Quantitative-Structure-Activity-Relationship (QSAR) models for the reaction rate and temperature of nitrogenous organic compounds in supercritical water oxidation (SCWO)

被引:28
作者
Cheng, Zhiwen [1 ]
Yang, Bowen [1 ]
Chen, Qincheng [2 ]
Gao, Xiaoping [1 ]
Tan, Yujia [1 ]
Yuan, Tao [1 ]
Shen, Zhemin [1 ,3 ]
机构
[1] Shanghai Jiao Tong Univ, Sch Environm Sci & Engn, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Sch Agr & Biol, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
[3] Shanghai Inst Pollut Control & Ecol Secur, Shanghai 200092, Peoples R China
基金
美国国家科学基金会;
关键词
Supercritical water oxidation; QSAR models; Reaction rate constants; Reaction temperature; Quantum chemical parameter; Nitrogenous organics; REACTION-RATE CONSTANTS; COKING WASTE-WATER; EMERGING CONTAMINANTS; POLYCHLORINATED-BIPHENYLS; APPLICABILITY DOMAIN; OZONATION PROCESS; GAS-PHASE; DEGRADATION; POLLUTANTS; VALIDATION;
D O I
10.1016/j.cej.2018.07.167
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Supercritical water oxidation (SCWO), in which hazardous wastes are removed from water at high temperature and pressure, is an effective method for wastewater treatment. To gain a better understanding of the removal rules for nitrogenous organics in SCWO, a Quantitative-Structure-Activity-Relationship (QSAR) approach was applied to establish the relationship between quantum chemical parameters and removal behaviors. In this study, 41 nitrogenous organics were used to study the removal behaviors, including the reaction rate constants of total nitrogen (k(TN)) and the temperature at which the total nitrogen removal efficiency is 50% (T-TN50). QSAR models were subsequently developed and evaluated. The two optimal models for kTN and TTN50 were stable, robust and accurate, with the associated statistical indices of R-2 = 0.725 and 0.951, q(2) = 0.568 and 0.931, Q(ext)(2) = 0.847 and 0.987, respectively. The two optimal models both contained f (-)(n), E-gap, q(N) and BOx, but varied in the correlation between these four parameters and dependent variables. A three factors theory was thus proposed based on the two optimal models: the selectivity of active site, the transfer of electrons, and the breaking of chemical bond. These two models not only offer theoretical methods for predicting k(TN) and T-TN50, but also have predictive power for the removal behaviors of other nitrogenous organics in SCWO, reducing the need for further experiments.
引用
收藏
页码:12 / 20
页数:9
相关论文
共 70 条
[1]  
Akgun M., 2014, NEAR CRITICAL SUPERC
[2]   Parameters affecting the photocatalytic degradation of dyes using TiO2-based photocatalysts: A review [J].
Akpan, U. G. ;
Hameed, B. H. .
JOURNAL OF HAZARDOUS MATERIALS, 2009, 170 (2-3) :520-529
[3]   Supercritical water oxidation (SCWO) for the removal of nitrogen containing heterocyclic waste hydrocarbons. Part II: System kinetics [J].
Al-Duri, Bushra ;
Alsoqyani, Faihan .
JOURNAL OF SUPERCRITICAL FLUIDS, 2017, 128 :412-418
[4]   Removal of pyridine and quinoline by bio-zeolite composed of mixed degrading bacteria and modified zeolite [J].
Bai, Yaohui ;
Sun, Qinghua ;
Xing, Rui ;
Wen, Donghui ;
Tang, Xiaoyan .
JOURNAL OF HAZARDOUS MATERIALS, 2010, 181 (1-3) :916-922
[5]   Nitrogen-containing organic compounds: Origins, toxicity and conditions of their photocatalytic mineralization over TiO2 [J].
Bamba, Drissa ;
Coulibaly, Mariame ;
Robert, Didier .
SCIENCE OF THE TOTAL ENVIRONMENT, 2017, 580 :1489-1504
[6]   Supercritical water oxidation of feeds with high ammonia concentrations Pilot plant experimental results and modeling [J].
Bermejo, M. D. ;
Cantero, F. ;
Cocero, M. J. .
CHEMICAL ENGINEERING JOURNAL, 2008, 137 (03) :542-549
[7]  
BIOVIA, MAT STUD 7 0 ONL HEL
[8]   A review of the effects of emerging contaminants in wastewater and options for their removal [J].
Bolong, N. ;
Ismail, A. F. ;
Salim, M. R. ;
Matsuura, T. .
DESALINATION, 2009, 239 (1-3) :229-246
[9]  
Bröll D, 1999, ANGEW CHEM INT EDIT, V38, P2999
[10]   Root mean square error (RMSE) or mean absolute error (MAE)? - Arguments against avoiding RMSE in the literature [J].
Chai, T. ;
Draxler, R. R. .
GEOSCIENTIFIC MODEL DEVELOPMENT, 2014, 7 (03) :1247-1250