环境工程学报2016,Vol.10Issue(10):5528-5534,7.DOI:10.12030/j.cjee.201504010
微波-均相Fenton法深度处理工业聚集型村镇复合废水
Advanced treatment of composite wastewater effluents from industrial cluster towns adopting with microwave-homogeneous Fenton method
摘要
Abstract
In order to enhance the treatment efficiency of integrated wastewater,we evaluated the advanced treatment process by adopting the microwave (MW)-homogeneous Fenton method.Based on the Box-Behnken model,we adopted response surface methodology to evaluate the main influencing factors,including initial pH,the molar ratios of H2O2/Fe2+,the input amount of H2O2,MW power,and MW irradiation time,as well as the single-factor experiment and combined effects of MW.Moreover,a quadratic response surface model,adopting the response of COD removal efficiency,was also established and the model accuracy was confirmed with variance analysis.The results indicated that the influencing factors on COD removal efficiency ranked as follows:initial pH > HxO2 dosage > MW power > H2O2/Fe2+ molar ratio > MW irradiation time.Among these,the interaction between the initial pH and H2O2 input dosage was significant.In addition,the above response surface methodology showed a satisfactory mathematical regression model,with the optimized reaction conditions identified as initial pH of 3.43,H2O2 input dosage of 19.2 mmol·L-1,H2O2/Fe2+ molar ratio of 39.42,MW power of 597.55 W,and MW irradiation time of 5.12 min.The variance was about 4.7% compared with the predicted value.Accordingly,the effluent COD value for wastewater adopted with the MW-Fenton process was lower than 100 mg·L-1,which is in comolete agreement with the demand of the Integrated Wastewater Discharge Standard (GB 8978-1996).关键词
微波-均相Fenton法/工业聚集型村镇复合废水/Box-Behnken响应曲面法/深度处理Key words
microwave-homogeneous Fenton method/integrated industrial wastewater/Box-Behnken response surface methodology/advanced treatment分类
资源环境引用本文复制引用
权维强,檀笑,牛航宇,康娟,任学昌,鞠勇明,庞志华..微波-均相Fenton法深度处理工业聚集型村镇复合废水[J].环境工程学报,2016,10(10):5528-5534,7.基金项目
国家科技支撑计划项目(2012BAJ21B07) (2012BAJ21B07)
广东省科技计划项目(2016A020221017) (2016A020221017)
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