Multi year sun-photometer measurements for aerosol characterization in a Central Mediterranean site

作者:Boselli A*; Caggiano R; Cornacchia C; Madonna F; Mona L; Macchiato M; Pappalardo G; Trippetta S
来源:Atmospheric Research, 2012, 104: 98-110.
DOI:10.1016/j.atmosres.2011.08.002

摘要

Aerosol characterization at a Mediterranean site is carried out on the base of 40-month (November 2005-March 2009) measurements of aerosol optical depth (ACID) at 440 nm and Angstrom coefficient (a) at 440/870 nm collected at the atmospheric observatory of the Istituto di Metodologie per l%26apos;Analisi Ambientale of the Italian National Research Council (CNR-IMAA). Mean values of 0.161 +/- 0.004 and 1.44 +/- 0.54 are observed for AOD and a, respectively. Both AOD and a are characterized by a wide range of values from 0.03 to 0.6 and from 0.15 to 3.14, respectively, and a day-to-day variability larger than 100% for AOD %26lt;0.18 and alpha %26lt;0.95. A seasonal behavior is found with higher AOD and lower alpha values in spring-summer. Four aerosol populations are found in the count distribution of AOD. The k-means cluster analysis allowed the identification of measurements belonging to each one of the four populations identified in the AOD distribution. Four prevailing aerosol classes are identified by using back-trajectories and model analyses: dust, continental, maritime and mixed aerosols. Dust and continental aerosol are the most common at Central Mediterranean (37.5% and 41% of the cases, respectively), with a wide variability in both AOD and alpha. Only in about 4% of the cases can aerosol be classified as maritime, and however the mixing with other aerosol is not negligible. A comparative study of cluster results and aerosol type identification reveals that the classification, based on the cluster analysis, is reliable for dust event and continental case, with a confidence level of 85% and 65% respectively. Finally, the Principal Component Analysis (PCA) applied on each cluster%26apos;s PM1 and trace element daily concentration reveals an influence of dust on PM1 measurements at ground level.

  • 出版日期2012-2