Pollutants

Cyanobacterial bloom events that produce natural toxins occur in freshwaters across the globe, yet the potential risk of many cyanobacterial metabolites remains mostly unknown. Only microcystins, one class of cyanopeptides, have been studied intensively and the wealth of evidence regarding exposure concentrations and toxicity led to their inclusion in risk management frameworks for water quality. However, cyanobacteria produce an incredible diversity of hundreds of cyanopeptides beyond the class of microcystins. The question arises, whether the other cyanopeptides are in fact of no human and ecological concern or whether these compounds merely received (too) little attention thus far. Current observations suggest that an assessment of their (eco)toxicological risk is indeed relevant: First, other cyanopeptides, including cyanopeptolins and anabaenopeptins, can occur just as frequently and at similar nanomolar concentrations as microcystins in surface waters. Second, cyanopeptolins, anabaenopeptins, aeruginosins and microginins inhibit proteases in the nanomolar range, in contrast to protein phosphatase inhibition by microcystins. Cyanopeptolins, aeruginosins, and aerucyclamide also show toxicity against grazers in the micromolar range comparable to microcystins. The key challenge for a comprehensive risk assessment of cyanopeptides remains their large structural diversity, lack of reference standards, and high analytical requirements for identification and quantification. One way forward would be a prevalence study to identify the priority candidates of tentatively abundant, persistent, and toxic cyanopeptides to make comprehensive risk assessments more manageable.

In this study, a manganese(IV) oxide-mediator (MnO₂-mediator) system for the abatement of sulfonamide antibiotics was evaluated. Two simple model humic constituents, syringaldehyde (SA) and acetosyringone (AS), could promote the transformation of sulfonamides at pH 5–8. Two additional potential mediators, tannic acid and 2,2′-azino-bis(3-ethylbenzothiazoline)-6-sulfonate (ABTS), had negligible enhancement on the transformation of sulfonamides by MnO₂. The enhancing effect was attributed to the reaction of the oxidized mediator (i.e., phenoxy radical or benzoquinone-like compounds) produced from the oxidation of the mediators by MnO₂ with SMX. Thereby cross-coupling products from sulfamethoxazole (SMX) with oxidized SA were formed in the MnO₂-SA system, which was confirmed by liquid chromatography/electrospray ionization-triple quadrupole mass spectrometry. Coexisting metal ions (i.e., Ca(II), Mg(II) and Mn(II)) showed inhibitory effects in the order of Mn(II)> Ca(II)> Mg(II). For repetitive runs of the MnO₂-SA-SMX system, MnO₂ lost its oxidative capacity due to the sorption of Mn(II) on the reactive sites of the MnO₂ surface. A full regeneration of partially deactivated MnO₂ by oxidation of the sorbed Mn(II) with Mn(VII) could be achieved.

Nanomaterial risk governance requires models to estimate the material flow, fate and transport as well as uptake/bioavailability, hazard and risk in the environment. This study assesses the fit of such available models to different stages during the innovation of nano-enabled products. Through stakeholder consultations, criteria were identified for each innovation stage from idea conception to market launch and monitoring. In total, 38 models were scored against 41 criteria concerning model features, applicability, resource demands and outcome parameters. A scoring scheme was developed to determine how the models fit the criteria of each innovation stage. For each model, the individual criteria scores were added, yielding an overall fit score to each innovation stage. Three criteria were critical to stakeholders and incorporated as multipliers in the scoring scheme; the required time/costs and level of expertise needed to use the model, and for risk assessment models only, the option to compare PEC and PNEC. Regulatory compliance was also identified as critical, but could not be incorporated, as a nanomaterial risk assessment framework has yet to be developed and adopted by legislators. In conclusion, the scoring approach underlined similar scoring profiles across stages within model categories. As most models are research tools designed for use by experts, their score generally increased for later stages where most resources and expertise are committed. In contrast, stakeholders need relatively simple models to identify potential hazards and risk management measures at early product development stages to ensure safe use of nanomaterials without costs and resource needs hindering innovation.

Considerable pollutant loads can enter surface waters during rain events. Three factors challenge quantification of these pollutant fluxes using traditional sampling methods: (i) concentration fluctuations; (ii) unknown event duration; and (iii) placement, operation, and maintenance of equipment. Passive samplers offer the advantage of sampling in a continuous mode without power supply. However, variable uptake rates due to environmental factors and desorption in the case of fluctuating concentrations can affect the accuracy of time-weighted average (TWA) concentration estimates. While uncertainties related to environmental factors could be accounted for with additional effort, we can neither control nor quantify the concentration variability. We present measured and modelled concentration profiles at high temporal resolution and provide a systematic approach to assessing deviations from true TWA concentration due to fluctuating concentration profiles. We evaluate sampling of sewer overflows (0.3–14 h) with Chemcatcher and 1-week sampling in rivers. The uncertainty due to fluctuating concentrations is small, and other factors such as chemical analyses and sampler calibration have a similar or higher impact. The uncertainty due to fluctuations clearly increases with the sampling duration, particularly when exceeding the half-life of equilibrium. We conclude that passive sampling can also be used in wastewater systems with potentially high concentration variations.