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Improved recovery of sub-millimeter microplastics in simple and complex aqueous matrices using a novel sampling approach
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Researchers evaluated the FC1 closed-system sampler for recovering sub-millimeter microplastics from water, achieving separation efficiencies of 96–99.6% in clean matrices and 91–98.3% in turbid environmental samples including wastewater effluent, river water, and lake water — demonstrating consistent performance across polymer types and complex matrices.
ABSTRACT: The accurate quantification of microplastics (MPs) in the 1–1000 µm size range is important for environmental monitoring but remains challenging due to particle heterogeneity, high turbidity, and potential loss during sampling and processing. This technical report evaluates the FC1, a closed-system sampler incorporating a passive size-based separation chamber designed for controlled-volume sampling. The device was tested using two matrix groups: (i) controlled water samples spiked with single and mixed polymer microplastics, and (ii) environmentally relevant samples, including wastewater effluent, river water, and lake water under high-turbidity conditions. All validation experiments were conducted using 20 mL sample volumes, within the operational range of the device (20–90 mL). Separation performance was quantified by comparing microplastic concentrations before and after passage through the device, based on three independent replicates using microscopy-based particle counting and size–shape analysis. The FC1 achieved separation efficiencies ranging from 96.0–99.6% in controlled matrices and 91.2–98.3% in environmental samples. These results demonstrate consistent recovery across diverse polymer types and matrix conditions, defining the operational performance range of the system for microplastic separation.
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Improved recovery of sub-millimeter microplastics in simple and complex aqueous matrices using a novel sampling approach
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Improved recovery of sub-millimeter microplastics in simple and complex aqueous matrices using a novel sampling approach
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