Summary
Reliable assessment of the ecological risks posed by chemicals is a fundamental component of European policies concerned with safe use of chemicals e.g. REACh, The Green Deal, and protection of ecosystem functioning and ecosystem services (Water Framework Directive). Chemical risk assessment typically involves extrapolation of effects observed in-vitro and in-vivo under laboratory conditions to predictions of effects at the ecosystem level. This is a very challenging task and current extrapolation models have limitations, notably due to a number of ecological processes that are disregarded by the models and the paucity of data for parameterisation and validation. QTOX will develop mechanistic knowledge and data efficient modelling tools to bridge the gap between standard toxicity data (typically acute effects of single chemicals) and ecologically relevant end points arising from chronic, time variable exposures to chemical mixtures. The results will be achieved through an interdisciplinary and intersectoral research and training program in which 10 doctoral candidates will characterise the mechanistic processes describing the successive events from exposure to ecosystem-level effects and develop models for extrapolation of adverse effects across levels of biological organisation under environmentally realistic conditions. Notably, the effects of chemical mixtures, dynamic exposure conditions and their interaction with climate change scenarios will be characterised in a series of mesocosm experiments at three sites in central and southern Europe. The mesocosm work will serve as a uniting training element and a rich source of data for testing and validating the modelling framework. QTOX will produce an open access toolbox for quantitative extrapolations in ecotoxicology and a cohort of researchers equipped with the knowledge and skills necessary to implement and develop rigorous approaches for predicting adverse effects of chemicals.
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Web resources: | https://cordis.europa.eu/project/id/101072531 |
Start date: | 01-02-2023 |
End date: | 31-01-2027 |
Total budget - Public funding: | - 2 727 057,00 Euro |
Cordis data
Original description
Reliable assessment of the ecological risks posed by chemicals is a fundamental component of European policies concerned with safe use of chemicals e.g. REACh, The Green Deal, and protection of ecosystem functioning and ecosystem services (Water Framework Directive). Chemical risk assessment typically involves extrapolation of effects observed in-vitro and in-vivo under laboratory conditions to predictions of effects at the ecosystem level. This is a very challenging task and current extrapolation models have limitations, notably due to a number of ecological processes that are disregarded by the models and the paucity of data for parameterisation and validation. QTOX will develop mechanistic knowledge and data efficient modelling tools to bridge the gap between standard toxicity data (typically acute effects of single chemicals) and ecologically relevant end points arising from chronic, time variable exposures to chemical mixtures. The results will be achieved through an interdisciplinary and intersectoral research and training program in which 10 doctoral candidates will characterise the mechanistic processes describing the successive events from exposure to ecosystem-level effects and develop models for extrapolation of adverse effects across levels of biological organisation under environmentally realistic conditions. Notably, the effects of chemical mixtures, dynamic exposure conditions and their interaction with climate change scenarios will be characterised in a series of mesocosm experiments at three sites in central and southern Europe. The mesocosm work will serve as a uniting training element and a rich source of data for testing and validating the modelling framework. QTOX will produce an open access toolbox for quantitative extrapolations in ecotoxicology and a cohort of researchers equipped with the knowledge and skills necessary to implement and develop rigorous approaches for predicting adverse effects of chemicals.Status
SIGNEDCall topic
HORIZON-MSCA-2021-DN-01-01Update Date
09-02-2023
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