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BackgroundThis paper describes a conceptual framework for solutions-focused management of chemical contaminants built on novel and systematic approaches for identifying, quantifying and reducing risks of these substances.MethodsThe conceptual framework was developed in interaction with stakeholders representing relevant authorities and organisations responsible for managing environmental quality of water bodies. Stakeholder needs were compiled via a survey and dialogue. The content of the conceptual framework was thereafter developed with inputs from relevant scientific disciplines.ResultsThe conceptual framework consists of four access points: Chemicals, Environment, Abatement and Society, representing different aspects and approaches to engaging in the issue of chemical contamination of surface waters. It widens the scope for assessment and management of chemicals in comparison to a traditional (mostly) perchemical risk assessment approaches by including abatement- and societal approaches as optional solutions. The solution-focused approach implies an identification of abatement- and policy options upfront in the risk assessment process. The conceptual framework was designed for use in current and future chemical pollution assessments for the aquatic environment, including the specific challenges encountered in prioritising individual chemicals and mixtures, and is applicable for the development of approaches for safe chemical management in a broader sense. The four access points of the conceptual framework are interlinked by four key topics representing the main scientific challenges that need to be addressed, i.e.: identifying and prioritising hazardous chemicals at different scales; selecting relevant and efficient abatement options; providing regulatory support for chemicals management; predicting and prioritising future chemical risks. The conceptual framework aligns current challenges in the safe production and use of chemicals. The current state of knowledge and implementation of these challenges is described.ConclusionsThe use of the conceptual framework, and addressing the challenges, is intended to support: (1) forwarding sustainable use of chemicals, (2) identification of pollutants of priority concern for cost-effective management, (3) the selection of optimal abatement options and (4) the development and use of optimised legal and policy instruments.

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Multi-objective performance assessment of operational strategies at wastewater treatment plants (WWTPs) is a challenging task. The holistic perspective applied to evaluation of modern WWTPs, including not only effluent quality but also resource efficiency and recovery, global environmental impact and operational cost calls for assessment methods including both on- and off-site effects. In this study, a method combining dynamic process models – including greenhouse gas (GHG), detailed energy models and operational cost – and life cycle assessment (LCA) was developed. The method was applied and calibrated to a large Swedish WWTP. In a performance assessment study, changing the operational strategy to chemically enhanced primary treatment was evaluated. The results show that the primary objectives, to enhance bio-methane production and reduce GHG emissions were reached. Bio-methane production increased by 14% and the global warming potential decreased by 28%. However, due to increased consumption of chemicals, the operational cost increased by 87% and the LCA revealed that the abiotic depletion of elements and fossil resources increased by 77 and 305%, respectively. The results emphasize the importance of using plant-wide mechanistic models and life cycle analysis to capture both the dynamics of the plant and the potential environmental impacts.

QSAR regression models of the toxicity of triazoles and benzotriazoles ([B]TAZs) to an alga (Pseudokirchneriella subcapitata), Daphnia magna and a fish (Onchorhynchus mykiss), were developed by five partners in the FP7-EU Project, CADASTER. The models were developed by different methods —Ordinary Least Squares (OLS), Partial Least Squares (PLS), Bayesian regularised regression and Associative Neural Network (ASNN) — by using various molecular descriptors (DRAGON, PaDEL-Descriptor and QSPR-THESAURUS web). In addition, different procedures were used for variable selection, validation and applicability domain inspection. The predictions of the models developed, as well as those obtained in a consensus approach by averaging the data predicted from each model, were compared with the results of experimental tests that were performed by two CADASTER partners. The individual and consensus models were able to correctly predict the toxicity classes of the chemicals tested in the CADASTER project, confirming the utility of the QSAR approach. The models were also used for the prediction of aquatic toxicity of over 300 (B)TAZs, many of which are included in the REACH pre-registration list, and were without experimental data. This highlights the importance of QSAR models for the screening and prioritisation of untested chemicals, in order to reduce and focus experimental testing.