title: Integrating Saharan dust forecasts into a regional chemical transport model: a case study over Northern Italy.
abstract: The Po Valley in Northern Italy is frequently affected by high PM10 concentrations, where both natural and anthropogenic sources play a significant role. To improve air pollution modeling, 3D dust fields, produced by means of the DREAM dust forecasts, were integrated as boundary conditions into the mesoscale 3D deterministic Transport Chemical Aerosol Model (TCAM). A case study of the TCAM and DREAM integration was implemented over Northern Italy for the period May 15-June 30, 2007. First, the Saharan dust impact on PM10 concentration was analyzed for eleven remote PM10 sites with the lowest level of air pollution. These remote sites are the most sensitive to Saharan dust intrusions into Northern Italy, because of the absence of intensive industrial pollution. At these remote sites, the observed maxima in PM10 concentration during dust events is evidence of dust aerosol near the surface in Northern Italy. Comparisons between modeled PM10 concentrations and measurements at 230 PM10 sites in Northern Italy, showed that the integrated TCAM-DREAM model more accurately reproduced PM10 concentration than the base TCAM model, both in terms of correlation and mean error. Specifically, the correlation median increased from 0.40 to 0.65, while the normalized mean absolute error median dropped from 0.5 to 0.4.
authors.affiliation: Dept. of Information Engineering, Faculty of Engineering, University of Brescia, Italy. carneval@ing.unibs.it
authors.forename: C
authors.initials: C
authors.lastname: Carnevale
authors.forename: G
authors.initials: G
authors.lastname: Finzi
authors.forename: E
authors.initials: E
authors.lastname: Pisoni
authors.forename: M
authors.initials: M
authors.lastname: Volta
authors.forename: P
authors.initials: P
authors.lastname: Kishcha
authors.forename: P
authors.initials: P
authors.lastname: Alpert
mesh_terms: D000352:Africa, Northern; D004391:Dust / Q000032:analysis; D005544:Forecasting / Q000379:methods; D007558:Italy; D008956:Models, Chemical; D010316:Particle Size; D052638:Particulate Matter / Q000032:analysis*; D012822:Silicon Dioxide / Q000032:analysis*; D014919:Wind
chemical_list: D004391:Dust; D052638:Particulate Matter; D012822:Silicon Dioxide