4.8 Article

What You Net Depends on if You Grab: A Meta-analysis of Sampling Method's Impact on Measured Aquatic Microplastic Concentration

Journal

ENVIRONMENTAL SCIENCE & TECHNOLOGY
Volume 55, Issue 19, Pages 12930-12942

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.est.1c03019

Keywords

plastic; pollution; surface water; net; grab; pump; contamination; mesh size

Funding

  1. National Science Foundation Graduate Research Fellowship [2017228528]
  2. NSF MRSEC program [DMR-1719875]

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Different sampling methods result in varying measured microplastic concentrations, with a strong log-linear relationship between sample volume and measured concentration highlighted. Potential biasing factors such as filtration size, net volume overestimation, and contamination were explored and emphasized as important considerations in research.
Microplastic pollution is measured with a variety of sampling methods. Field experiments indicate that commonly used sampling methods, including net, pump, and grab samples, do not always result in equivalent measured concentration. We investigate the comparability of these methods through a meta-analysis of 121 surface water microplastic studies. We find systematic relationships between measured concentration and sampled volume, method of collection, mesh size used for filtration, and waterbody sampled. Most significantly, a strong log-linear relationship exists between sample volume and measured concentration, with small-volume grab samples measuring up to 10(4) particles/L higher concentrations than larger volume net samples, even when sampled concurrently. Potential biasing factors explored included filtration size (+/- 10(2) particles/L), net volume overestimation (+/- 10(1) particles/L), fiber loss through net mesh (unknown magnitude), intersample variability (+/- 10(1) particles/L), and contamination, the potential factor with an effect large enough (+/- 10(3) particles/L) to explain the observed differences. On the basis of these results, we caution against comparing concentrations across multiple studies or combining multiple study results to identify regional patterns. Additionally, we emphasize the importance of contamination reduction and quantification strategies, namely that blank samples from all stages of field sampling be collected and reported as a matter of course for all studies.

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