A non-linear analysis to detect the origin of PM10 concentrations in Northern Italy

• Published in: The Science of the total environment Vol. 409; no. 1; pp. 182 - 191
• Main Authors: Carnevale, Claudio, Pisoni, Enrico, Volta, Marialuisa
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier B.V 01.12.2010; [Amsterdam; New York]: Elsevier Science; Elsevier
• Subjects: Air Pollutants - analysis; Air pollution; Air Pollution - statistics & numerical data; Applied sciences; Atmospheric pollution; Emission analysis; Emission control strategies; Emissions control; Environmental Monitoring; Exact sciences and technology; Factor separation technique; General processes of purification and dust removal; Italy; Mathematical models; Nonlinear Dynamics; Nonlinearity; Particle Size; Particulate matter; Particulate Matter - analysis; Pollution; Precursors; Prevention and purification methods; Rural areas; Separation; Three dimensional; Urban areas; Italy; Plain of Po; Europe; Factor separation technique; Air pollution; Particulate matter; Emission control strategies; Factor analysis; Environmental policy; Pollution control; Precursor; Coarse particle; Source localization; Seasonal variation; Pollution source; Aerosols; Pollution abatement; Performance
• ISSN: 0048-9697; 1879-1026
• DOI: 10.1016/j.scitotenv.2010.09.038

This work presents the formalization and the application of the factor separation technique in order to investigate the impact of precursor emission and their nonlinear interaction (in particulate matter accumulation processes). By processing the simulations of a 3D multiphase modeling system, the factor separation methodology can support the Environmental Authority in quantifying the impact of precursor emissions on PM10 production and consequently in assessing the feasible efficiency of different emission control strategies over a considered domain. The case study proposed by this paper focuses on the Po Valley region (Northern Italy), characterized by critical PM10 levels claiming for sound emission reduction policies. The results show the heavy nonlinearities and the strong seasonal dependence in the formation of PM10, over the study domain. Furthermore the results highlight that peak PM10 concentrations are mainly related to primary PM emissions in urban areas, and gas emissions (mainly NOx and NH3) in rural areas.