Stream Dynamics and Chemical Transformations Control the Environmental Fate of Silver and Zinc Oxide Nanoparticles in a Watershed-Scale Model

Abstract

Mathematical models are needed to estimate environmental concentrations of engineered nanoparticles (NPs), which enter the environment upon the use and disposal of consumer goods and other products. We present a spatially resolved environmental fate model for the James River Basin, Virginia, that explores the influence of daily variation in streamflow, sediment transport, and stream loads from point and nonpoint sources on water column and sediment concentrations of zinc oxide (ZnO) and silver (Ag) NPs and their reaction byproducts over 20 simulation years. Spatial and temporal variability in sediment transport rates led to high NP transport such that less than 6% of NP-derived metals were retained in the river and sediments. Chemical transformations entirely eliminated ZnO NPs and doubled Zn mobility in the stream relative to Ag. Agricultural runoff accounted for 23% of total metal stream loads from NPs. Average NP-derived metal concentrations in the sediment varied spatially up to 9 orders of magnitude, highlighting the need for high-resolution models. Overall, our results suggest that "first generation" NP risk models have probably misrepresented NP fate in freshwater rivers due to low model resolutions and the simplification of NP chemistry and sediment transport.

Assessing the Risk of Engineered Nanomaterials in the Environment: Development and Application of the nanoFate Model

“…47,49,52,61,62 In a spatial model, Dale et al predict the 95th percentile total Zn from ZnO in a watershed to range from 10 −8 and 10 −2 μg/L which is similar to the range predicted by nanoFate (10 −6 and 10 −3 μg/L), even with rather different loading and spatial resolution. 57 nanoFate sediment [ENM] predictions tend to be on the low-end relative to previous models, resulting from the inclusion of dissolution in freshwater and marine sediment. If dissolution is set to zero, the sediment ZnO concentration increases by orders of magnitude, closer to Sun et al (Figure S5).…”

“…They are also limited with regard to the properties, transport, and transformations they include and the spatial scale and environmental compartments they consider. However, as observed in a recent study, 57 most models consider only steady state over a very large region, ignore stream loads resulting from surface runoff of biosolids or fertilizers containing ENMs, and do not track ENM reaction byproducts (such as the dissolved ion). Recent studies go further in accounting for material-specific descriptors and account for the dynamic behavior of ENMs; 50,58−61 however, these generally focus on one specific subset of the environment, usually water and sediments, instead of a comprehensive assessment of the total environment.…”

“…and temporal data for calibration (e.g., flow gauges in the river and tributaries, sediment bed depth over time, suspended sediments, water quality), which may not be easily available for other locations. 57,61,62 Higher spatial and temporal resolution is gained but at the cost of significant complexity.…”

Frameworks and tools for risk assessment of manufactured nanomaterials

“…The U.S. Center for Environmental Implications of Nanotechnology (CEINT) developed a similar tool to estimate environmental concentrations of MNs in surface waters and sediments (DALE et al, 2015). Some processes considered by the CEINT model include runoff from crop soils, sewage treatment plant effluent loads to the stream, flow-dependent sediment transport (settling and re-suspension) and its impact on nanoparticle mobility in the stream and the sediment bed.…”

“…In the SUN project the model was upgraded to consider important end-of-life scenarios such as incineration and recycling (Caballero-Guzman et al, 2015, Walser and, where significant release of MNs is expected to occur. CEINT tested their model with nanoscale ZnO and Ag using the James River Basin in Virginia as a case study (DALE et al, 2015).…”