摘 要
随着工业发展，化工废水成分日益复杂，传统处理技术难以有效去除其中的难降解有机物，高级氧化技术凭借其强氧化性、广谱性和高效性成为研究热点。本研究旨在探究不同高级氧化技术在化工废水处理中的效能及机制，以Fenton氧化、臭氧氧化和光催化氧化为主要研究对象，通过实验室模拟实验与实际工程案例相结合的方式开展研究。采用响应面法优化各工艺参数，考察了pH值、反应时间、氧化剂投加量等因素对COD去除率的影响，结果表明三种技术均能显著降低化工废水中有机污染物浓度，其中Fenton氧化对高浓度有机废水处理效果最佳，臭氧氧化适用于中低浓度且具有较好生物毒性的废水，光催化氧化则在特定波长光照条件下表现出优异的选择性降解能力。创新性地将机器学习算法引入高级氧化过程建模与预测，提高了模型精度和实用性，为实现精准控制提供了理论依据。本研究不仅丰富了高级氧化技术理论体系，还为化工废水处理工程实践提供了重要参考，有助于推动绿色化工发展进程。
关键词：高级氧化技术 Fenton氧化 臭氧氧化
Abstract
With the development of industry, the composition of chemical wastewater has become increasingly complex, and traditional treatment technologies struggle to effectively remove refractory organic compounds. Advanced oxidation processes (AOPs), characterized by their strong oxidizing properties, broad-spectrum applicability, and high efficiency, have emerged as a research focus. This study aims to investigate the performance and mechanisms of different AOPs in chemical wastewater treatment, focusing primarily on Fenton oxidation, ozone oxidation, and photocatalytic oxidation. By integrating laboratory simulation experiments with real-world engineering cases, response surface methodology was employed to optimize process parameters, examining the effects of pH, reaction time, and oxidant dosage on COD removal rates. The results indicate that all three technologies significantly reduce the concentration of organic pollutants in chemical wastewater, with Fenton oxidation demonstrating the best performance for high-concentration organic wastewater, ozone oxidation being suitable for medium-to-low concentration wastewater with good biotoxicity, and photocatalytic oxidation exhibiting excellent selective degradation under specific wavelengths of light. Innovatively, machine learning algorithms were introduced into the modeling and prediction of AOPs, enhancing model accuracy and practicality, thus providing a theoretical basis for precise control. This study not only enriches the theoretical fr amework of advanced oxidation technologies but also offers significant references for engineering practices in chemical wastewater treatment, contributing to the advancement of green chemistry.
Keyword:Advanced Oxidation Technology Fenton Oxidation Ozone Oxidation
目 录
1绪论 1
1.1化工废水处理的背景与意义 1
1.2高级氧化技术研究现状综述 1
1.3本文研究方法概述 1
2高级氧化技术原理分析 2
2.1氧化剂种类及其特性 2
2.2反应机制探讨 2
2.3影响因素分析 3
3高级氧化技术应用实例 4
3.1典型化工废水案例 4
3.2技术实施过程解析 4
3.3应用效果评估 5
4高级氧化技术优化策略 5
4.1工艺参数优化 5
4.2新型材料的应用 6
4.3成本效益分析 7
结论 7
参考文献 9
致谢 10
随着工业发展，化工废水成分日益复杂，传统处理技术难以有效去除其中的难降解有机物，高级氧化技术凭借其强氧化性、广谱性和高效性成为研究热点。本研究旨在探究不同高级氧化技术在化工废水处理中的效能及机制，以Fenton氧化、臭氧氧化和光催化氧化为主要研究对象，通过实验室模拟实验与实际工程案例相结合的方式开展研究。采用响应面法优化各工艺参数，考察了pH值、反应时间、氧化剂投加量等因素对COD去除率的影响，结果表明三种技术均能显著降低化工废水中有机污染物浓度，其中Fenton氧化对高浓度有机废水处理效果最佳，臭氧氧化适用于中低浓度且具有较好生物毒性的废水，光催化氧化则在特定波长光照条件下表现出优异的选择性降解能力。创新性地将机器学习算法引入高级氧化过程建模与预测，提高了模型精度和实用性，为实现精准控制提供了理论依据。本研究不仅丰富了高级氧化技术理论体系，还为化工废水处理工程实践提供了重要参考，有助于推动绿色化工发展进程。
关键词：高级氧化技术 Fenton氧化 臭氧氧化
Abstract
With the development of industry, the composition of chemical wastewater has become increasingly complex, and traditional treatment technologies struggle to effectively remove refractory organic compounds. Advanced oxidation processes (AOPs), characterized by their strong oxidizing properties, broad-spectrum applicability, and high efficiency, have emerged as a research focus. This study aims to investigate the performance and mechanisms of different AOPs in chemical wastewater treatment, focusing primarily on Fenton oxidation, ozone oxidation, and photocatalytic oxidation. By integrating laboratory simulation experiments with real-world engineering cases, response surface methodology was employed to optimize process parameters, examining the effects of pH, reaction time, and oxidant dosage on COD removal rates. The results indicate that all three technologies significantly reduce the concentration of organic pollutants in chemical wastewater, with Fenton oxidation demonstrating the best performance for high-concentration organic wastewater, ozone oxidation being suitable for medium-to-low concentration wastewater with good biotoxicity, and photocatalytic oxidation exhibiting excellent selective degradation under specific wavelengths of light. Innovatively, machine learning algorithms were introduced into the modeling and prediction of AOPs, enhancing model accuracy and practicality, thus providing a theoretical basis for precise control. This study not only enriches the theoretical fr amework of advanced oxidation technologies but also offers significant references for engineering practices in chemical wastewater treatment, contributing to the advancement of green chemistry.
Keyword:Advanced Oxidation Technology Fenton Oxidation Ozone Oxidation
目 录
1绪论 1
1.1化工废水处理的背景与意义 1
1.2高级氧化技术研究现状综述 1
1.3本文研究方法概述 1
2高级氧化技术原理分析 2
2.1氧化剂种类及其特性 2
2.2反应机制探讨 2
2.3影响因素分析 3
3高级氧化技术应用实例 4
3.1典型化工废水案例 4
3.2技术实施过程解析 4
3.3应用效果评估 5
4高级氧化技术优化策略 5
4.1工艺参数优化 5
4.2新型材料的应用 6
4.3成本效益分析 7
结论 7
参考文献 9
致谢 10
