A relative ranking approach for nano-enabled applications to improve risk-based decision making: A case study of Army materiel
Assessing the health and environmental risks of engineered nanomaterials (ENMs) continues to be a challenging endeavor. Due to extensive challenges related to applying traditional risk assessment frameworks to ENMs, decision making regarding the use of ENMs in products and applications may need to rely on structured decision support tools such as risk ranking approaches. This study examines the use of one risk ranking tool that incorporates both quantitative and qualitative information regarding the potential human health risks of ENMs, focused primarily on worker and soldier health. Using a case study involving Army materiel (i.e., equipment), a relative risk ranking algorithm is proposed that accounts for not only the physicochemical characteristics of the ENMs, but also the characteristics of the Army materiel. In this way, the resulting risk potential for soldiers and workers is not solely based on the inherent characteristics of the ENMs but is also influenced within the context of the technology being developed. Among other important findings, the results from applying this risk ranking algorithm in this case study suggest that inhalation from accidental exposures to carbon nanotubes and copper flakes incorporated into energy and obscurant materiel by Army workers rank highest relative to the other items evaluated in this baseline assessment. As the presence of data gaps was one of the greatest challenges to applying this risk ranking algorithm, future applications may benefit from reliance on a continually revised database that may be updated in real time and possibly synced with publically available databases in order to use the most current and comprehensive set(s) of data available.
Grieger, K., Redmon, J., Money, E., Widder, MW., van der Schalie, WH., Beaulieu, S., & Womack, D. (2015). A relative ranking approach for nano-enabled applications to improve risk-based decision making: A case study of Army materiel. Environment Systems and Decisions, 35(1), 42-53. DOI: 10.1007/s10669-014-9531-4