Source allocation of organic air pollutants by application of fuzzy c-varieties pattern recognition

Abstract Data for polynuclear aromatic hydrocarbons (PAH) from 44 air samples are processed by unsupervised clustering techniques in oder to resolve the contributions from two sources (domestic and motor vehicles). The fuzzy c-varieties (FCV) clustering algorithms are applied. The cluster configuration which best describes the characteristic properties of the samples is selected by computation of validity discriminant coefficients. the FCV method permits the data samples to belong partially to different clusters, and source apportionments are estimated by multiplying the membership values by the PAH concentrations of the individual samples. The results are compared to those obtained by other methods of dispersion or receptor modelling in the same areas. The FCV method is valuable for estimating contributions from two types of emission sources.