Abstract

This study was carried out to evaluate sediment pollution related to trace elements such as Cd, Cu, Ni, Pb, Zn, Hg, As and Cr and eight polycyclic aromatic hydrocarbons (PAHs) in 127 sites located in 85 rivers in Spain. Sediment samples were classified according to similar chemical characteristics by means of statistical multivariate techniques (principal component analysis, PCA) and artificial neural networks such as self-organizing maps (SOM). Sediment sample classification provided by PCA was not as useful as the one provided by the SOM, revealing itself as a powerful tool to be incorporated in the first steps of sediment quality assessments. The use of sediment quality guidelines such as the mean-probable effects concentration quotient (m-PECQ) predicted sediment quality and gave an overall view of sediment pollution throughout Spain. Most of the samples (118 out of 127) showed m-PECQ values below 0.5 highlighting their relative low potential risk to cause adverse effects on the benthic fauna. However, some samples presented m-PECQ values higher than 0.5 suggesting a clear potential risk to these fauna. Besides, unusual high concentrations of trace elements and PAHs were related to the human activities carried out near each sampling point.

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