The European Collaborative Project SOLUTIONS developed models to provide diagnostic and prognostic capacity and fill data gaps for chemicals of emerging concern

Abstract

The European Union Water Framework Directives aims at achieving good ecological status in member states’ water bodies. Insufficient ecological status could be the result of different interacting stressors, among them the presence of many thousands of chemicals. The diagnosis of the likelihood that these chemicals negatively affect the ecological status of surface waters or human health, and the subsequent development of abatement measures usually relies on water quality monitoring. This gives an incomplete picture of chemicals’ contamination, due to the limited number of monitoring stations, samples and substances. Information gaps thus limit the possibilities to protect against and effectively manage chemicals in aquatic ecosystems. The EU FP7 SOLUTIONS project has developed and validated a collection of integrated models (“Model Train”) to increase our understanding of issues related to emerging chemicals in Europe’s river basins and to complement information and knowledge derived from field data. Unlike pre-existing models, the Model Train is suitable to model mixtures of thousands of chemicals, to better approach a “real-life” mixture exposure situation. It can also be used to model new chemicals at a stage where not much is known about them. The application of these models on a European scale provides temporally and spatially variable concentration data to fill gaps in the space, time and substance domains left open by water quality monitoring, and it provides homogeneous data across Europe where water quality data from monitoring are missing. Thus, it helps to avoid overlooking candidate chemicals and possible hot spots for management intervention. The application of the SOLUTIONS Model Train on a European scale presents a relevant line of evidence for water system level prognostic and diagnostic impact assessment related to chemical pollution. The application supports the design of cost-effective programmes of measures by helping to identify the most affected sites and the responsible substances, by evaluating alternative abatement options and by exploring the consequences of future trends.