Avoiding and reducing microplastic false positives from dry glove contact

Abstract

To attenuate microplastics pollution, we first must quantify the number and types of microplastics found in the natural environment and identify their sources. Quantifying environmental microplastics requires distinguishing synthetic polymers from other naturally occurring species. Quality assurance and control measures – including wearing gloves when handling laboratory materials and samples – seek to reduce overestimating microplastic abundance. However, commonly used laboratory gloves release non-volatile residues, including stearate salts, that exhibit vibrational spectra similar to microplastics. In this work, we illustrate that dry surface contact with nitrile and latex laboratory gloves can cause overestimations of microplastics (mean 2000 false positives per mm2) when using traditional library matching approaches. We recommend a nitrile cleanroom glove (mean 100 false positives per mm2) to reduce contamination. For existing contaminated infrared and Raman spectral datasets, we outline workflows that differentiate between microplastics and stearate contamination from gloves. Applying these workflows to a case study of glove-contaminated environmental data, we illustrate that the proposed solutions reduce MP false positives at the smallest size ranges (<10 µm). By using this approach in conjunction with our included spectral libraries of stearate standards, researchers can address glove-based contamination in environmental datasets and provide more accurate estimates of environmental microplastic abundance.

Graphical abstract: Avoiding and reducing microplastic false positives from dry glove contact

Supplementary files

Article information

Article type
Paper
Submitted
29 Oct 2025
Accepted
11 Mar 2026
First published
26 Mar 2026
This article is Open Access
Creative Commons BY-NC license

Anal. Methods, 2026, Advance Article

Avoiding and reducing microplastic false positives from dry glove contact

M. E. Clough, E. Ochoa Rivera, A. M. Ayala, R. L. Parham, J. Pennacchio, H. E. Thurber, A. P. Ault, A. Tewari and A. J. McNeil, Anal. Methods, 2026, Advance Article , DOI: 10.1039/D5AY01801C

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