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Objective of the project This projects aims at adapting probabilistic environmental and health risk assessment methods for nanomaterials, with attention for uncertainties. Environmental risk assessments of nanomaterials can be based on comparing a predicted environmental concentration (PEC) with a predicted no-effect concentration (PMEC) (see e.g. Mueller and Nowack 2008). The purpose of the current proposal is to adapt the methods to include other measures of exposure that are more appropriate for nanomaterials. For this the project will be dependent on input from other projects.
Background In the larger program, current paradigms for ecological risk assessment will be adapted to manufactured nanoparticles (MNP) making scientific uncertainties explicit.
The ecological risk assessment of MNP will be different from current risk assessment of substances, because the current risk assessment is based on the paradigm that the active species is the molecular form. For MNP, however, the processes that control their environmental concentrations have not even adequately been identified. Colloid science predicts that MNP behavior is a result of aggregation/agglomeration and settling/resuspension, rather than from thermodynamic equilibrium partitioning.
Collected data can be used to adapt mathematical and statistical models to the special case of MNP, for probabilistic risk assessment of MNP. This project will critically and systematically review ecotoxicological data and risk assessment modeling procedures and propose alternate processes that need to be accounted for in order to make the current procedures and models used in EU risk assessment fit for use with MNP.
Problem definition Nanomaterials are examples of novel materials, materials which are newly synthesized and have no history of safe use. Another example of novel materials are GM materials. Risk assessment strategies for novel materials are just beginning to be looked at (Royal Commission on Environmental Pollution 2008, Knudsen et al. 2008). For all novel materials risk assessment is faced with similar problems.
Assuming that producers of nanomaterials should perform experiments (trials) in order to allow risk assessment, questions arise about experimental design and statistical analysis of such experiments. There is a need for design of intelligent testing strategies (better experimental design ) and development of methodology for analysis.
There are three lines of activity
1. Using available exposure measures, statistical models for assessing long-term exposure will be developed with Bayesian methods and resampling methods. 2. Description of variability (e.g. between species or between environmental conditions) and statistical characterisation of uncertainty. 3. Design of intelligent testing strategies
2011: appointment of AIO, literature overview of available data and analyses, first models and analyses on available and simulated data, for describing variability of MNP species and MNP-environmental interaction. 2012: development and application of models and methods for assessing long-term exposure with emphasis on characterization of uncertainty 2013: design of intelligent testing strategies 2014: finishing the above, finish papers.
Output - Adapt current paradigms for ecological risk assessment to MNP - Use probabilistic techniques for risk assessment to make uncertainties explicit - Design intelligent testing strategies
Output (number between brackets)are conference contributions (2), papers in scientific journals (4), a PhD thesis (1) and associated computer programs