Assessment of metal pollution based on multivariate statistical modeling of 'hot spot' sediments from the Black Sea

The paper deals with application of different statistical methods like clus ter and principal components analysis (PCA), partial least squares (PLSs) m odeling. These approaches are an efficient tool in achieving better underst anding about the contamination of two gulf regions in Black Sea. As objects of the study, a collection of marine sediment samples from Varna and Bourg as "hot spots" gulf areas are used. In the present case the use of cluster and PCA make it possible to separate three zones of the marine environment with different levels of pollution by interpretation of the sediment analys is (Bourgas gulf, Varna gulf and lake buffer zone). Further, the extraction of four latent factors offers a specific interpretation of the possible po llution sources and separates natural from anthropogenic factors, the latte r originating from contamination by chemical, oil refinery and steel-work e nterprises. Finally, the PLSs modeling gives a better opportunity in predic ting contaminant concentration on tracer (or tracers) element as compared t o the one-dimensional approach of the baseline models. The results of the s tudy are important not only in local aspect as they allow quick response in finding solutions and decision making but also in broader sense as a usefu l environmetrical methodology. (C) 2000 Elsevier Science Ltd. All rights re served.