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Improving knowledge on the apportionment of airborne particulate matter will be useful to handle and fulfill the legislation regarding this pollutant. The main aim of this work was to assess the influence of markers in the source apportionment of airborne PM10, in particular, whether the use of particle polycyclic aromatic hydrocarbon (PAH) and ions provided similar results to the ones obtained using not only the mentioned markers but also gas phase PAH and trace elements. In order to reach this aim, two receptor models: UNMIX and positive matrix factorization were applied to two sets of data in Zaragoza city from airborne PM10, a previously reported campaign (2003-2004) (Callén et al. Chemosphere 76:1120-1129, 2009), where PAH associated to the gas and particle phases, ions and trace elements were used as markers and a long sampling campaign (2001-2009), where only PAH in the particle phase and ions were analyzed. For both campaigns, positive matrix factorization was able to explain a higher number of sources than the UNMIX model. Independently of the sampling campaign and the receptor model used, soil resuspension was the main PM10 source, especially in the warm period (21st March-21st September), where most of the PM10 exceedances were produced. Despite some of the markers of anthropogenic sources were different for both campaigns, common sources associated to different combustion sources (coal, light-oil, heavier-oil, biomass, and traffic) were found and PAH in particle phase and ions seemed to be good markers for the airborne PM10 apportionment.
Ions, Air Pollutants, Source apportionment, PMF, Air pollution, PAH, Umix, Models, Theoretical, Chromatography, Ion Exchange, Gas Chromatography-Mass Spectrometry, PM10, Spain, Tandem Mass Spectrometry, Receptor model, Particulate Matter, Seasons, Cities, Particle Size, Polycyclic Aromatic Hydrocarbons, Environmental Monitoring
Ions, Air Pollutants, Source apportionment, PMF, Air pollution, PAH, Umix, Models, Theoretical, Chromatography, Ion Exchange, Gas Chromatography-Mass Spectrometry, PM10, Spain, Tandem Mass Spectrometry, Receptor model, Particulate Matter, Seasons, Cities, Particle Size, Polycyclic Aromatic Hydrocarbons, Environmental Monitoring
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