Abstract

A total of 137 samples of airborne particulates with an aerodynamic equivalent diameter of 10μm or less (PM10) were collected from April 2007 to July 2008 in four different areas (Potenza, Lavello, Viggiano, Matera) of the Basilicata region in southern Italy. A total of approximately 140,000 particles were analysed using a Field Emission Scanning Electron Microscope (FESEM) equipped with an Energy-Dispersive X-ray Spectrometer (EDS). To formulate a hypothesis on the origin of particles, the dataset was numerically reduced using mineralogical criteria. Eight particle groups were established (Silicate, Silica, Carbonate, Sea Salt, Polymineral, Industrial, Sulphur, and Biogenic Particles) among which Silicate, Sulphur and Industrial Particles were found to be the most abundant. Among the Silicate Particles, the alumosilicates were the most commonly occurring particles (mineral and fly ash particles), and the presence of a small metallurgical factory located in the industrial area of Potenza significantly affects the presence of metal particles (mainly Fe–Zn spinels). The anthropogenic pressure exerted by different types of Sulphur-rich (e.g., Na–Ca-Sulphates, S-only) Particles in the other areas is most likely linked to industrial combustion processes, i.e., waste incinerator oil and oil extraction. Significant differences were found in the particulate concentrations and the compositions of samples collected in different seasons as well as during the night and daytime periods. Crustal Particles were the most abundant in spring–summer, and both Sulphur-rich Particles and Industrial Particles increased in autumn–winter. The proportion of latter category of particles increases in the samples collected during the night periods due to weather conditions (atmospheric stability, thermal inversion, etc.). Sulphur-rich Particles were observed to be more abundant during the daytime due to anthropogenic processes (combustion) and solar radiation. In summary, mineralogical and geochemical approaches are fundamental to delineate the human and natural contributions from automated microscopic analyses.

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