@article{frere_semi-automated_2016,
	title = {A semi-automated {Raman} micro-spectroscopy method for morphological and chemical characterizations of microplastic litter},
	volume = {113},
	issn = {0025-326X},
	url = {http://www.sciencedirect.com/science/article/pii/S0025326X16308682},
	doi = {10.1016/j.marpolbul.2016.10.051},
	abstract = {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\%).},
	number = {1–2},
	urldate = {2017-01-02TZ},
	journal = {Marine Pollution Bulletin},
	author = {Frère, L. and Paul-Pont, I. and Moreau, J. and Soudant, P. and Lambert, C. and Huvet, A. and Rinnert, E.},
	year = {2016},
	note = {00000},
	keywords = {ACL, Automating, Environmental monitoring, Microplastics, Morphology, Raman micro-spectroscopy, Surface seawater, panorama},
	pages = {461--468}
}

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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%).","number":"1–2","urldate":"2017-01-02TZ","journal":"Marine Pollution Bulletin","author":[{"propositions":[],"lastnames":["Frère"],"firstnames":["L."],"suffixes":[]},{"propositions":[],"lastnames":["Paul-Pont"],"firstnames":["I."],"suffixes":[]},{"propositions":[],"lastnames":["Moreau"],"firstnames":["J."],"suffixes":[]},{"propositions":[],"lastnames":["Soudant"],"firstnames":["P."],"suffixes":[]},{"propositions":[],"lastnames":["Lambert"],"firstnames":["C."],"suffixes":[]},{"propositions":[],"lastnames":["Huvet"],"firstnames":["A."],"suffixes":[]},{"propositions":[],"lastnames":["Rinnert"],"firstnames":["E."],"suffixes":[]}],"year":"2016","note":"00000","keywords":"ACL, Automating, Environmental monitoring, Microplastics, Morphology, Raman micro-spectroscopy, Surface seawater, panorama","pages":"461--468","bibtex":"@article{frere_semi-automated_2016,\n\ttitle = {A semi-automated {Raman} micro-spectroscopy method for morphological and chemical characterizations of microplastic litter},\n\tvolume = {113},\n\tissn = {0025-326X},\n\turl = {http://www.sciencedirect.com/science/article/pii/S0025326X16308682},\n\tdoi = {10.1016/j.marpolbul.2016.10.051},\n\tabstract = {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\\%).},\n\tnumber = {1–2},\n\turldate = {2017-01-02TZ},\n\tjournal = {Marine Pollution Bulletin},\n\tauthor = {Frère, L. and Paul-Pont, I. and Moreau, J. and Soudant, P. and Lambert, C. and Huvet, A. and Rinnert, E.},\n\tyear = {2016},\n\tnote = {00000},\n\tkeywords = {ACL, Automating, Environmental monitoring, Microplastics, Morphology, Raman micro-spectroscopy, Surface seawater, panorama},\n\tpages = {461--468}\n}\n\n","author_short":["Frère, L.","Paul-Pont, I.","Moreau, J.","Soudant, P.","Lambert, C.","Huvet, A.","Rinnert, E."],"key":"frere_semi-automated_2016","id":"frere_semi-automated_2016","bibbaseid":"frre-paulpont-moreau-soudant-lambert-huvet-rinnert-asemiautomatedramanmicrospectroscopymethodformorphologicalandchemicalcharacterizationsofmicroplasticlitter-2016","role":"author","urls":{"Paper":"http://www.sciencedirect.com/science/article/pii/S0025326X16308682"},"keyword":["ACL","Automating","Environmental monitoring","Microplastics","Morphology","Raman micro-spectroscopy","Surface seawater","panorama"],"downloads":0,"html":""},"search_terms":["semi","automated","raman","micro","spectroscopy","method","morphological","chemical","characterizations","microplastic","litter","frère","paul-pont","moreau","soudant","lambert","huvet","rinnert"],"keywords":["acl","automating","environmental monitoring","microplastics","morphology","raman micro-spectroscopy","surface seawater","panorama"],"authorIDs":[],"dataSources":["SawGM9CiMpS8S2icT"]}