Multivariate Chemometric Analysis of a Polluted River of a Megalopolis

Abstract

A chemometrical study regarding a 10-years water quality monitoring plan at 15 sampling points along a section of the Reconquista River and its stream channels, which embraces 21 campaigns, is presented. The original data were pre-treated in order to eliminate missing data and outliers, obtaining a final data matrix of 270 samples by 26 physical-chemistry variables. Multivariate statistical methods like multi curve resolution, canonical correlation analysis and factor analysis methods, as well as current univariate statistics were applied. The interpretation was simplified when variables were separated in groups containing environmentally and chemically related variables instead of analyzing them all together. These methods have shown that the presence of metals likely come from at least 3 different type of sources. Although the stream channels arriving to the main river course are highly polluted, their flow rates are so low that do not significantly decrease its water quality. They mainly contribute to the high levels of biochemical-oxygen demand and chemical-oxygen demand as well as nitrogen-content species. Furthermore, regarding metals, the pollution of the river coming from the upstream is higher than those introduced by all channels.