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荧光光谱结合平行因子分析研究夏季周村水库溶解性有机物的分布与来源 被引量:52

Analysis of Distribution Characteristics and Source of Dissolved Organic Matter from Zhoucun Reservoir in Summer Based on Fluorescence Spectroscopy and PARAFAC
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摘要 利用三维荧光光谱(EEMs)并结合平行因子分析(PARAFAC)模型,解析了2015年8月夏季周村水源水库中溶解性有机物(DOM)的组分并利用主成分分析法对影响水体DOM的主要因素及其相对贡献量进行了研究.结果表明,周村水库水体中的DOM可分为3个组分,分别为类富里酸荧光组分C1(260,350/420 nm)、类蛋白荧光组分C2(280/360 nm)和类腐殖酸组分C3(270,390/530 nm),且3个组分具有同源性;各组分平面分布均匀,入库口总荧光强度略高;较高的荧光指数FI,较高的自生源指标BIX,较低的腐殖化指标HIX以及接近于1的新鲜度指数(β∶α)综合表明夏季周村水库DOM的来源以自生源为主,并结合主成分分析得出,内源对DOM贡献率高达70.96%.与此同时,周村水库水体DOM各组分与aph(440)拟合相关性较好.因此可以通过对DOM三维荧光光谱的研究,有助于水库管理者更有目的地进行污染源的控制和治理,同时可以在一定程度上指示周村水库水体富营养化水平. The fluorescent components were examined using excitation emission matrix fluorescence spectroscopy-parallel factor analysis technique for samples collected in August,2015 from Zhouncun Reservoir. Principal component analysis was used to study the main factors and their relative contributions to DOM. Three fluorescent components were identified by PARAFAC,including fulvic-like component( C1: 260,350 /420 nm),protein-like( C2: 280 /360 nm) and humic-like( C3: 270,390 /530 nm) which showed the same source. The even spatial distribution of each component,higher total fluorescence intensity in storage port,high fluorescence index,high biological index,low humification index and the freshness index which was close to one showed that the DOM had a strong autochthonous contribution. The results of PCA showed that the autochthonous contribution reached 70. 86%, and those three components of Zhoucun Reservoir could be connected with aph( 440) by nonlinear multiple regression which means we can use the three-dimensional fluorescence spectrum results of DOM to control the pollution sources and indicate the eutrophication degree of Zhoucun Reservoir.
出处 《环境科学》 EI CAS CSCD 北大核心 2016年第9期3394-3401,共8页 Environmental Science
基金 国家自然科学基金(51478378) 国家科技支撑计划项目(2012BAC04B02)
关键词 溶解性有机物 平行因子分析(PARAFAC) 周村水库 荧光特性 主成分分析 dissolved organic matter(DOM) PARAFAC Zhoucun Reservoir fluorescence property principal component analysis
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