微动力曝气技术应用于黑臭水体治理的参数优化研究
|
摘要
为了得到微动力曝气技术在黑臭水体治理过程中优化后的条件参数及预测模型,以曝气量、曝气时长和曝气位置为自变量,脱氮效果(氨氮消除时长和总氮削减率)为响应变量,根据Design-expert设置了17组试验。在试验过程中考虑内源污染释放等因素,然后以试验数据为基础,结合响应面模型分析,研究得出优化后的条件参数和预测模型。研究结果表明:两个响应面模型调整后的拟合度分别为0.99和0.96,预测模型的拟合度为0.95和0.69,具有良好的拟合度;优化后的条件参数曝气量为1 L/min、曝气时长12 h/d和曝气位置位于上覆水中部;此试验组下的氨氮消除时长和总氮削减率分别为5.50 d±0.00 d和51.84%±1.14%,与预测模型的预测值相比较,两者标准差分别为0.00%和0.98%。最终得出结论:优化条件参数后的微动力曝气技术应用于黑臭水体治理可以取得较好脱氮效果,模型可以较准确地预测水体修复效果。
In order to obtain the optimized condition parameters and prediction models for the micro-dynamic aeration technology in the process of black-odor water treatment, 17 groups of tests are set in accordance with Design-expert by taking aeration amount, aeration duration and aeration position as the independent variables and nitrogen removal effect(ammonium removal duration and total nitrogen removal rate) as the response variables. During the test, the factors of endogenous pollution releasing, etc. are considered, and then the optimized condition parameters and the prediction models are obtained from the study in combination with the relevant response surface model based on the test data. The study result shows that the adjusted fitting degrees of two response surface models are 0.99 and 0.96, while the fitting degrees of the prediction models are 0.95 and 0.69, of which all have better fitting degrees. The optimized condition parameter aeration amount is 1 L/min with the aeration duration of 12 h/d and the aeration position is situated at the mid-part of the overlying water. The ammonium removal duration and total nitrogen removal rate of this group of tests are 5.50 d±0.00 d and 51.84%±1.14% respectively; if compared with the predicting values from the prediction model, the standard deviations between both of them are 0.00% and 0.98% respectively. It is finally concluded that better nitrogen removal effect can be obtained from applying the micro-dynamic aeration technology after optimizing the condition parameters to black-odor water treatment; for which the models can more accurately predict the restoration effect of the water body concerned.
In order to obtain the optimized condition parameters and prediction models for the micro-dynamic aeration technology in the process of black-odor water treatment, 17 groups of tests are set in accordance with Design-expert by taking aeration amount, aeration duration and aeration position as the independent variables and nitrogen removal effect(ammonium removal duration and total nitrogen removal rate) as the response variables. During the test, the factors of endogenous pollution releasing, etc. are considered, and then the optimized condition parameters and the prediction models are obtained from the study in combination with the relevant response surface model based on the test data. The study result shows that the adjusted fitting degrees of two response surface models are 0.99 and 0.96, while the fitting degrees of the prediction models are 0.95 and 0.69, of which all have better fitting degrees. The optimized condition parameter aeration amount is 1 L/min with the aeration duration of 12 h/d and the aeration position is situated at the mid-part of the overlying water. The ammonium removal duration and total nitrogen removal rate of this group of tests are 5.50 d±0.00 d and 51.84%±1.14% respectively; if compared with the predicting values from the prediction model, the standard deviations between both of them are 0.00% and 0.98% respectively. It is finally concluded that better nitrogen removal effect can be obtained from applying the micro-dynamic aeration technology after optimizing the condition parameters to black-odor water treatment; for which the models can more accurately predict the restoration effect of the water body concerned.
引文
[1] 应太林,张国莹,吴芯芯. 苏州河水体黑臭机理及底质再悬浮对水体的影响[J]. 上海环境科学,1997,17(1):23- 26.
[2] 俞欣,陈天安. 河道黑臭污染简易评价方法研究[J].环境科学与管理,2015,40(3):176- 179.
[3] 贾紫永,刘强,伍灵,等.微纳米曝气技术在黑臭河道治理中的应用研究[J].化工管理,2017(36):106.
[4] 张绍君. 纯氧曝气快速消除河流黑臭工程效果及河道影响因素研究[D].北京:清华大学,2010.
[5] ZENG R J, LEMAIRE R, YUAN Z, et al.Simultaneous nitrification, denitrification, and phosphorus removal in a lab-scale sequencing batch reactor[J]. Biotechnology and Bioengineering, 2003, 84(2):170- 178.
[6] ZHANG Z J, ZHU J, KING J, et al. A two-step fed SBR for treating swine manure[J]. Process Biochemistry, 2006, 41(4):892- 900.
[7] WEISSBACH M, THIEL P, DREWES J E, et al. Nitrogen removal and intentional nitrous oxide production from reject water in a coupled nitritation/nitrous denitritation system under real feed-stream conditions[J]. Bioresource Technology, 2018, 255: 58- 66.
