Classifying Nanomaterial Risks Using Multi-Criteria Decision Analysis

Abstract

Abstract. There is rapidly growing interest by regulatory agencies and stakeholders in the potential toxicity and other risks associated with nanomaterials throughout the different stages of the product life cycle (e.g., development, production, use and disposal). Risk assessment methods and tools developed and applied to chemical and biological material may not be readily adaptable for nanomaterials because of the current uncertainty in identifying the relevant physico-chemical and biological properties that adequately describe the materials. Such uncertainty is further driven by the substantial variations in the properties of the original material because of the variable manufacturing processes employed in nanomaterial production. To guide scientists and engineers in nanomaterial research and application as well as promote the safe use/handling of these materials, we propose a decision support system for classifying nanomaterials into different risk categories. The classification system is based on a set of performance metrics that measure both the toxicity and physico-chemical characteristics of the original materials, as well as the expected environmental impacts through the product life cycle. The stochastic

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