Spatial and seasonal variation of organic pollutants in surface water using multivariate statistical techniques

Abstract

In this study, analysis of variance (ANOVA), cluster analysis (CA) and principal component analysis (PCA) were employed in order to evaluate the concentration profile of organic contaminants found in three main river from central Transylvania, Romania. Samples were collected from nine sampling stations, in two different sampling campaigns (wet season and dry season). Water samples were extracted using solid-phase extraction and analyzed using gas chromatography coupled with mass spectrometry (GC/MS). Twelve organic pollutants belonging to different classes were used for further interpretations. ANOVA highlighted compounds which distinguished Olt River from Mures River, and compounds that are influenced by increased river flow from the wet season. CA was applied to group the sampling stations. Three clusters were obtained, according to their organic load. PCA extracted five principal components explaining 87.330% from data set variability. Based on these results, a future monitoring study may be optimized by reducing the sampling points and compounds to those that are representative for each river, thereby reducing costs, without any information loss.