An innovative approach for microplastic sampling in all surface water bodies using an aquatic drone

Gabriel Pasquier , Périne Doyen (1, 2, 3) , Nicolas Carlesi , Rachid Amara (4, 2)

1 BioEcoAgro - UMR transfrontalière INRAE 1158
2 ULCO - Université du Littoral Côte d'Opale
3 BioEcoAgro - Equipe 8 - Food and Digestive Microbial Ecosystems: Interactions - Dynamics - Application(s)
4 LOG - Laboratoire d’Océanologie et de Géosciences (LOG) - UMR 8187

The lack of one standardized method to evaluate microplastic pollution in different aquatic environments worldwide represent a gap to fill for the scientist's community. To help overcome this challenge, we adapted an aquatic drone, named Jellyfishbot®, to sample microplastics. The aquatic drone has been compared with the actual most used method for sampling MPs in surface waters: the Manta net. In order to test the reliability of the aquatic drone in different environments, samples were collected in a river and coastal waters sites. The results obtained with the two methods were similar in term of MPs abundances, shapes and colors. It provides also a better reproducibility and more accurate sampling of MPs located in the surface waters mainly the lighter and smaller ones. This sampling method has the advantage of combining the benefits of Manta net sampling (i.e. a representative surface water sampling method that covers a large sampling area and volume (several tens m3) with those of pump filtration and grab sampling (easy access to confined and hard-to-reach areas). This new sampling method could be applied in different aquatic environments making it possible to compare the data and hence become a new standardized approach to evaluate microplastic pollution levels.

Mots clés: Microplastics; Sampling; Water; Aquatic drone; Harmonization Methods

Domaines: Sciences du Vivant [q-bio]

Gabriel Pasquier, Périne Doyen, Nicolas Carlesi, Rachid Amara. An innovative approach for microplastic sampling in all surface water bodies using an aquatic drone. Heliyon, 2022, 8 (11), pp.e11662. ⟨10.1016/j.heliyon.2022.e11662⟩. ⟨hal-04049574⟩