土壤电荷对离子有效淌度的影响研究
发布时间：2019-05-28 05:45
【摘要】：随着工业的发展,土壤重金属污染问题日益严重,其主要修复技术有:化学稳定/固化、化学还原、生物修复、淋洗、电动修复等。其中电动修复技术作为一个新兴的土壤原位修复技术受到国内外研究者们的广泛关注。但在修复的过程中,会受到各种因素的影响,如土壤和污染物的特性、电压梯度、吸附/解吸机制、聚焦现象、工作液性质、温度、含水率等。这些因素都有可能决定着电动修复的效率和修复时间,而数值模拟可以综合考虑多方面的影响因素,从而优化电动修复过程,为实际工程提供了有利的预测。国内外研究者们已经建立了很多数学模型来预测电动修复过程中污染物的迁移,这些模型结果与实验结果拟合很好,但仅限于对单一的污染物进行数值模拟。有些模型虽然同时对两、三种离子进行模拟,但与实验结果的拟合难以令人满意。现有电动修复数值模拟中,离子在土壤中的淌度通常用无限稀释溶液下的离子淌度乘以土壤有效淌度系数k进行估算,而k值通常又由土壤孔隙度n和扭曲度τ估算而得,与离子特征及其与土壤颗粒之间的相互作用无关。本课题将通过直接测量分别在三个浓度下有色离子Mn O4-离子和Cr O42-离子在高岭土中的淌度,研究影响离子有效淌度系数的因素,为电动修复模型中计算有效离子淌度的表达式进行修正。本实验结果证明影响离子有效淌度系数的因素有土壤几何特性(f(n,τ))、离子溶液浓度(kc)和土壤颗粒表面电荷与离子之间相互作用(kz)。其中土壤几何特性用孔隙度n和扭曲度τ的函数来表示,只与土壤的结构有关。离子溶液浓度引起的有效淌度系数可通过在溶液中测量离子淌度计算而得,结果表明离子溶液浓度对有效淌度系数有影响。土壤颗粒表面电荷与离子之间相互作用引起的有效淌度系数通过在高岭土(或加入阳离子树脂)中测量离子淌度计算而得,结果表明土壤颗粒表面电荷与离子之间的相互作用对有效淌度系数有影响,且在高岭土中对不同离子的影响幅度不同。故现有的电动修复模型中对于有效淌度的计算表达式应修正为:zce×××=kknfuu￥),( t根据本研究结果,可在同一土壤介质中同时对多个离子进行数值模拟,其中f(n,τ)取值相同,kc分别测得,通过调整每个离子的kz值,使数值模拟结果与实验结果匹配。
[Abstract]:With the development of industry, the problem of heavy metal pollution in soil is becoming more and more serious. The main remediation technologies are chemical stability / curing, chemical reduction, bioremediation, leaching, electric remediation and so on. As a new in-situ soil remediation technology, electric remediation technology has been widely concerned by researchers at home and abroad. However, in the process of remediation, it will be affected by various factors, such as the characteristics of soil and pollutants, voltage gradient, adsorption / desorption mechanism, focusing phenomenon, working liquid properties, temperature, moisture content and so on. These factors may determine the efficiency and repair time of electric repair, and numerical simulation can consider many factors comprehensively, so as to optimize the process of electric repair and provide a favorable prediction for practical engineering. Researchers at home and abroad have established many mathematical models to predict the migration of pollutants in the process of electric remediation. The results of these models fit well with the experimental results, but are limited to the numerical simulation of a single pollutant. Although some models simulate two or three ions at the same time, the fitting with the experimental results is not satisfactory. In the existing numerical simulation of electric remediation, the mobility of ions in soil is usually estimated by multiplying the ion mobility in infinite dilute solution by the soil effective mobility coefficient k, and the k value is usually estimated by soil porosity n and torsional degree tau. It has nothing to do with the characteristics of ions and the interaction between them and soil particles. In this paper, the mobility of colored ions Mn O4-ion and Cr O42-ion in kaolin at three concentrations will be directly measured, and the factors affecting the effective mobility coefficient of ions will be studied. The expression for calculating the effective ion mobility in the electric repair model is modified. The results show that the factors affecting the effective mobility coefficient of ions are soil geometric characteristics (f (n, 蟿), ion solution concentration (kc) and the interaction between soil particle surface charge and ions (kz). The geometric properties of the soil are represented by the functions of porosity n and distortion tau, which are only related to the structure of the soil. The effective mobility coefficient caused by the ion solution concentration can be calculated by measuring the ion mobility in the solution. The results show that the ion solution concentration has an effect on the effective mobility coefficient. The effective mobility coefficient caused by the interaction between the surface charge of soil particles and ions is calculated by measuring the ion mobility in kaolin (or adding cationic resin). The results show that the interaction between surface charge and ions of soil particles has an effect on the effective mobility coefficient, and the effect on different ions in Kaolin is different. Therefore, the calculation expression of effective mobility in the existing electric repair model should be modified to zce 脳 脳 = kknfuu), (t. According to the results of this study, multiple ions can be simulated simultaneously in the same soil medium, in which f (n, can be used to simulate multiple ions at the same time. The values of tau) are the same. Kc measured them respectively. By adjusting the KZ value of each ion, the numerical simulation results match the experimental results.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X53
