Materials (Apr 2024)

Assessing Microplastics and Nanoparticles in the Surface Seawater of Venice Lagoon—Part I: Methodology of Research

  • Teresa Cecchi,
  • Davide Poletto,
  • Andrei Constantin Berbecaru,
  • Elfrida Mihaela Cârstea,
  • Maria Râpă

DOI
https://doi.org/10.3390/ma17081759
Journal volume & issue
Vol. 17, no. 8
p. 1759

Abstract

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Microplastics (MPs) and nanoplastics (NPs) both represent significant concerns in environmental sciences. This paper aims to develop a convenient and efficient methodology for the detection and measurement of MPs and nanoparticles from surface seawater and to apply it to the water samples collected from the UNESCO site of Venice and its lagoon, more precisely in the Venice-Lido Port Inlet, Grand Canal under Rialto Bridge, and Saint Marc basin. In this study, MPs were analyzed through optical microscopy for their relative abundance and characterized based on their color, shape, and size classes, while the concentration and the mean of nanoparticles were estimated via the Nanoparticle Tracking Analysis technique. Bulk seawater sampling, combined with filtration through a cascade of stainless-steel sieves and subsequent digestion, facilitates the detection of MPs of relatively small sizes (size classes distribution: >1 mm, 1000–250 μm, 250–125 μm, 125–90 μm, and 90–32 μm), similar to the size of MPs ingested by marine invertebrates and fishes. A protocol for minimizing interference from non-plastic nanoparticles through evaporation, digestion, and filtration processes was proposed to enrich the sample for NPs. The findings contribute to the understanding of the extent and characteristics of MPs and nanoparticle pollution in the Venice Lagoon seawater, highlighting the potential environmental risks associated with these pollutants and the need for coordinated approaches to mitigate them. This article is based on scientific research carried out within the framework of the H2020 In-No-Plastic—Innovative approaches towards prevention, removal and reuse of marine plastic litter project (G.A. ID no. 101000612).

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