| 长江武汉段沉积物再悬浮过程中PAHs释放的预测模型 |
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| 引用本文： | 冯精兰,祁巧艳,孙剑辉.长江武汉段沉积物再悬浮过程中PAHs释放的预测模型[J].中国环境科学,2011,31(12):2065-2070. |
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| 作者姓名： | 冯精兰 祁巧艳 孙剑辉 |
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| 作者单位： | 1. 河南师范大学化学与环境科学学院,黄淮水环境与污染防治省部共建教育部重点实验室,河南省环境污染控制重点实验室,河南新乡453007;北京师范大学环境学院,水环境模拟国家重点实验室,北京100875
2. 河南师范大学化学与环境科学学院,黄淮水环境与污染防治省部共建教育部重点实验室,河南省环境污染控制重点实验室,河南新乡453007 |
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| 基金项目： | 国家自然科学基金资助项目 |
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| 摘 要： | 为研究长江武汉段沉积物再悬浮过程中多环芳烃的释放,采用回归方法建立了剪应力与再悬浮颗粒物浓度、有机碳含量及PAHs浓度之间的定量关系模型,并结合PAHs在悬浮颗粒物-水体分配系数,建立了不同剪应力条件下再悬浮过程中上覆水体PAHs浓度预测模型,通过模型预测结果与实验结果的比较,表明模型具有良好的预测效果,可用来进行不同剪应力条件下沉积物再悬浮过程PAHs释放的预测.
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| 关 键 词： | 多环芳烃(PAHs) 长江 沉积物再悬浮 释放 预测模型 |
| 收稿时间： | 2011-03-14; |
Predictive model of PAHs release during the resuspension of sediments from Wuhan catchment of Yangtze River. |
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| FENG Jing-lan,QI Qiao-yan,SUN Jian-hui.Predictive model of PAHs release during the resuspension of sediments from Wuhan catchment of Yangtze River.[J].China Environmental Science,2011,31(12):2065-2070. |
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| Authors: | FENG Jing-lan QI Qiao-yan SUN Jian-hui |
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| Institution: | FENG Jing-lan1,2,QI Qiao-yan1,SUN Jian-hui1*(1.Henan Key Laboratory of Environmental Pollution Control,Key Laboratory for Yellow River and Huai Rviver Water Environment and Pollution Control,Ministry of Education,College of Chemistry and Environmental Sciences,Henan Normal University,Xinxiang 453007,China,2.State Key Laboratory of Water Environment Simulation,School of Environment,Beijing Normal University,Beijing 100875,China). |
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| Abstract: | Release of PAHs during the resuspension of sediment samples at Wuhan section of Yangtze River was determined using a particle entrainment simulator(PES).Quantitative relationships between applied shear and TSS concentrations,TOC in TSS,PAHs concentrations in TSS were set up by regression analysis,respectively.Combined these quantitative relationships with PAHs partition coefficients,mathematic models were developed to predict PAHs concentrations in overlying water during sediment resuspension.It was found t... |
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| Keywords: | polycyclic aromatic hydrocarbons Yangtze River release sediment resuspension predictive model |
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