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Functionalization and Dispersion of Carbon Nanomaterials Using an Environmentally Friendly Ultrasonicated Ozonolysis Process
Published on: May 30, 2017
Proxy Measures for Simplified Environmental Assessment of Manufactured Nanomaterials
Rickard Arvidsson1,2, Anders Baun2, Anna Furberg1
1Division of Environmental Systems Analysis , Chalmers University of Technology , Vera Sandbergs Allé 8 , 412 96 Gothenburg , Sweden.
Abstract:
Proxy measures have been proposed as a low-data option for simplified assessment of environmental threat given the high complexity of the natural environment. We here review studies of environmental release, fate, toxicity, and risk to identify relevant proxy measures for manufactured nanomaterials (MNMs). In total, 18 potential proxy measures were identified and evaluated regarding their link to environmental risk, an aspect of relevance, and data availability, an aspect of practice. They include socio-technical measures (e.g., MNM release), particle-specific measures (e.g., particle size), partitioning coefficients (e.g., the octanol-water coefficient), and other fate-related measures (e.g., half-life) as well as various ecotoxicological measures (e.g., 50% effect concentration). For most identified proxy measures, the link to environmental risk was weak and data availability low. Two exceptions were global production volume and ecotoxicity, for which the links to environmental risk are strong and data availability relatively decent. As proof of concept, these were employed to assess seven MNMs: titanium dioxide, cerium dioxide, zinc oxide, silver, silicon dioxide, carbon nanotubes, and graphene. The results show that none of the MNMs have both high production volumes and high ecotoxicity. Several refinements of the assessment are possible, such as higher resolution regarding the MNMs assessed (e.g., different allotropes) and different metrics (e.g., particle number and surface area). The proof of concept shows the feasibility of using proxy measures for environmental assessment of MNMs, in particular for novel MNMs in early technological development, when data is particularly scarce.
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