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Microplastics in a deep, dimictic lake of the North German Plain with special regard to vertical distribution patterns
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Researchers assessed the vertical distribution of microplastics in Lake Tollense, a deep dimictic lake in northern Germany, sampling particles 63-5000 μm at surface, 7 m, and 10 m depths on three occasions. The study found that vertical distribution patterns varied with lake stratification and depth, contributing new data on how physical processes in freshwater lakes influence where microplastics accumulate.
The investigation of microplastics (MPs) in freshwater has received increased attention within the last decade. To date, sampling is mainly conducted at the surface of both rivers and lakes and only a few studies assessed the vertical distribution of MPs in the water column of freshwater bodies. To contribute to the understanding of MP pollution in the water column of freshwater lakes, this study evaluated the vertical profile of MPs in Lake Tollense considering particles between 63 and 5000 μm in size. Sampling was conducted on three occasions at three depths (surface, 7 m and 10 m) along a transect including eight sampling stations. The retrieved samples were digested with hydrogen peroxide and sodium hypochlorite and investigated via Nile Red staining and fluorescence microscopy. Subsequently, a sub-sample of stained particles was verified by μRaman-spectroscopy. The vertical distribution of MPs in Lake Tollense differed considerably between particle shapes (irregular particles (IPs) and fibers). Fibers did not show a noticeable pattern with depth and ranged between 22 fibers m³ at 0 m to 19 fibers m³ at 10 m. In contrast, IPs were distinctly less abundant in sub-surface samples with concentrations between 50 IPs m³ at 0 m to 29 IPs m³ at 10 m. Concerning IPs, buoyant polymers (mainly PE and PP) and concerning fibers PET and PP dominated the polymeric composition. Besides particle inherent properties, wind-induced mixing is likely affecting the intensity of vertical concentration gradients. This study highlights the need for depth-integrated sampling approaches in order to achieve representative data without over- or underestimating the overall abundances.
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