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The influence of complex matrices on method performance in extracting and monitoring for microplastics

Academic article
Year of publication
2023
Journal
Chemosphere
External websites
Cristin
Doi
Contributors
Leah M. Thornton Hampton, Hannah De Frond, Kristine Gesulga, Syd Kotar, Wenjian Lao, Cindy Matuch, Stephen B. Weisberg, Charles S. Wong, Susanne Brander, Silke Christansen, Cayla R. Cook, Fangni Du, Sutapa Ghosal, Andrew B. Gray, Jeanne Hankett, Paul A. Helm, Kay T. Ho, Timnit Kefela, Gwendolyn Lattin, Amy Lorraine Lusher, Lei Mai, Rachel E. McNeish, Odette Mina, Elizabeth C. Minor, Sebastian Primpke, Keith Rickabaugh, Violet C. Renick, Samiksha Singh, Bert van Bavel, Florian Vollnhals, Chelsea M. Rochman

Summary

Previous studies have evaluated method performance for quantifying and characterizing microplastics in clean water, but little is known about the efficacy of procedures used to extract microplastics from complex matrices. Here we provided 15 laboratories with samples representing four matrices (i.e., drinking water, fish tissue, sediment, and surface water) each spiked with a known number of microplastic particles spanning a variety of polymers, morphologies, colors, and sizes. Percent recovery (i.e., accuracy) in complex matrices was particle size dependent, with ∼60–70% recovery for particles >212 μm, but as little as 2% recovery for particles <20 μm. Extraction from sediment was most problematic, with recoveries reduced by at least one-third relative to drinking water. Though accuracy was low, the extraction procedures had no observed effect on precision or chemical identification using spectroscopy. Extraction procedures greatly increased sample processing times for all matrices with the extraction of sediment, tissue, and surface water taking approximately 16, 9, and 4 times longer than drinking water, respectively. Overall, our findings indicate that increasing accuracy and reducing sample processing times present the greatest opportunities for method improvement rather than particle identification and characterization.