The Degradation of Sulfamethoxazole via the Fe2+/Ultraviolet/Sodium Percarbonate Advanced Oxidation Process: Performance, Mechanism, and Back-Propagate-Artificial Neural Network Prediction Model

被引:1
作者
Chen, Juxiang [1 ]
Ruan, Chong [1 ]
Xie, Wanying [1 ]
Dai, Caiqiong [1 ]
Gao, Yuqiong [2 ]
Liao, Zhenliang [3 ]
Gao, Naiyun [3 ]
机构
[1] Xinjiang Univ, Coll Civil Engn & Architecture, Urumqi 830017, Peoples R China
[2] Univ Shanghai Sci & Technol, Sch Environm & Architecture, Shanghai 200093, Peoples R China
[3] Tongji Univ, Coll Environm Sci & Engn, State Key Lab Pollut Control & Resources Reuse, Shanghai 200092, Peoples R China
基金
中国国家自然科学基金;
关键词
Fe2+/UV/SPC oxidation system; sulfonamides antibiotics; degradation mechanism; BP-ANN; predicting model; PERSONAL CARE PRODUCTS; HYDROGEN-PEROXIDE; WASTE-WATER; FENTON; PEROXYMONOCARBONATE; CHEMILUMINESCENCE; PHARMACEUTICALS; UV/PERSULFATE; DECOMPOSITION; KINETICS;
D O I
10.3390/w16040532
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The degradation of sulfamethoxazole (SMX) via the Fe2+/Ultraviolet (UV)/sodium percarbonate (SPC) system was comprehensively investigated in this study, including the performance optimization, degradation mechanism, and predicting models. The degradation condition of SMX was optimized, and it was found that appropriate amounts of C-Fe(2+) (10 similar to 30 mu M) and C-SPC (10 mu M) under an acidic condition (pH = 4 similar to 6) were in favor of a higher degradation rate. According to probe compound experiments, it was considerable that center dot OH and center dot CO3- was the primary and subordinate free radical in SMX degradation, and k(center dot OH,SMX) maintained two times more than that of k(center dot CO3-,SMX), especially under acidic conditions. The UV direct photolysis and other active intermediates were also responsible for the SMX degradation. These active intermediates were produced via the Fe2+/UV/SPC system, involving center dot HO2, HCO4-, center dot O-2(-), or O-1(2). Furthermore, when typical anions co-existed, the degradation of SMX was negatively influenced, owing to HCO3- and CO32- possibly consuming center dot OH or H2O2 to compete with SMX. In addition, the prediction model was successfully established via the back-propagate artificial neural network (BP-ANN) method. The degradation rate of SMX was well forecasted via the Back-Propagate-Artificial Neural Network (BP-ANN) model, which was expressed as Y-pre=tanh(tanh(x(i)W(ih))Who). The BP-ANN model reflected the relative importance of influence factors well, which was pH > t > C-Fe(2+)approximate to C-SPC. Compared to the response surface method Box-Behnken design (RSM-BBD) model (R-2 = 0.9765, relative error = 3.08%), the BP-ANN model showed higher prediction accuracy (R-2 = 0.9971) and lower error (1.17%) in SMX degradation via the Fe2+/UV/SPC system. These findings help us to understand, in-depth, the degradation mechanism of SMX; meanwhile, they are conducive to promoting the development of the Fe2+/UV/SPC system in SMX degradation, especially in some practical engineering cases.
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页数:23
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