有机污染物土壤吸附预测模型及其影响因素

刘娴; 闻洋; 赵元慧

doi:10.7524/j.issn.0254-6108.2013.07.011

环境化学

有机污染物土壤吸附预测模型及其影响因素

, ,

刘娴, 闻洋, 赵元慧. 有机污染物土壤吸附预测模型及其影响因素[J]. 环境化学, 2013, 32(7): 1199-1204. doi: 10.7524/j.issn.0254-6108.2013.07.011

引用本文:

刘娴, 闻洋, 赵元慧. 有机污染物土壤吸附预测模型及其影响因素[J]. 环境化学, 2013, 32(7): 1199-1204. doi: 10.7524/j.issn.0254-6108.2013.07.011

LIU Xian, WEN Yang, ZHAO Yuanhui. Predictive model for soil sorption of organic pollutants and influencing factors[J]. Environmental Chemistry, 2013, 32(7): 1199-1204. doi: 10.7524/j.issn.0254-6108.2013.07.011

Citation:

LIU Xian, WEN Yang, ZHAO Yuanhui. Predictive model for soil sorption of organic pollutants and influencing factors[J]. Environmental Chemistry, 2013, 32(7): 1199-1204. doi: 10.7524/j.issn.0254-6108.2013.07.011

有机污染物土壤吸附预测模型及其影响因素

1.
国家环境保护湿地生态与植被恢复重点实验室,东北师范大学环境学院, 长春, 130024
基金项目:
国家自然科学基金项目(20977015)

东北师范大学中央高校基本科研业务费专项资金(11SSXT138)资助.

Predictive model for soil sorption of organic pollutants and influencing factors

1.
Key Laboratory of Wetland Ecology and Vegetation Restoration of National Environmental Protection, School of Environmental Sciences, Northeast Normal University, Changchun, 130024, China
Fund Project:

摘要: 以701种有机化合物的土壤吸附系数作为数据集,选取594种有机化合物作为训练集,剩余107种作为测试集.根据训练集化合物建立土壤吸附系数Koc与辛醇/水分配系数Kow的线性和非线性模型,应用平均残差(AE),平均绝对残差(AAE)和均方根误差(RMSE)来检验模型的预测能力,模型具有良好的预测能力.同时,比较不同类型的化合物的实测值与预测值,发现部分同系物的预测值与实测值存在系统的偏差,这些偏差主要是由吸附机理,溶解度,水解作用,挥发作用,实验误差等原因造成,这些因素均会对土壤吸附系数的预测产生影响.
- 土壤吸附 /
- 分配系数 /
- 模型检验 /
- 疏水性
Abstract: The hydrophobic parameter represented by the octanol/water partition coefficient (Kow) is commonly used to predict the soil sorption coefficient (Koc). In the present paper, soil sorption data for 701 compounds were analyzed. The results show that lgKoc is linearly related to lgKow for the compounds with lgKow in the range of 0.5—7.5 and non-linearly related to lgKow for the compounds in a wide range of lgKow. A non-linear model was developed between lgKoc and lgKow for a wide range of compounds in the training set. The models were validated terms of average error (AE), average absolute error (AAE) and root-mean squared error (RMSE) by using an external test set with 107 compounds. Systemic predictive deviations were been observed for some class-specific compounds. The reasons for systemic deviations may be attributed to the difference of sorption mechanism for hydrophilic compounds, low solubility for highly hydrophobic compounds, hydrolysis of esters in solution, volatilization for volatile compounds and highly experimental errors for compounds with extremely high or low sorption coefficient.
- soil sorption /
- partition coefficient /
- model validation /
- hydrophobicity

