Impact of Operational Condition on the Membrane Permeate Flux and Quality of Domestic Wastewater Treatment using Hollow Fiber Membrane Module in Cross-Flow Mode
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Keywords

Membrane bioreactor
Operational condition
Multivariate linear regression

How to Cite

1.
Khan Bushra, Liu Mei, Natsagdorj Khaliunaa, Rooha Khurram, Zhan Wang. Impact of Operational Condition on the Membrane Permeate Flux and Quality of Domestic Wastewater Treatment using Hollow Fiber Membrane Module in Cross-Flow Mode. J. Chem. Eng. Res. Updates. [Internet]. 2018 Dec. 30 [cited 2024 Nov. 21];5(1):1-9. Available from: https://avantipublisher.com/index.php/jceru/article/view/891

Abstract

In this paper, the impacts of process conditions on the membrane permeate flux (J) and the quality of effluent in domestic wastewater treated by using 0.1 μm hollow fiber membrane module in cross-flow mode were quantificationally analyzed with a statistical method. The results showed that (1) trans-membrane pressure (TMP), crossflow velocity (u), mixed liquor suspended solids (MLSS), dissolved oxygen concentration (DO), pH, temperature (T), sludge retention time (SRT) and hydraulic retention time (HRT) were all the influencing factors of the permeate flux. Among them, MLSS, T, SRT and HRT are negative contributors to the permeate flux while TMP, u, DO and pH are positive contributors. In addition, the quantitative relationship between the permeate flux and process conditions is established. (2) TMP and u had no effect on the quality of effluent COD while other operating conditions were the influencing factors. Only HRT had a negative effect on the quality of effluent NH3-N. The quantitative relationships between COD, TOC, NH3-N and process conditions were also established. These mathematical expressions, to some extent, could be used to optimize operational conditions, predict the permeate flux and efficiency of domestic wastewater treatment using hollow fiber membrane module in cross flow mode.

https://doi.org/10.15377/2409-983X.2018.05.1
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References

Choi J. G., Baea T. H., Kimb J. H., Tak T. M., Randall A. A. The behavior of membrane fouling initiation on the cross flow membrane bioreactor system, J. Membr. Sci 2002; 203: 103- 113. https://doi.org/10.1016/S0376-7388(01)00790-6

Jiang T., Kennedy M.D., van der Meer W.G. J., Vanrolleghem P.A., Schippers J.C. The role of blocking and cake filtration in MBR fouling, Desalination 2003; 157: 335- 343. https://doi.org/10.1016/S0011-9164(03)00414-4

Visvanathan C., Aim R.B., Parameshwaran K. Membrane separation bioreactors for wastewater treatment, Critical Rev. Environ. Sci. Technol. 2000; 30: 1-48. https://doi.org/10.1080/10643380091184165

Chang I.S., Kim S.N. Wastewater treatment using membrane filtration: effect of biosolids concentration on cake resistance, Process Biochem. 2005; 40: 1307-1314. https://doi.org/10.1016/j.procbio.2004.06.019

Wang Z., Chu J., Song Y., Cui Y., Zhang H., Zhao X., Li Z., Yao J. Influence of operating conditions on the efficiency of domestic wastewater treatment in membrane bioreactors, Desalination 2009; 245: 73-81. https://doi.org/10.1016/j.desal.2008.06.011

Le-Clech P., Jefferson B., Judd S.J. Impact of aeration, solids concentration and membrane characteristics on the hydraulic performance of a membrane bioreactor. J. Membr. Sci. 2003; 218: 117-129. https://doi.org/10.1016/S0376-7388(03)00164-9

Fane A.G., Fell C.J.D., Nor M.T. Ultrafiltration/activated sludge system -development of a predictive model. Polym. Sci. Technol. 1981; 13: 631-658.

