Characterization of aerosol sources in León (Spain) using Positive Matrix Factorization and weather types

• Autor(a) principal: Oduber, Fernanda
• Data de Publicação: 2021
• Outros Autores: Calvo, Ana Isabel, Castro, Amaya, Blanco-Alegre, Carlos, Alves, Célia, Calzolai, Giulia, Nava, Silvia, Lucarelli, Franco, Nunes, Teresa, Barata, Joana, Fraile, Roberto
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10773/36913
• topic: Aerosol; Circulation weather types; Linear models; PMF; Source apportionment

A one-year aerosol sampling campaign, between 2016 and 2017, was conducted in a suburban area of León city, Spain. An association between the Positive Matrix Factorization (PMF) results and air masses through circulation weather types was carried out, through the construction of linear models from the PM10 concentrations and its chemical composition. The aerosol sources, identified by PMF six-factor solution, were: traffic (29%), aged sea salt (26%), secondary aerosols (16%), dust (13%), marine aerosol (7%) and biomass burning (3%). Traffic and secondary factors showed the highest PM10 contribution in the hybrid cyclonic types with wind component from the first and second quadrant. Anticyclonic types with wind component from the first quadrant exhibited high values of secondary, aged sea salt and dust factors. The highest contributions of the dust factor were also associated with northerly types. The linear models built for estimating the source apportionment of PM10, from aerosol chemical composition and geostrophic flow, showed positive coefficients for: westerly flows (WF) in marine factor, southerly flows (SF) in secondary and traffic factors, and shear southerly vorticities (ZS) in dust factor. Negative dependences were observed for ZS in aged sea salt factor and for SF in dust factor. The PM10 mass concentration calculated by the linear models and by the PMF model were strongly correlated. This can be very useful to determine the contribution of a specific source to PM10 in León, only by knowing some meteorological and chemical variables.