A review of analytical techniques for quantifying microplastics in sediments

Investor logo

Warning

This publication doesn't include Institute of Computer Science. It includes Faculty of Science. Official publication website can be found on muni.cz.
Authors

HANVEY Joanne S. LEWIS Phoebe J. LAVERS Jennifer L. CROSBIE Nicholas D. POZO Karla Andrea CLARKE Bradley O.

Year of publication 2017
Type Article in Periodical
Magazine / Source Analytical Methods
MU Faculty or unit

Faculty of Science

Citation
web http://pubs.rsc.org/en/Content/ArticleLanding/2017/AY/C6AY02707E#!divAbstract
Doi http://dx.doi.org/10.1039/c6ay02707e
Keywords SMALL-PLASTIC DEBRIS; PERSISTENT ORGANIC POLLUTANTS; MARINE-SEDIMENTS; BEACH SEDIMENTS; QUANTITATIVE-ANALYSIS; SPATIAL-DISTRIBUTION; RAMAN-SPECTROSCOPY; MEDITERRANEAN SEA; SYNTHETIC-FIBERS; SANDY BEACHES
Description In this review the analytical techniques for measuring microplastics in sediment have been evaluated. Four primary areas of the analytical process have been identified that include (1) sampling, (2) extraction, (3) quantitation and (4) quality assurance/quality control (QAQC). Each of those sections have their own subject specific challenges and require further method development and harmonisation. The most common approach to extracting microplastics from sediments is density separation. Following extraction, visual counting with an optical microscope is the most common technique for quantifying microplastics; a technique that is labour intensive and prone to human error. Spectroscopy (FTIR; Raman) are the most commonly applied techniques for identifying polymers collected through visual sorting. Improvements and harmonisation on size fractions, sampling approaches, extraction protocols and units for reporting plastic abundance would aid comparison of data generated by different research teams. Further, we advocate the development of strong QAQC procedures to be adopted like other fields of analytical chemistry. Finally, inter-laboratory proficiency testing is recommended to give an indication of the variation and reliability in measurements reported in the scientific literature that may be under- or overestimations of environmental burdens.
Related projects:

You are running an old browser version. We recommend updating your browser to its latest version.

More info