Selective Imaging of Microplastic and Organic Particles in Flow by Multimodal Coherent Anti-Stokes Raman Scattering and Two-Photon Excited Autofluorescence Analysis
Selective Imaging of Microplastic and Organic Particles in Flow by Multimodal Coherent Anti-Stokes Raman Scattering and Two-Photon Excited Autofluorescence Analysis
复制标题
通过多模态相干反斯托克斯拉曼散射和双光子激发自发荧光分析对流动中的微塑料和有机颗粒进行选择性成像
DOI：
10.1021/acs.analchem.0c05474
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发表时间：
2021
影响因子：
7.4
通讯作者：
Mahajan Sumeet
中科院分区：
文献类型：
--
作者：
Takahashi Tomoko;Herdzik Krzysztof Pawel;Bourdakos Konstantinos Nikolaos;Read James Arthur;Mahajan Sumeet
微塑料污染是一个紧迫的全球性问题。虽然光谱技术已被广泛用于鉴定从水生环境中收集的塑料，但由于样品收集，制备和测量时间长，这些技术通常是劳动密集型和耗时的。基于相干反斯托克斯拉曼散射（汽车）和双光子激发自发荧光（TPEAF）信号的同时检测，提出了一种高时空分辨率的流动塑料微粒和有机生物微粒的二维检测和分类方法。通过汽车线扫描，在平均速度为4.17 mm/s的流动中选择性地检测到尺寸从几十到几百微米的聚甲基丙烯酸甲酯（PMMA）、聚苯乙烯（PS）和低密度聚乙烯（LDPE）颗粒。在相同的流速下，使用汽车和TPEAF信号的多模态系统测量流动的PMMA和PMMA颗粒。在2940 cm-1频率下，汽车信号中PMMA和PMMA颗粒的平均强度均高于背景水平，而只有藻类发出TPEAF信号。这使得PMMA和PMMA颗粒的分类，以成功地进行流动的汽车和TPEAF信号的同时检测。使用所提出的方法，可以在不收集或提取的情况下监测连续水流中的微塑料，这对于目前基于采样的微塑料分析来说是一种改变。
Microplastic pollution is an urgent global issue. While spectroscopic techniques have been widely used for the identification of plastics collected from aquatic environments, these techniques are often labor-intensive and time-consuming due to sample collection, preparation, and long measurement times. In this study, a method for the two-dimensional detection and classification of flowing microplastic and organic biotic particles with high spatial and temporal resolutions has been proposed based on the simultaneous detection of coherent anti-Stokes Raman scattering (CARS) and two-photon excited autofluorescence (TPEAF) signals. Poly(methyl methacrylate) (PMMA), polystyrene (PS), and low-density polyethylene (LDPE) particles with sizes ranging from several tens to hundreds of micrometers were selectively detected in flow with an average velocity of 4.17 mm/s by CARS line scanning. With the same flow velocity, flowing PMMA and alga particles were measured using a multimodal system of CARS and TPEAF signals. The average intensities of both PMMA and alga particles in the CARS signals at a frequency of 2940 cm–1were higher than the background level, while only algae emitted TPEAF signals. This allowed the classification of PMMA and alga particles to be successfully performed in flow by the simultaneous detection of CARS and TPEAF signals. With the proposed method, the monitoring of microplastics in a continuous water flow without collection or extraction is possible, which is game-changing for the current sampling-based microplastic analysis.