[8] BAS D, BOYACI I H. Modeling and optimization I: Usability of response surface methodology[J]. Journal offood engineering, 2007, 78(3): 836- 845.
[9] ZHANG Z, ZHENG H. Optimization for decolorization of azo dye acid green 20 by ultrasound and H2O2 using response surface methodology[J]. Journal of Hazardous Materials, 2009,172(2- 3): 1388- 1393.
[10] AGHAIE E, PAZOUKI M, HOSSEINI M R, et al. Response surface methodology (RSM) analysis of organic acid production for Kaolin beneficiation by Aspergillus nigerv[J]. Chemical Engineering Journal, 2009, 147(2- 3): 245- 251.
[11] ITOKAWA H, HANAKI K, MATSUO T, et al. Nitrous oxide production in high-loading boilogical nitrogen removal process under low COD/N ratio condition[J]. Water Research, 2001, 35(3): 657- 664.
[12] BATEMAN E J, BAGGS E M. Contributions of nitrification and denitrification to N2O emissions from soils at different water-filled pore space[J]. Biology And Fertility of Soils, 2005 41(6):379- 388.
[13] FRANCIS C A, ROBERTS K J, BEMAN J M,et al. Ubiquity and diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(41):14683- 14688.
[14] POLLICE A, TANDOI V, LESTINGI C. Influence of aeration and sludge retention time on ammonium oxidation to nitrite and nitrate[J]. Water Research,2002, 36(10):2541- 2546.
[15] CHO Y, HAN K, KIM N, et al.Estimating in situ biodegradation rates of petroleum hydrocarbons and microbial population dynamics by performing single-well push-pull tests in a fractured bedrock aquifer[J]. Water Air And Soil Pollution, 2013,224(2):1364- 1368.
[16] XU P, SUN Y, ZHANG H, et al. Experimental study on the effects of multi-parameter setting on fine bubble aeration system[J]. Technology of Water Treatment, 2016, 42(6):51- 54,58.
[17] ZHEN Z, CONJUN S, XIAO P, et al. Study on black and odorous water restoration with low-intensity aeration technology[J]. Technology of Water Treatment, 2009, 35(4):104- 107.
[18] JENSEN W A. Response surface methodology: Process and product optimization using designed experiments 4th edition[J]. Journal of Quality Technology, 2017, 49(2):186- 187.
[19] GUYEN G, PERENDECI A, TANYOLAC A. Electrochemical treatment of deproteinated whey wastewater and optimization of treatment conditions with responses surface methodology[J]. Journal of Hazardous Materials, 2008, 157(1): 69- 78.
[20] SAID K A, AMIN M A.Overview on the response surface methodology (RSM) in extraction processes[J]. Journal of Applied Science & Process Engineering, 2016, 2(1):1- 8.
[21] AZAMAN S N A, RAMAKRIAHNAN N R, TAN J S, et al. Optimization of an induction strategy for improving interferon-alpha 2b production in the periplasm of Escherichia coli using response surface methodology[J]. Biotechnology And Applied Biochemistry, 2010, 56:141- 150.
[22] BEZERRA M A, SANTELLI R E, OLIVERA E P, et al. Response surface methodology (RSM) as a tool for optimization in analytical chemistry[J]. Talanta, 2008,76(5):965- 977.
[23] KALIL S J, MAUFERI F,RODRIGUES M I. Response surface analysis and simulation as a tool for bioprocess design and optimization[J]. Process Biochemistry, 2000, 35(6): 539- 550.
[24] HEYDARNEZHAD F, HOODAJI M, SHAHRIARINOUR M, et al. Optimizing toluene degradation by bacterial strain isolated from oil-polluted soils[J]. Polish Journal of Environmental Studies, 2018, 27(2):655- 663.
[25] RAMANAN R N, TAN J S, MOHAMED M S, et al. Optimization of osmotic shock process variables for enhancement of the release of periplasmic interferon-alpha 2b from Escherichia coli using response surface method[J]. Process Biochemistry, 2010, 45(2): 196- 202.
[26] 谌伟,李小平,孙从军,等. 低强度曝气技术修复河道黑臭水体的可行性研究[J]. 中国给水排水,2009,25(1):57- 59.
[2] 俞欣,陈天安. 河道黑臭污染简易评价方法研究[J].环境科学与管理,2015,40(3):176- 179.
[3] 贾紫永,刘强,伍灵,等.微纳米曝气技术在黑臭河道治理中的应用研究[J].化工管理,2017(36):106.
[4] 张绍君. 纯氧曝气快速消除河流黑臭工程效果及河道影响因素研究[D].北京:清华大学,2010.
[5] ZENG R J, LEMAIRE R, YUAN Z, et al.Simultaneous nitrification, denitrification, and phosphorus removal in a lab-scale sequencing batch reactor[J]. Biotechnology and Bioengineering, 2003, 84(2):170- 178.
