Microplastic pollution characteristic in surface water and freshwater fish of Gehu Lake, China
Abstract
Abstract Much more attention has been poured into microplastic pollution in freshwater systems recently. In the present study, the pollution of microplastics (MPs) in surface water and freshwater fish (crucian carp, etc.) were investigated from Gehu Lake, which is the second largest lake in southern Jiangsu after Taihu Lake. The result manifested that the average abundance of MPs was respectively 6.33 ± 2.67 n/L for surface water and 10.7 items per individual for freshwater fish. The distribution of MPs in Gehu Lake varied from place to place, with the highest abundance of MPs was observed in the two estuaries of the eastern part of the lake. It was speculated that topographical factors and human factors were the main factors affecting the abundance and distribution of MPs. Transparent fibers were the main type of MPs in water samples, accounting for 69.70% of all detected particles. Meanwhile, most of the MPs ingested by freshwater fish were fibers, and the main colors were transparent and blue. In addition, the dominant size of the MPs was between 0.1 mm to 0.5 mm in water and fish samples. Moreover, PES, Man-made fiber, and PP were the dominant polymer types in the surface water and fish samples. The results of this investigation can provide basic data for the research and management of MPs in freshwater systems.
Read the paper
Related studies
- Green Chemistry: A Framework for a Sustainable Future
- Nano/micro-plastic, an invisible threat getting into the brain
- Emerging contaminants antibiotic resistance genes and microplastics in the environment: Introduction to 21 review articles published in CREST during 2018–2022
- Water Resources and Sustainable Development
- Nano- and microplastics in the workplace
- Water Enclosure and World-Literature: New Perspectives on Hydro-Power and World-Ecology
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.