[1]	Karickhoff S W. Organic pollutant sorption in aquatic systems[J]. Journal of Hydraulic Engineering, 1984,110(6): 707-735
[2]	Baker J R, Mihelcic J R, Luehrs D C, et al. Evaluation of estimation methods of organic carbon normalized sorption coefficients[J]. Water Environment Research, 1997, 69(2): 136-145
[3]	Gwalik B M, Sotirious N, Feicht N, et al. Alternative for the determination of soil adsorption coefficient, K_oc of non-ionicorganic compoundsA review[J]. Chemosphere, 1997, 34(12): 2525-2551
[4]	Doucette W J. Quantitative structure-activity relationships for predicting soil-sediment sorption coefficients for organic chemicals[J]. Environmental Toxicology Chemistry, 2003, 22(8): 1771-1788
[5]	Baker J R, Mihelcic J R, Shea E. Estimating K_ocfor persistent organic pollutants: Limitations of correlations with K_ow[J]. Chemosphere, 2000, 41(6): 813-817
[6]	Gramatica P, Giani, Papa E. Statistical external validation and consensus modeling: A QSPR case study for K_oc prediction[J]. Journal of Molecular Graphics Modeling, 2007. 25(6): 755-766
[7]	Franco A, Fu W J, Trapp S. Influence of soil pH on the sorption of ionizable chemicals: Modeling advance[J]. Environmental Toxicology Chemistry, 2009, 28(3): 458-464
[8]	Cheng H H. Organic residues in soils: Mechanisms of retention and extractability[J]. International Journal of Environmental Analytical Chemistry, 1990, 39(2): 165-171
[9]	Mackay D, Fraser A, Bioaccumulation of persistent organic chemicals: mechanisms and models[J]. Environmental Pollution, 2000, 110(3): 375-391
[10]	Bintein S, Devillers J. QSAR for organic chemical sorption in soils and sediments[J]. Chemosphere, 1994,28(6): 1171-1188
[11]	Franco A, Trapp S. Estimation of the soil-water partition coefficient normalized to organic carbon for ionizable organic chemicals[J]. Environmental Toxicology Chemistry, 2008, 27(10): 1995-2004
[12]	Cousins I T, Beck A J, Jones K C. A review of the processes involved in the exchange of semi-volatile organic compounds (SVOC) across the air-soil interface[J]. Science of the Total Environment, 1999, 228(1): 5-24
[13]	Delle S A. Factors affecting sorption of organic compounds in natural sorbent/water systems and sorption coefficients for selected pollutants. A review[J]. Journal of Physical Chemical Reference Data, 2001, 30: 187-439

点击查看大图

计量

文章访问数: 2265
HTML全文浏览数: 2224
PDF下载数: 2031
施引文献: 0

刘娴, 闻洋, 赵元慧. 有机污染物土壤吸附预测模型及其影响因素[J]. 环境化学, 2013, 32(7): 1199-1204. doi: 10.7524/j.issn.0254-6108.2013.07.011

引用本文:

刘娴, 闻洋, 赵元慧. 有机污染物土壤吸附预测模型及其影响因素[J]. 环境化学, 2013, 32(7): 1199-1204. doi: 10.7524/j.issn.0254-6108.2013.07.011

Citation:

有机污染物土壤吸附预测模型及其影响因素

1. 国家环境保护湿地生态与植被恢复重点实验室,东北师范大学环境学院, 长春, 130024

收稿日期: 2013-01-30

基金项目:

国家自然科学基金项目(20977015)

东北师范大学中央高校基本科研业务费专项资金(11SSXT138)资助.

关键词:

摘要: 以701种有机化合物的土壤吸附系数作为数据集,选取594种有机化合物作为训练集,剩余107种作为测试集.根据训练集化合物建立土壤吸附系数Koc与辛醇/水分配系数Kow的线性和非线性模型,应用平均残差(AE),平均绝对残差(AAE)和均方根误差(RMSE)来检验模型的预测能力,模型具有良好的预测能力.同时,比较不同类型的化合物的实测值与预测值,发现部分同系物的预测值与实测值存在系统的偏差,这些偏差主要是由吸附机理,溶解度,水解作用,挥发作用,实验误差等原因造成,这些因素均会对土壤吸附系数的预测产生影响.

English Abstract

Predictive model for soil sorption of organic pollutants and influencing factors

1. Key Laboratory of Wetland Ecology and Vegetation Restoration of National Environmental Protection, School of Environmental Sciences, Northeast Normal University, Changchun, 130024, China

Received Date: 2013-01-30

Fund Project:

Keywords:

Abstract: The hydrophobic parameter represented by the octanol/water partition coefficient (Kow) is commonly used to predict the soil sorption coefficient (Koc). In the present paper, soil sorption data for 701 compounds were analyzed. The results show that lgKoc is linearly related to lgKow for the compounds with lgKow in the range of 0.5—7.5 and non-linearly related to lgKow for the compounds in a wide range of lgKow. A non-linear model was developed between lgKoc and lgKow for a wide range of compounds in the training set. The models were validated terms of average error (AE), average absolute error (AAE) and root-mean squared error (RMSE) by using an external test set with 107 compounds. Systemic predictive deviations were been observed for some class-specific compounds. The reasons for systemic deviations may be attributed to the difference of sorption mechanism for hydrophilic compounds, low solubility for highly hydrophobic compounds, hydrolysis of esters in solution, volatilization for volatile compounds and highly experimental errors for compounds with extremely high or low sorption coefficient.

全文HTML

参考文献 (13)

下载: 全尺寸图片幻灯片

返回文章

用微信扫码二维码

分享至好友和朋友圈

有机污染物土壤吸附预测模型及其影响因素

Predictive model for soil sorption of organic pollutants and influencing factors

计量

出版历程

有机污染物土壤吸附预测模型及其影响因素

English Abstract

Predictive model for soil sorption of organic pollutants and influencing factors

全文HTML

目录