RIVER POLLUTION DATA INTERPRETED BY MEANS OF CHEMOMETRIC METHODS

Environmental data, including river pollution data, are characterized by high variability. Much information is lost by using only univariate graphical or statistical methods for data evaluation and interpretati on. Chemometric methods, in particular methods of multivariate data an alysis, help to extract the latent information in such data. The combi nation of cluster analysis as the first step and multivariate analysis of variance and discriminant analysis as the second step enables iden tification of similar locations in a river. Pollution sources and disc hargers can be detected by means of factor analysis. The deposition-re mobilization behavior of metals in a river can be described using part ial least squares regression. Summarizing, it can be stated that metho ds of multivariate data analysis are powerful tools for the evaluation and interpretation of river pollution data. (C) 1998 Academic Press.