Beaubien M. Baty, F. Jeannot, E. Francoeur, J. Manem. Design and operation of anaerobic membrane bioreactors: development of a filtration testing strategy. J. Membr. Sci. 1996,109 (2): 173-184 https://doi.org/10.1016/0376-7388(95)00199-9

Cicek N., Winnen H., Suidan M.T., Wrenn B.E. Effectiveness of the membrane bioreactor in the biodegradation of high molecular weight compounds. Water Res. 1998; 32: 1553- 1563. https://doi.org/10.1016/S0043-1354(97)00350-3

Chang I. S., Kim S. Na. Wastewater treatment using membrane filtration -effect of biosolids concentration on cake resistance. Process Biochem. 2005; 40: 1307-1314. https://doi.org/10.1016/j.procbio.2004.06.019

Jina Y. L., Lee W. N. Effect of DO concentration on biofilm structure and membrane filterability in submerged membrane bioreactor. Water Res. 2006; 40: 2829-2836. https://doi.org/10.1016/j.watres.2006.05.040

Ma B. C., Lee Y. N. Correlation between dissolved oxygen concentration, microbial community and membrane permeability in a membrane bioreactor. Process Biochem. 2006; 41: 1165-1172. https://doi.org/10.1016/j.procbio.2005.12.017

Ognier S., Wisniewski C., Grasmick. A. Characterisation and modelling of fouling in membrane bioreactors. Desalination 2002; 146: 141~147. https://doi.org/10.1016/S0011-9164(02)00508-8

Zhang S., Yang F. Performance of a metallic membrane bioreactor treating simulated distillery wastewater at temperatures of 30 to 45 °C. Desalination 2006; 194: 146- 155. https://doi.org/10.1016/j.desal.2005.10.029

Han S. S., Bae T. H., Jang G. G., Tak T. M. Influence of sludge retention time on membrane fouling and bioactivities in membrane bioreactor system. Process Biochem. 2005;40: 2393-2400. https://doi.org/10.1016/j.procbio.2004.09.017

Huang X., Gui P., Qian Y. Effect of sludge retention time on microbial behaviour in a submerged membrane bioreactor. Process Biochem 2001;36: 1001~1006. https://doi.org/10.1016/S0032-9592(01)00135-2

Lee W., Kang S., Shin H. Sludge characteristics and their contribution to microfiltration in submerged membrane bioreactors. J. Membr. Sci. 2003; 216: 217-227. https://doi.org/10.1016/S0376-7388(03)00073-5

Massé A., Spérandio M. Comparison of sludge characteristics and performance of a submerged membrane bioreactor and an activated sludge process at high solids retention time. Water Res. 2006; 40: 2405-2415. https://doi.org/10.1016/j.watres.2006.04.015

Ahmed Z., Cho J., Lim B. R. Effects of sludge retention time on membrane fouling and microbial community structure in a membrane bioreactor. J. Membr. Sci. 2007; 287: 211-218. https://doi.org/10.1016/j.memsci.2006.10.036

Shane T. R., Rion M. P. The effect of organic loading on process performance and membrane fouling in a submerged membrane bioreactor treating municipal wastewater. Water Res. 2006; 40: 2675-2683. https://doi.org/10.1016/j.watres.2006.04.020

Lee J., Ahn W.Y., Lee C.H. Comparison of the filtration characteristics between attached and suspended growth microorganisms in submerged membrane bioreactor. Water Res. 2001; 35: 2435-2445. https://doi.org/10.1016/S0043-1354(00)00524-8

Nuengjamnong C., Kweon J. H. Membrane fouling caused by extracellular polymeric substances during microfiltration processes. Desalination 2005; 179: 117-124. https://doi.org/10.1016/j.desal.2004.11.060

Ognier S., Wisniewski C., Grasmick A. Influence of macromolecule adsorption during filtration of a membrane bioreactor mixed liquor suspension. J Membr Sci. 2002; 209: 27-37. https://doi.org/10.1016/S0376-7388(02)00123-0

Liu R., Huang X., Xi J., Qian Y. Microbial behaviour in a membrane bioreactor with complete sludge retention. Process Biochem 2005; 40: 3165-3170. https://doi.org/10.1016/j.procbio.2005.01.021

Magara Y., Itoh M. The effect of operational factors on solid/liquid separation by ultra-membrane filtration in a biological denitrification system for collected human excreta treatment plants. Water Sci. Technol. 1991; 23: 1583-1590. https://doi.org/10.2166/wst.1991.0612

Gui P., Huang X., Chen Y. Effect of operational parameters on sludge accumulation on membrane surfaces in a submerged membrane bioreactor. Desalination 2003; 151: 185-194. https://doi.org/10.1016/S0011-9164(02)00997-9

Jianying X., Zheng Z., Xiaoying Y., Xiaodong D., Tao Z., Jian H., Xingzhang L. Recovery of NH3-N from mature leachate via negative pressure steam stripping pretreatment and its benefits on MBR systems: A pilot scale study. J. of Clean. Prod. 203 (2018) 918-925. https://doi.org/10.1016/j.jclepro.2018.08.285

