Identification of groundwater pollution from livestock farming using fluorescence spectroscopy coupled with multivariate statistical methods
Identification of groundwater pollution from livestock farming using fluorescence spectroscopy coupled with multivariate statistical methods
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荧光光谱结合多元统计方法识别畜牧业地下水污染
DOI：
10.1016/j.watres.2021.117754
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发表时间：
2021
期刊：
影响因子：
12.8
通讯作者：
Zhang Li
中科院分区：
文献类型：
--
作者：
Zhang Yuanzheng;Liu Yunde;Zhou Aiguo;Zhang Li
大规模的畜牧业对地下水水质构成了严重威胁，因此需要一种快速有效的方法来确定这些地区的地下水水质。荧光光谱法已被公认为是一种可解释的方法，用于跟踪水质的人为影响，但其适用于确定地下水污染的畜牧业仍然未知。采用荧光激发发射矩阵（EEM）-平行因子分析（PARAFAC）结合多元统计方法，对典型畜禽养殖区地下水中溶解有机物（DOM）的荧光特征进行了研究。结果表明，畜牧业活动显著改变了地下水中DOM的含量和组成，且这种影响主要表现在研究区浅层地下水中。基于荧光参数的层次聚类分析将地下水样品分为3个污染程度差异显著的聚类：聚类A，未污染;聚类B，高度污染;聚类C，中度污染。特别是，在污染的地下水中，类荧光的强度很高，但在未污染的地下水中几乎检测不到，这表明它是一个潜在的地下水质量指标。基于荧光参数的主成分分析解释了前两个主成分的91.5%的方差，表明污染程度主导了研究区地下水的荧光特征。此外，NO3-在簇B和C中含量丰富，而在簇A中含量较低，验证了荧光光谱分析结果。这些结果表明，DOM荧光对畜禽养殖污染敏感，可用于识别、监测和评价畜禽养殖对地下水的污染。
Extensive livestock farming has highly threatened groundwater quality, thereby necessitating a rapid and effective method to identify groundwater quality in such areas. Fluorescence spectroscopy has been recognized as an interpretable method for tracking anthropogenic influences on water quality, but its applicability in identifying the groundwater pollution from livestock farming remains unknown. In this study, the fluorescence characteristics of dissolved organic matter (DOM) in groundwater from a typical livestock farming area were investigated by using fluorescence excitation emission matrix (EEM)-parallel factor analysis (PARAFAC) coupled with multivariate statistical methods. The results showed that livestock farming significantly altered the content and composition of DOM in groundwater, and these effects were mainly observed in shallow groundwater in the study area. Hierarchical cluster analysis based on fluorescence parameters divided the groundwater samples into three clusters with significantly different pollution degrees: Cluster A, unpolluted; Cluster B, highly polluted; Cluster C, moderately polluted. In particular, the intensity of tryptophan-like fluorescence was high in the polluted groundwater but was almost undetectable in the unpolluted groundwater, suggesting that it is a potential indicator of groundwater quality. Principal component analysis based on the fluorescence parameters explained 91.5% of the variance with the first two principal components, and revealed that the degree of pollution dominated the fluorescence characteristics of groundwater in the study area. In addition, NO3–was abundant in Clusters B and C, while it was low in Cluster A, validating the analysis results of fluorescence spectroscopy. These findings indicated that DOM fluorescence was sensitive to livestock farming pollution and could be applied to identify, monitor, and assess groundwater pollution from livestock farming.