[6] ZHANG Z J, ZHU J, KING J, et al. A two-step fed SBR for treating swine manure[J]. Process Biochemistry, 2006, 41(4):892- 900.
[7] WEISSBACH M, THIEL P, DREWES J E, et al. Nitrogen removal and intentional nitrous oxide production from reject water in a coupled nitritation/nitrous denitritation system under real feed-stream conditions[J]. Bioresource Technology, 2018, 255: 58- 66.
[8] BAS D, BOYACI I H. Modeling and optimization I: Usability of response surface methodology[J]. Journal offood engineering, 2007, 78(3): 836- 845.
[9] ZHANG Z, ZHENG H. Optimization for decolorization of azo dye acid green 20 by ultrasound and H2O2 using response surface methodology[J]. Journal of Hazardous Materials, 2009,172(2- 3): 1388- 1393.
[10] AGHAIE E, PAZOUKI M, HOSSEINI M R, et al. Response surface methodology (RSM) analysis of organic acid production for Kaolin beneficiation by Aspergillus nigerv[J]. Chemical Engineering Journal, 2009, 147(2- 3): 245- 251.
[11] ITOKAWA H, HANAKI K, MATSUO T, et al. Nitrous oxide production in high-loading boilogical nitrogen removal process under low COD/N ratio condition[J]. Water Research, 2001, 35(3): 657- 664.
[12] BATEMAN E J, BAGGS E M. Contributions of nitrification and denitrification to N2O emissions from soils at different water-filled pore space[J]. Biology And Fertility of Soils, 2005 41(6):379- 388.
[13] FRANCIS C A, ROBERTS K J, BEMAN J M,et al. Ubiquity and diversity of ammonia-oxidizing archaea in water columns and sediments of the ocean[J]. Proceedings of the National Academy of Sciences of the United States of America, 2005, 102(41):14683- 14688.
[14] POLLICE A, TANDOI V, LESTINGI C. Influence of aeration and sludge retention time on ammonium oxidation to nitrite and nitrate[J]. Water Research,2002, 36(10):2541- 2546.
[15] CHO Y, HAN K, KIM N, et al.Estimating in situ biodegradation rates of petroleum hydrocarbons and microbial population dynamics by performing single-well push-pull tests in a fractured bedrock aquifer[J]. Water Air And Soil Pollution, 2013,224(2):1364- 1368.
[16] XU P, SUN Y, ZHANG H, et al. Experimental study on the effects of multi-parameter setting on fine bubble aeration system[J]. Technology of Water Treatment, 2016, 42(6):51- 54,58.
[17] ZHEN Z, CONJUN S, XIAO P, et al. Study on black and odorous water restoration with low-intensity aeration technology[J]. Technology of Water Treatment, 2009, 35(4):104- 107.
[18] JENSEN W A. Response surface methodology: Process and product optimization using designed experiments 4th edition[J]. Journal of Quality Technology, 2017, 49(2):186- 187.
[19] GUYEN G, PERENDECI A, TANYOLAC A. Electrochemical treatment of deproteinated whey wastewater and optimization of treatment conditions with responses surface methodology[J]. Journal of Hazardous Materials, 2008, 157(1): 69- 78.
[20] SAID K A, AMIN M A.Overview on the response surface methodology (RSM) in extraction processes[J]. Journal of Applied Science & Process Engineering, 2016, 2(1):1- 8.
[21] AZAMAN S N A, RAMAKRIAHNAN N R, TAN J S, et al. Optimization of an induction strategy for improving interferon-alpha 2b production in the periplasm of Escherichia coli using response surface methodology[J]. Biotechnology And Applied Biochemistry, 2010, 56:141- 150.
[22] BEZERRA M A, SANTELLI R E, OLIVERA E P, et al. Response surface methodology (RSM) as a tool for optimization in analytical chemistry[J]. Talanta, 2008,76(5):965- 977.
[23] KALIL S J, MAUFERI F,RODRIGUES M I. Response surface analysis and simulation as a tool for bioprocess design and optimization[J]. Process Biochemistry, 2000, 35(6): 539- 550.
[24] HEYDARNEZHAD F, HOODAJI M, SHAHRIARINOUR M, et al. Optimizing toluene degradation by bacterial strain isolated from oil-polluted soils[J]. Polish Journal of Environmental Studies, 2018, 27(2):655- 663.
[25] RAMANAN R N, TAN J S, MOHAMED M S, et al. Optimization of osmotic shock process variables for enhancement of the release of periplasmic interferon-alpha 2b from Escherichia coli using response surface method[J]. Process Biochemistry, 2010, 45(2): 196- 202.
[26] 谌伟,李小平,孙从军,等. 低强度曝气技术修复河道黑臭水体的可行性研究[J]. 中国给水排水,2009,25(1):57- 59.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |