Conceptual modeling for identification of worst case conditions in environmental risk assessment of nanomaterials using nZVI and C60 as case studies

Abstract

Conducting environmental risk assessment of engineered nanomaterials has been an extremely challenging endeavor thus far. Moreover, recent findings from the nano-risk scientific community indicate that it is unlikely that many of these challenges will be easily resolved in the near future, especially given the vast variety and complexity of nanomaterials and their applications. As an approach to help optimize environmental risk assessments of nanomaterials, we apply the Worst-Case Definition (WCD) model to identify best estimates for worst-case conditions of environmental risks of two case studies which use engineered nanoparticles, namely nZVI in soil and groundwater remediation and C(60) in an engine oil lubricant. Results generated from this analysis may ultimately help prioritize research areas for environmental risk assessments of nZVI and C(60) in these applications as well as demonstrate the use of worst-case conditions to optimize future research efforts for other nanomaterials. Through the application of the WCD model, we find that the most probable worst-case conditions for both case studies include i) active uptake mechanisms, ii) accumulation in organisms, iii) ecotoxicological response mechanisms such as reactive oxygen species (ROS) production and cell membrane damage or disruption, iv) surface properties of nZVI and C(60), and v) acute exposure tolerance of organisms. Additional estimates of worst-case conditions for C(60) also include the physical location of C(60) in the environment from surface run-off, cellular exposure routes for heterotrophic organisms, and the presence of light to amplify adverse effects. Based on results of this analysis, we recommend the prioritization of research for the selected applications within the following areas: organism active uptake ability of nZVI and C(60) and ecotoxicological response end-points and response mechanisms including ROS production and cell membrane damage, full nanomaterial characterization taking into account detailed information on nanomaterial surface properties, and investigations of dose-response relationships for a variety of organisms.