曲面优化高铁酸钾与活性炭协同修复黑臭水体
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摘要
以某小型封闭黑臭水体为对象,研究了高铁酸钾(K_2FeO_4)与粒状活性炭(GAC)协同强化混凝修复黑臭水体的最佳工艺参数和处理效果。采用响应曲面法建立了以氨氮(NH3-N)和化学需氧量(COD)的去除率为响应值的二次回归模型,对两者协同作用时K_2FeO_4投加量、预氧化时间、GAC的投加量和pH值4个影响因子进行优化。结果表明:回归模型极其显著,对NH3-N去除效果的影响显著程度排序为:K_2FeO_4投加量> pH> GAC投加量> K_2FeO_4预氧化时间;对COD去除效果的影响显著程度排序:GAC投加量> K_2FeO_4投加量> pH> K_2FeO_4预氧化时间。K_2FeO_4最佳投加量1. 036 mg/L,最佳预氧化时间10. 159 min,GAC最佳投加量16. 152 mg/L,最佳pH值7. 362,此时NH_3-N和COD的去除率分别达到了85. 500%和69. 262%。模型预测值与实验验证结果的实际误差小于5%。
Taking a small closed black-odor water body as the research object,the optimum technological parameters and treatment effect of synergistic restoration with potassium ferrate( K_2FeO_4) and granular activated carbon( GAC) in enhanced coagulation treatment of black-odor water body were studied. The response surface methodology was used to establish the quadratic regression models with the removal rate of NH_3-N and COD as response values. The four influence factors of K_2FeO_4 dosage,pre-oxidation time,GAC dosage and pH value were optimized. The results show that the regression models are extremely significant. The order of influence on NH_3-N removal efficiency is K_2FeO_4 dosage >pH > GAC dosage > pre-oxidation time of K_2FeO_4; The order of influence on COD removal efficiency is GAC dosage >K_2FeO_4 dosage > pH > K_2FeO_4 pre-oxidation time. The optimum dosage of K_2FeO_4 is 1. 036 mg/L,the optimum preoxidation time of K_2FeO_4 is 10. 159 min,the optimum dosage of GAC is 16. 152 mg/L,and the optimum p H value is7. 362,the removal rates of NH_3-N and COD are 85. 500% and 69. 262%,respectively. The actual error between the experimental results and the predicted values of the models is less than 5%,which indicates that the models can predict well the actual situation of the combined use of K_2FeO_4 and GAC in the treatment of black-odor water body.
Taking a small closed black-odor water body as the research object,the optimum technological parameters and treatment effect of synergistic restoration with potassium ferrate( K_2FeO_4) and granular activated carbon( GAC) in enhanced coagulation treatment of black-odor water body were studied. The response surface methodology was used to establish the quadratic regression models with the removal rate of NH_3-N and COD as response values. The four influence factors of K_2FeO_4 dosage,pre-oxidation time,GAC dosage and pH value were optimized. The results show that the regression models are extremely significant. The order of influence on NH_3-N removal efficiency is K_2FeO_4 dosage >pH > GAC dosage > pre-oxidation time of K_2FeO_4; The order of influence on COD removal efficiency is GAC dosage >K_2FeO_4 dosage > pH > K_2FeO_4 pre-oxidation time. The optimum dosage of K_2FeO_4 is 1. 036 mg/L,the optimum preoxidation time of K_2FeO_4 is 10. 159 min,the optimum dosage of GAC is 16. 152 mg/L,and the optimum p H value is7. 362,the removal rates of NH_3-N and COD are 85. 500% and 69. 262%,respectively. The actual error between the experimental results and the predicted values of the models is less than 5%,which indicates that the models can predict well the actual situation of the combined use of K_2FeO_4 and GAC in the treatment of black-odor water body.
引文
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[3]韩琦,董文艺.新型高效水处理剂高铁酸钾的研究进展[J].环境科学与技术,2012,35(S2):200-205.
[4]冯浩,尚文健,金佳,等.高铁酸钾氧化法处理电子工业清洗废水的试验研究[J].环境科学与技术,2010,33(S1):353-356.
[5]程爽.高铁酸钾的制备及预氧化强化混凝效果研究[D].成都:西南交通大学,2017.
[6]王群,柴彬,卢晓辉,等.响应曲面法优化高铁酸钾预氧化强化混凝效果[J].水处理技术,2017,43(3):42-46.
[7]李亚峰,李秒,刘莎.高铁酸钾预氧化强化混凝处理混合染料废水[J].沈阳建筑大学学报(自然科学版),2012,28(5):904-908.
[8]李瑞,凌琪,包金梅.高锰酸钾-粉末活性炭强化混凝效果的研究[J].安徽建筑工业学院学报,2011,19(3):71-75.
[9]任崴,武福平.粉末活性炭强化混凝处理西北村镇集雨窖水的试验研究[J].河南化工,2011,28(15):29-32.
[10]李玲.高铁酸钾辅助PAC去除污水中Cu(Ⅱ)、CODcr、氨氮和总磷的研究[D].太原:太原理工大学,2012.
[11]狄军贞,赵微,朱志涛,等.响应曲面法优化强化混凝工艺处理微污染水[J].环境工程学报,2017,11(1):27-32.
[12] Erick B B,Yung T H,Oliver M. The effects of chemical coagulants on the decolorization of dyes by electrocoagulation using response surface methodology(RSM)[J]. Applied Water Science,2017,7(5):2357-2371.
[13] Yang Y,Zhou Z,Lu C,et al. Treatment of chemical cleaning wastewater and cost optimization by response surface methodology coupled nonlinear programming[J]. Journal of Environmental Management,2017,198(2):12-20.
[14] Lin C,Liao J B,Wei C H. Modeling and optimization of the coagulation of highly concentrated coking wastewater by ferrous sulfate using a response surface methodology[J]. Desalination&Water Treatment,2015,56(12):3334-3345.
[15] Smaoui Y,Chaabouni M,Sayadi S,et al. Coagulation-flocculation process for landfill leachate pretreatment and optimization with response surface methodology[J]. Desalination&Water Treatment,2016,57(31):14488-14495.
[16]李莉,张赛,何强,等.响应面法在试验设计与优化中的应用[J].实验室研究与探索,2015,34(8):41-45.
[17] Lessoued R,Souahi F,Pelaez L C. Modelization and statistical optimization of coagulation-flocculation treatment of an old leachate[J]. Water Environment Research,2017,89(12):2136-2141.
[18] Iva R E,Wahyono H,Agus S. Clarification of pharmaceutical wastewater with moringa oleifera:optimization through response surface methodology[J]. Journal of Ecological Engineering,2018,19(3):126-134.
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