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The Degradation of Sulfamethoxazole via the Fe2+/Ultraviolet/Sodium Percarbonate Advanced Oxidation Process: Performance, Mechanism, and Back-Propagate–Artificial Neural Network Prediction Model
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 (10~30 μM) and CSPC (10 μM) under an acidic condition (pH = 4~6) were in favor of a higher degradation rate. According to probe compound experiments, it was considerable that and was the primary and subordinate free radical in SMX degradation, and maintained two times more than that of , 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 , , , or 1O2. Furthermore, when typical anions co-existed, the degradation of SMX was negatively influenced, owing to and possibly consuming 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 . The BP-ANN model reflected the relative importance of influence factors well, which was pH > t > . Compared to the response surface method Box–Behnken design (RSM-BBD) model (R2 = 0.9765, relative error = 3.08%), the BP-ANN model showed higher prediction accuracy (R2 = 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.
The Degradation of Sulfamethoxazole via the Fe2+/Ultraviolet/Sodium Percarbonate Advanced Oxidation Process: Performance, Mechanism, and Back-Propagate–Artificial Neural Network Prediction Model
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 (10~30 μM) and CSPC (10 μM) under an acidic condition (pH = 4~6) were in favor of a higher degradation rate. According to probe compound experiments, it was considerable that and was the primary and subordinate free radical in SMX degradation, and maintained two times more than that of , 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 , , , or 1O2. Furthermore, when typical anions co-existed, the degradation of SMX was negatively influenced, owing to and possibly consuming 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 . The BP-ANN model reflected the relative importance of influence factors well, which was pH > t > . Compared to the response surface method Box–Behnken design (RSM-BBD) model (R2 = 0.9765, relative error = 3.08%), the BP-ANN model showed higher prediction accuracy (R2 = 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.
The Degradation of Sulfamethoxazole via the Fe2+/Ultraviolet/Sodium Percarbonate Advanced Oxidation Process: Performance, Mechanism, and Back-Propagate–Artificial Neural Network Prediction Model
Juxiang Chen (Autor:in) / Chong Ruan (Autor:in) / Wanying Xie (Autor:in) / Caiqiong Dai (Autor:in) / Yuqiong Gao (Autor:in) / Zhenliang Liao (Autor:in) / Naiyun Gao (Autor:in)
2024
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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