Linking Clusters of Micropollutants in Surface Water to Emission Sources, Environmental Conditions, and Substance Properties

Abstract

Water quality monitoring programs yield a wealth of data. It is often unclear why a certain substance occurs in higher concentrations at a certain location or time. In this study, substances were considered in clusters with co-varying concentrations rather than in isolation. A total of 196 substance clusters at 19 monitoring sites in the rivers Rhine and Meuse were identified. A total of nine clusters were found repeatedly with a similar composition at different monitoring sites. Several environmental conditions and substance properties could be linked to clusters. In addition, overlap with reference substance lists was determined. These lists group multiple substances according to emission sources, substance types, or type of use. The reference substance lists revealed that Rhine and Meuse are similarly affected. The nine ‘repeating clusters’ were analyzed in more detail to identify drivers. For instance, a repeating cluster with herbicides was specifically linked to high temperatures and a high number of hours in the sun per day, e.g., summer conditions. A cluster containing polychlorinated biphenyls, identified as persistent and with a high tendency to bind organic matter, was linked to high river discharge and attributed to a potential release from sediment resuspension. Not all substances could be clustered, because their concentration did not structurally vary in the same way as other substances. The presented explorative cluster analyses, along with the obtained relations with substance properties, local environmental conditions, and reference substance lists, may facilitate the reconstruction of the processes that lead to the observed variation in concentrations. This knowledge can subsequently be used by water managers to improve water quality.