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An integrated science-based methodology to assess potential risks and implications of engineered nanomaterials
Citation:
Tolaymat, T., A. El Badawy, R. Sequeira, AND A. Genaidy. An integrated science-based methodology to assess potential risks and implications of engineered nanomaterials. Diana Aga, Wonyong Choi, Andrew Daugulis, Gianluca Li Puma, Gerasimos Lyberatos, and Joo Hwa Tay (ed.), JOURNAL OF HAZARDOUS MATERIALS. Elsevier Science Ltd, New York, NY, 298:270-281, (2015).
Impact/Purpose:
The following specific aims are formulated to achieve the study objective: (1) to propose a system of systems (SoS) architecture that builds a network management among the different entities in the large SEE system to track the flow of ENMs emission, fate and transport from the source to the receptor; (2) to establish a staged approach for knowledge synthesis methodology (in the form of a decision tree) to assess the risks (if any) of exposure to ENMs for all constituents of the SEE system; (3) to build a decision tree for ENM emissions in support of aim 2 and create a process model for the factors affecting nanoparticle state at the different points of emission sources; (4) to create a process model for the transformation of ENMs (if any) upon entry into environmental compartments and to build a decision tree for ENM environmental transformations in support of aim 2; (5) to create process models for potential biological transformation, accumulation, transfer, and toxicological impacts of ENMs to human and non-human entities in support of aim 2; and (6) to formulate an algorithmic computational approach for the quantification of risk (if any) of exposure to ENMs at different endpoints at the source (e.g., production), environmental compartments, and reception (i.e., biological/botanical entities).
Description:
There is an urgent need for broad and integrated studies that address the risks of engineered nanomaterials (ENMs) along the different endpoints of the society, environment, and economy (SEE) complex adaptive system. This article presents an integrated science-based methodology to assess the potential risks of engineered nanomaterials. To achieve the study objective, two major tasks are accomplished, knowledge synthesis and algorithmic computational methodology. The knowledge synthesis task is designed to capture “what is known” and to outline the gaps in knowledge from ENMs risk perspective. The algorithmic computational methodology is geared toward the provision of decisions and an understanding of the risks of ENMs along different endpoints for the constituents of the SEE complex adaptive system. The approach presented herein allows for addressing the formidable task of assessing the implications and risks of exposure to ENMs, with the long term goal to build a decision-support system to guide key stakeholders in the SEE system towards building sustainable ENMs and nano-enabled products.
