Agricultural and Biological Sciences: Aquatic Science
; Earth and Planetary Sciences: Oceanography
; Environmental Science: Pollution
英文摘要:
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 <�3�h. 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 2–5�mm range (59%), polyethylene in the 1–2�mm range (40%) and polypropylene in the 0.335–1�mm range (42%). � 2016 Elsevier Ltd
Laboratoire des Sciences de l'Environnement Marin (LEMAR), UMR 6539. CNRS/UBO/IRD/Ifremer, Institut Universitaire Europ�en de la Mer, Plouzan�, France; Ifremer, Laboratoire D�tection, Capteurs et Mesures, CS 10070, Plouzan�, France; Ifremer, LEMAR UMR 6539 CNRS/UBO/IRD/Ifremer, CS 10070, Plouzan�, France
Recommended Citation:
Fr�re L.,Paul-Pont I.,Moreau J.,et al. A semi-automated Raman micro-spectroscopy method for morphological and chemical characterizations of microplastic litter[J]. Marine Pollution Bulletin,2016-01-01,113(2018-01-02)