Gebejes A, Hrovat B, Semenov D, Kanyathare B, Itkonen T, Keinänen M, Koistinen A, Peiponen K-E, Roussey M
Department of Physics and Mathematics, Center for Photonics Sciences, University of Eastern Finland, P.O. Box 111, 80101 Joensuu, Finland.
Department of Technical Physics, University of Eastern Finland, P.O. Box 1627, 70211 Kuopio, Finland.
Sci Total Environ. 2024 Sep 20;944:173811. doi: 10.1016/j.scitotenv.2024.173811. Epub 2024 Jun 8.
In this article, we demonstrate detection and identification of ten microplastic types directly in a water sample using an identification table derived from microplastic hyperspectral images. We selected a total of fourteen wavelengths which can be used to distinguish these ten microplastic types. We enhanced the visibility of these wavelengths by computationally removing water and baseline correcting with reflectance at 1550 nm. This method avoids, prevents, and eases most of the laborious sample preparation mandatory prior to analysis with robust techniques such as Raman spectroscopy and Fourier transform infrared spectroscopy. The ten different plastics were studied in water, first separately and then in a mixture. The microplastic concentrations varied depending on microplastic type and were kept <12 mg/ml per type. Finally, detection and identification were confirmed pixel-wise in a hyperspectral image of a realistic water matrix simulant including mixtures of only a few microplastic particles. All measurements have been performed with microplastics of different sizes and irregular shapes made in-house by milling commercial pellets and sheets. It enabled the establishment of a procedure for the identification of these vicious particles in real water samples. The present measurement setup of hyperspectral imaging and method of data analysis of a mixture of microplastics directly from a water-based sample may open a path towards fast, reliable, and on-site detection.
在本文中，我们展示了使用从微塑料高光谱图像得出的识别表直接在水样中检测和识别十种微塑料类型的方法。我们总共选择了14个波长，可用于区分这十种微塑料类型。通过计算去除水并以1550 nm处的反射率进行基线校正，增强了这些波长的可见性。该方法避免、防止并简化了使用拉曼光谱和傅里叶变换红外光谱等强大技术进行分析之前所需的大部分繁琐样品制备工作。对十种不同的塑料在水中进行了研究，首先是单独研究，然后是混合研究。微塑料浓度因微塑料类型而异，每种类型均保持在<12 mg/ml。最后，在包含仅少量微塑料颗粒混合物的真实水基质模拟物的高光谱图像中逐像素确认了检测和识别。所有测量均使用通过研磨商业颗粒和片材在内部制成的不同尺寸和不规则形状的微塑料进行。它使得能够建立一种在实际水样中识别这些有害颗粒的程序。当前的高光谱成像测量设置以及直接从水基样品中分析微塑料混合物的数据分析方法可能会开辟一条通往快速、可靠和现场检测的道路。
