taihu lake
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2022 ◽  
Vol 204 ◽  
pp. 111940
Author(s):  
Hao Lu ◽  
Liuyan Yang ◽  
Yifan Fan ◽  
Xin Qian ◽  
Tong Liu

2022 ◽  
Vol 113 ◽  
pp. 1-11
Author(s):  
Jiabao Li ◽  
Haifeng Zhang ◽  
Juan Wang ◽  
Zhiyong Yu ◽  
Hongyan Li ◽  
...  

Author(s):  
W. Zhang ◽  
T. Li ◽  
B. Dong

Abstract The three-dimensional fluorescence spectrum has a significant 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 the 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. While the SOM analysis results exhibited that the fluorescence characteristics of the dissolved organics in Taihu Lake varied seasonally. Therefore, the combined method of the three-dimensional fluorescence spectrum analysis, PARAFAC and SOM analysis can provide important information for the characterization of the fluorescence properties of dissolved organic matter in surface water bodies.


2021 ◽  
Author(s):  
Xiaobo Liu ◽  
Congtian Lin ◽  
Yangyu Wu ◽  
Haining Huang ◽  
Liting Zhu ◽  
...  

Abstract The ecological risks and health hazards of heavy metals pollution in Taihu Lake have received widespread concern. This study has developed a nationwide dataset on pollutant loads in species, and the dataset records 55,297 data from 310 articles, covering 778 species and 537 pollutants. In this paper, we extract and systematically integrate data on heavy metals concentrations in Taihu fish from the dataset. The Pi (single pollution index) and MPI (metal pollution index) models were used to assess the level of contamination in fish and the THQ (target hazard quotient) and ILCR (incremental lifetime cancer risk) models were used to assess the health hazards of fish consumption. The contamination levels varied in a feeding habit and living habit dependent manner. The risk of non-cancer health is the highest in omnivorous fish, then in carnivorous fish and herbivorous fish. ILCR model predicted that the values of As and Cd in omnivorous fish for children exceeded the risk threshold limits set by the EPA, and the ILCR values of As in omnivorous fish and Cd in carnivorous fish for adults also exceeded the risk threshold limits. In all, this study provided a comprehensive understanding of the risk of heavy metals in Taihu.


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