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利用高光谱成像技术对意大利波河淡水中微塑料的分类与分布研究。

Classification and distribution of freshwater microplastics along the Italian Po river by hyperspectral imaging.

机构信息

Department of Chemical Engineering, Materials & Environment, Sapienza University of Rome, Via Eudossiana 18, 00184, Rome, Italy.

ARPAE, Regional Agency for Environmental Prevention and Energy of Emilia-Romagna, Oceanographic Unit Daphne - V. le Vespucci 2, 47042, Cesenatico, FC, Italy.

出版信息

Environ Sci Pollut Res Int. 2022 Jul;29(32):48588-48606. doi: 10.1007/s11356-022-18501-x. Epub 2022 Feb 23.

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/m, 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.

摘要

在这项工作中,对从意大利波河的四个不同站点采集的淡水微塑料样本进行了特征描述,包括丰度、分布、类别、形态和形态特征以及聚合物类型。还评估了微塑料类别和聚合物类型之间的相关性。聚合物鉴定是通过开发和实施一种新的、有效的分层分类逻辑来实现的,该逻辑应用于短波长红外范围(SWIR:1000-2500nm)获得的高光谱图像。结果表明,微塑料的浓度范围为 1.89 至 8.22 个/立方米,最丰富的类别是碎片,其次是泡沫、颗粒、颗粒、长丝,最广泛分布的聚合物是膨胀聚苯乙烯,其次是聚乙烯、聚丙烯、聚苯乙烯、聚酰胺、聚对苯二甲酸乙二醇酯和聚氯乙烯,不同站点之间的聚合物分布存在一些差异。高光谱成像(HSI)作为一种快速、非破坏性的方法来对环境监测中的淡水微塑料进行分类,代表了该领域的一种全新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6578/9252960/fa474d7eeaaf/11356_2022_18501_Fig1_HTML.jpg

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