This novel single-particle multi-element fingerprinting (spMEF) method makes it possible to discriminate engineered and natural nanoparticles in complex matrices.

No abstract

To reliably assess the fate of engineered nanoparticles (ENP) in soil, it is important to understand the performance of models employed to predict vertical ENP transport. We assess the ability of seven routinely employed particle transport models (PTMs) to simulate hyperexponential (HE), nonmonotonic (NM), linearly decreasing (LD), and monotonically increasing (MI) retention profiles (RPs) and the corresponding breakthrough curves (BTCs) from soil column experiments with ENPs. Several important observations are noted. First, more complex PTMs do not necessarily perform better than simpler PTMs. To avoid applying overparameterized PTMs, multiple PTMs should be applied and the best model selected. Second, application of the selected models to simulate NM and MI profiles results in poor model performance. Third, the selected models can well-approximate LD profiles. However, because the models cannot explicitly generate LD retention, these models have low predictive power to simulate the behavior of ENPs that present LD profiles. Fourth, a term for blocking can often be accounted for by parameter variation in models that do not explicitly include a term for blocking. We recommend that model performance be analyzed for RPs and BTCs separately; simultaneous fitting to the RP and BTC should be performed only under conditions where sufficient parameter validation is possible to justify the selection of a particular model.