry model bolchem |
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Publication Type | Articolo su Rivista peer-reviewed |
Year of Publication | 2021 |
Authors | Cesari, R., Landi T.C., D'Isidoro Massimo, Mircea Mihaela, Russo Felicita, Malguzzi P., Tampieri F., and Maurizi A. |
Journal | Atmosphere |
Volume | 12 |
ISSN | 20734433 |
Keywords | Air pollution, Air pollution control, Atmosphere monitoring, Atmospheric movements, Chemistry modeling, Chemistry transport model, Correlation coefficient, Environmental agency, Horizontal resolution, particulate matter, Transport and dispersions |
Abstract | This work presents the on-line coupled meteorology–chemistry transport model BOLCHEM, based on the hydrostatic meteorological BOLAM model, the gas chemistry module SAPRC90, and the aerosol dynamic module AERO3. It includes parameterizations to describe natural source emissions, dry and wet removal processes, as well as the transport and dispersion of air pollutants. The equations for different processes are solved on the same grid during the same integration step, by means of a time-split scheme. This paper describes the model and its performance at horizontal resolution of 0.2∘× 0.2∘ over Europe and 0.1∘× 0.1∘ in a nested configuration over Italy, for one year run (December 2009–November 2010). The model has been evaluated against the AIRBASE data of the European Environmental Agency. The basic statistics for higher resolution simulations of O3, NO2 and particulate matter concentrations (PM2.5 and PM10) have been compared with those from Copernicus Atmosphere Monitoring Service (CAMS) ensemble median. In summer, for O3 we found a correlation coefficient R of 0.72 and mean bias of 2.15 over European domain and a correlation coefficient R of 0.67 and mean bias of 2.36 over Italian domain. PM10 and PM2.5 are better reproduced in the winter, the latter with a correlation coefficient R of 0.66 and the mean bias MB of 0.35 over Italian domain. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. |
Notes | cited By 0 |
URL | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101110699&doi=10.3390%2fatmos12020192&partnerID=40&md5=ffd2b4cf3775eb29a52cca1b57cdb905 |
DOI | 10.3390/atmos12020192 |
Citation Key | Cesari2021 |