QSARs to predict adsorption affinity of organic micropollutants for activated carbon and β-cyclodextrin polymer adsorbents

被引：52

作者：

Ling, Yuhan ^{[1
]}

Klemes, Max J. ^{[2
]}

Steinschneider, Scott ^{[3
]}

Dichtel, William R. ^{[2
]}

Helbling, Damian E. ^{[1
]}

机构：

[1] Cornell Univ, Sch Civil & Environm Engn, Ithaca, NY 14853 USA

[2] Northwestern Univ, Dept Chem, 2145 Sheridan Rd, Evanston, IL 60208 USA

[3] Cornell Univ, Dept Biol & Environm Engn, Ithaca, NY 14853 USA

来源：

WATER RESEARCH | 2019年 / 154卷

基金：

美国国家科学基金会;

关键词：

Micropollutant; Adsorption; Distribution coefficient; Activated carbon; beta-cyclodextrin polymer; ENDOCRINE DISRUPTING COMPOUNDS; SOLVATION ENERGY RELATIONSHIP; MOLECULAR CONNECTIVITY; PARTITION-COEFFICIENTS; EMERGING CONTAMINANTS; VARIABLE SELECTION; WATER; REMOVAL; PHARMACEUTICALS; REGRESSION;

D O I：

10.1016/j.watres.2019.02.012

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

The removal of organic micropollutants (MPs) from water by means of adsorption is determined by the physicochemical properties of the adsorbent and the MPs. It is challenging to predict the removal of MPs by specific adsorbents due to the extreme diversity in physicochemical properties among MPs of interest. In this research, we established Quantitative Structure-Activity Relationships (QSARs) between the physicochemical properties of a diverse set of MPs and their distribution coefficients (K-D ) measured on coconut shell activated carbon (CCAC) and porous beta-cyclodextrin polymer (P-CDP) adsorbents. We conducted batch experiments with a mixture of 200 MPs and used the data to calculate K-D values for each MP on each adsorbent under conditions of infinite dilution (i.e., low adsorbate concentrations). We used computational software to calculate 3656 molecular descriptors for each MP. We then developed and applied a model-selection workflow to identify the most significant molecular descriptors for each adsorbent. The functional stability and predictive power of the resulting QSARs were confirmed with internal cross validation and external validation. The applicability domain of the QSARs was defined based on the most significant molecular descriptors selected into each QSAR. The QSARs are predictive tools for evaluating adsorption-based water treatment processes and provide new insights into CCAC and P-CDP adsorption mechanisms. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页码：217 / 226

页数：10

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