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Microplastic contamination of lakes and rivers is an emerging environmental issue. Sources, environmental fate, in-situ behaviour, concentration and harmful impacts of microplastics on aquatic life are the focus of this review paper. Present review summarises the current state of information about microplastics in riverine ecosystems around the world. The tiny plastic particles can serve as substrate as well as transporters of a variety of toxicants, including recalcitrant chemical compounds from miscellaneous sources having potential to seriously harm people's health. Further, intake and entanglement of microplastics can inflict a number of adverse bio-physico-chemical impacts on people and other living creatures. Secondary microplastics are produced by the disintegration of bigger size primary plastic particles and ultimately end up in the terrestrial and aquatic habitats. Comprehensive information on microplastic pollution in fresh water ecosystems is still limited on a single platform. This review critically addresses the microplastic pollution in rivers, sources, and its impact around the world. Further, possible replacements for plastics like modified starch, cellulose, esters of cellulose, polylactic acid etc. derived from biomass and microorganisms are also examined. [ABSTRACT FROM AUTHOR]

Climate change and the reliance on carbon-intensive fuels have made electromobility necessary to reduce greenhouse gas (GHG) emissions in transport. This study analyses the potential environmental impact of a shallow-draught vessel operating within a section of Colombia’s Atrato River basin by estimating CO₂-equivalent emissions across various technological alternatives (conventional, hybrid, and electric) using a life cycle analysis. Data on engine performance, fuel type, and operating conditions were gathered. A battery propulsion system was modelled using both ‘conventional’ and renewable energy sources. The analysis focused on four impact categories: global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), and photochemical ozone creation potential (POCP). Results indicated significant reductions with renewable energy: 92.6% in GWP, 94.2% in AP, 82.4% in EP, and 93.7% in POCP. The selection of energy sources for electricity generation is crucial in assessing the viability of battery technology for sustainable shipping. [ABSTRACT FROM AUTHOR]

Recently, the impact of climate change has led to an increase in the scale and frequency of extreme rainfall and flash floods. Due to this, the occurrence of floods and various river disasters has increased, necessitating the acquisition of technologies to prevent river disasters. Owing to the nature of rivers, areas with poor accessibility exist, and obtaining information over a wide area can be time-consuming. Artificial intelligence technology, which has the potential to overcome these limits, has not been broadly adopted for river detection. Therefore, the current study conducted a performance analysis of artificial intelligence for automatic river path setting via the YOLOv8 model, which is widely applied in various fields. Through the augmentation feature in the Roboflow platform, many river images were employed to train and analyze the river spatial information of each applied image. The overall results revealed that the models with augmentation performed better than the basic models without augmentation. In particular, the flip and crop and shear model showed the highest performance with a score of 0.058. When applied to rivers, the Wosucheon stream showed the highest average confidence across all models, with a value of 0.842. Additionally, the max confidence for each river was extracted, and it was found that models including crop exhibited higher reliability. The results show that the augmentation models better generalize new data and can improve performance in real-world environments. Additionally, the RivDet artificial intelligence model for automatic river path configuration developed in the current study is expected to solve various problems, such as automatic flow rate estimation for river disaster prevention, setting early flood warnings, and calculating the range of flood inundation damage. [ABSTRACT FROM AUTHOR]

This article introduces a methodology utilizing the Analytical Hierarchy Process (AHP) integrated with a Geographic Information System (GIS) to classify sub-basins within a large river basin in terms of pollution levels.The research uses data from the Haraz River basin, located in northern Iran near the Caspian Sea. The river basin under investigation comprises seven sub-basins. The primary pollution sources in this region include domestic wastewater from urban areas, effluents from fish farms, discharge from sand and gravel mines, sewage from restaurants and tourism centers, as well as land use (agriculture, forests, and rangelands). In addition to these pollution-related factors, other criteria such as basin area, river length, road network length, and slope were also considered.Using scores assigned by experts and leveraging the Expert Choice software, all sub-basins, and factors contributing to river pollution were identified. According to the findings, urban domestic wastewater was the most significant contributor to pollution in the study Basin, accounting for 42.2% of the total pollution. The sub-basins were classified according to their final weighted scores, identifying those with the highest and lowest pollution levels.The studied approach offers substantial advantages in terms of time, cost, and resource efficiency. [ABSTRACT FROM AUTHOR]