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Marine Microplastic Classification by Hyperspectral Imaging: Case Studies from the Mediterranean Sea, the Strait of Gibraltar, the Western Atlantic Ocean and the Bay of Biscay
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Using advanced hyperspectral imaging across water samples from four ocean regions, researchers characterized the polymer types and physical dimensions of collected microplastics, finding polyethylene, polypropylene, polystyrene, and expanded polystyrene as the most common materials. Hyperspectral imaging can analyze many particles quickly and simultaneously capture morphological data, making it a powerful tool for large-scale environmental monitoring programs.
In this work, a comprehensive characterization of microplastic samples collected from unique geographical locations, including the Mediterranean Sea, Strait of Gibraltar, Western Atlantic Ocean and Bay of Biscay utilizing advanced hyperspectral imaging (HSI) techniques working in the short-wave infrared range (1000–2500 nm) is presented. More in detail, an ad hoc hierarchical classification approach was developed and applied to optimize the identification of polymers. Morphological and morphometrical attributes of microplastic particles were simultaneously measured by digital image processing. Results showed that the collected microplastics are mainly composed, in decreasing order of abundance, by polyethylene (PE), polypropylene (PP), polystyrene (PS) and expanded polystyrene (EPS), in agreement with the literature data related to marine microplastics. The investigated microplastics belong to the fragments (86.8%), lines (9.2%) and films (4.0%) categories. Rigid (thick-walled) fragments were found at all sampling sites, while film-type microplastics and lines were absent in some samples from the Mediterranean Sea and the Western Atlantic Ocean. Rigid fragments and lines are mainly made of PE, whereas PP is the most common polymer for the film category. Average Feret diameter of microplastic fragments decreases from EPS (3–4 mm) to PE (2–3 mm) and PP (1–2 mm). The setup strategies illustrate that the HSI-based approach enables the classification of the polymers constituting microplastic particles and, at the same time, to measure and classify them by shape. Such multiple characterization of microplastic samples at the individual level is proposed as a useful tool to explore the environmental selection of microplastic features (i.e., composition, category, size, shape) and to advance the understanding of the role of weathering, hydrodynamic and other phenomena in their transport and fragmentation.
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