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采用傅里叶变换红外光谱和拉曼光谱联用技术分析商业上重要贻贝中宽范围粒径的微塑料。

Analysis of microplastics of a broad size range in commercially important mussels by combining FTIR and Raman spectroscopy approaches.

机构信息

Animal Ecology I and BayCEER, University of Bayreuth, Universitätsstrasse 30, 95440, Bayreuth, Germany.

Animal Ecology I and BayCEER, University of Bayreuth, Universitätsstrasse 30, 95440, Bayreuth, Germany.

出版信息

Environ Pollut. 2021 Jan 15;269:116147. doi: 10.1016/j.envpol.2020.116147. Epub 2020 Nov 24.

Abstract

Microplastic (MP) contamination is present in the entire marine environment from the sediment to the water surface and down to the deep sea. This ubiquitous presence of MP particles opens the possibility for their ingestion by nearly all species in the marine ecosystem. Reports have shown that MP particles are present in local commercial seafood species leading to the possible human ingestion of these particles. However, due to a lack of harmonized methods to identify microplastics (MPs), results from different studies and locations can hardly be compared. Hence, this study was aimed to detect, quantify, and estimate MP contamination in commercially important mussels originating from 12 different countries distributed worldwide. All mussels were obtained from supermarkets and were intended for human consumption. Using a combinatorial approach of focal plane array (FPA)-based micro- Fourier-transform infrared (FTIR) spectroscopy and micro-Raman spectroscopy allowed the detection and characterization of MP down to a size of 3 μm in the investigated mussels. Further, a gentle sample purification method based on enzymes has been modified in order to optimize the digestion of organic material in mussels. A random forest classification (RFC) approach, which allows a rapid discrimination between different polymer types and thus fast generation of data on MP abundance and size distributions with high accuracy, was implemented in the analytical pipeline for IR spectra. Additionally, for the first time we also applied a RFC approach for the automated characterization of Raman spectra of MPs.

摘要

微塑料(MP)污染存在于海洋环境的各个部分,从沉积物到水面,再到深海。这些无处不在的 MP 颗粒为它们被海洋生态系统中的几乎所有物种摄入提供了可能性。报告显示,MP 颗粒存在于当地商业海鲜物种中,可能导致人类摄入这些颗粒。然而,由于缺乏识别微塑料(MPs)的统一方法,不同研究和地点的结果几乎无法进行比较。因此,本研究旨在检测、定量和估计来自全球 12 个不同国家的商业上重要的贻贝中的 MP 污染。所有贻贝均来自超市,供人类食用。使用基于焦平面阵列(FPA)的微傅里叶变换红外(FTIR)光谱和微拉曼光谱的组合方法,可以检测和表征在所研究的贻贝中尺寸低至 3μm 的 MP。此外,为了优化贻贝中有机物质的消化,对基于酶的温和样品纯化方法进行了修改。随机森林分类(RFC)方法允许快速区分不同的聚合物类型,从而快速生成具有高精度的 MP 丰度和尺寸分布数据。此外,我们还首次将 RFC 方法应用于 MPs 的拉曼光谱的自动特征描述。

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