For a proactive risk assessment of engineered nanoparticles (ENPs) it is imperative to derive predicted environmental concentration (PEC) values for ENPs in different environmental compartments; PECs can then be compared to effect thresholds. From the basis of established multimedia environmental fate models for organic pollutants, we develop a new concept of environmental fate modeling for ENPs with process descriptions based on the specific properties of ENPs. Our new fate modeling framework is highly flexible and can be adjusted to different ENPs and various environmental settings. As a first case study, the fate and transport of TiO(2) NPs in the Rhine River is investigated. Predicted TiO(2) NP concentrations lie in the ng/L range in the water compartment and mg/kg in the sediment, which represents the main reservoir for the nanoparticles. We also find that a significant downstream transport of ENPs is possible. A fundamental process, the heteroaggregation between TiO(2) NPs and suspended particulate matter (SPM), is analyzed in more detail. Our modeling results demonstrate the importance of both the SPM properties (concentration, size, density) as well as the affinity of TiO(2) NPs and SPM, characterized by the attachment efficiency, α(het-agg), on the transport potential of ENPs in a surface water system.

Adequate fate descriptors are crucial input parameters in models used to predict the behaviour and transport of a contaminant in the environment and determine predicted environmental concentrations for risk assessment. When new fate models are being developed for emerging contaminants, such as engineered nanoparticles (ENPs), special care has to be applied in adjusting conventional approaches and fate descriptors to a new set of substances. The aim of this paper is to clarify misconceptions about the applicability of equilibrium partition coefficients, such as the octanol-water partition coefficient (K ow ) or the soil-water distribution coefficient (K d ), whose application in the context of ENP fate assessment is frequently suggested despite lacking scientific justification. ENPs are present in the environment as thermodynamically unstable suspensions and their behaviour must be represented by kinetically controlled attachment and deposition processes as has been established by colloid science. Here, we illustrate the underlying theories of equilibrium partitioning and kinetically controlled attachment and discuss why the use of any coefficient based on equilibrium partitioning is inadequate for ENPs and can lead to significant errors in ENP fate predictions and risk assessment.

The derivatization of 3-amino-9-ethylcarbazole with a diamino-alkyl anchor affords a fluorescent dye suitable for indicator displacement from cucurbituril macrocycles. The novel compound 1 shows, due to a complexation-induced pKa shift, a large and predictable dual fluorescence response (100-fold increase at 375 nm and 9-fold decrease at 458 nm) upon supramolecular encapsulation and a strong affinity for cation-receptor macrocycles, in particular cucurbit[6]uril (CB6). A direct application is presented by monitoring the enzymatic activity of lysine decarboxylase.

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

The heteroaggregation of engineered nanoparticles (ENPs) with natural colloids (NCs), which are ubiquitous in natural surface waters, is a crucial process affecting the environmental transport and fate of ENPs. Attachment efficiencies for heteroaggregation, α hetero, are required as input parameters in environmental fate models to predict ENP concentrations and contribute to ENP risk assessment. Here, we present a novel method for determining α hetero values by using a combination of laser diffraction measurements and aggregation modeling based on the Smoluchowski equation. Titanium dioxide nanoparticles (TiO2 NPs, 15 nm) were used to demonstrate this new approach together with larger silicon dioxide particles (SiO2, 0.5 μm) representing NCs. Heteroaggregation experiments were performed at different environmentally relevant solution conditions. At pH 5 the TiO2 NPs and the SiO2 particles are of opposite charge, resulting in α hetero values close to 1. At pH 8, where all particles are negatively charged, α hetero was strongly affected by the solution conditions, with α hetero ranging from <0.001 at low ionic strength to 1 at conditions with high NaCl or CaCl2 concentrations. The presence of humic acid stabilized the system against heteroaggregation.

Detecting and quantifying engineered nanoparticles (ENPs) in complex environmental matrices requires the distinction between natural nanoparticles (NNPs) and ENPs.

Microplastics (MPs) have been identified as contaminants of emerging concern in aquatic environments and research into their behavior and fate has been sharply increasing in recent years. Nevertheless, significant gaps remain in our understanding of several crucial aspects of MP exposure and risk assessment, including the quantification of emissions, dominant fate processes, types of analytical tools required for characterization and monitoring, and adequate laboratory protocols for analysis and hazard testing. This Feature aims at identifying transferrable knowledge and experience from engineered nanoparticle (ENP) exposure assessment. This is achieved by comparing ENP and MPs based on their similarities as particulate contaminants, whereas critically discussing specific differences. We also highlight the most pressing research priorities to support an efficient development of tools and methods for MPs environmental risk assessment.

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