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Metallic engineered nanomaterial in natural aquatic environments: data generation, management and integration into environmental exposure modelling (nanoADJUST)
Start date: Dec 1, 2013, End date: Nov 30, 2016 PROJECT  FINISHED 

The success of novel, new technologies often depends to a large degree on the public’s risk-benefit perception. Engineered nanomaterials (ENMs) perceived risk is largely based on uncertainty as to their release and fate in the environment. The “nanoADJUST” project will develop expertise in the application of techniques and tools used to characterise and analyse the behaviour of metallic ENMs in natural aquatic media and integrate this expertise with environmental exposure modelling and risk management data requirements and processes. Data handling throughout the risk assessment (RA) process will be analysed and a statistical framework for the acquisition and management of nano-relevant data at all stages will be developed.Partitioning experiments in natural aquatic matrices shall address current research questions on ENM behaviour and fate, generating data for use in exposure modelling and RA. Fit-for-purpose analytical methodology shall be developed for quantification of nanoparticle related elemental concentrations in model experiments and aquatic environmental matrices. Within this work the concept of isotope tracer studies will be introduced into the emerging area of environmental based ENM research. Behavioural indicators or descriptors (i.e. partitioning likelihood distributions) shall also be developed for use in metallic ENM experimental analysis, exposure monitoring and risk assessment, and identification of organisms at risk of metallic ENM toxicity.The analytical and modelling expertise gained through this research work will complement RA projects related to other biological and chemical risks (pesticides, pathogens, etc.) at the researcher’s European institution. It will also provide support and risk assessment expertise to other nano-related projects undertaken on an institutional and an EU level. The ability to generate, analyse and manage relevant ENM fate and behaviour data will support the high level risk modelling efforts under way within the EU.

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