Tardieua E. Hydrodynamic control of bioparticle deposition in a MBR applied to wastewater treatment. J Membr Sci. 1998; 147: 1-12 https://doi.org/10.1016/S0376-7388(98)00091-X

Tardieua E., Grasmick A. Infuence of hydrodynamics on fouling velocity in a recirculated MBR for wastewater treatment. J. Membr. Sci. 1999; 156: 131-140. https://doi.org/10.1016/S0376-7388(98)00343-3

Muhammad A., Rizwan A., Jeonghwan K., Recent developments in biofouling control in membrane bioreactors for domestic wastewater treatment. Sep. Purif. Technol. 206 (2018) 297-315. https://doi.org/10.1016/j.seppur.2018.06.004

Kui W., Ahmed A., Mohammad A, Nidal H., Marwan K. Mechanical properties of water desalination and wastewater treatment membranes. Desalination 401 (2017) 190-205. https://doi.org/10.1016/j.desal.2016.06.032

Chin H., Zainura Z., Noor S., Chi K. Green technology in wastewater treatment technologies: Integration of membrane bioreactor with various wastewater treatment systems. Chem. Eng. J 283 (2016) 582-594. https://doi.org/10.1016/j.cej.2015.07.060

Wang Z., Yao J., Zhou C., Chu J. The Influence of various operating conditions on the permeation flux during dead-end microfiltration, Desalination 2007; 212: 209-218. https://doi.org/10.1016/j.desal.2006.11.007

Wang Z., Yao J., Chu J., Cui Y., Liang Y. The influence of various operating conditions on specific cake resistance in the cross-flow microfiltration of yeast suspensions. Desalination and Wat.Treat.1 2009; 237-247. https://doi.org/10.5004/dwt.2009.124

Dong W., Wang X., Ye X., Wang Z., Zhang X. Impact of operating conditions on the flux changing rate during deadend microfiltration process, Desalination and Water Treatment 2013; 51: 3878-3882. https://doi.org/10.1080/19443994.2013.781738

Liu M., Wang Z., Shi L., Song Y., Dong W., Zhou Y., Zhang J., Yang L., Zhang Q., The influence of operating conditions on the filtration behavior of actual extracellular polymeric substances (EPS) using dead-end membrane filtration cell, Desalination and Wat. Treat.2012; 44: 52-59. https://doi.org/10.1080/19443994.2012.691755

Bai R., Leow H.F. Microfiltration of activated sludge wastewater: the effect of system operation parameters, Separation and Purification Technol. 2002; 29: 189-198. https://doi.org/10.1016/S1383-5866(02)00075-8

Gui P, Huang X. Effect of operational parameters on sludge accumulation on membrane surfaces in a submerged membrane bioreactor, Desalination 2002; 151: 185-194. https://doi.org/10.1016/S0011-9164(02)00997-9

Junwon P., Naoyuki Y., Hiroaki T. Membrane fouling control and enhanced removal of pharmaceuticals and personal care products bycoagulation-MBR Chemosphere 197.2018; 467- 476.

David A. Statistical Models: Theory and Practice. Camb. Uni. Press. 2009; 26.

Rencher A., Christensen W. Methods of Multivariate Analysis, Wiley Series in Probability and Statistics, 709 (3rd ed.), John Wiley & Sons, 2012.p. 19.

Hilary L. The historical development of the Gauss linear model. Biometrika. 1967.54 (1/2): 1-24.

Yan, X. Linear Regression Analysis: Theory and Computing, World Scientific. 2009. pp. 1-2. https://doi.org/10.1142/6986

Chinese SEPA, Water and Wastewater Monitoring Methods, 3rd ed., Chinese Environ. Sci. Pub Hous, 1997.

Ueda T, Hata K, Kikuoka Y. Treatment of domestic sewage from rural settlements by a membrane bioreactor. Wat. Sci. Tech. 1996; 34: 189-196 https://doi.org/10.2166/wst.1996.0209

Liu R, Qian Y. Behaviour of soluble microbial products in a membrane bioreactor. Process Biochem. 2000; 36: 401-406. https://doi.org/10.1016/S0032-9592(00)00206-5

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Copyright (c) 2018 Khan Bushra, Liu Mei, Natsagdorj Khaliunaa, Rooha Khurram, Zhan Wang