Science Inventory

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

Citation:

Thornton Hampton, L., H. De Frond, K. Gesulga, S. Kotar, W. Lao, C. Matuch, S. Weisberg, C. Wong, S. Brander, S. Christiansen, C. Cook, F. Du, S. Ghosal, A. Gray, J. Hankett, P. Helm, K. Ho, T. Kefela, G. Lattin, A. Lusher, L. Mai, R. McNeish, O. Mina, E. Minor, S. Primpke, K. Rickabaugh, V. Renick, S. Singh, B. van Bavel, F. Vollnhals, AND C. Rochman. The influence of complex matrices on method performance in extracting and monitoring for microplastics. CHEMOSPHERE. Elsevier Science Ltd, New York, NY, 334(September 2023):138875, (2023). https://doi.org/10.1016/j.chemosphere.2023.138875

Impact/Purpose:

This article discusses the technical problems associated with microplastic extraction from complex natural matrices. It highlights best practices and the importance of appropriate QA and QC for working with microplastics. It shows the increasing complexity in extracting relatively simple matrices such as water to more complicated sediment matrices and quantifies general percent recoveries that can be expected from each matrix. It also demonstrates the accuracy of instrumental identification, both FTIR and Raman are very effective, and discusses the relatively long process times needed for environmental samples. Finally, the article has suggestions for focusing future research on extraction methods and reducing sample processing times. Overall, this article gives scientists and managers an idea of expectations of recovery a, process time and costs associated with microplastic extraction and identification.

Description:

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.