Please use this identifier to cite or link to this item: https://www.um.edu.mt/library/oar/handle/123456789/54031
Title: Automating the characterisation of beach microplastics through the application of image analyses
Authors: Gauci, Adam
Deidun, Alan
Montebello, John
Abela, John
Galgani, Francois G.
Keywords: Image processing -- Data processing
Microplastics -- Analysis
Marine debris
Issue Date: 2019
Publisher: Elsevier Ltd.
Citation: Gauci, A., Deidun, A., Montebello, J., Abela, J., & Galgani, F. (2019). Automating the characterisation of beach microplastics through the application of image analyses. Ocean & Coastal Management, 182, 104950
Abstract: Four sandy beaches on the island of Malta in the Central Mediterranean were regularly sampled for Large MicroPlastic (LMP) particles having a diameter between 1 mm and 5 mm, at stations located at the waterline and 10 m inshore. The 10975 extracted LMP particles were characterised (dimensions, surface roughness, colour) through unaided visual observation, microscopic analyses, and an algorithm developed within the current study. Two-thirds of the isolated particles were smooth and the majority of these belonged to the grey-white colour category, with a low degree of opaqueness and discolouration, and a high degree of transparency, suggesting that these were dominated by low-density polyethylene LMPs. Conflicting evidence concerning the relative residence time of the isolated LMPs within seawater emerged from the colour and contour roughness determination, although an abundance of primary LMPs (production pellets) within our sample might have been responsible for the low contour roughness results obtained. Roughly six times as many particles were recorded within the inshore sampling stations as the particles recorded at the waterline stations. The developed algorithm performed very well when the dimension and colour parameter values it delivered were compared with those obtained by microscopic analyses.
URI: https://www.um.edu.mt/library/oar/handle/123456789/54031
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