Atenolol (ATN) is a drug that is widely used to treat some heart diseases, and since it cannot be completely decomposed in the human body, some amounts of it are found in surface water. These amounts may bring risks to the environment and humans, and for this reason, its removal is a must. In the present study, the combined sono-electro-persulfate method was used for ATN removal. Based on the design of the experiment conducted by response surface methodology (RSM), the effects of 5 main factors (pH, time, PS concentration, current intensity, and initial ATN concentration) have been investigated at 5 levels. After passing the test steps in different conditions, the remaining amount of ATN has been measured by high-performance liquid chromatography (HPLC). Finally, an adaptive neuro-fuzzy inference system (ANFIS) with 99.63% accuracy and a genetic algorithm (GA) were used to analyze and interpret data and predict optimal conditions. The obtained results indicate the possibility of a maximum efficiency of 99.8% in the mentioned conditions (Ph of 7.4, time of 18 min, PS concentration of 2000 mg/L, current intensity of 3.35 A, and initial ATN concentration of 11.2 mg/L). According to the obtained results, the initial concentration of ATN can be considered as the most effective factor in this process, and the best Ph range for this experiment was the neutral range. The sono-electro persulfate process can be mentioned as a new and effective method for removing ATN from water sources.
Atenolol (ATN) is a slowly biodegradable antagonist β-blocker drug and remains in the environment for a long period of time. This drug has a harmful effect on the environment and human and animal bodies. In this study, using activated persulfate with ultrasound for the degradation of ATN was investigated. The effect of independent variables including pH, ATN concentration, persulfate dose, contact time, and ultrasonic power has been studied at 5 levels. Central composite design (CCD) was used for designing the experiments in Design Expert 11.0 software. The ATN concentration was measured using high-performance liquid chromatography (HPLC). Genetic algorithms (GA) and artificial neural network (ANN) were used for optimization and prediction, respectively. The results indicated that at the optimal conditions for the experiment (pH of 6.79, reaction time of 19 min, initial ATN concentration of 15.92 mg/L, US power of 109.56 W, and PS dose of 1317.88 mg/L), the highest ATN degradation efficiency was 98.9%. The ATN degradation could be represented by the pseudo-zero-order kinetics. Also, the data of ATN were well fitted with the ANN model (R2 = 0.98). The results showed that the best pH range to eliminate ATN is the near neutral range and the GA was found to be an effective tool to optimize the experimental conditions for the removal of ATN. The ultrasonic/persulfate process as a useful technique has a high potential to remove ATN from aqueous solutions.
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