Beijing General Municipal Engineering Design & Research Institute Co., Ltd., Beijing 100082, China.
State Key Laboratory of Pollution Control and Resource Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China E-mail:
Water Sci Technol. 2022 Jan;85(2):706-718. doi: 10.2166/wst.2022.010.
The three-dimensional fluorescence spectrum has a significantly greater amount of information than the single-stage scanning fluorescence spectrum. At the same time, the parallel factor (PARAFAC) analysis and neural network method can help explore the fluorescence characteristics further, thus could be used to analyse multiple sets of three-dimensional matrix data. In this study, the PARAFAC analysis and the self-organizing mapping (SOM) neural network method are firstly introduced comprehensively. They are then adopted to extract information of the three-dimensional fluorescence spectrum data set for fluorescence characteristics analysis of dissolved organic matter (DOM) in Taihu Lake water. Forty water samples with DOM species were taken from different seasons with the fluorescence information obtained through three-dimensional fluorescence spectrum analysis, PARAFAC analysis and SOM analysis. The PARAFAC analysis results indicated that the main fluorescence components of dissolved organic matter in Taihu Lake water were aromatic proteins, fulvic acids, and dissolved microorganisms. The SOM analysis results showed that the fluorescence characteristics of the dissolved organics in Taihu Lake varied seasonally. Therefore, the combined method of three-dimensional fluorescence spectrum analysis, PARAFAC and SOM analysis can provide important information for characterization of the fluorescence properties of dissolved organic matter in surface water bodies.
三维荧光光谱比单阶段扫描荧光光谱具有更多的信息量。同时，平行因子（PARAFAC）分析和神经网络方法可以帮助进一步探索荧光特性，从而可以用于分析多组三维矩阵数据。在这项研究中，全面介绍了 PARAFAC 分析和自组织映射（SOM）神经网络方法，然后将其用于提取三维荧光光谱数据集的信息，以分析太湖水中溶解有机物（DOM）的荧光特征。从不同季节采集了 40 个具有 DOM 物种的水样，通过三维荧光光谱分析，PARAFAC 分析和 SOM 分析获得了荧光信息。PARAFAC 分析结果表明，太湖水中溶解有机物的主要荧光成分为芳香族蛋白质，腐殖酸和溶解微生物。SOM 分析结果表明，太湖水中溶解有机物的荧光特征具有季节性变化。因此，三维荧光光谱分析，PARAFAC 和 SOM 分析的组合方法可以为地表水溶解有机物的荧光特性描述提供重要信息。
