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从富含有机物的沉积物中鉴定和量化微塑料:经过验证的实验室方案。

Microplastic identification and quantification from organic rich sediments: A validated laboratory protocol.

机构信息

Laboratory for Coastal Ecology and Conservation, Faculty of Agriculture and Marine Science, Kochi University, Japan; Dept. Environmental Science, Faculty of Science, Radboud University, The Netherlands.

Laboratory for Coastal Ecology and Conservation, Faculty of Agriculture and Marine Science, Kochi University, Japan; Dept. Environmental Science, Faculty of Science, Radboud University, The Netherlands.

出版信息

Environ Pollut. 2020 Jul;262:114298. doi: 10.1016/j.envpol.2020.114298. Epub 2020 Feb 29.

Abstract

Plastic pollution presents a global environmental concern with potentially widespread ecological, socio-economic and health implications. Methodological advances in microplastic extraction, quantification and identification from sediments have been made. However, integrating these fragmentary advances into a holistic, cost-effective protocol and applying it to organic rich sediments with fine grain size remains a challenge. Nonetheless, many hot spots of microplastic contamination such as harbour and estuarine sediments are characterised by such sediments. We conducted a series of experiments to integrate methodological advances, and clarify their applicability to organic rich sediments with fine grain size. The resulting protocol consisted of three stages. First, pre-treatment with Fenton's reagent was found to be efficient in reducing organic matter content, compatible with later Fourier Transform-Infrared Spectroscopy (FT-IR) for polymer identification, although it did affect the size of polyethylene (PE) and polyethylene terephthalate (PET). Secondly, a novel density separation column with a top overflow (the OC-T) obtained recovery rates above 90% for microplastics present in a ZnCL solution. Finally, automated epifluorescence microscopic image analysis of Nile Red stained filters with selected validation of polymer identities using FT-IR revealed 91.7% of stained particles to be plastics. A case study on estuarine sediments demonstrated a high extraction efficiency with quantification possible down to 125 μm and detection possible down to 62.5 μm. This makes this protocol suitable for large scale monitoring of microplastics in sediments of estuarine origin provided polymer specific recovery rates, background contamination and uncertainty in Nile Red identification is accounted for. Subject to further validation, the protocol could also offer a solution to similar organic rich sediments with fine grain size, such as some soils and sludge, to improve our ability to conduct cost-effective, large scale monitoring of microplastic contamination.

摘要

塑料污染是一个全球性的环境问题,可能会对生态、社会经济和健康产生广泛影响。在从沉积物中提取、定量和识别微塑料方面已经取得了方法学上的进展。然而,将这些零碎的进展整合到一个整体的、具有成本效益的方案中,并将其应用于富含有机物且粒度较小的沉积物仍然是一个挑战。尽管如此,许多微塑料污染热点,如港口和河口沉积物,都具有这样的沉积物特征。我们进行了一系列实验,将方法学上的进展整合起来,并澄清它们在富含有机物且粒度较小的沉积物中的适用性。最终的方案包括三个阶段。首先,发现芬顿试剂预处理在降低有机物含量方面非常有效,与后来用于聚合物识别的傅里叶变换红外光谱(FT-IR)兼容,尽管它确实会影响聚乙烯(PE)和聚对苯二甲酸乙二醇酯(PET)的大小。其次,一种新型带有顶部溢流的密度分离柱(OC-T)在 ZnCL 溶液中获得了超过 90%的微塑料回收率。最后,使用 FT-IR 对尼罗红染色滤膜进行自动荧光显微镜图像分析,并对聚合物身份进行了选择性验证,结果显示 91.7%的染色颗粒为塑料。对河口沉积物的案例研究表明,该方案具有很高的提取效率,可定量检测到 125μm 以下的微塑料,检测到 62.5μm 以下的微塑料。这使得该方案适用于对具有河口来源的沉积物中的微塑料进行大规模监测,前提是考虑到聚合物特定的回收率、背景污染和尼罗红识别的不确定性。在进一步验证的前提下,该方案也可能为其他富含有机物且粒度较小的沉积物,如某些土壤和污泥,提供解决方案,以提高我们进行具有成本效益的大规模微塑料污染监测的能力。

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