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Novel feature extraction method for rapid analysis of water contaminants based on three-dimensional fluorescence and absorption spectroscopy

机译:基于三维荧光和吸收光谱的水污染物快速特征提取新方法

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Fluorescence spectroscopy and absorption spectroscopy are common physical methods used for water quality monitoring and analysis. However, in terms of sensitivity and selectivity, the absorption spectroscopy is still inferior; limited categories of organic contaminants can emit fluorescence, which constrains the analytical range. Here in, a novel feature extraction method is proposed in conjoint analysis of fluorescence and absorption spectroscopy to predict the category of water contaminants. The three-dimensional fluorescence spectra and absorption spectra of eight typical substances were studied. We extracted the outline of every three-dimensional fluorescence spectrum along the emission wavelengths axis, and then transformed it into a wavenumber spectrum. The symmetry axis and Stokes shift between fluorescence emission peak and absorption peak in their wavenumber spectra were set as two features. Theoretically, they depend only on the molecular structures of different substances. Moreover, four integral parameters in different absorption spectral ranges corresponding to functional groups were introduced to expand the analytical coverage of diverse contaminants including some non-fluorescent substances. Furthermore, we conducted long-term monitoring of river water near a dyeing and printing plant to demonstrate the prediction potential of this method. As an early warning system, the rapid prediction results can provide guidance for more targeted and detailed analysis and treatment.
机译:荧光光谱法和吸收光谱法是用于水质监测和分析的常用物理方法。但是,就灵敏度和选择性而言,吸收光谱仍然不佳。有限种类的有机污染物会发出荧光,从而限制了分析范围。在此,在荧光和吸收光谱的联合分析中提出了一种新颖的特征提取方法,以预测水污染物的类别。研究了八种典型物质的三维荧光光谱和吸收光谱。我们沿发射波长轴提取每个三维荧光光谱的轮廓,然后将其转换为波数光谱。将波数谱中的荧光发射峰和吸收峰之间的对称轴和斯托克斯位移设置为两个特征。从理论上讲,它们仅取决于不同物质的分子结构。此外,引入了与官能团相对应的不同吸收光谱范围内的四个积分参数,以扩大包括某些非荧光物质在内的多种污染物的分析范围。此外,我们对染色厂附近的河水进行了长期监测,以证明该方法的预测潜力。作为预警系统,快速预测结果可以为更有针对性和更详细的分析和处理提供指导。

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