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应用多元统计研究城市河流沉积物孔隙水中DOM紫外光谱特征
引用本文:杨楠,于会彬,宋永会,袁林江,彭剑峰,唐小雨,张晓孟.应用多元统计研究城市河流沉积物孔隙水中DOM紫外光谱特征[J].环境科学学报,2014,34(7):1751-1757.
作者姓名:杨楠  于会彬  宋永会  袁林江  彭剑峰  唐小雨  张晓孟
作者单位:1. 西安建筑科技大学 环境与市政工程学院, 西安 710055;2. 中国环境科学研究院 城市水环境科技创新基地, 北京 100012;中国环境科学研究院 城市水环境科技创新基地, 北京 100012;1. 中国环境科学研究院 城市水环境科技创新基地, 北京 100012;2. 北京师范大学 水科学研究院, 北京 100875;西安建筑科技大学 环境与市政工程学院, 西安 710055;中国环境科学研究院 城市水环境科技创新基地, 北京 100012;1. 中国环境科学研究院 城市水环境科技创新基地, 北京 100012;2. 中国矿业大学(北京) 化学与环境工程学院, 北京 100083;1. 西安建筑科技大学 环境与市政工程学院, 西安 710055;2. 中国环境科学研究院 城市水环境科技创新基地, 北京 100012
基金项目:国家水体污染控制与治理科技重大专项(No.2012ZX07202-005);博士后基金项目(No.2012M510515)
摘    要:应用紫外-可见光吸收光谱研究白塔堡河丰水期沉积物孔隙水中水溶性有机物(DOM)的来源、结构及腐殖化程度.采集白塔堡河干流13个沉积物孔隙水样品,分析DOM紫外光谱特性,推演出9个紫外光谱指数(SUVA254、E2/E4、E4/E6、E2/E3、S275~295、S350~400、A2/A1、A3/A1和A3/A2),研究DOM的组成与结构特征,评价DOM的腐殖化水平.白塔堡河沉积物孔隙水中DOM组成、机构及腐殖化水平呈现沿农村河段向城镇与城市河段递变,农村河段DOM分子量大于城镇与城市河段的,农村河段的DOM分子的聚合度、芳化度、腐殖化水平高于城镇与城市河段的,而DOM中富里酸的含量沿农村河段向城镇与城市河段增加.A2/A1、A3/A1和A3/A2和其它6个指标呈负相关,表明DOM的腐殖化水平随着A2/A1、A3/A1和A3/A2的值增大而升高,而随着其它指标的增大而降低.A2/A1、A3/A1和A3/A2更加精确地评价DOM腐殖化水平,辨识不同采样点DOM腐殖化进程.

关 键 词:水溶性有机物  紫外光谱  空间分布  相关性分析  主成分分析
收稿时间:2013/9/11 0:00:00
修稿时间:2013/10/29 0:00:00

Application of multivariable analysis to study UV-Visble spectra properties of dissolved organic matter from sediment pore water in an urban river
YANG Nan,YU Huibin,SONG Yonghui,YUAN Linjiang,PENG Jianfeng,TANG Xiaoyu and ZHANG Xiaomeng.Application of multivariable analysis to study UV-Visble spectra properties of dissolved organic matter from sediment pore water in an urban river[J].Acta Scientiae Circumstantiae,2014,34(7):1751-1757.
Authors:YANG Nan  YU Huibin  SONG Yonghui  YUAN Linjiang  PENG Jianfeng  TANG Xiaoyu and ZHANG Xiaomeng
Institution:1. School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055;2. Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012;Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012;1. Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012;2. College of Water Science, Beijing Normal University, Beijing 100875;School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055;Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012;1. Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012;2. School of Chemical and Environmental Engineering, China University of Mining and Technology, Beijing 100083;1. School of Environmental and Municipal Engineering, Xi'an University of Architecture and Technology, Xi'an 710055;2. Department of Urban Water Environmental Research, Chinese Research Academy of Environmental Sciences, Beijing 100012
Abstract:UV-Visble spectra were used to analyze structural compositions, identify sources and assess humification level of dissolved organic matter (DOM) extracted from sediment pore water in Baitabuhe River during high-flow period. Thirteen sediment pore water samples were collected from mainstream of the river, and DOM UV spectra of sediment pore water were comprehensively analyzed. Nine indices (SUVA254, E2/E4, E4/E6, E2/E3, S275-295, S350~400, A2/A1, A3/A1 and A3/A2) were deduced. These indices indicated structural compositions and assessed humification level of DOM. Humification level of DOM in the rural region was different from the urban region, and it was obviously higher in the urban region than that in the rural region. A2/A1, A3/A1 and A3/A2 showed negative correlations with other indices, indicating that humification degree increased with increases in A2/A1, A3/A1 and A3/A2 but decreased with increases in other indices. Moreover A2/A1, A3/A1 and A3/A2 were accuracy indices to completely assess humification level of DOM and discriminate humification process of the samples.
Keywords:DOM  UV-Vis spectra  spatial distribution  correlation analysis  principal component analysis
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