Assessing the properties of and characterizing nanomaterials is a task that has quickly blossomed into arguably the most multidisciplinary field to date. As physical chemistry joins forces with the biological sciences to engineer substances with novel properties, researchers are faced with a multitude of possibilities. It is often remarked that this spectrum of possibilities means a spectrum of concerns: to qualify and quantify how such materials would be altered upon environmental release has fate chemistry increasingly coming into the synthesis laboratory. The recent bloom of nano funding has at a minimum made the long-desired goal of proactive regulation via predictive ecotoxicology a leading research mandate. In this Viewpoint, the Duke-based team of Wiesner et al. describe their approach in these (early) heady days of empirical nanomaterial risk assessment.

Mathematical models improve our fundamental understanding of the environmental behavior, fate, and transport of engineered nanomaterials (NMs, chemical substances or materials roughly 1-100 nm in size) and facilitate risk assessment and management activities. Although today's large-scale environmental fate models for NMs are a considerable improvement over early efforts, a gap still remains between the experimental research performed to date on the environmental fate of NMs and its incorporation into models. This article provides an introduction to the current state of the science in modeling the fate and behavior of NMs in aquatic environments. We address the strengths and weaknesses of existing fate models, identify the challenges facing researchers in developing and validating these models, and offer a perspective on how these challenges can be addressed through the combined efforts of modelers and experimentalists.

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We assess the effect of CuO nanoparticle (NP) concentration and soil aging time on the extractability of Cu from a standard sandy soil (Lufa 2.1). The soil was dosed with CuO NPs or Cu(NO3)2 at 10 mg/kg or 100 mg/kg of total added Cu, and then extracted using either 0.01 M CaCl or 0.005 M diethylenetriaminepentaacetic acid (DTPA) (pH 7.6) extraction fluid at selected times over 31 days. For the high dose of CuO NPs, the amount of DTPA-extractable Cu in soil increased from 3 wt % immediately after mixing to 38 wt % after 31 days. In contrast, the extractability of Cu(NO) was highest initially, decreasing with time. The increase in extractability was attributed to dissolution of CuO NPs in the soil. This was confirmed with synchrotron X-ray absorption near edge structure measurements. The CuO NP dissolution kinetics were modeled by a first-order dissolution model. Our findings indicate that dissolution, concentration, and aging time are important factors that influence Cu extractability in CuO NP-amended soil and suggest that a time-dependent series of extractions could be developed as a functional assay to determine the dissolution rate constant.

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.

It is anticipated that the next generation of computational epidemic models will simulate both infectious disease transmission and dynamic human behaviour change. Individual agents within a simulation will not only infect one another, but will also have situational awareness and a decision algorithm that enables them to modify their behaviour. This paper develops such a model of behavioural response, presenting a mathematical interpretation of a well-known psychological model of individual decision making, the health belief model, suitable for incorporation within an agent-based disease-transmission model. We formalize the health belief model and demonstrate its application in modelling the prevalence of facemask use observed over the course of the 2003 Hong Kong SARS epidemic, a well-documented example of behaviour change in response to a disease outbreak.

It has been suggested, but not previously measured, that dissolution kinetics of soluble nanoparticles such as CuO nanoparticles (NPs) in soil affect their phytotoxicity. An added complexity is that such dissolution is also affected by the presence of plant roots. Here, we measured the rate of dissolution of CuO NPs in bulk soil, and in soil in which wheat plants ( Triticum aestivum) were grown under two soil NP dosing conditions: (a) freshly added CuO NPs (500 mg Cu/kg soil) and (b) CuO NPs aged for 28 d before planting. At the end of the plant growth period (14 d), available Cu was measured in three different soil compartments: bulk (not associated with roots), loosely attached to roots, and rhizosphere (soil firmly attached to roots). The labile Cu fraction increased from 17 mg/kg to 223 mg/kg in fresh treatments and from 283 mg/kg to 305 mg/kg in aged treatments over the growth period due to dissolution. Aging CuO NPs increased the toxicity to Triticum aestivum (reduction in root maximal length). The presence of roots in the soil had opposite and somewhat compensatory effects on NP dissolution, as measured in rhizosphere soil. pH increased 0.4 pH units for fresh NP treatments and 0.6 pH units for aged NPs. This lowered CuO NP dissolution in rhizosphere soil. Exudates from T. aestivum roots also increased soluble Cu in pore water. CaCl extractable Cu concentrations increaed in rhizosphere soil compared to bulk soil, from 1.8 mg/kg to 6.2 mg/kg in fresh treatment and from 3.4 mg/kg to 5.4 mg/kg in aged treatments. Our study correlated CuO NP dissolution and the resulting Cu ion exposure profile to phytotoxicity, and showed that plant-induced changes in rhizosphere conditions should be considered when measuring the dissolution of CuO NPs near roots.

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