Core C: Modeling and Risk Forecasting

The information generated in our experimental efforts must be synthesized in a manner that facilitates interpretation among researchers and communication to students, and stakeholders. A risk assessment framework is an ideal vehicle to accomplish this task. CEINT research priorities are informed by a rigorous assessment of their risks vs. their benefits. Building on strategies from traditional environmental risk analysis for identifying research objectives, bounding problems, articulating uncertainties, and defining endpoints for analysis, we model complex and dynamic interactions of nanomaterials with the environment, and address life cycle considerations while reflecting the uncertainties in the current state of the science.

Selected Publicaitons

A. L. Dale, Casman, E. A. , Lowry, G. V. , Lead, J. R. , Viparelli, E. , and Baalousha, M. , Modeling Nanomaterial Environmental Fate in Aquatic Systems, Environmental Science & Technology, vol. 49, no. 5, pp. 2587 - 2593, 2015.
C. O. Hendren, Lowry, G. V. , Unrine, J. M. , and Wiesner, M. R. , A functional assay-based strategy for nanomaterial risk forecasting, Science of The Total Environment, 2015.
L. E. Barton, Auffan, M. , Durenkamp, M. , McGrath, S. , Bottero, J. - Y. , and Wiesner, M. R. , Monte Carlo simulations of the transformation and removal of Ag, TiO2, and ZnO nanoparticles in wastewater treatment and land application of biosolids, Science of The Total Environment, vol. 511, pp. 535 - 543, 2015.