A means for identifying and prioritising the treatment of uncertainty (UnISERA) in environmental risk assessments (ERAs) is tested, using three risk domains where ERA is an established requirement and one in which ERA practice is emerging. UnISERA's development draws on 19 expert elicitations across genetically modified higher plants, particulate matter, and agricultural pesticide release and is stress tested here for engineered nanomaterials (ENM). We are concerned with the severity of uncertainty; its nature; and its location across four accepted stages of ERAs. Using an established uncertainty scale, the risk characterisation stage of ERA harbours the highest severity level of uncertainty, associated with estimating, aggregating and evaluating expressions of risk. Combined epistemic and aleatory uncertainty is the dominant nature of uncertainty. The dominant location of uncertainty is associated with data in problem formulation, exposure assessment and effects assessment. Testing UnISERA produced agreements of 55%, 90%, and 80% for the severity level, nature and location dimensions of uncertainty between the combined case studies and the ENM stress test. UnISERA enables environmental risk analysts to prioritise risk assessment phases, groups of tasks, or individual ERA tasks and it can direct them towards established methods for uncertainty treatment.

Microplastics (particle size <5 mm) are an emerging contaminant for aquatic environmental, which have attracted increasing attention in worldwide range. In this study, an improved fluorescent staining method for detection and quantification of microplastics was developed based on thermal expansion and contraction. This method is effective in detection of polyethylene, polystyrene, polyvinyl chloride and polyethylene terephthalate plastic particles. In order to avoid error statistics caused by pretreatment, various characterizations of microplastics were measured after heated, such as microstructure, compositions and thermostability. The results showed that there was no significant damage to microplastics even under heating condition at 75 °C for 30 min, and the stained microplastics had strong stability for up to two months. Moreover, this method has been successfully applied to the quantification of microplastics in biological samples and result showed there were about 54 particles g⁻¹ (dry weight) microplastics in the Sipunculus nudus. This new method provides a reliable method for quantitative analysis of microplastics in environment and biological tissue.

International audience | The present work was carried out to quantify microplastics (MP) from three sandy beaches along the Côte d’Opale coastline located in the Hauts-de-France region of northern France. Three different study sites located along the English Channel were investigated due to different levels of anthropopression and hydrodynamic conditions. Sediments were collected at three different tide lines: high tide line (HTL), middle of the intertidal zone (IZ), and low tide line (LTL), to investigate the effects of tide line on microplastic contamination. Particles and fibers were counted and colors were recorded; polymer identification was then performed using pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS). Particle and fiber abundances ranged from 23.4 ± 18.9 to 69.3 ± 30.6 items kg−1 dry weight sediment, with a trend towards fiber predominance, were observed. No difference in particle and fiber abundance was found between the different beaches and tide lines, except for Boulogne-sur-Mer, where the particle number was significantly different between tide lines. Major polymers identified were polyethylene (36.6%) and polypropylene (10.7%). This citizen science project provided preliminary data about the abundance and polymeric nature of MP along the Côte d’Opale coastline.

The analysis of microplastics in various environmental samples requires the identification of microplastics from natural materials. The identification technique lacks a standardized protocol. Herein, stereomicroscope and Fourier transform infrared spectroscope (FT-IR) identification methods for microplastics (<1mm) were compared using the same samples from the sea surface microlayer (SML) and beach sand. Fragmented microplastics were significantly (p<0.05) underestimated and fiber was significantly overestimated using the stereomicroscope both in the SML and beach samples. The total abundance by FT-IR was higher than by microscope both in the SML and beach samples, but they were not significantly (p>0.05) different. Depending on the number of samples and the microplastic size range of interest, the appropriate identification method should be determined; selecting a suitable identification method for microplastics is crucial for evaluating microplastic pollution.

In this study, the climate change, tsunami and biodiversity for 336 km coastline endangered at the South China Sea was investigated with the review for the past, current and prediction models for the future. The hydraulic study of the coastal area was conducted using a well-established 2D numerical model suite Delft3D. The study revealed that the generated earthquakes at the convergence zone in the last century are small (Mw7.3), the possibility that a megathrust earthquake event in the SCS basin occurs in the future. The study area comprises a narrow strip of vegetation notably dominated by Casuarina equisetifolia with other coastal plants. Mangrove forests are found along the coastline and estuaries that are overlaid with marine alluvial soils. The current paper is the first comprehensive study of the South China Sea, and the findings increase the awareness among the public to understand the risk associated with environmental pollution.

We investigated the applicability of Nile Red (NR), a fluorescent dye, for microplastic analysis, and determined the optimal staining conditions. Five mg/L NR solution in n-hexane effectively stained plastics, and they were easily recognized in green fluorescence. The NR staining method was successfully applied to micro-sized polyethylene, polypropylene, polystyrene, polycarbonate, polyurethane, and poly(ethylene-vinyl acetate), except for polyvinylchloride, polyamide and polyester. The recovery rate of polyethylene (100–300μm) spiked to pretreated natural sand was 98% in the NR stating method, which was not significantly (p<0.05) different with FT-IR identification. The NR staining method was suitable for discriminating fragmented polypropylene particles from large numbers of sand particles in laboratory weathering test samples. The method is straightforward and quick for identifying and quantifying polymer particles in the laboratory controlled samples. Further studies, however, are necessary to investigate the application of NR staining to field samples with organic remnants.