Occurrence of regulated pollutants in populated Mediterranean basins: Ecotoxicological risk and effects on biological quality.

Chemical stressors co-occur in mixtures into watercourses and this complicates predicting their effects on their ecological status. Our knowledge of river basin specific pollutants (RBSPs) is still limited, but it remains necessary to ensure the good chemical and ecological status. We performed an exercise on Mediterranean river sites exposed to urban and industrial pressures in order to, i) prioritize the occurring chemicals, ii) assessing the site's specific chemical risk (RQsite), and iii) relating the chemical risk to the biological quality, using as evidences invertebrates and diatom indices. Mediterranean rivers suffer from strong pressures which lead to a poor dilution ability, which makes the inhabiting biota highly vulnerable. The most frequent pollutants in the 89 sites surveyed included pharmaceutical products such as the antibiotics azithromycin, clarithromycin, and erythromycin, and the anti-inflammatory diclofenac, and products of industrial origin such as perfluorinated PFOS, nickel, and nonylphenol. Both the diatom index IPS and the macroinvertebrate index IBMWP hold strong negative correlations to RQsite, indicating a significant contribution of chemicals to biological impairment. Chemical contaminants (but not nutrients or dissolved organic carbon) were associated with significant changes to the taxonomic composition of invertebrate communities, but not to that of diatom communities. Our analyses indeed reveal that the impact of co-occurring chemicals translates onto negative effects in the biological quality. Our approach may be of use to evidence impacts on water resources and water quality in rivers under strong human pressure.

Water toxicity assessment and spatial pollution patterns identification in a Mediterranean River Basin District. Tools for water management and risk analysis.

In compliance with the requirements of the EU Water Framework Directive, monitoring of the ecological and chemical status of Catalan river basins (NE Spain) is carried out by the Catalan Water Agency. The large amount of data collected and the complex relationships among the environmental variables monitored often mislead data interpretation in terms of toxic impact, especially considering that even pollutants at very low concentrations might contribute to the total toxicity. The total dataset of chemical monitoring carried out between 2007 and 2008 (232 sampling stations and 60 pollutants) has been analyzed using sequential advanced modeling techniques. Data on concentrations of contaminants in water were pre-treated in order to calculate the bioavailable fraction, depending on substance properties and local environmental conditions. The resulting values were used to predict the potential impact of toxic substances in complex mixtures on aquatic biota and to identify hot spots. Exposure assessment with Species Sensitivity Distribution (SSD) and mixture toxicity rules were used to compute the multi-substances Potentially Affected Fraction (msPAF). The combined toxicity of the pollutants analyzed in the Catalan surface waters might potentially impact more than 50% of the species in 10% of the sites. In order to understand and visualize the spatial distribution of the toxic risk, Self Organising Map (SOM), based on the Kohonen's Artificial Neural Network (ANN) algorithm, was applied on the output data of these models. Principal Component Analysis (PCA) was performed on top of Neural Network results in order to identify main influential variables which account for the pollution trends. Finally, predicted toxic impacts on biota have been linked and correlated to field data on biological quality indexes using macroinvertebrate and diatom communities (IBMWP and IPS). The methodology presented could represent a suitable tool for water managers in environmental risk assessment and management.