Demonstration of a Modelling-based Multi-criteria Decision Analysis Procedure for Prioritization of Occupational Risks from Manufactured Nanomaterials

Several tools to facilitate the Risk Assessment and Management of manufactured nanomaterials (MN) have been developed. Most of them require input data on physicochemical properties, toxicity and scenario-specific exposure information. However, such data are yet not readily available, and tools that can handle data gaps in a structured way to ensure transparent risk analysis for industrial and regulatory decision making are needed.
This paper proposes such a quantitative risk prioritisation tool, based on a Multi-criteria Decision Analysis algorithm, which combines advanced exposure and dose-response modelling to calculate Margins of Exposure for a number of MN in order to rank their occupational risks. We demonstrated the tool in a number of workplace exposure scenarios involving the production and handling of nanoscale Titanium Dioxide, Zinc Oxide, Silver, and multi-walled carbon nanotubes.
The results of this application demonstrated that bag/bin filling, manual un/loading, and dumping of large amounts of dry powders led to high emissions, which resulted in high risk associated with these exposure scenarios. The Zinc Oxide MN revealed considerable hazard potential in vivo, which significantly influenced the risk prioritization results.
In order to study how variations in the input data affect our results we performed probabilistic Monte Carlo sensitivity/uncertainty analysis, which demonstrated that the performance of the proposed model is stable against changes in the exposure and hazard input variables.

Source: Hristozov D, Zabeo A, Jensen KA, et al. Nanotoxicology, 2016.

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