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Separation of microplastics from mass-limited samples by an effective adsorption technique
Summary
Researchers compared adsorption-based separation techniques for extracting microplastics from mass-limited environmental samples, evaluating efficacy and potential degradative effects on polymer integrity. The optimized method improved recovery rates and comparability of results across different sample matrices.
Microplastic in the environment hides visible and invisible dangers for the ecosystems and domiciled organisms. Due to the large quantities of microplastics already distributed worldwide, comparative studies to investigate the associated hazards, distribution patterns, and abundances are becoming increasingly important. Due to varying efforts and budgets, there is still no homogenized detection method for microplastics in the environment, which severely compromises the comparability and reliability of results between previous studies. In this study, we compare the efficacy, degradative effect on microplastics, and microplastic recovery rates of different digestion and separation methods for isolating microplastics from mass-limited environmental samples with high biogenic content. Our results show that the most gentle and effective isolation method is an adsorption-based technique that exploits the lipophilic properties of plastic for separation. This technique achieves an average microplastic recovery rate of 98.0 ± 3.8% and a matrix removal of 96.3 ± 0.3% at low cost and minimum effort. To examine the applicability of this technique to natural environmental samples, eight sediments and two plankton net samples from the South China Sea were selected to determine microplastic abundances. In the analyzed sediment samples, 0-9 microplastic items per 10 g sediment d. w. were found, while 17-25 items per m3 were detected in net samples. Considering the respective mean plastic density, this corresponds to a calculated microplastic mass of 0-39 μg (10 g d.w.)-1 and 3.7-7.1 μg m-3 in sediment and water samples, respectively. This study represents a new way of microplastic extraction from matrix-rich mass-limited samples with high accuracy and easy feasibility at low costs, which would be useful as a worldwide homogenized method in future microplastic research projects and related data comparability.
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