Classification and modeling of different fractions of aerosol monitoring data.
The present study deals with the application of self-organizing maps (SOM) of Kohonen and four-way Tucker method for the classification and modeling, respectively, of aerosol monitoring data sets from two sampling points (Arnoldstein and Unterloibach) located close to the border, between Austria and Slovenia. The goal of the chemometric data treatment was to find some specific patterns in the classification maps and in the four-way model of complexity [2422] for 5 different aerosol fractions collected in 4 different seasons of the year. The results indicated a distinct separation of the ultrafine particles (PM 0.01-PM 0.4) from the other fractions, which underlines their specific effect on human health. Seasonal separation (but only between summer and winter sampling) is also observed.
Chair of Analytical Chemistry, Faculty of Chemistry, University of Sofia "St. Kl. Okhridski", Sofia, Bulgaria.
Stefan
S
Tsakovski
Pavlina
P
Simeonova
Vasil
V
Simeonov
D000336:Aerosols / Q000032:analysis* / Q000737:chemistry; D000393:Air Pollutants / Q000032:analysis* / Q000737:chemistry; D000465:Algorithms; D001185:Artificial Intelligence; D001317:Austria; D004784:Environmental Monitoring; D008956:Models, Chemical; D010316:Particle Size; D012621:Seasons; D017524:Slovenia
D000336:Aerosols; D000393:Air Pollutants