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A semi-automated Raman micro-spectroscopy method for morphological and chemical characterizations of microplastic litter
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Researchers developed a semi-automated Raman micro-spectroscopy method coupled with static image analysis for characterizing microplastics, achieving morphological and chemical identification of over 1,000 particles in under three hours, with polyethylene, polystyrene, and polypropylene as the dominant types in the environmental sample.
Every step of microplastic analysis (collection, extraction and characterization) is time-consuming, representing an obstacle to the implementation of large scale monitoring. This study proposes a semi-automated Raman micro-spectroscopy method coupled to static image analysis that allows the screening of a large quantity of microplastic in a time-effective way with minimal machine operator intervention. The method was validated using 103 particles collected at the sea surface spiked with 7 standard plastics: morphological and chemical characterization of particles was performed in <3h. The method was then applied to a larger environmental sample (n=962 particles). The identification rate was 75% and significantly decreased as a function of particle size. Microplastics represented 71% of the identified particles and significant size differences were observed: polystyrene was mainly found in the 2-5mm range (59%), polyethylene in the 1-2mm range (40%) and polypropylene in the 0.335-1mm range (42%).
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