Source apportionment of PM10 and PM2.5 samples collected in an industrial area of the Po Valley was performed by using the Positive Matrix Factorization (PMF) model and a semiempirical calculation of five macro-source contributions. Samples were collected during four monitoring periods, January-February 2011, June 2012, January-February 2012, May-June 2012, resulting in a total of 720 samples (360 for PM10 and 360 for PM2.5). PMF variables included major elements, ions, elemental carbon and organic compounds and minor and trace elements. In order to increase the selectivity of minor and trace elements as source tracers, a chemical fractionation methodology based on the elemental solubility was employed; it was thus possible to include the extractable, the residual or both thefractions of the minor and trace elements in the database. PMF resolved six factors for PM10 (crustal matter, marine aerosol, industry, secondary/oil combustion, secondary nitrate/biomass burning/exhaust particles

Source apportionment of PM10 and PM2.5 samples collected in an industrial area of the Po Valley was performed by using the Positive Matrix Factorization (PMF) model and a semiempirical calculation of five macro-source contributions. Samples were collected during four monitoring periods, January-February 2011, June 2012, January-February 2012, May-June 2012, resulting in a total of 720 samples (360 for PM10 and 360 for PM2.5). PMF variables included major elements, ions, elemental carbon and organic compounds and minor and trace elements. In order to increase the selectivity of minor and trace elements as source tracers, a chemical fractionation methodology based on the elemental solubility was employed; it was thus possible to include the extractable, the residual or both thefractions of the minor and trace elements in the database. PMF resolved six factors for PM10 (crustal matter, marine aerosol, industry, secondary/oil combustion, secondary nitrate/biomass burning/exhaust particles, brake/tyre wear/re-suspended road dust) and seven factors for PM2.5 (crustal matter, marine aerosol, industry, secondary nitrate, biomass burning, other secondary components, secondary sulphate/oil combustion). Mixing properties of the lower atmosphere were monitored by using natural radioactivity. The lack in the separation of some sources was shown to be due to their co-variation during periods of high atmospheric stability in the cold months. Seasonal variations of the source contributions were evaluated and discussed. PMF results were compared with those obtained by a semiempirical calculation method in which analytical results are grouped into five macro-sources (crustal matter, marine aerosol, secondary inorganic compounds, combustion products from vehicular emissions and organics). Although similar trends in the temporal variation of the main PM sources were obtained, the absolute magnitude of the concentrations varied in some cases, especially for crustal matter and marine aerosol sources.

Sources of PM in an Industrial Area: Comparison between Receptor Model Results and Semiempirical Calculations of Source Contributions / Farao, Carmela; Canepari, Silvia; Perrino, Cinzia; Roy M., Harrison. - In: AEROSOL AND AIR QUALITY RESEARCH. - ISSN 1680-8584. - (2014), pp. 658-669. [10.4209/aaqr.2013.08.0281]

Sources of PM in an Industrial Area: Comparison between Receptor Model Results and Semiempirical Calculations of Source Contributions

FARAO, CARMELA;CANEPARI, Silvia;PERRINO, CINZIA;
2014

Abstract

Source apportionment of PM10 and PM2.5 samples collected in an industrial area of the Po Valley was performed by using the Positive Matrix Factorization (PMF) model and a semiempirical calculation of five macro-source contributions. Samples were collected during four monitoring periods, January-February 2011, June 2012, January-February 2012, May-June 2012, resulting in a total of 720 samples (360 for PM10 and 360 for PM2.5). PMF variables included major elements, ions, elemental carbon and organic compounds and minor and trace elements. In order to increase the selectivity of minor and trace elements as source tracers, a chemical fractionation methodology based on the elemental solubility was employed; it was thus possible to include the extractable, the residual or both thefractions of the minor and trace elements in the database. PMF resolved six factors for PM10 (crustal matter, marine aerosol, industry, secondary/oil combustion, secondary nitrate/biomass burning/exhaust particles
2014
Source apportionment of PM10 and PM2.5 samples collected in an industrial area of the Po Valley was performed by using the Positive Matrix Factorization (PMF) model and a semiempirical calculation of five macro-source contributions. Samples were collected during four monitoring periods, January-February 2011, June 2012, January-February 2012, May-June 2012, resulting in a total of 720 samples (360 for PM10 and 360 for PM2.5). PMF variables included major elements, ions, elemental carbon and organic compounds and minor and trace elements. In order to increase the selectivity of minor and trace elements as source tracers, a chemical fractionation methodology based on the elemental solubility was employed; it was thus possible to include the extractable, the residual or both thefractions of the minor and trace elements in the database. PMF resolved six factors for PM10 (crustal matter, marine aerosol, industry, secondary/oil combustion, secondary nitrate/biomass burning/exhaust particles, brake/tyre wear/re-suspended road dust) and seven factors for PM2.5 (crustal matter, marine aerosol, industry, secondary nitrate, biomass burning, other secondary components, secondary sulphate/oil combustion). Mixing properties of the lower atmosphere were monitored by using natural radioactivity. The lack in the separation of some sources was shown to be due to their co-variation during periods of high atmospheric stability in the cold months. Seasonal variations of the source contributions were evaluated and discussed. PMF results were compared with those obtained by a semiempirical calculation method in which analytical results are grouped into five macro-sources (crustal matter, marine aerosol, secondary inorganic compounds, combustion products from vehicular emissions and organics). Although similar trends in the temporal variation of the main PM sources were obtained, the absolute magnitude of the concentrations varied in some cases, especially for crustal matter and marine aerosol sources.
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Sources of PM in an Industrial Area: Comparison between Receptor Model Results and Semiempirical Calculations of Source Contributions / Farao, Carmela; Canepari, Silvia; Perrino, Cinzia; Roy M., Harrison. - In: AEROSOL AND AIR QUALITY RESEARCH. - ISSN 1680-8584. - (2014), pp. 658-669. [10.4209/aaqr.2013.08.0281]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/555364
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