本文编号：2486787
[Abstract]:With the development of industry, the problem of heavy metal pollution in soil is becoming more and more serious. The main remediation technologies are chemical stability / curing, chemical reduction, bioremediation, leaching, electric remediation and so on. As a new in-situ soil remediation technology, electric remediation technology has been widely concerned by researchers at home and abroad. However, in the process of remediation, it will be affected by various factors, such as the characteristics of soil and pollutants, voltage gradient, adsorption / desorption mechanism, focusing phenomenon, working liquid properties, temperature, moisture content and so on. These factors may determine the efficiency and repair time of electric repair, and numerical simulation can consider many factors comprehensively, so as to optimize the process of electric repair and provide a favorable prediction for practical engineering. Researchers at home and abroad have established many mathematical models to predict the migration of pollutants in the process of electric remediation. The results of these models fit well with the experimental results, but are limited to the numerical simulation of a single pollutant. Although some models simulate two or three ions at the same time, the fitting with the experimental results is not satisfactory. In the existing numerical simulation of electric remediation, the mobility of ions in soil is usually estimated by multiplying the ion mobility in infinite dilute solution by the soil effective mobility coefficient k, and the k value is usually estimated by soil porosity n and torsional degree tau. It has nothing to do with the characteristics of ions and the interaction between them and soil particles. In this paper, the mobility of colored ions Mn O4-ion and Cr O42-ion in kaolin at three concentrations will be directly measured, and the factors affecting the effective mobility coefficient of ions will be studied. The expression for calculating the effective ion mobility in the electric repair model is modified. The results show that the factors affecting the effective mobility coefficient of ions are soil geometric characteristics (f (n, 蟿), ion solution concentration (kc) and the interaction between soil particle surface charge and ions (kz). The geometric properties of the soil are represented by the functions of porosity n and distortion tau, which are only related to the structure of the soil. The effective mobility coefficient caused by the ion solution concentration can be calculated by measuring the ion mobility in the solution. The results show that the ion solution concentration has an effect on the effective mobility coefficient. The effective mobility coefficient caused by the interaction between the surface charge of soil particles and ions is calculated by measuring the ion mobility in kaolin (or adding cationic resin). The results show that the interaction between surface charge and ions of soil particles has an effect on the effective mobility coefficient, and the effect on different ions in Kaolin is different. Therefore, the calculation expression of effective mobility in the existing electric repair model should be modified to zce 脳 脳 = kknfuu), (t. According to the results of this study, multiple ions can be simulated simultaneously in the same soil medium, in which f (n, can be used to simulate multiple ions at the same time. The values of tau) are the same. Kc measured them respectively. By adjusting the KZ value of each ion, the numerical simulation results match the experimental results.
【学位授予单位】：重庆大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X53
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