Modeling Approaches for Characterizing and Evaluating Environmental Exposure to Engineered Nanomaterials in Support of Risk-Based Decision Making

• Published in: Environmental science & technology 2013-02, Vol.47 (3), p.1190-1205
• Main Authors: Hendren, Christine Ogilvie, Lowry, Michael, Grieger, Khara D, Money, Eric S, Johnston, John M, Wiesner, Mark R, Beaulieu, Stephen M
• Format: Article
• Language: English
• Subjects: Animal, plant and microbial ecology; Applied ecology; Applied sciences; Biological and medical sciences; Decision Making; Earth sciences; Earth, ocean, space; Ecotoxicology, biological effects of pollution; Engineering and environment geology. Geothermics; Environmental Exposure - analysis; Environmental impact statements; Exact sciences and technology; Fundamental and applied biological sciences. Psychology; General aspects; Global environmental pollution; Human exposure; Models, Theoretical; Nanomaterials; Nanostructures - adverse effects; Nanotechnology - methods; Pollution; Pollution, environment geology; Risk Assessment
• ISSN: 0013-936X; 1520-5851
• DOI: 10.1021/es302749u

As the use of engineered nanomaterials becomes more prevalent, the likelihood of unintended exposure to these materials also increases. Given the current scarcity of experimental data regarding fate, transport, and bioavailability, determining potential environmental exposure to these materials requires an in depth analysis of modeling techniques that can be used in both the near- and long-term. Here, we provide a critical review of traditional and emerging exposure modeling approaches to highlight the challenges that scientists and decision-makers face when developing environmental exposure and risk assessments for nanomaterials. We find that accounting for nanospecific properties, overcoming data gaps, realizing model limitations, and handling uncertainty are key to developing informative and reliable environmental exposure and risk assessments for engineered nanomaterials. We find methods suited to recognizing and addressing significant uncertainty to be most appropriate for near-term environmental exposure modeling, given the current state of information and the current insufficiency of established deterministic models to address environmental exposure to engineered nanomaterials.