Abstract
Abstract The results of elemental analyses show that information about seasonal trends and emission sources is obtainable only with some uncertainties because the variability of environmental data is naturally very high. The multivariate data analysis enables a comprehensive and causal interpretation of complex and intricate environmental data sets, and therefore the extraction of their latent information content. In every case the chemometrical interpretation of environmental data requires knowledges on the emission structure and the orographical situation in the investigated territory. On these conditions the application of methods of cluster analysis, multidimensional variance and discriminant analysis and factor analysis yields information about temporal alterations of immission situations, main pollution sources and their seasonal variations and trends, respectively.
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