Microplastics can contaminate water owing to their small size. If aquatic biota consume microplastics, they disrupt their reproductive processes, digestive tracts, and development. This study aimed to identify microplastic waste from silkworms (Tubifex spp.) in the Brantas River. The study was conducted in a descriptive manner by collecting samples of microplastic waste from silkworms and examining the shape, type, amount, and percentage of microplastic abundance in the river. An FTIR test was used to determine the microplastic content. Using a Zeiss Axio Zoom.V16 at 50x magnification, microplastic particles from individual worms and worm samples were visually identified. Then, the 50% hot needle test was used to determine the composition of the plastic. A total of 263 microplastic particles were found in the worm samples. Silkworms (Tubifex spp.) in the Brantas River, Kediri City, were shown to contain four types of microplastics, namely fibers, filaments, fragments, and granules, which were dominated by filament particles with 49% filament content, 45% fiber, 5% fragments, and 1% granules. The microplastic polymers identified via FTIR were polyethylene and ethylene-polypropylene-diene copolymers. These microplastics can originate from plastic bags, used drinking bottles, rope fibers, and pieces of water hose, which are often found around the Brantas River. Silkworms found in the Brantas River contain microplastic waste from various pollution sources.

Chloroorganic chemicals emitted from the pulp and paper mill at Nekoski in central Finland were monitored for several years. Concentration time series are used for evaluating the environmental fate and the applicability and validity of an exposure models. Fitted elimination rates of 3,4,5-Tri-, 4,5,6-Tri-, Tetrachloroguaiacol and 2,4,6-Trichlorophenol are approx. 0.22 per day, or rather the half-lives are approx. 3 days. The elimination is most likely by biodegradation and transport-controlled. For 2,3,6-trichloro-p-cymene, fate simulations indicate significant volatilization and sedimentation. Good agreement is achieved with a one-dimensional steady-state box model, except for concentrations in fish. For a reliable assessment of environmental damage, laboratory experiments, monitoring and simulations need to be in tune.

The Black Sea receives increasing amounts of microplastics from rivers. In this study, we explore options to reduce future river export of microplastics to the Black Sea. We develop five scenarios with different reduction options and implement them to a Model to Assess River Inputs of pollutaNts to seA (MARINA-Global) for 107 sub-basins. Today, European rivers draining into the Black Sea export over half of the total microplastics. In 2050, Asian rivers draining into the sea will be responsible for 34–46% of microplastic pollution. Implemented advanced treatment will reduce point-source pollution. Reduced consumption or more collection of plastics will reduce 40% of microplastics in the sea by 2050. In the optimistic future, sea pollution is 84% lower than today when the abovementioned reduction options are combined. Reduction options affect the share of pollution sources. Our insights could support environmental policies for a zero pollution future of the Black Sea.

Water quality has recently emerged as one of the utmost severe ecological problems being faced by the developing countries all over the world, and Bangladesh is no exception. Both surface and groundwater sources contain different contaminants, which lead to numerous deaths due to water-borne diseases, particularly among children. This study presents one of the most comprehensive reviews on the current status of water quality in Bangladesh with a special emphasis on both conventional pollutants and emerging contaminants. Data show that urban rivers in Bangladesh are in a critical condition, especially Korotoa, Teesta, Rupsha, Pashur, and Padma. The Buriganga River and few locations in the Turag, Balu, Sitalakhya, and Karnaphuli rivers have dissolvable oxygen (DO) levels of almost zero. Many waterways contain traces of NO3, NO2, and PO4-3 pollutants. The majority of the rivers in Bangladesh also have Zn, Cu, Fe, Pb, Cd, Ni, Mn, As, and Cr concentrations that exceed the WHO permissible limits for safe drinking water, while their metal concentrations exceed the safety threshold for irrigation. Mercury poses the greatest hazard with 90.91% of the samples falling into the highest risk category. Mercury is followed by zinc 57.53% and copper 29.16% in terms of the dangers they pose to public health and the ecosystem. Results show that a considerable percentage of the population is at risk, being exposed to contaminated water. Despite hundreds of cryptosporidiosis cases reported, fecal contamination, i.e., Cryptosporidium, is totally ignored and need serious considerations to be regularly monitored in source water.

International audience | This paper presents a new Remote Hyperspectral Imaging System (RHIS) embedded on an Unmanned Aquatic Drone (UAD) for plastic detection and identification in coastal and freshwater environments. This original system, namely the Remotely Operated Vehicle of the University of Littoral Côte d’Opale (ROV-ULCO), works in a near-field of view, where the distance between the hyperspectral camera and the water surface is about 45 cm. In this paper, the new ROV-ULCO system with all its components is firstly presented. Then, a hyperspectral image database of plastic litter acquired with this system is described. This database contains hyperspectral data cubes of different plastic types and polymers corresponding to the most-common plastic litter items found in aquatic environments. An in situ spectral analysis was conducted from this benchmark database to characterize the hyperspectral reflectance of these items in order to identify the absorption feature wavelengths for each type of plastic. Finally, the ability of our original system RHIS to automatically recognize different types of plastic litter was assessed by applying different supervised machine learning methods on a set of representative image patches of marine litter. The obtained results highlighted the plastic litter classification capability with an overall accuracy close to 90%. This paper showed that the newly presented RHIS coupled with the UAD is a promising approach to identify plastic waste in aquatic environments.

In this paper the results of determination of natural waters from the territory of the township Smederevska Palanka and Rekovac (Serbia, Yugoslavia) are presented. The content of metals in waters was determined by the AAS method and other parameters were determined by spectrophotometric and potentiometric method.