Atmospheric particulate concentrations were measured at an industrial site in southern Italy from September 2001 to December 2004. In this period, we collected 741 daily samples of PM2.5 by means of a low-volume gravimetric automatic sequential sampler. The 24-h PM2.5 samples were analysed for heavy metal content (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn). We also measured temperature, relative humidity, wind speed and wind direction. Data analysis was performed with univariate and multivariate statistical methods. Principal component analysis and cluster analysis were applied in order to point out the correlation structure among particulate concentrations and heavy metal content and to highlight source profile characterization. In order to discriminate between natural and anthropogenic origin of the trace elements, we also applied the enrichment factor method. In the investigated period, PM2.5 concentrations ranged from 0.04 μg m− 3 to 117 μg m− 3, with a mean value of 13 μg m− 3 and a median value of 10 μg m− 3. A mix of different source emissions and different meteorological conditions may determine this large variation in PM2.5 values. Regarding heavy metal levels, we observed that they decreased during the four years assuming the lowest values in 2004. All the measured elements, except Mn, showed high values of the enrichment factor, suggesting a prevailing anthropogenic origin. The analysis of the relationships among pollutant concentrations and meteorological parameters showed that they were influenced by wind speed and relative humidity. The multivariate analysis allowed us to identify two source profiles for heavy metals. The first profile was characterized both by elements typical of soil dust and crustal material (Fe, Mn) and by elements typical of industrial processes (Ni, Cr and Cu). The second profile was characterized by Pb, Zn and Cd and it may be mainly related to exhaust emissions from both gasoline and diesel fuelled road vehicles.

Trace elements in daily collected aerosol: levels characterization and source identification in a four-year study

RAGOSTA, Maria;
2008

Abstract

Atmospheric particulate concentrations were measured at an industrial site in southern Italy from September 2001 to December 2004. In this period, we collected 741 daily samples of PM2.5 by means of a low-volume gravimetric automatic sequential sampler. The 24-h PM2.5 samples were analysed for heavy metal content (Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn). We also measured temperature, relative humidity, wind speed and wind direction. Data analysis was performed with univariate and multivariate statistical methods. Principal component analysis and cluster analysis were applied in order to point out the correlation structure among particulate concentrations and heavy metal content and to highlight source profile characterization. In order to discriminate between natural and anthropogenic origin of the trace elements, we also applied the enrichment factor method. In the investigated period, PM2.5 concentrations ranged from 0.04 μg m− 3 to 117 μg m− 3, with a mean value of 13 μg m− 3 and a median value of 10 μg m− 3. A mix of different source emissions and different meteorological conditions may determine this large variation in PM2.5 values. Regarding heavy metal levels, we observed that they decreased during the four years assuming the lowest values in 2004. All the measured elements, except Mn, showed high values of the enrichment factor, suggesting a prevailing anthropogenic origin. The analysis of the relationships among pollutant concentrations and meteorological parameters showed that they were influenced by wind speed and relative humidity. The multivariate analysis allowed us to identify two source profiles for heavy metals. The first profile was characterized both by elements typical of soil dust and crustal material (Fe, Mn) and by elements typical of industrial processes (Ni, Cr and Cu). The second profile was characterized by Pb, Zn and Cd and it may be mainly related to exhaust emissions from both gasoline and diesel fuelled road vehicles.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11563/4441
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