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<p>In this study, persulfate (PS)-zero-valent iron (ZVI) system, which combined advanced oxidation process and flocculation precipitation, was used to remove enrofloxacin in water (initial concentration: 200&#xa0;mg/L). To investigate the mechanism and optimize the process, the central composite design (CCD) and response surface method (RSM) were applied to design and guide the experiments. The CCD was employed to design the experimental matrix, which was then executed to obtain the response value removal efficiency (RE). Subsequently, the variables and response values were modeled to produce a second-order equation, which was evaluated by analysis of variance (ANOVA) and the results proved that the fit was significant and the signal was sufficient. Next, the interactive relationships between two factors were displayed by the software with 3D response surface diagrams, and the results showed that the synergistic effect of ZVI dosage and reaction time had the greatest influence on RE and the rough region with high RE value was as PS dosage: 0.30–0.6.00&#xa0;g/L, ZVI dosage: 6.50–8.00&#xa0;g/L and reaction time: 100.00–120.00&#xa0;min. Finally, the optimal point condition predicted by the software, under this condition we actually carried out the verification experiments and the average RE obtained was 97.32% consistent with the predicted value of the model, which proved the model was effective and had good predicting ability. Compared with the other similar processes using enhancement methods, the RE achieved the same level and the method had the advantages of gentle reaction conditions, low cost and high efficiency.</p>

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Intelligent guidance by modeling for enrofloxacin removal based on advanced oxidation process

  • 期刊论文

  • 发表日期：

    2025年6月10日

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  • Q. Li,
  • K. Shi,
  • Y. Hu

摘要

In this study, persulfate (PS)-zero-valent iron (ZVI) system, which combined advanced oxidation process and flocculation precipitation, was used to remove enrofloxacin in water (initial concentration: 200 mg/L). To investigate the mechanism and optimize the process, the central composite design (CCD) and response surface method (RSM) were applied to design and guide the experiments. The CCD was employed to design the experimental matrix, which was then executed to obtain the response value removal efficiency (RE). Subsequently, the variables and response values were modeled to produce a second-order equation, which was evaluated by analysis of variance (ANOVA) and the results proved that the fit was significant and the signal was sufficient. Next, the interactive relationships between two factors were displayed by the software with 3D response surface diagrams, and the results showed that the synergistic effect of ZVI dosage and reaction time had the greatest influence on RE and the rough region with high RE value was as PS dosage: 0.30–0.6.00 g/L, ZVI dosage: 6.50–8.00 g/L and reaction time: 100.00–120.00 min. Finally, the optimal point condition predicted by the software, under this condition we actually carried out the verification experiments and the average RE obtained was 97.32% consistent with the predicted value of the model, which proved the model was effective and had good predicting ability. Compared with the other similar processes using enhancement methods, the RE achieved the same level and the method had the advantages of gentle reaction conditions, low cost and high efficiency.