Characterization of PM10 sources in a coastal area near Venice (Italy): an application of factor-cluster analysis.

In this study a factor-cluster analysis (FCA) applied to chemical composition of atmospheric particulate matter was carried out. Relating specific wind data and back-trajectories to the daily samples grouped using FCA can be useful in atmospheric pollution studies to identify polluting sources and better interpret source apportionment results. The elemental composition and water soluble inorganic ions content of PM(10) were determined in a coastal site near Venice during the sea/land breeze season. From the factor analysis four sources were identified: mineral dust, road traffic, fossil fuels and marine aerosol. From a hierarchical cluster analysis, applied on the factor scores, samples with a similar source profile were grouped. Five clusters were identified: four with samples highly characterized by one identified source, one interpreted as general background pollution. Finally, by interpreting cluster results with wind direction data and back-trajectory analysis further detailed information was obtained on potential source locations and possible links between meteorological conditions and PM(10) chemical composition variations were detected. The proposed approach can be useful for air quality assessment studies and PM(10) reduction strategies.