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%). Display omitted •Semi-automated micro-spectroscopy Raman method coupled to static image analysis•Time-effective and reproducible method requiring minimum operator intervention•High particles identification rate (>70%)•Fast morphological and chemical characterization of environmental particles•Efficient method for microplastics monitoring in marine environment