Abstract
In this work, freshwater microplastic samples collected from four different stations along the Italian Po river were characterized in terms of abundance, distribution, category, morphological and morphometrical features, and polymer type. The correlation between microplastic category and polymer type was also evaluated. Polymer identification was carried out developing and implementing a new and effective hierarchical classification logic applied to hyperspectral images acquired in the short-wave infrared range (SWIR: 1000–2500 nm). Results showed that concentration of microplastics ranged from 1.89 to 8.22 particles/m3, the most abundant category was fragment, followed by foam, granule, pellet, and filament and the most diffused polymers were expanded polystyrene followed by polyethylene, polypropylene, polystyrene, polyamide, polyethylene terephthalate and polyvinyl chloride, with some differences in polymer distribution among stations. The application of hyperspectral imaging (HSI) as a rapid and non-destructive method to classify freshwater microplastics for environmental monitoring represents a completely innovative approach in this field.
Highlights
Microplastic particles were first found on the sea surface as early as the 1970s (Carpenter and Smith 1972) and the accumulation of plastic waste in both aquatic and terrestrial ecosystems has become nowadays one of the main environmental emergencies, considering that every year around 8 million tons of plastic end up in the ocean (Jambeck et al 2015).To face this problem, it is first necessary to identify and quantify abundances, sources and pathways of microplastics (Werner et al 2017)
Concerning the possible sources of microplastics, fragment, foam and granule microplastic categories, being of secondary origin, indicate their fragmentation from larger items probably started in land environment and their transportation by surface runoff
Freshwater microplastics collected along the Italian Po river were characterized by developing and implementing a hierarchical partial least squares-discriminant analysis (PLS-DA) classification model applied to hyperspectral images acquired in the short-wave infrared range (SWIR) range
Summary
Microplastic particles were first found on the sea surface as early as the 1970s (Carpenter and Smith 1972) and the accumulation of plastic waste in both aquatic and terrestrial ecosystems has become nowadays one of the main environmental emergencies, considering that every year around 8 million tons of plastic end up in the ocean (Jambeck et al 2015). To face this problem, it is first necessary to identify and quantify abundances, sources and pathways of microplastics (Werner et al 2017). According to Koelmans et al (2019) the most frequent categories of microplastics detected in freshwaters from many sites around the world are, in descending order, fragment, fiber, film, foam and pellet
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
