Organic matter digestion methods for microplastic extraction from estuarine samplings

, Fertala Laila, Palazot Maialen, Soccalingame Lata, Kedzierski Mikaël, Bruzaud Stéphane.

Microplastics (MP) in the marine ecosystems is a global pollution of increasing scientific and societal concern. With the majority of plastics found in these ecosystems coming from land-based sources [1], through rivers and run-off, studies on MP has recently shifted focus toward freshwater ecosystems. The Tara Microplastics 2019 expedition collected samples from 9 of the main European rivers and revealed the presence of plastic particles in all the sampled sites. However, the samples contain a high amount of complex organic matter, hindering the characterization of MP. Therefore, developing methods to accurately and safely extract microplastics from field-collected waters is a key element to assess this pollution. Since literature varies greatly in the optimum method, there is a clear need for the development of a standardized, robust and efficient protocol. Standardizing a protocol will not only allow for efficient sample processing, but also promote consistency in data collection and analysis, and increase comparability between studies. In this work, two digestion protocols using hydrogen peroxide (H2O2)were tested. Protocol A combined H2O2 with an iron catalyst for a more advanced oxidation reaction known as the Fenton's reagent [2]. Protocol B consisted in two successive steps: first, a potassium hydroxide (KOH) treatment then a H2O2 digestion. Both protocols were completed with a density separation step to remove inorganic matter. Both protocols have shown to maintain MP physical integrity, allowed a clear polymer identification by infrared spectroscopy, and resulted in similar and high organic matter removal rates. Taking in consideration these results and the need to efficiently process a large set of samples, a new protocol is suggested combining those two methods, to be applied separately according to the nature of matter present within each sample.

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