Exposure assessment for nanoparticles: The "other" side of the risk equation

Abstract

The classical risk assessment for chemicals includes the assessment of exposure and identification of toxicological endpoints. However, exposure assessments very often suffer from a lack of data (Sheldon & Cohen Hubal, 2009), and the fact that the toxicological target is not yet specified. In the case of engineered nanoparticles (ENP), an additional issue arises: various parameters, such as size, composition or shape, have been identified to influence the toxicological effects, and most ENP contained in market products have property distributions rather than defined physical properties.

Therefore, our exposure assessment for ENP includes the definition of realistic placeholders for different ENP species (Lorenz et al., 2009). The model scenarios are tailored to these placeholders. We kept our approach generic, with the advantage that it may be translated to exposure assessments of other new substances with partly unknown properties and that newly available information can easily be introduced into the model.

Biography of the speaker
Dr rer. nat. Natalie von Götz (ETHZ) is senior scientist at the Swiss Federal Institute of Technology Zurich in the Safety and Environmental Technology Group. Since 2008 she is leading a research group for modelling consumer exposure to chemicals of concern. Chemist by training, she worked ten years at the chemical company BASF as an expert for the fate of pesticides in the environment, as laboratory manager for environmental exposure studies for pesticides and as environmental exposure modeller. At that time, she was part of national and international working groups on pesticide guidelines (e.g. the EPPO working group on Guidance for measurement and regulation of pesticides in air) and headed the scientific work group "water expert team BASF".
Her research interests encompass the development of methodology for consumer exposure modelling, assessing aggregate consumer exposure to chemicals of concern (e.g. EDC, Nanoparticles) as well as translating academic insights into information useful for decision makers.