Principal Component Analysis and Hierarchical and nonhierarchical Cluster Analysis were applied on PM10 particles data in order to: identify clusters of particles that can be differentiated on the bases of their chemical composition and morphology; investigate the relationship existing among the chemical and morphological parameters and evaluate the differences among the sampling sites. PM10 was collected in three different sites in central Italy and then analysed by scanning electron microscopy (SEM) coupled with microanalysis (EDS) and processed by a image analysis software.
Application of PCA and HCA to PM10 Data Collected by SEM/EDS in Three Site of Center Italy
GENGA, Alessandra;SICILIANO, Maria;SICILIANO, Tiziana;TEPORE, Antonio;MICOCCI, Gioacchino;
2010-01-01
Abstract
Principal Component Analysis and Hierarchical and nonhierarchical Cluster Analysis were applied on PM10 particles data in order to: identify clusters of particles that can be differentiated on the bases of their chemical composition and morphology; investigate the relationship existing among the chemical and morphological parameters and evaluate the differences among the sampling sites. PM10 was collected in three different sites in central Italy and then analysed by scanning electron microscopy (SEM) coupled with microanalysis (EDS) and processed by a image analysis software.File in questo prodotto:
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